Effecs of iron on nitrogen-fixing and non-fixing cyanobacteria

The role of iron in regulation of the

freshwater cyanobacteria

Microcystis aeruginosa and

Cylindrospermopsis raciborskii

by

Anna Chi Ying Yeung

A thesis in fulfilment of the requirements for the degree of

Doctor of Philosophy

School of Civil and Environmental Engineering

Faculty of Engineering

August 2016

THE UNIVERSITY OF NEW SOUTH WALES Thesis/Dissertation Sheet

Surname or Family name: Yeung

First name: Anna Other name/s: Chi Ying

Abbreviation for degree as given in the University calendar: PhD

School: Civil & Environmental Engineering Faculty: Engineering

Title: The role of iron in the regulation of Microcystis aeruginosa and Cylindrospermopsis raciborskii (Cyanobacteria) in freshwater reservoirs

Abstract 350 words maximum: (PLEASE TYPE) Cyanobacterial blooms occur globally. Excessive anthropogenic input of nutrients has contributed to their increased frequency and persistence in the environment. Toxigenic cyanobacteria are often recovered from waters limited by N and P and trace metals including Fe. This important micronutrient is involved in many biological processes, yet its bioavailability in water is limited by the rapid oxidation of the soluble ferrous form to the highly insoluble ferric form. This thesis describes the effects that Fe limitation has on two cyanobacterial species with different metabolic capabilities. A continuous culturing system was used to compare the physiological response of a MCYST-producing Microcystis aeruginosa to both low and high Fe concentrations and different growth rates. Fe limitation resulted in higher internal and external MCYST quotas which support cellular roles in oxidative stress protection and cell signalling. An iTRAQ-based proteomic analysis was performed on the same M. aeruginosa cultures and revealed a vast number of protein changes in response to Fe limitation. Proteins relating to energy metabolism and photosynthesis were negatively affected while membrane transporters increased in abundance, consistent with increases in external MCYST seen before. The effect of calcium and magnesium ions on Fe transformation was tested in EDTA and SRFA buffered systems, with effects on Fe bioavailability assessed by Fe uptake assay. We found that Ca and Mg can significantly reduce Fe bioavailability depending on which ligand is present in the system. The physiological changes in two Cylindrospermopsis raciborskii strains with different toxicities were examined under N and Fe conditions. It was expected that Fe requirement would increase during diazotrophy in order to maintain nitrogenase activity. Surprisingly, Fe uptake rate was lower during N2-fixing conditions yet the enzyme remained active and functional. iTRAQ was used for the same C. raciborskii strains and co-limiting conditions to determine how they adapt at a molecular level. Changes were strain-specific with CYN+ maintaining growth by increasing photosynthesis, nitrogen and transport pathways, while CYN- maintained viability by increasing protein stability and oxidative stress protection. Overall, this thesis provides new insights into the physiological and proteomic adaptations of two freshwater cyanobacterial species in response to Fe availability and the strategies employed to survive.

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Abstract

I

Abstract

Cyanobacterial blooms occur globally. Excessive anthropogenic input of nutrients

has contributed to their increased frequency and persistence in the environment.

Toxigenic cyanobacteria are often recovered from waters limited by N and P and trace

metals including Fe. This important micronutrient is involved in many biological

processes, yet its bioavailability in water is limited by the rapid oxidation of the soluble

ferrous form to the highly insoluble ferric form. This thesis describes the effects that Fe

limitation has on two cyanobacterial species with different metabolic capabilities.

A continuous culturing system was used to compare the physiological response of

a MCYST-producing Microcystis aeruginosa to both low and high Fe concentrations

and different growth rates. Fe limitation resulted in higher internal and external MCYST

quotas which support cellular roles in oxidative stress protection and cell signalling.

An iTRAQ-based proteomic analysis was performed on the same M. aeruginosa

cultures and revealed a vast number of protein changes in response to Fe limitation.

Proteins relating to energy metabolism and photosynthesis were negatively affected

while membrane transporters increased in abundance, consistent with increases in

external MCYST seen before.

The effect of calcium and magnesium ions on Fe transformation was tested in

EDTA and SRFA buffered systems, with effects on Fe bioavailability assessed by Fe

uptake assay. We found that Ca and Mg can significantly reduce Fe bioavailability

depending on which ligand is present in the system.

The physiological changes in two Cylindrospermopsis raciborskii strains with

Abstract

II

different toxicities were examined under N and Fe conditions. It was expected that Fe

requirement would increase during diazotrophy in order to maintain nitrogenase

activity. Surprisingly, Fe uptake rate was lower during N2-fixing conditions yet the

enzyme remained active and functional.

iTRAQ was used for the same C. raciborskii strains and co-limiting conditions to

determine how they adapt at a molecular level. Changes were strain-specific with

CYN+ maintaining growth by increasing photosynthesis, nitrogen and transport

pathways, while CYN- maintained viability by increasing protein stability and oxidative

stress protection.

Overall, this thesis provides new insights into the physiological and proteomic

adaptations of two freshwater cyanobacterial species in response to Fe availability and

the strategies employed to survive.

Acknowledgements

III

Acknowledgements

Firstly to my patient and supportive supervisors, Prof. T. David Waite &

Prof. Brett Neilan: Thank you for your guidance and understanding throughout my

candidature, being part of your labs has been a valuable experience for my personal

growth and development as a researcher. I’m grateful to have worked with the attentive

post-docs: Dr Mark Bligh, Dr Leanne Pearson, Dr Manabu Fujii, & Dr Paul

D’Agostino, who have assisted with experiments, editing drafts and been great mentors

at various stages of my PhD. I also want to express my appreciation to Dr Ralitza

Alexova & Dr Philip Orr for their invaluable feedback during the write up of the

Microcystis manuscript.

I must extend my gratitude to the Australian Research Council for funding this

work (LP883561) and Water Research Australia for the top-up scholarship. Thank you

to Ms Carolyn Bellamy & Dr Michele Akeroyd for your pep talks, and positivity.

I’m grateful to Dr Gautam Chattopadhyay & Mr Kelvin Ong, who over the years

have lent several hands troubleshooting various instruments, and Mr Chris Brownlee for

the training on the flow cytometer. The LC/MS experiments wouldn’t have been

possible without Dr James McDonald & Dr Anne Poljak. To the wonderful Ms Patricia

McLaughlin & Ms Kate Brown, your kindness and encouragement all these years is

beyond words. To the past and present lab members, especially Cuong, Will, Rati,

Sarah & Jason, you were great teachers and made it such a positive work environment.

Some would say that you don’t enter a PhD to make friends (!), but I can only say

that I’ve been so lucky; I’m particularly thankful for Xabier, Lam & Conrad, you guys

Acknowledgements

IV

kept the days interesting but more importantly, your stubborn belief and support got me

through the difficult days. To Bethany & Sara, thank you for getting me out to see the

sun, you certainly bring out the bright side of life!

My most amazing Mum and Dad, thank you for standing by me, through it all you

have been patient and unconditional with your love. No amount of thank-you’s would

suffice but I should start with – “Thanks for always saving me dinner!” And to Allen

and his family, thank you for the late-night pickups – you really earned the BBB badge.

…and finally to Dr Alen Faiz, who is aiming for his name to be last in a

publication, I hope this gets you a bit closer. Despite the geographic separation and the

way-too-early Skype calls, you were always there to encourage me to take on new

challenges. Can’t wait to see you on the flip side!

Publications

V

Publications

Refereed journals

Yeung A. C. Y., D’Agostino P. M., Poljak A., McDonald J., Bligh M. W., Waite T. D.,

Neilan B. A. (2016) Physiological and proteomic changes in Microcystis aeruginosa

PCC 7806 on long-term continuous culturing under iron-limiting conditions. Applied

Environmental Microbiology. doi: 10.1128/AEM.01207-16

D’Agostino P. M., Woodhouse J. N., Makower A. K., Yeung A. C. Y., Micallef M. L.,

Moffitt M. C., Neilan B. A. (2016) Advances in genomics, transciptomics and

proteomics of toxin-producing cyanobacteria. Environmental Microbiology Reports.

doi: 10.1111/1758-2229.12366

Fujii M., Yeung A. C. Y., Waite T. D. (2015) Competitive effects of calcium and

magnesium on the photochemical transformation and associated cellular uptake of iron

by the freshwater cyanobacterial phytoplankton Microcystis aeruginosa. Environmental

Science and Technology. doi: 10.1021/acs.est.5b01583

Local and international conferences

Yeung A., Neilan B.A., and Waite T. D. (2015) Proteomics in the water industry: How

do toxic Microcystis aeruginosa respond to iron limitation? Algae Research

Symposium, November 2015, Sydney, Australia [Oral and Poster presentation]

Yeung A., D’Agostino P., Poljak A., Pearson L., Neilan B., Waite T.D. (2014) Using

iTRAQ to uncover growth rate dependent proteomic changes in Microcystis aeruginosa

under iron limitation. 2nd

Proteomics and Beyond Symposium, November 2014,

Sydney, Australia [Poster presentation]

Publications

VI

Yeung, A., Dang, T.C., Muenchhoff, J., McDonald, J., Waite, T. D., Neilan, B. A.

(2013) Effects of growth rate on the proteomic changes and toxin production in

Microcystis aeruginosa under iron limitation. 9th

International Conference on Toxic

Cyanobacteria Conference, August 2013, Pilanesberg, South Africa. [Oral presentation]

Yeung, A., Dang, T. C., Le-Minh, N., Bligh, M., Neilan, B. A., Waite, T. D. (2012)

Impact of iron availability on the toxicity of M. aeruginosa. OzWater ‘12, May 2012,

Sydney, Australia [Poster presentation]

Abbreviations and symbols

VII


[D-Asp3]MCYST-LR Demethylated microcystin-LR

BLAST Basic Local Alignment Search Tool

CBB Coomassie Brilliant Blue

Chl a Chlorophyll a

CS-506 Cylindrospermopsis raciborskii CS-506

CS-509 Cylindrospermopsis raciborskii CS-509

CYN Cylindrospermopsin

DCF 2',7'-dichlorofluorescein

DMSO Dimethyl Sulfoxide

EDTA Ethylenediaminetetraacetic acid

H2DCF 2’, 7’dichlorodihydrofluorescein

H2DCFDA 2', 7’-dichlorodihydrofluorescein diacetate

H2O2 Hydrogen peroxide

HFBA Heptafluorobutyric acid

HEPES 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid

iTRAQ Isobaric Tag for Relative and Absolute Quantitation

KEGG Kyoto Encyclopedia of Genes and Genomes

LC/MS/MS Tandem Liquid Chromatography-Mass Spectrometry

Me Divalent metal ions

MCYST Microcystins

MCYST-LR Microcystin-LR

MQ MilliQ water


VIII

N2-fixation Nitrogen fixation

NCBI National Center for Biotechnology Information

PAGE PolyAcrylamide Gel Electrophoresis

PAR Photosynthetically active radiation

PMSF Phenylmethylsulfonyl Fluoride

RAST Rapid Annotation Subsystems Technology

ROS Reactive Oxygen Species

SDS Sodium Dodecyl Sulphate

SDS-PAGE Sodium dodecyl sulphate polyacrylamide gel electrophoresis

TCEP tris-(2-carboxyethyl) phosphine

Table of Contents

IX

Table of Contents

Abstract ............................................................................... I

Acknowledgements .......................................................... III

Publications ....................................................................... V

Abbreviations and symbols ........................................... VII

Table of Contents ............................................................. IX

List of figures .................................................................. XV

List of tables .................................................................. XVII

Chapter 1: Introduction ..................................................... 1

Introduction ..................................................................................................... 1

Algal blooms, associated toxins and management ......................................... 3

Types of cyanotoxins .......................................................................................................... 4

Microcystin – chemistry, toxicology, and biosynthesis ....................................................... 7

Cylindrospermopsin – chemistry, toxicology, and biosynthesis........................................ 11

Putative functions of cyanotoxins .................................................................. 12

Allelopathy ........................................................................................................................ 13

Cell signalling .................................................................................................................... 13

Putative siderophores ....................................................................................................... 14

Protection from oxidative stress ........................................................................................ 15

Environmental conditions on toxin production .............................................. 15

Phosphorous ..................................................................................................................... 16

Nitrogen ............................................................................................................................ 18

Iron and other trace metals ............................................................................................... 20

Molecular research into cyanobacterial toxicity regulation ............................ 23

Table of Contents

X

Genomic studies of cyanobacteria .................................................................................... 23

Proteomic studies of cyanobacteria .................................................................................. 24

Scope and objectives ................................................................................... 27

Objectives .......................................................................................................................... 28

Thesis outline .................................................................................................................... 28

Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures of different iron bioavailability and growth rates .............. 31

Introduction ................................................................................................... 31

Materials and methods ................................................................................. 33

Strain and culturing conditions .......................................................................................... 33

Continuous culturing .......................................................................................................... 34

Physiological measurements ............................................................................................. 35

Oxidative stress detection ................................................................................................. 37

Results .......................................................................................................... 39

Steady-state physiological differences .............................................................................. 39

Microcystin analysis........................................................................................................... 41

Oxidative stress response at different Fe concentration and growth rates ....................... 44

Discussion .................................................................................................... 47

The relationship between MCYST production and growth rate changes under different Fe availability .......................................................................................................................... 49

Role of MCYST in oxidative stress protection ................................................................... 49

Putative function of extracellular MCYST .......................................................................... 50

Conclusion .................................................................................................... 52

Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron concentration .. 53

Introduction ................................................................................................... 53

Materials and Methods ................................................................................. 54

Experimental design .......................................................................................................... 54

Strain and culturing condition ............................................................................................ 55

Protein extraction and visualisation ................................................................................... 55

iTRAQ labelling .................................................................................................................. 56

Sample preparation and mass spectrometry analysis ...................................................... 57

Table of Contents

XI

Results .......................................................................................................... 58

Core proteomes of Fe-limited and Fe-replete chemostat changes .................................. 58

Overview of the functional categories affected by growth rate at different iron availabilities .......................................................................................................................................... 61

Growth rate influenced protein changes ........................................................................... 63

Discussion .................................................................................................... 67

Global proteomic and physiological response to Fe-limitation at different growth rates .. 67

Changes to transporter proteins ....................................................................................... 70

Conclusion .................................................................................................... 71

Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa ............... 85

Introduction ................................................................................................... 85

Material and Methods ................................................................................... 91

Strain and culturing condition ........................................................................................... 91

Photochemical Fe transformation ..................................................................................... 91

Short-term iron uptake ...................................................................................................... 93

Kinetic and thermodynamic model for 55

Fe uptake ........................................................... 94

Results and Discussion .............................................................................. 102

Photochemical Fe(II) formation ....................................................................................... 102

Conclusion .................................................................................................. 114

Chapter 5: The physiological responses of two closely related strains of Cylindrospermopsis raciborskii to differing iron availability under nitrogen-fixing conditions ....................................................................... 117

Introduction ................................................................................................. 117

Material and Methods ................................................................................. 119

Strains and culturing conditions ...................................................................................... 119

Physiological characterisations ....................................................................................... 120

Acetylene reduction assay .............................................................................................. 120

Short term iron uptake .................................................................................................... 121

Results ........................................................................................................ 123

Physiological characterisations ....................................................................................... 123

Table of Contents

XII

Nitrogenase activity ......................................................................................................... 126

Short term 55

Fe uptake .................................................................................................... 127

Discussion .................................................................................................. 129

Physiological responses to different Fe availability under N2-fixation ............................. 129

Effects of Fe on nitrogenase activity ............................................................................... 130

Competition between CYN+ and CYN

- under combined N and Fe limitation .................. 132

Conclusion .................................................................................................. 132

Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in response to iron under N2-fixing conditions ............................................ 135

Introduction ................................................................................................. 135

Materials and methods ............................................................................... 137

Experimental design ........................................................................................................ 137

Strains and culturing conditions ...................................................................................... 138

Protein extraction and visualisation ................................................................................. 138

iTRAQ labelling ................................................................................................................ 139

Sample preparation and mass spectrometry analysis .................................................... 139

Results ........................................................................................................ 140

Effects of Fe availability on growth under N2-fixing conditions ........................................ 140

Comparative proteome analysis ...................................................................................... 141

Effects of Fe availability on protein expression in CYN+ strain ....................................... 143

Effects of Fe availability on protein expression in CYN- strain ........................................ 144

Discussion .................................................................................................. 157

Conclusion .................................................................................................. 159

Chapter 7: Summary and future work ......................... 161

Summary .................................................................................................... 161

Future work ................................................................................................. 164

References ..................................................................... 167

Appendix A ..................................................................... 185

Table of Contents

XIII

BG11 .......................................................................................................... 186

Jaworski Medium (JM) ................................................................................ 187

Modified Jaworski Medium (JM*) ................................................................ 188

Fraquil* and Fraquil*BG11 ............................................................................. 189

Appendix B ..................................................................... 191

1 Introduction .............................................................................................. 191

2 Materials and methods ............................................................................ 192

Cyanobacterial culture conditions ................................................................................... 192

Buffer compositions ........................................................................................................ 192

Bead beating procedure ................................................................................................. 193

Sonication procedure ...................................................................................................... 193

Quantification of protein extracts .................................................................................... 194

SDS-PAGE gel electrophoresis ...................................................................................... 194

3 Results and discussion ............................................................................ 195

Sonication versus bead beating ...................................................................................... 195

Comparison of the buffer compositions .......................................................................... 196

4 Conclusions ............................................................................................. 198

Appendix C ..................................................................... 199

1 Details of Experimental Procedures ......................................................... 199

Reagents ......................................................................................................................... 199

Culturing medium ............................................................................................................ 202

Long-term cell culturing................................................................................................... 204

Light condition ................................................................................................................. 204

Photochemical experiment ............................................................................................. 205

Fe uptake experiment ..................................................................................................... 207

2 Analytical concerns .................................................................................. 208

Concentration and reactivity of Fe that originally present in SRFA ................................ 208

Effect of HEPES on the Fe complexation ....................................................................... 211

Effect of thermal redox reactions on the Fe(II) formation ............................................... 212

Fe(II) concentration in the equilibrated FeSRFA solution ............................................... 214

Fulvic acid adsorption to cell surface and availability of photolyzed Fe-ligand complex in the Fe uptake experiment ............................................................................................... 215

Table of Contents

XIV

3 Formation rate of FeIIEDTA complex in the absence and presence of Me ................................................................................................................... 217

Methods ........................................................................................................................... 217

Results and Discussion ................................................................................................... 218

4 Detailed procedure of parameter determination ...................................... 221

Photochemical Fe(II) generation ..................................................................................... 221

Cellular uptake ................................................................................................................. 222

Model fitting ..................................................................................................................... 224

5 Fe concentrations in the 55Fe uptake assay ............................................ 224

Selection of important reactions via sensitivity analysis .................................................. 224

Calculation of unchelated Fe concentrations .................................................................. 227

List of figures

XV

List of figures

Figure 1.1 Map of Sydney catchment. ................................................................ 2

Figure 1.2 Warragamba dam, New South Wales, Australia, in August, 2007. .... 6

Figure 1.3 Chemical structure of the hepatotoxin, microcystin. ........................... 7

Figure 1.4 Microcystin gene cluster. ................................................................... 9

Figure 1.5 Chemical structure of cylindrospermopsin. ...................................... 11

Figure 1.6 Structural organisation of cylindrospermopsin gene cluster of C. raciborskii. ......................................................................................................... 12

Figure 1.7 Putative FurA binding sites identified in the mcyA/D promoter region. .......................................................................................................................... 22

Figure 2.1 Setup for Fe-limited and Fe-replete chemostats. ............................. 34

Figure 2.2 Growth of M. aeruginosa PCC 7806 in (A) Fe-limited and (B) Fe-replete chemostats at different dilution rates .................................................... 40

Figure 2.3 Total MCYST detected at different dilution rates ............................. 42

Figure 2.4 (A) Intracellular and (B) Extracellular MCYST quota in Fe-limited chemostat cultures. ........................................................................................... 43

Figure 2.5 Total intracellular MCYST quota in Fe-replete chemostat cultures. . 44

Figure 2.6 Differences in cellular oxidative stress at different growth rates caused by culturing in (A) Fe-limited and (B) Fe-replete chemostats. ............... 45

Figure 2.7 Response of M. aeruginosa from different growth rates to oxidative stress induced by H2O2 under Fe-limited conditions. ........................................ 46

Figure 2.8 Response of M. aeruginosa from different growth rates to oxidative stress induced by H2O2 under Fe-replete conditions......................................... 47

Figure 3.1 Schematic presentation of the experimental design for M. aeruginosa PCC 7806 iTRAQ studies. ................................................................................ 54

Figure 3.2 Summary of the proteins identified in continuous cultures of M. aeruginosa PCC 7806 in (A) Fe-limited and (B) Fe-replete chemostats. .......... 59

List of figures

XVI

Figure 3.3 Regulatory processes affected by growth rate in (A) Fe-limited and (B) Fe-replete chemostats. ............................................................................... 62

Figure 3.4 Heat maps of Fe-limited and Fe-replete protein changes arranged into functional categories. ................................................................................. 64

Figure 4.1 Iron uptake model for Microcystis aeruginosa in the absence and presence of major divalent metals (Me). ........................................................... 90

Figure 4.2 Effects of Me concentration on the photochemical FeIIFZ3 formation in Fraquil* buffered by (A) EDTA (Ca: black-coloured square, Mg: grey-coloured triangle, no Me: open diamond) and (B) SRFA. .............................................. 103

Figure 4.3 (A) 55Fe uptake rate in a range of Me concentration in EDTA-buffered Fraquil*. .......................................................................................................... 110

Figure 5.1 Growth curves of (A) CYN+ and (B) CYN– C. raciborskii in different N and Fe treatments. .......................................................................................... 123

Figure 5.2 C. raciborskii CYN+ (Left) and CYN- (Right) culture in different nitrogen and iron conditions. ........................................................................... 125

Figure 5.3 Ethylene production by (A) CYN+ and (B) CYN- strains of C. raciborskii during the ARA experiment. ........................................................... 126

Figure 5.4 Preliminary 55Fe uptake by C. raciborskii in the presence and absence of light. .............................................................................................. 127

Figure 5.5 55Fe uptake by C. raciborskii strains in the presence or absence of combined nitrogen. ......................................................................................... 129

Figure 6.1 Experimental design for comparative proteomics of C. raciborskii strains with different toxigenicity. .................................................................... 137

Figure 6.2 Growth curves of CYN+ (left) and CYN- (right) in N-free media with varying Fe concentrations. .............................................................................. 140

Figure 6.3 Representative SDS PAGE gels of C. raciborskii CYN+ (left) and CYN- (right) at exponential phase and stationary phrase. ............................... 141

Figure 6.4 Distribution of identified proteins in functional groups from CYN+ (Top) and CYN- (Bottom)................................................................................. 142

Figure 6.5 Heat map of differentially expressed proteins from exponential phase arranged by functional categories. .................................................................. 155

Figure 6.6 Heat map of differentially expressed proteins from stationary phase arranged by functional groups. ....................................................................... 156

List of tables

XVII

List of tables

Table 1.1 Summary of cyanobacterial species and associated toxins ................ 5

Table 2.1 Summary of the physiological changes to M. aeruginosa under iron and growth rate control ..................................................................................... 41

Table 3.1 M. aeruginosa iTRAQ overview from Fe-limited and Fe-replete chemostats........................................................................................................ 59

Table 3.2 Differentially expressed proteins in M. aeruginosa under Fe-limited chemostats at different dilution rates. ............................................................... 73

Table 3.3 Differentially expressed proteins in M. aeruginosa under Fe-replete chemostats at different dilution rates. ............................................................... 82

Table 4.1 Kinetic and thermodynamic rate constants used in this study. ........ 107

Table 5.1 Physiological changes in C. raciborskii under different Fe concentrations. ................................................................................................ 124

Table 5.2 Nitrogenase activity in (A) CYN+ and (B) CYN- strains of C. raciborskii relative to chlorophyll content.......................................................................... 127

Table 6.1 Differentially expressed proteins in CYN+ CS-506 at exponential phase. ............................................................................................................. 146

Table 6.2 Differentially expressed proteins in CYN+ CS-506 at stationary phase. ........................................................................................................................ 148

Table 6.3 List of significantly differentiated proteins in CYN- CS-509 at exponential phase. .......................................................................................... 151

Table 6.4 List of significantly differentiated proteins in CYN- CS-509 at stationary phase. ............................................................................................. 154

Chapter 1: Introduction

1


Introduction

Water is an essential resource for the sustainability of all living things however,

blooms of harmful cyanobacteria – commonly referred to as “blue-green algae” – in

oceans and freshwater reservoirs can sometimes render these sources unusable.

Although algal blooms occur naturally worldwide, increased anthropogenic activities

and the changing climate have also contributed to the increased frequency and

persistence of algal blooms (Paerl and Huisman, 2009, Sinha et al., 2012).

Apart from affecting the aesthetics of the water body, cyanobacteria can also

produce odour compounds and toxic metabolites (e.g. cyanotoxins) which pose

potential risks to humans and animals (Codd et al., 2005). As such, water management

authorities are under pressure to provide safe quality water for communities. Existing

water management strategies include drawing water from greater depths of the reservoir

and filtration through either deep bed sand filters or membranes where the majority of

debris and algal cells are removed, however there still remains the possibility that toxic

molecules remain present in the water source long after treatment, with the result that

these waters could still pose a danger to consumers. As such, understanding how

environmental conditions influence the regulation of cyanobacteria toxicity at a

molecular level permits the understanding of cyanobacterial growth and succession in


2

nature.

Figure 1.1 Map of Sydney catchment. The network of rivers, dams and reservoirs in the greater Sydney region managed by WaterNSW (formally Sydney Catchment Authority). Source: SCA

In Australia, freshwater blooms occur frequently in reservoirs and rivers, with

weather and the chemistry of the waterbody all playing a role in seasonal algal blooms.

Microcystis aeruginosa is a unicellular freshwater cyanobacteria species and has been a

dominant contributor of algal blooms in Sydney catchments, particularly in Lakes

Burragorang, Wingcarribee, Yarrunga and Nepean (Figure 1.1). However, the changing

climate has seen the invasion of the traditionally tropical species Cylindrospermopsis

into temperate freshwater environments in recent years (Kinnear, 2010, Sinha et al.,

2012, Al-Tebrineh et al., 2012). Following is a literature review of research to date

regarding the proliferation of these species and their response to the changing


3

environment. The scope and objectives of this research is also introduced with attention

given to Microcystis aeruginosa and Cylindrospermopsis raciborskii. These two

cyanobacterial species have different metabolic abilities and thus are hypothesised to

have different physiological and proteomic response to iron limitation.

Algal blooms, associated toxins and management

Environmental factors that contribute to the growth and development of algal

blooms include temperature, pH, light and the availability of nutrients. Although

freshwater algal blooms occur naturally worldwide, increased anthropogenic activities

along with climatic changes have resulted in the increased occurrence and persistence of

algal blooms. Warm temperatures in conjunction with the abundance of sunlight

stratifies water bodies with these conditions favouring the growth of the buoyant

cyanobacteria over larger and denser plankton (Verspagen et al., 2004). Cyanobacteria

are able to control their position within the water column by adjusting their cellular gas

vesicles thus rise from the nutrient rich sediments and photosynthesise in surface waters

(Oliver, 1994). By day, carbohydrate is accumulated during photosynthesis causing the

bacteria to sink within the water column then, during night time as the carbohydrate is

consumed, carbon dioxide fills the gas vesicles allowing the cyanobacteria to rise and

collect at the water surface (Baptista and Vasconcelos, 2006). High photosynthetic

activity at the scum layer can result in disturbances to the natural ecosystem of the

surrounding water, including increases in water temperature, the level of dissolved

oxygen as well as depletion of organic carbon. As well, the composition of species and

strains that makes up the scum layer change throughout the development of the bloom,


4

which may persist from weeks to months at a time (Zohary and Breen, 1989). At the

senescence of the algal bloom, mass cell lysis releases cellular components and

molecules that foul the taste and odour of water. Oxygen depletion within the water has

also been observed when the organic components degrade (Carmichael, 2001). More

importantly cell lysis also releases toxic secondary metabolites, termed cyanotoxins,

occurring in approximately 50-75% of algal blooms.

Cyanobacterial control strategies for reservoirs and catchments may be chemical

(such as the addition of algaecides and coagulants), physical (the use of mixers and

aerators to destraify the waterbody, use of booms or floating objects to isolate and

contain bloom-affected areas) and biological (introduce viral or fungal organisms and

zooplankton to maximise feeding on cyanobacteria). Although biomanipulation

strategies have been effectively employed in Europe, more extensive research is

required for Australia as the biological composition in the water differs dramatically

from that in Europe (Boon et al., 1994, Davis and Koop, 2006). Furthermore, most of

the available control strategies are either still in development or not suitable to use for

large scale areas managed by the Sydney Catchment Authority (SCA, 2010). For

example, the addition of large quantities of metal salts or coagulants into the reservoirs

during a bloom event could have negative ramifications on the ecosystem in the long

run. Therefore it is essential that we understand the “inner workings” of cyanobacterial

growth and response to the environment in order to provide effective control strategies.

Types of cyanotoxins

Cyanotoxins are commonly classed according to the organ systems they attack.

Table 1.1 summarises the major classes of cyanotoxins associated with toxic blooms

where exposure to these toxins can have acute or long-term detrimental effects on


5

health.

Table 1.1 Summary of cyanobacterial species and associated toxins

Toxin class Example Target Producing organisms

Hepatotoxic cyclic heptapeptides

Microcystin, Nodularin Liver, hepatocytes Microcystis sp, Anabaena sp

Hepatotoxic alkaloids Cylindrospermopsin Liver and kidney

Cylindrospermopsis (Australian strains)

Aphanzimenon

Umezakia

Neurotoxic alkaloids Saxitoxin,

Anatoxin-a

Nervous system, heart

Anabaena

Cylindrospermopsis (European strains)

Dermatotoxins Lipopolysacchairides, Lynbyatoxin-a

Skin, exposed tissue Lyngbya

The first recorded cyanobacterial bloom in Australia occurred in South Australia’s

Lake Alexandria in 1878 (Codd et al., 1994), with subsequent regular outbreaks in the

Darling-Barwon river system in 1991, in 2007 at the Warragamba dam (Figure 1.2) and

another extensive bloom in the Murray River during 2009 and 2010 (Ryan et al., 2009).

Generally speaking, cyanobacterial blooms in Australia are concentrated in the south-

eastern corner with Microcystis sp. the main culprit, however climatic changes in the

past two decades have seen typically tropical species such as Cylindrospermopsis

spread into temperate regions (Haande et al., 2008, Sinha et al., 2012). Interestingly, the

2009 bloom had appeared suddenly and was actually several blooms occurring

simultaneously with different community profiles (Al-Tebrineh et al., 2012).

Cylindrospermopsis was also reported in the Murray River bloom (Al-Tebrineh et al.,

2012), therefore should also be included in the list of cyanobacterial species that the

Australian water management authorities should focus on in the future. As concluded by

Vilhena and colleagues (2010), future increases in temperature from climate change

results in warmer inflows from water sources and, in turn, causes changes to the


6

stratification behaviour of the water body.

Figure 1.2 Warragamba dam, New South Wales, Australia, in August, 2007. Up to 20,000 Microcystis cells mL

-1 was detected in water samples, however, toxin was not

detected in this bloom.

Several strains are capable of producing cyanotoxins, such as the hepatotoxins

microcystin (produced by Microcystis and Anabaena sp.) and cylindrospermopsin

(produced by Cylindrospermopsis, Raphidiopsis etc) as well the neurotoxins, saxitoxin

and anatoxin-a (Anabaena sp.), with more classes mentioned in Table 1.1 Summary of .

As the name suggests, hepatotoxins are a group of metabolites that target the liver cells,

with two particular hepatotoxins, microcystin and cylindrospermopsin discussed in

more detail a little later. These toxins pose dangers to the health of wildlife, livestock

and humans that rely on the water source. In the past, cyanotoxins in water sources have

been responsible for livestock deaths and, have been shown to promote tumour growth

in humans after chronic exposure to sub-lethal doses (Falconer, 2005).

Traditional methods of bloom control include the addition of lytic agents or

algaecides to the affected waters. Although this method is effective in the short term, the

approach is not desirable as it is not species specific, resulting in mass cell lysis and the

release of cellular components and toxins into the water, thus altering the conditions of

the water body with further detrimental effects on aquatic life. Other physical control

strategies incorporate artificial destratification to promote mixing between water layers

and reduce stratification, as well as planting riparian zones in an attempt to reduce


7

nutrient inflow into water systems (Codd, 2000). As toxin biosynthesis pathways are

elucidated, research has shifted towards the physiological contribution of the toxin to

the producing cells in an attempt to understand the interaction between environment and

toxin regulation with the purpose, ultimately, to establish more advanced strategies of

bloom prediction and management control. The following section focuses on two

particular hepatotoxins, microcystin (MCYST) and cylindrospermopsin (CYN)

produced by Microcystis aeruginosa and Australian strains of Cylindrospermopsis

raciborskii respectively.

Microcystin – chemistry, toxicology, and biosynthesis

Figure 1.3 Chemical structure of the hepatotoxin, microcystin. Variable amino acid substitutions occur at positions 2X and 4Y; e.g. in Microcystin-LR, X is L-Leu and Y is L-Arg.

Microcystin is a cyclic heptapeptide classed under the group of hepatotoxins.

There are approximately 90 isoforms of MCYST identified, making it the one of the

most structurally diverse cyanotoxins. Each isoform varies by the level of methylation,

hydroxylation, epimerisation, peptide sequence and toxicity (Pearson et al., 2010). The

general structure of MCYST is cyclo(-D-Ala-L-X-D-MeAsp-L-Z-Adda-D-Glu-Mdha)

where Adda is (2S,3S,8S,9S)-3-amino-9- methoxy-2,6,8-trimethyl-10-phenyl-


8

(4E),(6E)-decadienoic acid, MeAsp is 3-methylaspartic acid and MeDha is N-methyl-

dehydroalanine (Figure 1.3). Microcystin diversity is created by substituting amino

acids at positions X and Y and named according to the amino acids at those positions,

resulting in isoforms such as microcystin-YR, -RR, -LA, with each differing in polarity

and toxicity. By far the most common and best-studied and most toxic isoform is

microcystin-LR with a molecular weight of 995 Da where X and Y substitutions are

amino acids L-Leu and L-Arg respectively.

Microcystin is toxic to animals by inhibiting protein phosphatases 1 and 2A,

leading to excessive phosphorylation and subsequent oxidative stress. For animals and

humans, the toxin is actively transported via anion transporters to the liver where the

damage takes place (Pearson et al., 2010). Firstly the Adda moiety binds weakly to the

cysteine residue at the active site of the phosphatase enzyme, then MeDha forms a

strong covalent bond between Adda and cysteine residue, preventing the remodelling of

the structural filaments. This results in the collapse of the hepatocyte structures from

neighbouring cells causing blood to pool within the liver, ultimately leading to tissue

necrosis and haemorrhagic shock (Soares et al., 2006, Bagu et al., 1997). The

recommended safe limit for microcystin-LR in water is set at 1 μg/L, however typical

concentrations found during bloom occurrences can range from 0.5-5 μg/L (Babica et

al., 2006) making the water unsafe for consumption. Laboratory studies have observed

the development of skin and liver tumours in mice and rats after chronic exposure to

sub-lethal concentrations of the toxin. There is strong evidence that these effects are

transcribed to humans after cases of liver failure were observed in a haemodialysis

clinic in Brazil, 1996 (Jochimsen et al., 1998, Carmichael, 2001) and in Haimen city in

China (Ueno et al., 1996, Apeldoorn et al., 2007). Liver tissues obtained from autopsies


9

on the Brazilian patients showed extensive cell deformity and necrosis at the liver plate

(Jochimsen et al., 1998).

Figure 1.4 Microcystin gene cluster. Microcystin gene cluster. Gene arrangements within the mcy cluster are similar between Microcystis PCC7806 and Anabaena sp. 90 in that both species have a bidirectionally transcribed operon (figure adapted from (Sivonen, 2009).

Dittmann and co-workers (1997) were the first to elucidate the biosynthesis

pathway for MCYST using M. aeruginosa PCC 7806 which has since become the

model organism for subsequent MCYST investigations. Microcystins are produced non-

ribosomally meaning that the peptide is synthesised independently of messenger RNA

(mRNA); instead, synthetase enzymes called non-ribosomal peptide synthetase (NRPS)

and polyketide synthetase (PKS) carry out the procedure in a stepwise manner as each

amino acid of the peptide is added by a different domain of the enzyme, similar to that

of an assembly line. These MCYST synthetases are encoded by the gene cluster mcyS

which has been sequenced and characterised form a number of species; Microcystis,

Planktothrix and Anabaena (Figure 1.4) (Sivonen, 2009).

The mcyS cluster from M. aeruginosa PCC7806 consists of 10 genes that are

bidirectionally transcribed from a central promoter located between mcyA and mcyD

genes, essentially dividing the gene cluster into two operons (Figure 1.4). The smaller

operon, mcyA-C, encodes three NRPS (McyA – C) while the larger operon, mcyD-J,


10

encodes a PKS (McyD), two hybrid NRPS/ PKS enzymes (McyE and McyG), tailoring

enzymes (McyJ, F and I) and finally a putative ABC (ATP-binding cassette) transporter

(McyH) (Pearson et al., 2004, Tillett et al., 2000). Insertion sequences found within mcy

genes is the most likely explanation for the loss of gene function and hence existence of

non-toxic strains within species (Ostermaier and Kurmayer, 2009, Tooming-Klunderud

et al., 2008). There is evidence that transcription of the mcyA/D promoter region is

sensitive to changes in the environment. Dittmann et al (2001) demonstrated the effect

of high light stress on the transcription of mcyB and mcyD. The quantity of both

transcripts increased when cells were transferred from low to high light intensities,

however when oxidative stress was induced in the cultures, the quantity of these

transcripts decreased. The authors thus concluded that while light has a positive effect

on mcyB and mcyD transcription, it is not a response to oxidative stress. Moreover the

availability of nitrogen and iron also indirectly influence the level of transcription in the

mcy operon through binding of transcriptional regulators, NtcA and FurA, for nitrogen

and iron respectively (Sevilla et al., 2008, Sevilla et al., 2010, Ginn et al., 2010, Martin-

Luna et al., 2006).


11

Cylindrospermopsin – chemistry, toxicology, and biosynthesis

Figure 1.5 Chemical structure of cylindrospermopsin. There are three variants of the toxin: CYN, 7-deoxy CYN and 7-epi CYN which is shown here. The molecular weight of CYN is 415 Da.

Cylindrospermopsin (CYN) is a tricylic uracil derivative (Figure 1.5) with

hepatotoxic, cytotoxic and neurotoxic effects (Mihali et al., 2008) where the mode of

toxicity acts by inhibition of glutathione and protein synthesis as well as cytochrome

P450 inhibition. There are three structural variants documented thus far:

cylindrospermopsin (CYN), 7-epicylindrospermopsin (7-epi CYN) and 7-

deoxycylindrospermopsin (7-deoxy CYN) (Kinnear, 2010). It is not only a highly

water-soluble toxin but also resists decomposition in various heat, light and pH

conditions (Chiswell et al., 1999). CYN production is controlled by the 43 kb long cyr

gene cluster which contains 15 open reading frames for the genes, cyrA – cyrO, that

control its biosynthesis, regulation and transport from the cell (Figure 1.6). Similar to

the biosynthesis of MCYST, CYN is also produced non-ribosomally and requires cyrA

as the first step to catalyze the reaction between glycine and guanidinacetate for the

formation of carbon skeleton, PKS/NRPS genes cyrB,C,D,E and F, genes for tailoring

the toxin cyrI,J,N, transporter – cyrK, transposase – cyrL and M, and cyrO for

amidinotransferase (Mihali et al., 2008).


12

Figure 1.6 Structural organisation of cylindrospermopsin gene cluster of C. raciborskii. Each operon for genes cyrA – cryO, see in text for the function of each gene figure adapted from (Mihali et al., 2008).

Similar to MCYST, CYN also targets the liver cells however the mode of toxicity

differs slightly; it has been suggested that the uracil moiety is crucial to the toxicity of

CYN which is theorised to bind to catalytic sites involved in pyrimidine nucleotide

synthesis and transformation (Reisner et al., 2004). CYN is also associated with the

generation of ROS which causes degeneration of the hepatocytes, leading to liver

necrosis. There is evidence that CYN promotes the likelihood of cancers (Falconer and

Humpage, 2006).

Putative functions of cyanotoxins

Examinations of algal blooms have recovered non-toxic strains within bloom

populations (Christiansen et al., 2008), questioning the functional role of cyanotoxins

and whether it is essential for survival. While cyanotoxins are not necessary, they

appear to be advantageous for the production of cells under nutrient limited conditions

(Lukac and Aegerter, 1993). Studies to date have focussed on the function of MCYST

over other cyanotoxins, perhaps motivated by the fact that multiple genera of

cyanobacteria (Nostoc, Synechococcus and Plantothrix) also produce this toxin


13

(Sivonen, 2009, Pearson et al., 2010). The true function of MCYST is still unknown

however theories thus far have revolved around four major themes; allelopathy, cell

signalling, iron chelation (Kaebernick and Neilan, 2001, Sivonen, 2009, Ginn et al.,

2009) and oxidative stress defence (Zilliges et al., 2011) though it would not be

unreasonable to assume some of these functions could also apply to other cyanotoxins.

Allelopathy

Allelopathy is the chemical effect of inhibiting the growth of competing

organisms by the release of a metabolite. Several studies have exhibited the deterrent

effect of MCYST on competing cyanobacteria (Singh et al., 2001, Pflugmacher, 2002)

and aquatic plants (LeBlanc et al., 2005) as well as the advantage over non-toxic strains,

however there are also discrepancies in this theory as purified MCYST was unable to

reproduce the same effect suggesting that other secondary metabolites are also required

to produce the effect (Schatz et al., 2005, Sivonen, 2009). There is also evidence that

cylindrospermopsin causes surrounding phytoplankton to release alkaline phosphatases

to transform organic phosphorus into inorganic phosphorus sources to be utilised by the

producing cell (Bar-Yosef et al., 2010).

Cell signalling

Another putative function for cyanotoxins is in cell signalling. This theory is

supported by the research of Pearson et al (2004) who observed a loss in toxicity when a

gene encoding a putative transporter was disrupted. Since transporters are anchored at

the thylakoid membrane, there are implications that MCYST is actively transported

from the cell thus suggests a possible cell signalling molecule. Immuno-gold labelling

used in the past had localised MCYST within a wildtype cell (Shi et al., 1995), and the

toxin was found to be most concentrated around the thylakoid membrane consistent


14

with the speculation of the transporter role. Once MCYST is released from the cell,

whether through transport or cell lysis, it may function as a putative chemo-signalling

molecule (Kaebernick and Neilan, 2001), arresting growth of surrounding cells and

triggering cell lysis in a proportion of the bloom so as to provide nutrients for the

remaining cells. Interestingly, addition of cell lysates into fresh cultures also induces

toxin synthesis in a young population possibly to enhance the fitness of the population

(Babica et al., 2006, Schatz et al., 2007). The functional role of CYN has been

hypothesised to be a defensive mechanism against grazing aquatic zooplanktons as

supported by studies where juvenile Daphnia magna suffered impaired growth when

incubated with CYN (Rzymski and Poniedzialek, 2014). However in Aphanizomenon

ovalisporum, CYN production is increased when external sources of inorganic

phosphorus were removed. It appeared to have a role in phosphorus acquisition by

causing surrounding organisms to release alkaline phosphatases to utilise existing

organic P-sources, thus replenishing the supply of inorganic P-sources (Bar-Yosef et al.,

2010).

Putative siderophores

Catechol-type chelators are the most common type of siderophore produced by

both marine and freshwater cyanobacteria, and hydroxamate-type siderophores have

been discovered in Anabaena, Synechococcus and Oscillatoria sp. with siderophore-

mediated iron uptake recorded in Anabaena (Simpson and Neilands, 1976, Goldman et

al., 1983). Microcystin has also been shown to have high affinity for iron, zinc and

copper and as such, making them potential candidates as siderophores for metal

scavenging (Utkilen and Gjolme, 1995, Xing et al., 2007). It is hypothesised that the tail

structure (Adda) of MCYST is anchored to the thylakoid membrane while the polar


15

cyclic peptide extends from the cytoplasm to bind to metals (Ginn et al., 2009). This

affinity for metals could be advantageous for the toxin-producing cell at both

extracellular and intracellular levels. Under low iron conditions, if the cell can secrete

MCYST, the toxin can then bind metals from the surrounding environment and provide

iron to the starved cell, while on the intracellular level, microcystins can be useful in

chelating excess iron by forming iron-MCYST complexes which could also function as

a potential reserve for later times when iron supplies are low, however this remains to

be proven (Kaebernick and Neilan, 2001). Furthermore localisation of the toxin at the

thylakoid membrane suggests it may also be closely associated with photosynthesis

(Lyck, 2004), as demonstrated by increased transcription of the MCYST operon (mcy)

under high light intensity (Kaebernick et al., 2000).

Protection from oxidative stress

Several natural processes generate reactive oxygen species, such as

photosynthesis and iron reduction and cause oxidative damage to proteins in organisms.

In a recent study, MCYST was shown to bind to certain proteins which protects proteins

sensitive to redox changes (Zilliges et al., 2011). As such protein binding could increase

the fitness of the producing strain under oxidative stress inducing conditions. The role

of MCYST has also been shown to link with carbon-nitrogen metabolism (Zilliges et

al., 2011, Alexova et al., 2011c) therefore MCYST might serve a more global function

in regulation of processes within the cell than first thought.

Environmental conditions on toxin production

A balanced combination of environmental factors such as nutrient and trace metal

availability, pH, temperature and light intensity are required for successful growth of


16

cyanobacteria (Baptista and Vasconcelos, 2006). Studies conducted to date have

focussed on nutrients such as phosphorus, nitrogen and iron (Lukac and Aegerter, 1993,

Utkilen and Gjolme, 1995, Orr and Jones, 1998, Downing et al., 2005, Lopez-Gomollon

et al., 2007, Ginn et al., 2009), suggesting the availability of these nutrients plays a

significant role in the growth and toxicity of Microcystis and Cylindrospermopsis.

While both organisms are able to utilise various forms of these nutrients, their

requirements and uptake mechanisms are quite different. Anabaena sp. are nitrogen-

fixing species and, as such, phosphorus and iron are more likely to be the limiting

factors for growth. On the other hand, nitrogen may become the limiting factor for

Microcystis sp. since this species cannot undergo nitrogen fixation. The following

section summarises the current knowledge of effects of nitrogen, phosphorus and iron

on production of toxins.

Phosphorous

Microorganisms require phosphorus for three main purposes; i) as a structural

component for outer membrane and the backbone of nucleic acids, ii) as the energy

carrying molecule – adenosine triphosphate (ATP) and iii) as signalling molecules

between regulatory pathways (Tonk et al., 2005). Unlike nitrogen, there are no gaseous

forms of phosphate available; as such, soluble orthophosphate is most likely to be the

form taken up by organisms (Reynolds, 1998). In nature, phosphate availability in water

is determined by the rate of complexation and sedimentation as these processes

essentially lock away the nutrient. Therefore phosphate concentration is an important

factor to consider for cyanobacterial growth and toxicity.

A linear relationship exists between cell biomass and total phosphorus availability

in the water body therefore it is expected that phosphorus limitation would affect the


17

growth rate of M. aeruginosa as well as the physiology of the cell during replication

(Ou et al., 2006, Ou et al., 2004). However it is also important to note that other abiotic

factors including pH, light intensity and inorganic carbon concentration also come into

play during cell growth and numerous studies have proposed the importance of

macronutrient (nitrogen to phosphorus) ratios in the overall dominance of particular

strains in blooms (Downing et al., 2005, Jin et al., 2005). Recent research has

demonstrated the negative effect of phosphorus deficiency on photosynthetic ability

(Wang et al., 2010b) due to the close association of phosphate with the electron

transport pathway of the photosystem. In this study, the fluidity of the thylakoid

membrane, which contains the key components of the photosystem, exhibited a lower

electron transport rate under phosphate limitation, thereby inhibiting photosynthetic

carbon assimilation and subsequently resulting in poor growth. In regards to

cyanobacterial toxicity, a phosphate limited chemostat study by Oh et al. (2000),

observed that toxin synthesis not only increased under phosphate limitation, but also

resulted in an increase in the production of the more toxic isoform, MCYST-LR.

However these results contradicted previous findings where toxin production was

shown to be positively correlated with phosphorus concentration (Sivonen, 1990). Both

studies investigated the physiological changes in cyanobacteria as the result of altering

one growth factor at a time, however, as Vezie’s findings (2002) would prove, it may be

more relevant to study the physiological changes due to interactions between nutrients

to give a more realistic comparison of the nutrient dynamics in nature. The authors were

able to show that toxic and non-toxic cells respond differently to varying ratios of

nitrogen and phosphorus, where toxic cells had higher nutrient demands than nontoxic

cells. However like many of the predecessors of this field, the authors could only


18

conclude that a complex relationship exists between environmental conditions and toxin

regulation and cannot be resolved down to the change of one abiotic factor. As such

there is scope for further investigation in monitoring the effects of interacting nutrients

on the physiological changes in cells at a molecular level. It is often difficult to compare

cyanobacterial studies due to the different culturing conditions employed as well as the

strains used for each study. Therefore genomic and proteomic studies may provide a

more sensitive examination of how toxin synthesis pathways respond to environmental

changes.

Nitrogen

Nitrogen is an important resource incorporated into the environment through

various assimilatory processes carried out by plants and microorganisms. Nitrogen

sources are stored in the form of inorganic molecules such as ammonium (NH4+) and

nitrate (NO3-) or organic molecules such as urea, nucleic acids and amino acids;

furthermore, various bacterial species are able to directly utilise atmospheric nitrogen by

a process called nitrogen fixation (Herrero et al., 2001). The regulation of nitrogen

assimilation is tightly controlled, as some nitrogen sources, such as NH4+ and

glutamine, are more easily absorbed and therefore preferred over others. Generally,

other nitrogen assimilation pathways will be repressed until the easily accessible source

becomes scarce. Various transporters have been identified within cyanobacteria, which

are specific for the uptake of particular forms of nitrogen, such as ammonium, urea and

nitrate transporters (Herrero et al., 2001).

Nitrogen is involved in several cross-regulatory pathways relating to nutrient

uptake, redox control and photosynthesis (Espinosa and Forchhammer, 2006, Osanai

and Tanaka, 2007) and, as such, it is not surprising that nitrogen limitation (an issue for


19

non-nitrogen fixers) results in physiological adaptations including degradation of the

phycobiliprotein and subsequent chlorosis and poor growth yields as well as oxidative

stress in the photosystem (Ginn et al., 2009). NtcA is the nitrogen specific

transcriptional regulator essential for the maintenance of nitrogen control and

assimilation processes within the cyanobacterial cell. Upon detection of changes in

nitrogen levels, this protein binds to the promoter region of the nitrogen responsive

gene, thereby activating transcription. However in some cases, NtcA has also been

observed to have a repressor effect on transcription (Jiang et al., 1997). PII is a signal

transduction protein regulated by NtcA at the transcription and post-translation level,

however PII along with another small protein, the PII-interacting protein (PipX) are also

required to stimulate NtcA activity in nitrogen starved conditions (Espinosa and

Forchhammer, 2006). Furthermore DNA binding assays performed by Jiang and

colleagues (1997) also illustrated that NtcA was able to bind to its own promoter which

would infer a self-regulating mechanism.

Several studies have investigated the interrelationships between nitrogen

depletion, degradation of phycobiliproteins and toxin concentration although the exact

mechanism remains largely unknown. In a Finnish study (Vézie et al., 2002) which

investigated the difference in growth between a wild type toxic Microcystis sp. and its

nontoxic mutant, the authors found that, overall, the nontoxic mutant was able to

achieve better growth over the wild type toxic strain. The authors concluded that

because various enzyme complexes are required to synthesise the toxins in addition to

the energy costs involved in producing the toxin constitutively meant that the toxic cells

would require more nutrients in order to grow. The authors also argued that in

congruence with another study (Hesse et al., 2001) under light limitation, nontoxic cells


20

were more photosynthetically active than the toxic counterpart. However this is more

likely to reflect the change in ratio of PSI/PSII in the wild type cells and thus a

reasonable speculation is that toxin production also plays a role in adaptation to light

and photosynthetic changes. Cross-talk between nitrogen and iron control has been

linked to toxicity in Anabaena (Lopez-Gomollon et al., 2007) suggesting that perhaps a

similar regulatory mechanism exists in Microcystis as well.

Iron and other trace metals

Iron is the fourth most abundant metal on earth and is vital for numerous living

organisms as it plays a role in photosynthesis, nitrogen fixation, respiration and radical

scavenging. Natural unchelated forms of iron, Fe2+

and Fe3+

, are readily assimilated by

microorganisms however its bioavailability in the environment is largely determined by

processes such as redox reactions, complexation with natural ligands, adsorption and

precipitation (Pham et al., 2006). These processes reduce the bioavailability of iron in

the environment and iron limitation is often observed in open oceans and coastal waters

due to the rapid oxidation of Fe2+

to Fe3+

in surface waters and the low solubility of Fe3+

around circumneutral pH (Fujii et al., 2010a).

Iron plays a crucial role in the functioning of various components of

photosynthetic machinery, for example it is a cofactor for photosystem I and II (PSI and

PSII respectively), ferredoxin, cytochrome c6 and NADH dehydrogenase just to name a

few (Baptista and Vasconcelos, 2006). Furthermore it has been found that iron

limitation also regulates the expression of ferric uptake regulator (FurA) and increases

transcription of the MCYST promoter (Martin-Luna et al., 2006, Sevilla et al., 2008).

Iron homeostasis is crucial for cyanobacteria so to avoid formation of strongly oxidising

reactive oxygen species (ROS) such as the hydroxyl radical (OH•) which is formed


21

from the reaction of hydrogen peroxide (H2O2) with intracellular ferrous iron (Fe2+

)

through the so-called Fenton reaction:

Fe2+

+ H2O2 → OH- + FeO2 + H

+ → Fe

3+ + OH

- + OH•

The reactive species OH• resulting from the Fenton reaction attacks PSI, a trimeric

protein rich in Fe4S4 clusters, causing the clusters to degrade and release more free iron

within the cell perpetuating the oxidation reaction (Latifi et al., 2009).

Cyanobacteria employ various strategies to cope with oxidative stress including

alternative electron transfer pathways followed by replacement of proteins containing

iron with iron free substitutes and finally iron stress inducible genes (isiA and isiB)

transcribed to modify the PSI and PSII to promote dissipation of electrons throughout

the system (Baptista and Vasconcelos, 2006, Latifi et al., 2009). Increased production of

MCYST during oxidative stress has been attributed to its role as a siderophore to bind

excess intracellular free iron (Utkilen and Gjolme, 1995, Kaebernick and Neilan, 2001,

Sivonen, 2009).

There is still little known about the correlation between iron limitation, oxidative

stress and toxin synthesis in cyanobacteria however, in Anabaena, iron availability has

been reported to influence the expression of furA (Kaebernick and Neilan, 2001, Lopez-

Gomollon et al., 2007). In addition putative binding sites for FurA, termed “iron boxes”,

have been located in the bidirectionally transcribed mcyA/D promoter region (Martin-

Luna et al., 2006) (Figure 1.7).


22

Figure 1.7 Putative FurA binding sites identified in the mcyA/D promoter region. Grey regions represent A-T rich sites indicative of binding sites whereas bold boxed regions represent a possible distribution of the iron boxes (figure from Martin-Luna et al., 2006).

Furthermore, increased transcription of mcyD, encoding the well conserved Adda

structure in MCYST, has been observed under iron limitation (Sevilla et al., 2008). Fujii

et al recently demonstrated the effects of divalent metal ions (calcium and magnesium)

on the transformations of iron from the complexed or insoluble ferric form into the

soluble and bioavailable ferrous form (Fujii et al., 2015). The implications of this study

meant water hardness (caused by calcium and magnesium ions) may also influence the

availability of iron for cyanobacteria.

Other metal ions such as zinc, copper and cobalt are also required as metal

cofactors for maintaining a homeostatic cellular environment, and are often involved in

functioning of the photosynthetic machinery; e.g. copper is required by cytochrome

oxidase and plastocyanin and zinc is required to regulate some transcriptional factors.


23

Molecular research into cyanobacterial toxicity regulation

Genomic studies of cyanobacteria

The discovery of the toxin gene clusters was a milestone which provided a sound

starting point for gene manipulation and allowed researchers to determine the function

and biosynthesis pathways of toxins. By far, the most common approach for studying

functions of genes is to create a knock out mutant (Dittmann et al., 1997, Dittmann et

al., 2001, Pearson et al., 2004) where antibiotic cassettes are inserted into the gene in

order to deactivate it. However, knockout mutants may not necessarily represent

nontoxic strains found in nature, as noted the difference in cell size between the

naturally nontoxic isolate and knockout mutant when compared with the wildtype toxic

strain (Schatz et al., 2005).

Genomic studies using quantitative real-time PCR (qRT-PCR) provide a useful

analysis of the differential gene expression as a result of the experimental conditions,

however, mRNA transcripts do not always correlate with the protein levels. For

example although Kabernick and colleagues found that the transcript copies for mcy

genes increased with light intensity, it did not correlate with the actual level of toxin

present (Kaebernick et al., 2000). Furthermore, advances in the “-omics” technologies

has seen the move away from genomic studies into other “-omic” type analyses such as

proteomics which provide a more realistic insight into the functional components of

cellular pathways present at one particular time (Burja et al., 2003, Ow and Wright,

2009). Most work has been carried out on Synechocystis sp. PCC6803 and Anabaena

sp. PCC7120 as these two species represent model organisms for cyanobacteria

(Barrios-Llerena et al., 2006). However, there has been an increase in M. aeruginosa

and C. raciborskii studies as well with annotated genomic data now available. This is


24

further complicated by the genomic plasticity of M. aeruginosa - long repeated

sequences, transposons, leading to frequent acquisition of atypical genes (Frangeul et

al., 2008) thus one particular strain may not be representative of the whole genus

(Alexova et al., 2011c).

Proteomic studies of cyanobacteria

By examining the changes in the abundance of proteins in response to tested

parameters, we can begin to map these responses to pathways and increase our

understanding of how the organisms have adapted to their external environment.

Proteomics is also considered to be a more robust approach to studying the organism as

mRNA transcripts are liable to degradation and post-translational modifications could

occur, thus affecting the correlation between genomic and proteomic data.

Typically, the workflow of proteomic studies involves the extraction of protein,

followed by their separation on a polyacrylamide gel. Alternatively, extracted proteins

are digested and the resulting peptides are separated by liquid chromatography and

detected by mass spectrometry (Morisawa et al., 2006, Bantscheff et al., 2012). Peptides

are searched against a database of known gene sequences (or a translated version of the

organism’s genome) to predict the identified protein. A popular method of choice for

separating complex protein mixtures is two-dimension gel electrophoresis (2DE) which

separates firstly by isoelectric point (pI) followed by molecular weight; however,

multiple replicate gels would have to be run in parallel for accurate quantitation.

Alternatively, gel-free methods have gained recent popularity and involve chemical

labeling, which are either in vivo – such as stable isotope labelling for amino acids in

cell cultures (SILAC) or elemental labelling; or in vitro – such as isotope-coated affinity

tags (ICAT) and isobaric tags for relative and absolute quantitation (iTRAQ) (Wiese et


25

al., 2007). However when proteomic methods are applied to cyanobacteria, one of the

limiting factors is the separation of proteins, another is the masking of low-abundance

proteins by high-abundance proteins such as phycobiliproteins (Ow and Wright, 2011)

which can cause smearing on 2DE gels, however, these issues have been largely

addressed through optimization procedures to improve protein extraction as well as

separation (De la Cerda et al., 2007, Fulda et al., 2006). Alternative methods to 2DE,

such as the gel-free iTRAQ technique, have also become a popular choice which has

been shown to have improved reproducibility compared to 2DE (Choe et al., 2005), and

already applied to some nontoxic cyanobacterial strains like Synechocystis (Pandhal et

al., 2008) and Prochlorococcus (Pandhal et al., 2007). These proteomic studies have

laid the groundwork for the application of proteomics in a toxic cyanobacterial setting

as the availability of toxic cyanobacterial genome sequences increase.

The first comparative proteomic studies of toxic cyanobacteria were performed by

Alexova et al. (2011c) and Tonietto et al. (2012) who both investigated multiple strains

of Microcystis with varying toxicity. The study by Alexova et al. (2011c) compared the

proteomes of toxic and nontoxic M. aeruginosa strains, with the aim of finding any

proteins that could be used as a biomarker for toxicity. Although none of the proteins

proved to be a potential biomarker, the study did confirm a high level of variability

across the proteomes of the tested strains. Likewise, in the Tonietto proteomics study

(2012) proteins involved in energy metabolism, photosynthesis and carbon fixation

were up-regulated in the toxic Microcystis proteome, which led the authors to draw the

same conclusion: that toxin production was related to primary metabolism (Tonietto et

al., 2012). In addition, these highlighted processes are also affected under nitrogen and

phosphorus limitation as demonstrated in the recent 2DE study by Yue et al (2014),


26

however no significant differences were reported when comparing control conditions

and combined macronutrient limitation.

Proteomics has also been applied to filamentous species of cyanobacteria, which

began with Plominsky and colleagues who optimized the protein extraction protocol for

a CYN-producing and non-CYN producing Cylindrospermopsis as well as a saxitoxin-

producing Raphidiopsis (Plominsky et al., 2009). Although the authors have noted

regions of proteins uniquely expressed in the toxic strains, further identification of these

proteins would be a long process due to the requirements for sequencing and

characterization and validation (Plominsky et al., 2009) therefore comparative

proteomic studies for toxic filamentous cyanobacterial species are still rare. Recently

iTRAQ labelling was used for a comparative study on toxic and nontoxic strain of

Anabaena circinalis (D’Agostino et al., 2014) with over 800 proteins in each ecotype

identified. In addition, the method also captured proteins involved in the saxitoxin

biosynthesis pathway which are generally considered low abundance proteins,

demonstrating the potential of the method for improved sensitivities in protein

identification. The identification of strain-specific proteins, differences of protein

abundance within the same protein functional categories and found that at the proteomic

level, isolates of the same species can be highly variable.

Although 2DE proteomics remains a popular choice for protein separation, as the

costs of regents for labelled methods become more accessible, we may see a rise in the

use of gel free proteomics in the same way that genomic and transcriptomic work

increased when high throughput sequencing and microarray technologies became

available. There is also scope for integrating iTRAQ labelling with other proteomic

methods as demonstrated by the recent findings of Guo and colleagues (Guo et al.,


27

2014). The researchers used tandem mass tags combined with resin enrichment to assess

redox-sensitive changes in the proteome of Synechocystis during light and dark cycles

and provided new insights into the identification of functional sites for redox related

proteins. The integration of methods provides a more comprehensive examination of the

target organism and may even provide validation of genomic sequences of multiple

closely related species (Kucharova and Wiker, 2014). There are also further

opportunities to examine posttranslational modifications through phosphorylation

experiments to better our understanding of the organism’s response to changes in

environmental conditions.

Scope and objectives

It is increasingly difficult to single out environmental parameters which are the

sole cause for algal bloom succession and toxicity as multiple conditions come together

in natural systems to drive these processes. However, we can build on what is

happening by beginning with single factor studies then increasing to combinatory

studies. Understanding the interaction between toxigenic cyanobacteria and iron in the

environment is a key motivation behind this research because the findings can lead to

reassessments of bloom control methods and managing water quality. This research will

utilise labelled proteomics to examine the response of Microcystis aeruginosa and

Cylindrospermopsis raciborskii to iron limitation. The role of MCYST in oxidative

stress protection is also examined. We also explore the putative advantages that toxin

producers have over non-producers in iron uptake, and also under nitrogen stress for

Cylindrospermopsis raciborskii. As chemostat system provides a stable and controlled

environment while also allowing cells to be examined at desired growth states as cells


28

would be homogenous. This is recommended for molecular studies which rely on

homogeneity across the population when capturing the protein expression at particular

growth stages.

Objectives

The objectives of this research cover the following:

1) To examine the physiological and the molecular changes that take place in toxigenic

and nontoxigenic Microcystis aeruginosa and Cylindrospermopsis raciborskii species

as a result of culturing under Fe limiting and N2-fixing conditions.

2) To examine how nutrient uptake, growth conditions and oxidative stress affect toxin

regulation.

3) Compare the strategies used by toxigenic and nontoxigenic strains to establish within

a bloom population.

4) To examine how Fe bioavailability is regulated and the implications for

cyanobacteria

5) Using results from the study to infer whether the conditions found in the catchment

sites, such as Lakes Burragorang and Wingcarribee are likely to result in future toxic

blooms.

Thesis outline

This thesis features five results chapters covering the above objectives.

In Chapter 2 to 4, the physiological characteristics of the MCYST-producing

Microcystis aeruginosa PCC7806 are compared between Fe-limited and Fe-replete


29

chemostat systems to examine the physiological changes that occur at various growth

rates. Chapter 3 utilises the chemostat cultures to perform a comparative proteomic

study to uncover the changes in the global responses to Fe availability at different

growth rates. Chapters 2 and 3 have been combined and published as:

Physiological and proteomic responses of continuous cultures of Microcystis

aeruginosa PCC 7806 to changes in iron bioavailability and growth rate. Anna C.

Y. Yeung, Paul M. D'Agostino, Anne Poljak, James McDonald, Mark W. Bligh, T.

David Waite and Brett A. Neilan. Applied and Environmental Microbiology. Accepted

29 July, 2016. doi: 10.1128/AEM.01207-16

In Chapter 4, the influence of divalent metals on iron transformation and its effect

on iron uptake by Microcystis is explored. This chapter has been published as:

Competitive Effects of Calcium and Magnesium Ions on the Photochemical

Transformation and Associated Cellular Uptake of Iron by the Freshwater

Cyanobacterial Phytoplankton Microcystis aeruginosa. Manabu Fujii, Anna C. Y.

Yeung, and T. David Waite. Environmental Science & Technology 2015 49 (15), 9133-

9142. DOI: 10.1021/acs.est.5b01583

In Chapters 5 and 6, the research progresses to Cylindrospermopsis raciborskii as

this bloom-forming species has become more prevalent in the last decade. This species

is able to utilise atmospheric nitrogen for biomass which differs from M. aeruginosa

and, as such, it is expected that iron requirements will also differ. The physiological

responses to Fe availability is explored in Chapter 5 while Chapter 6 compares the


30

proteome of the toxigenic and nontoxigenic strains of C. raciborskii under combined

iron and nitrogen limitation to uncover the proteomic changes from these stressors.

Chapter 7 summarises the major findings of this research for two species of

freshwater cyanobacteria with different energetic requirements and their response to Fe

limitation and the implications of this research in the water sector. A discussion for

future investigations in this field concludes Chapter 7.

Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures

of different iron bioavailability and growth rates

31

Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures of different iron

bioavailability and growth rates

Chapters 2 and 3 have been published as: Physiological and proteomic responses

of continuous cultures of Microcystis aeruginosa PCC 7806 to changes in iron

bioavailability and growth rate. Anna C. Y. Yeung, Paul M. D'Agostino, Anne Poljak,

James McDonald, Mark W. Bligh, T. David Waite and Brett A. Neilan. Applied and

Environmental Microbiology. Accepted 29 July, 2016. doi: 10.1128/AEM.01207-16

Introduction

Iron is an important trace nutrient required for numerous processes within a

photosynthetic organism; as such its limitation could have significant effects on the

cellular processes. In M. aeruginosa, most studies have been conducted on batch

cultures where the biggest challenge lies in the uncertainty of a response to the tested

variable, since the external environment is under constant change throughout the growth

cycle of the culture. Conversely, the chemostat studies performed have mainly focussed

on macronutrients; however the traditional chemostat theory doesn’t apply to



32

photoreactive species such as iron in the growth medium. This was thoroughly

discussed by Dang et al (2012a) in their Microcystis study on iron uptake variability

between cells under differing levels of iron limitation.

Chemostats are specialised vessels where the growth rate of the cells is tightly

controlled by the dilution rate of the culture. Traditional batch cultures supply a finite

source of nutrients within the growth medium which is depleted as the culture grows

(closed systems) and therefore cell growth can be monitored as having distinct phases:

lag, log, stationary and death. Unlike batch culture systems, the nutrient source in

chemostats are supplied continuously (open systems), thus the bacterial culture is

diluted at a set rate (dilution rate) which also dictates the growth rate of the culture since

cells must replenish at the same rate as the removal, or else risk being washed out.

Therefore chemostat systems produce cells which are said to be in a “steady state”

meaning that the cells are at the same growth phase and homogeneous in their

physiological responses.

The objective of this chapter is to characterise the physiological differences

between Microcystis aeruginosa PCC 7806 cells under iron-limited and iron-replete

chemostat conditions. To achieve this, two 12-channel chemostat systems were set up in

iron-limited and iron-replete conditions and controlled at four dilution rates

representative of different stages on the growth curve, where the fastest dilution rate

was similar to early log phase down to the slowest dilution rate mimicking early

stationary phase. The effects of iron availability on physical characteristics differences

such as cell size, chlorophyll content, and MCYST content were monitored between the

tested growth rates, as well as the short term iron uptake response and resistance to

oxidative stress.



33

Materials and methods

Strain and culturing conditions

The MCYST-producing strain M. aeruginosa PCC 7806 was acquired from

Pasteur Culture Collection and maintained in BG11 medium (Appendix A). To study the

effects of iron, M. aeruginosa was subcultured into Fraquil*, a defined medium in

which the chemical speciation of trace metals is well-defined and therefore suitable for

the investigation on cellular responses to trace metal availability (Anderson, 2005).

However, the concentrations of some major nutrients including nitrate are relatively low

in Fraquil*, therefore a nutrient-replete Fraquil* (referred to as Fraquil*BG11) was

developed in previous study (Fujii et al., Submitted) by modifying major nutrient

concentrations to be equivalent to those in BG11 medium.

In this study, M. aeruginosa PCC7806 were subcultured twice into Fraquil*BG11

and acclimated to this medium before the commencement of chemostat experiments.

Cultures were incubated with agitation at 27 oC under photon irradiance of 157 µmol

photon m-2

s-1

PAR in 14:10 h light to dark regime to mimic the natural photoperiod in

the environment.



34

Continuous culturing

Figure 2.1 Setup for Fe-limited and Fe-replete chemostats. See in text for description.

The chemostat system used was the same as that developed in a previous study

(Dang et al., 2012a) where all culture vessels and plumbing were constructed from

metal-free materials. Briefly, the chemostat system was set up inside a refrigerated

incubator (Thermoline Scientific, Australia) to test four dilution rate (D) conditions in

triplicates (Figure 2.1). Sterile Fraquil*BG11 was supplied to the culture vessels through

a high-precision peristaltic pump (Ismatec, Germany) where D was determined using a

combination of tubing with different diameters. Culture volume was maintained at 200

mL by the positive pressure created by the air supplied into each vessel, which forces

excess wasted media and cyanobacterial cells into the waste ports (Figure 2.1). Culture

vessels were set up on shakers to maintain a homogeneous culture and incubated at



35

27 °C under fluorescent lights with photon irradiance of 157 µmol m-1

s-1

in 14:10 h

light:dark cycle to mimic the natural photoperiod in the environment.

Under steady-state conditions, dilution rate (D) is equal to the specific growth rate

(µ) (Dang et al., 2012a), in this chemostat setup D = 0.07 d-1

, 0.15 d-1

, 0.30 d-1

and 0.45

d-1

which were determined by the diameter of the feed tubes (Dang et al., 2012a). Fe

concentration in Fraquil*BG11 was 100 nM for Fe-limited conditions, and 1000 nM for

Control conditions. Continuous cultures were maintained until cells reached and

remained in steady-state for seven consecutive samplings as determined by manual cell

counting and chlorophyll extract measurements. Aliquots were harvested at day 42 for

Control and day 40 for Fe-limited chemostat for physiological analyses including cell

concentration, size, chlorophyll content, oxidative stress, and MCYST content

measurements. The remainder of the culture was sacrificed for proteomic experiments

in Chapter 3.

Physiological measurements

Cell size and cell enumeration

Samples were taken from the chemostat cultures and observed under light

microscopy to determine cell numbers and sizes from the four different dilution rates.

Two samples were taken from each culture for cell enumeration using a Neubauer

haemocytometer. Cell size – taken as the diameter across the cell – was estimated by

taking an average of 50 cells using the accompanying Leica Application Suite.

Chlorophyll measurement

Chlorophyll a (Chl a) was extracted from 1 mL of culture using 90% (v/v)

methanol as instructed in Meeks laboratory (Meeks and Castenholz, 1971). Cells were

pelleted and 90% of the supernatant was removed and replaced with methanol then



36

mixed at maximum speed in a FastPrep FP120 Cell Disrupter (Thermo Savant,

Carlsbad, USA) to extract the pigment. Samples were steeped for 1 h in the dark and the

absorbance at 665nm was multiplied by 12.7 (extinction coefficient of Chl a) to

calculate chlorophyll (µg Chl a mL-1

).

Microcystin extraction and quantification

MCYST was extracted from 2 mL of steady-state culture. After centrifugation in

an Eppendorf 5415D centrifuge (14,000 × g, 10 min), the cell pellet was used for

MCYST extraction while the supernatant was reserved for extracellular MCYST

analysis. Intracellular MCYST was extracted by resuspending the cell pellet in 80%

(v/v) aqueous methanol and disrupting the cells for 2 × 30 s in a in a FastPrep FP120

Cell Disrupter (Thermo Savant, Carlsbad, USA) at top speed using 0.5 mm zirconium

silicate beads. Cell debris and beads were removed by centrifugation and the

supernatant was evaporated in a Savant SpeedVac SC110 Concentrator. As an

additional purification step, equal volumes of 40% methanol and chloroform were

added to the samples and the tubes were incubated for 3 minutes with shaking to purify

the MCYST from the pigmented residue. Extracts were centrifuged in an Eppendorf

5415D centrifuge (12,000 × g, 15 min) to separate the aqueous methanol and

chloroform mixture, of which the methanol layer was collected. The extracellular and

intracellular MCYST samples were submitted to Dr James McDonald (UNSW,

Australia) for analysis by Liquid Chromatography Tandem Mass Spectrometry

(LCMS/MS) against MCYST-LR and [D-Asp3]MCYST-LR standards with

Fraquil*BG11 medium and 40% aqueous methanol used as blank matrices. MCYST

measurements were normalized to cell number to give total MCYST quotas (QMC)

which is the sum of MCint (extracted MCYST) and MCext (MCYST in the medium) after



37

normalization to cell concentration. All LC-MS/MS results are presented as mean

values of three replicate cultures for each dilution condition. All data were analysed by

one-way ANOVA. Once a significant difference was detected post hoc multiple

comparisons were performed using the Tukey test. The level of significance was set at

0.05 for all tests.

Oxidative stress detection

Iron limitation interrupts photosynthetic processes and can generate reactive

oxygen species (ROS) which induce oxidative stress. To measure oxidative stress, 2’,7’-

dichlorodihydrofluorescein diacetate (H2DCFDA) was used as a probe to detect the

presence of ROS within the cells. The dye permeates the cell wall whereby cellular

esterases hydrolyze the diacetate bond to form the stable but non-fluorescent 2’,7’-

dichlorodihydrofluorescein (H2DCF). H2DCF reacts with intracellular ROS to form the

highly fluorescent 2’,7’-dichlorofluorescein (DCF) detectable by fluorescence methods.

Stock solutions of H2DCFHDA (10 mM) were prepared in dimethyl sulfoxide (DMSO)

to aid in permeability across the cell membrane in a procedure similar to Rastogi and

colleagues (2010). Approximately 0.5 – 1 ×107 cells were collected from each

chemostat and dilution rate condition. Cells were washed with fresh Fraquil*BG11, then

resuspended in 1 mL of the same medium supplemented with 25 µM of H2DCFHDA.

Since H2DCFHDA is light-sensitive, samples were wrapped in foil and incubated on a

shaker for 1 h at 25oC for the dye to be absorbed. After incubation, samples were

centrifuged and resuspended in fresh Fraquil*BG11 to remove the unabsorbed dye. DCF

fluorescence was measured from 5 ×105 cells with a BD FACSAria

TM II cell sorter flow

cytometer (BD Biosciences, San Jose, USA), using excitation and emission filters of

450 and 530 nm, respectively.



38

After the initial measurement, hydrogen peroxide (H2O2) was added to examine

the response of cells from different iron and growth rates to H2O2-induced oxidative

stress. An aliquot of 500 µL of each sample was transferred into a fresh tube and 4 mM

of H2O2 was added, mixed briefly then incubated at ambient room temperature covered

with foil. Fluorescence measurements with the flow cytometer were taken from 5 x105

cells at 10 and 30 min after the addition of H2O2.



39

Results

Steady-state physiological differences

The physiological characteristics of M. aeruginosa in continuous cultures

(chemostats) were compared under Fe-limited (100 nM Fe) or Fe-replete (1000 nM Fe)

conditions across four dilution rates representative of different growth phases of batch

culture conditions. Chemostats were maintained until cell counts remained constant

across consecutive sampling days, i.e. at steady state (approximately 40 days) where

cellular processes are homogenous for the cells at a particular growth state.

Physiological characteristics were recorded from cells harvested at steady state (Figure

2.2). In the Fe-limited chemostat, distinct differences in cell densities were observed at

the four growth rates, in agreement with what has been observed in batch cultures.

Under iron limitation, the highest cell density was observed at the slowest dilution

rate (0.07 d-1

), compared with the Fe-replete chemostat where the cell density was high

across all dilution rates (Figure 2.2). Chl a quota was highest at 0.07 d-1

for both iron

concentrations; however, Chl a quota in Fe-replete conditions was approximately five

times higher than Fe-limited conditions (Table 2.1). Overall Fe-replete cells were larger

in comparison with Fe-limited cells although the trend for increase in cell size with

decrease dilution rate was the same for both iron conditions.



40

Figure 2.2 Growth of M. aeruginosa PCC 7806 in (A) Fe-limited and (B) Fe-replete chemostats at different dilution rates Dashed lines indicate that cultures have reached steady-state. Sampling points for Fe-limited (Day 40) and Fe-replete (Day 42) are indicated by arrows.



41

Table 2.1 Summary of the physiological changes to M. aeruginosa under iron and growth rate control

D (d-1) Chl a (µg mL-1) Cell size (µm) QMC (fg cell-1)

Fe-limited Fe-replete Fe-limited Fe-replete Fe-limited Fe-replete

0.07 0.04 ±

0.02

0.10 ±

0.14

4.01 ±

0.03

4.35 ±

0.10

Tot 63.34

Int 59.24

Ext 4.10

Tot 41.39

Int 41.39

Ext nd

0.15 0.04 ±

0.02

0.20 ±

0.05

4.04 ±

0.05

4.27 ±

0.06

Tot 57.27

Int 55.63

Ext 1.64

Tot 41.52

Int 41.52

Ext nd

0.30 0.04 ±

0.03

0.40 ±

0.13

3.94 ±

0.07

4.15 ±

0.16

Tot 66.93

Int 65.54

Ext 1.39

Tot 22.71

Int 22.71

Ext nd

0.45 0.04 ±

0.01

0.60 ±

0.05

3.89 ±

0.09

4.08 ±

0.03

Tot 62.50

Int 60.97

Ext 1.53

Tot 17.90

Int 17.90

Ext nd

Tot: total MCYST; Int: intracellular MCYST; Ext: extracellular MCYST; nd: not detected

Microcystis cells were also heavier as a consequence of increasing iron

availability and would settle at the bottom of the culturing vessels while their

counterparts remained dispersed throughout the culture. Under iron-limited conditions,

total MCYST content was similar across all growth rates however had increased with

decreasing dilution rates under replete-iron conditions (Table 2.1). Interestingly

extracellular MCYST was not detected from any of the iron-replete samples.

Microcystin analysis

Iron availability and growth rate effects on toxin production was examined in both

iron conditions by monitoring the level of toxin extracted from cells (intracellular) as

well as the level of toxin in the surrounding media (extracellular). Although extracts

were tested against multiple MCYST standards for the LC/MS runs, only MCYST-LR

and [D-Asp3]MCYST-LR were detected in M. aeruginosa PCC 7806, unanimous with

previous studies (Wiedner et al., 2003, Downing et al., 2005) of MCYST isoforms

reported for this strain.



42

In this study, total microcystin (MCYSTtotal = Intracellular + Extracellular

MCYST; MCYST-LR + [D-Asp3] MCYST-LR) from chemostat samples are presented

in Figure 2.3; MCYST cell quotas were higher under Fe-limited than Fe-replete

conditions across all dilutions tested. Under iron limitation, the dilution rate did not

appear to influence the MCYST quota, which averaged ~60 fg/cell, however in the iron-

replete samples, MCYST quota was affected as there was a trend for increased MCYST

as dilution rates decreased with the highest level of 40 fg/cell recorded for the 0.07 d-1

growth rate (Figure 2.3).

Figure 2.3 Total MCYST detected at different dilution rates Total MCYST is the sum of

intracellular and extracellular MCYST fractions from Fe-limited samples () and the Fe-replete chemostat (). Error bars represent standard deviation from triplicate samples; asterisks represent statistical significance P < 0.05.

When the MCYSTtotal was separated into intracellular/extracellular fractions and

into the two detected isoforms, dilution rates did not affect MCYSTint under Fe-limited

conditions (Figure 2.4 A), however it did for the MCYSText which increased with

decreasing dilution rate (Figure 2.4 B) although the ratio of MCYST-LR to [D-Asp3]

MCYST-LR remained approximately 2.5 times higher under iron limitation, this ratio



43

fell to ~1.5x higher in the Fe-replete condition.

Figure 2.4 (A) Intracellular and (B) Extracellular MCYST quota in Fe-limited chemostat cultures.The average MCYST-LR (Blue) and [D-Asp3] MCYST-LR (Pink) quotas are presented with standard deviations indicated by the error bars (n = 3). Asterisks represent statistical significance P < 0.0001.

On the other hand, the MCYSTint content was lower across all dilution rates of the

Fe-replete cells compared to Fe-limited cells (Figure 2.5), as well as a trend for

increased MCYST levels at decreasing dilution rates, i.e. MCYST levels increased as

the growth rate slowed towards stationary phase, was also observed. [D-Asp3] MCYST-

LR levels were also lower under iron-replete conditions but were not significantly



44

different across the tested dilution rates. The ratio of MCYST-LR to [D-Asp3] MCYST-

LR averaged approximately 5x higher Furthermore, extracellular MCYST-LR and [D-

Asp3] MCYST-LR were not detected across the all the growth rates in the iron-replete

samples.

Figure 2.5 Total intracellular MCYST quota in Fe-replete chemostat cultures. The average MCYST-LR (Blue) and [D-Asp3] MCYST-LR (Pink) quotas are presented with standard deviations indicated by the error bars (n = 3). Extracellular MCYST was below the detection limit for all growth rates in the Fe-replete samples.

Oxidative stress response at different Fe concentration and growth rates

Majority of oxidative damage within the cells are generated by the photosynthetic

machinery, however iron limitation can disrupt the electron flow through during

photosynthesis, thus generate reactive oxygen species (ROS), inducing oxidative stress.

The difference in oxidative stress between growth rates was detected by fluorescein

assay coupled with flow cytometry. Fluorescence measurements were taken at 530 nm,

ROS was detected in all cells labelled with H2DCFDA.



45

Figure 2.6 Differences in cellular oxidative stress at different growth rates caused by culturing in (A) Fe-limited and (B) Fe-replete chemostats. Histograms are assigned different colours for different growth rates: red (0.07 d

-1), blue (0.15 d

-1), orange (0.30 d

-1)

and green (0.45 d-1

). Cells were incubated with H2DCFHDA for one hour then DCF (fluorescein) fluorescence is measured in a flow cytometer at 530 nm indicating the presence of ROS within the cells. The dashed line represents the origin where peak shifts to the right indicate increases in ROS and therefore oxidative stress.

In the Fe-limited chemostat samples, the 0.07 d-1

growth rate exhibited the highest

fluorescence intensity followed by 0.15 d-1

, while 0.30 and 0.45 d-1

had similar

fluorescence intensities (Figure 2.6 A). Conversely, ROS fluorescence was less in the

iron-replete chemostat cultures than the iron-limited cultures across all growth rates, as

such were not under as much oxidative stress. ROS level differences were also less

distinct between the growth rates of the iron-replete samples (Figure 2.6 B), however

had displayed the same pattern as iron-limited cells, where slower growth rates had the

most ROS, therefore under the most oxidative stress.

Chemostat cells from the different dilution rates and iron conditions were also

subjected to additional oxidative stress using hydrogen peroxide to examine its response

over 30 minutes. Figure 2.7 shows the response of Fe-limited cells to H2O2 addition at

different growth rates, strong peak shifts were observed in 0.07 d-1

growth rate in the

duration of the incubation and to a lesser extent in 0.15 d-1

, however not at the faster

A B 0.07 d-1

0.15 d-1

0.30 d-1

0.45 d-1



46

growth rates. These shifts signified that H2O2 induced further oxidative stress in cells at

the lower dilution rates but not at the higher dilution rates. In contrast, when iron-replete

samples were exposed to H2O2, peak shifts were observed in all growth rates (Figure

2.8) suggesting that the MCYST content of Fe-replete cells was unable to unable to

neutralise the ROS generated when H2O2 reacted with cellular components resulting in

oxidative stress. Furthermore, growth rates did not appear to affect the response to

oxidative stress induced by additional H2O2.

Figure 2.7 Response of M. aeruginosa from different growth rates to oxidative stress induced by H2O2 under Fe-limited conditions. Initial measurements (time 0) are taken prior to incubation with 4 mM H2O2 are indicated by the black lines. Changes to intracellular ROS levels were inferred by monitoring DCF fluorescence at 10 minutes (red lines) and 30 minutes (blue lines) after incubation.

1 0 2 1 0 3 1 0 4 1 0 50

2 0

4 0

6 0

8 0

1 0 0

F lu o re s c e n c e in te n s ity

% o

f P

op

ula

tio

n

1 0 2 1 0 3 1 0 40

2 0

4 0

6 0

8 0

1 0 0


% o

f P

op

ula

tio

n

1 0 2 1 0 3 1 0 40

2 0

4 0

6 0

8 0

1 0 0


% o

f P

op

ula

tio

n

1 0 2 1 0 3 1 0 40

2 0

4 0

6 0

8 0

1 0 0


% o

f P

op

ula

tio

n

0 .0 7 d- 1

0 .1 5 d- 1

0 .3 0 d- 1

0 .4 5 d- 1

L o w -F eFe-Limited



47

Figure 2.8 Response of M. aeruginosa from different growth rates to oxidative stress induced by H2O2 under Fe-replete conditions. Initial measurements (time 0) are taken prior to incubation with 4 mM H2O2 are indicated by the black lines. Changes to intracellular ROS levels were inferred by monitoring DCF fluorescence at 10 minutes (red lines) and 30 minutes (blue lines) after incubation.

Discussion

The physiological changes in the MCYST-producing M. aeruginosa PCC 7806

was investigated in Fe-limited and Fe-replete chemostats at different dilution rates.

Steady-state cell concentrations, determined by the balance established between the

wash-out rate and cellular growth rate in the reactor, increased with decreasing growth

rates (i.e. at lower dilution rates). These observations were consistent with previous

chemostat studies (Oh et al., 2000, Dang et al., 2012a). This trend resembled

conventional batch culture growth curves where low cell densities seen at high dilution

1 0 1 1 0 2 1 0 3 1 0 40

2 0

4 0

6 0

8 0

1 0 0


% o

f P

op

ula

tio

n

1 0 1 1 0 2 1 0 3 1 0 40

2 0

4 0

6 0

8 0

1 0 0


% o

f P

op

ula

tio

n

1 0 1 1 0 2 1 0 3 1 0 40

2 0

4 0

6 0

8 0

1 0 0


% o

f P

op

ula

tio

n

1 0 1 1 0 2 1 0 3 1 0 40

2 0

4 0

6 0

8 0

1 0 0


% o

f P

op

ula

tio

n

H ig h -F e

0 .0 7 d- 1

0 .1 5 d- 1

0 .3 0 d- 1

0 .4 5 d- 1

Fe-Replete



48

rates are associated with early (exponential) stages of growth, while high cell densities

achieved at low dilution rates are associated with the later (stationary) stages of batch

growth (Lyck, 2004). It is important to note that for Fe-limited chemostat cultures, the

degree of Fe limitation is a function of the dilution rate. For example, cultures grown at

low dilution rates experience a higher degree of Fe stress. In contrast, the degree of Fe

stress in Fe-replete chemostat cultures is minimal since the overall Fe concentration

remains high even in cultures grown at the lowest dilution rates. However, other

nutrients may become the limiting factor in Fe-replete chemostats, e.g. N or P or even

light.

Although Chl a content was lower in Fe-limited cultures compared to Fe-replete

cultures across growth rates tested, all cultures remained green. This feature appears to

be specific to the M. aeruginosa 7806 strain, as noted in previous Microcystis culturing

studies (Alexova et al., 2011a). The increased cell size observed in cultures grown under

decreasing dilution rates is consistent with the division rate in the reactor since fewer

divisions mean cells have more time to grow. This is also aligned with previous

Microcystis studies which suggested that cell size reflects the physiological state of the

cell where stressed cells are generally larger than unstressed cells (Long et al., 2001,

Krüger and Eloff, 1981). Interestingly however, our study also found that cell diameters

were smaller in Fe-limited (i.e. Fe-stressed) cultures compared to Fe-replete cultures

grown at the same dilution rate. This may be a result of altered protein compositions as

part of adaptations to lower Fe availability.



49

The relationship between MCYST production and growth rate changes

under different Fe availability

Cellular MCYST concentration under Fe-limited chemostat conditions was not

influenced by growth rate. These results were surprising given that previous studies

involving N-limited chemostats concluded that MCYST production was a direct

function of cell growth rate (Long et al., 2001). Interestingly, we observed an inverse

relationship between cellular MCYST concentration and growth rate in Fe-replete

cultures, which is consistent with batch culture findings and in situ Microcystis blooms,

where maximum MCYST concentrations are recorded at the end of the growth cycle

(i.e. lowest growth rate) or during bloom disintegration (Shirai et al., 1991). The Fe-

MCYST relationship observed here could be the result of growth in favorable versus

unfavorable conditions (Lyck, 2004). For example, in Fe-replete (favorable) conditions,

resources and metabolic processes are likely to be directed towards cell division.

However, in Fe-limited (unfavorable) conditions, resources are diverted to pathways

that increase cell fitness, such as the production of stress protection proteins and

MCYST. It is important to note that our study only measured unbound MCYST, which

may under represent the true total MCYST content since membrane and protein bound

MCYST constitutes a significant proportion of toxin within the cell (Meissner et al.,

2013). However, from a water quality perspective, membrane or protein bound MCYST

is considered to be inaccessible and unable to react with hepatocytes.

Role of MCYST in oxidative stress protection

One of the physiological effects of Fe limitation is increased ROS generation

which leads to oxidative stress (Latifi et al., 2009). As discussed in detail elsewhere



50

(Dang et al., 2012a), Fe availability in our study was controlled by both the initial Fe

concentration in the medium (i.e. 100 nM versus 1,000 nM) and the dilution rate at

which fresh medium was replenished (i.e. 0.07 d-1

, 0.15 d-1

, 0.30 d-1

and 0.45 d-1

).

Increased ROS production was observed in Fe-limited cultures and to a lesser extent, in

Fe-replete cultures grown at the lower dilution rates. The high MCYST quota in Fe-

limited cultures compared to Fe-replete cultures may provide partial explanation for

their different response to added H2O2. The in vitro binding of MCYST to intracellular

proteins reported by Zilliges et al (2011) suggested a functional role in protecting

proteins from oxidative damage. In agreement with this, we observed that Fe-limited

cultures were more resistant to H2O2 than Fe-replete cultures when grown at dilution

rates where QMCYST was significantly higher. These results suggest that MCYST may

indeed protect cells against oxidative stress. Interestingly, our study revealed that there

is a limit to the degree of oxidative stress protection afforded by MCYST, with cultures

grown at low dilution rates (0.30 d-1

and 0.45 d-1

) displaying increased DCF

fluorescence despite having high MCYSTint quotas. Overall these results suggest that

MCYST plays a role in protecting cells against oxidative stress, however the importance

of alternate ROS defense mechanisms should not be discounted.

Putative function of extracellular MCYST

In this study extracellular MCYST was only observed in Fe-limited cultures.

Microscopic inspection of cells throughout the experiment showed that they remained

intact (data not shown), suggesting that an active transport pathway is responsible for

the export of MCYST under these conditions. This hypothesis is in line with the

observed up-regulation of transporter proteins in Fe-limited cultures (as discussed



51

below).

Although MCYSText usually comprises only a small proportion of the total

QMCYST (this study and (Wiedner et al., 2003, Orr and Jones, 1998, Long et al., 2001), its

presence in unlysed cultures suggests a possible extracellular role for the toxin. Several

studies propose that MCYST may function as a siderophore (Shi et al., 1995, Utkilen

and Gjolme, 1995), however its weak affinity for Fe renders it an unlikely candidate for

Fe acquisition (Klein et al., 2013). Alternatively, MCYST might play a role in colony

formation by regulating polysaccharide biosynthesis genes (Gan et al., 2012). The

potential role of MCYST in allelopathy was recently examined by Phelan and Downing

(2014) who observed that exogenous MCYST taken up by non-toxic Synechocystis cells

resulted in impaired PSII activity in the thylakoid membrane. Microcystin released from

the cell may also act as a signalling molecule triggering MCYST production in

surrounding cells and enhancing the overall fitness of the colony and greater bloom

population (Schatz et al., 2007) (although MCYSText levels are typically highest

following cell lysis and bloom collapse (Orr and Jones, 1998, Li et al., 2009)). This

signalling effect was shown recently when free MCYST taken up in a receptor-mediated

manner triggered a signalling cascade in the pksI-pskIII gene cluster for secondary

metabolites in M. aeruginosa (Makower et al., 2015). In light of our results and

previous reports in the literature, we propose that MCYSText is likely to function as a

signalling molecule, which stimulates the production of MCYSTint, which in turn,

provides increased protection against ROS under Fe limitation. The allelopathic activity

of MCYST is likely to be a fortuitous secondary function.



52

Conclusion

The physiological responses to Fe limitation at different growth rates were

examined through the use of chemostats. Under Fe-limited conditions, although Fe-

limited cells were smaller, MCYST production was higher than when cells were grown

in Fe-replete conditions.

Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron

concentration

53

Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in

differing iron concentration

Chapters 2 and 3 have been published as: Physiological and proteomic responses

of continuous cultures of Microcystis aeruginosa PCC 7806 to changes in iron

bioavailability and growth rate. Anna C. Y. Yeung, Paul M. D'Agostino, Anne Poljak,

James McDonald, Mark W. Bligh, T. David Waite and Brett A. Neilan. Applied and

Environmental Microbiology. Accepted 29 July, 2016. doi: 10.1128/AEM.01207-16

Introduction

Iron is a required by cyanobacteria for the functioning of their photosynthetic

machinery, as cofactors and reaction centres of proteases and other enzymes, hence the

bioavailability of iron has a potential of affecting many downstream regulatory

pathways. Majority of the current cyanobacterial proteomic studies have used batch

cultures; however it is difficult to accurately assess the molecular response of cells to a

particular nutrient limitation due to the constantly changing environment of the medium

(since nutrients are constantly depleted as cells grow, hence the environment is under

constant change). As such the proteomic response of M. aeruginosa to iron limitation is


concentration

54

assessed at four growth rates created under chemostat conditions.

In this chapter the effects of iron limitation at different growth rates on changes to

the proteome is examined and the results of this chemostat study are compared with

earlier proteomic results under batch conditions (Alexova et al., 2011c, Tonietto et al.,

2012, Alexova et al., 2016)

Materials and Methods

Experimental design

Figure 3.1 Schematic presentation of the experimental design for M. aeruginosa PCC

7806 iTRAQ studies. See in text for description.A schematic of the experimental design

is presented in Figure 3.1. Protein extractions were performed on steady-state cells from

the chemostat experiments in Chapter 2. Two individual 4-plex iTRAQ studies were

conducted: Fe-limited (100 nM Fe) chemostat was designated iTRAQ-limited and the

Fe-replete (1000 nM Fe) chemostat was designated iTRAQ-replete. Protein extracted


concentration

55

from biological replicates were pooled for each dilution rate and labelled with different

iTRAQ tags. The lowest dilution rate, 0.07 d-1

, was labelled with iTRAQ tag 114, 0.15

d-1

with T115, 0.30 d-1

with T116, and the highest dilution rate, 0.45 d-1

, was labelled

T117. Technical replicates on tandem mass spectrometry were run for both iTRAQ

experiments where the highest dilution was used as the control treatment for each

chemostat study.

Strain and culturing condition

Please see Chapter 2, page 34.

Protein extraction and visualisation

A comparison of different protein extraction buffers and lysis methods is detailed

in Appendix B, which produced the optimised protein extraction protocol used in this

study. Microcystis chemostat cells were harvested by centrifuging 70 mL of culture in a

Beckman Coulter Allegre X-12 centrifuge (5000 × g, 15 min, 20 ºC), washing the cell

pellet with fresh media and resuspending in 500 µL of extraction buffer (50 mM

HEPES pH 7.0, 0.1% SDS, 0.01% Triton-X 100, MQ) (Battchikova et al., 2010)

supplemented with 1 mM PMSF (Phenylmethylsulfonyl Fluoride) as a protease

inhibitor. Cells were partially lysed using three freeze-thaw cycles alternating liquid

nitrogen and 37oC water bath, followed by sonication on ice with a Branson Sonifier,

USA (25 % amplitude, 3 x 30 s). Cell extracts were centrifuged (14,000 × g, 10 min,

20ºC) and the supernatant transferred to a clean 1.5 mL polypropylene tube. The cell

pellet was further extracted (500 µL extraction buffer) and the sonication process

repeated. The supernatant fractions were combined and biological triplicates were

pooled for precipitation with nine volumes of ice-cold acetone (overnight at 4 ºC on

ice). Protein pellets were air-dried then resuspended in dissolving buffer (50 mM


concentration

56

NaHCO3, 0.08 % SDS, MQ) for quantification by BCA analysis. A portion of each

sample (15 µg) was separated by SDS PAGE (NuPAGE 4-12 % Bis-Tris gradient gels,

Invitrogen, USA), and visualized by colloidal Coomassie staining (Dyballa and

Metzger, 2009).

iTRAQ labelling

Two individual 4-plex iTRAQ experiments were conducted corresponding to Fe-

limited (iTRAQ-limited) and Fe-replete (iTRAQ-replete) chemostat experiments

(Figure 3.1). iTRAQ labelling was carried out using the manufacturer’s instructions and

a previously published approach (Williams et al., 2010). In brief, 100 µg of protein was

reduced using 2 mM tris-(2-carboxyethyl) phosphine (TCEP, 60°C, 1 h) and alkylated

with 2 mM iodoacetamide (ambient temperature, 10 min). Proteins were then digested

overnight with trypsin (~18 h). Immediately prior to the addition of iTRAQ reagents, 1

µL Na2CO3 (500 mM) was added to ensure a basic pH (~8.5). The iTRAQ labels were

each resuspended in 70 µL of isopropanol. Each chemostat dilution rate, 0.07 d-1

, 0.15

d-1

, 0.30 d-1

, and 0.45 d-1

, had the unique iTRAQ labels, 114, 115, 116, and 117,

respectively. Samples were incubated with the iTRAQ labels at ambient temperature for

1 h after which time the labeled samples were combined.

The combined labeled peptide mixture was passed through a cation exchange

column (Applied Biosystems) to remove excess reagents and detergent. Following the

off-line strong cation exchange, the labeled peptides were dried under vacuum and

resuspended in 500 µL of 0.2% heptafluorobutyric acid (HFBA)/water. The sample was

passed through an off-line C18 desalting cartridge (Peptide MacroTrap, Michrom

Bioresources) and eluted with 500 µL CH3CN:water:formic acid (50:50:0.1, v:v:v),

followed by 200 µL neat CH3CN. The resulting eluent was dried and the pellet


concentration

57

dissolved in 0.05% HFBA/0.1% formic acid (400 µL).

Sample preparation and mass spectrometry analysis

2D LC/MS/MS mass spectrometry was performed on an API QStar Elite hybrid

tandem mass spectrometer (Applied Biosystems, Foster City, CA) by Dr Anne Poljak

(Biomolecular Mass Spectrometry Facility, UNSW, Australia). Peptides (3-5 µg total

load) were initially captured onto a SCX micro column (0.75 ~20mm, Poros S10,

Applied Biosystems) and the eluant from multiple salt elution steps (unbound load, 5,

10, 15, 20, 25, 30, 40, 50, 100, 250, 500 and 1,000 mM ammonium acetate) captured

and desalted on a C18 pre-column cartridge (500 µm 2 mm, Michrom Bioresources).

After a 10 min wash the pre-column was switched (Switchos) into line with a fritless

analytical column (75 µm 12 cm) containing C18 reverse phase packing material

(Magic, 5 μm, 200Å) (Gatlin et al., 1998). Peptides were eluted using a 90 min gradient

of buffer A (2% (v/v) CH3CN, 0.1% formic acid) to 45% buffer B (80% (v/v) CH3CN,

0.1% formic acid) at ~300 ml/min. An electric current (2,300 V) was applied through a

low volume tee (Upchurch Scientific) at the column inlet and the outlet positioned ~1

cm from the orifice of the mass spectrometer. Positive ions were generated by

electrospray and the QStar operated in information dependent acquisition mode (IDA).

A TOF MS survey scan was acquired (m/z 350-1700, 0.75 s) and the three largest

multiply charged ions (counts > 20, charge state +2 to +4) sequentially selected by Q1

for MS/MS analysis. Nitrogen was used as collision gas and an optimum collision

energy automatically chosen (based on charge state and mass). Tandem mass spectra

were accumulated for up to 2.5 s (m/z 65-2,000) with two repeats. Automated online 2D

LCMS/MS was carried out (with two technical replicates for each iTRAQ study) and


concentration

58

the combined data processed using ProteinPilot software V 4.5 (ABSciex) against a

database library comprised of available M. aeruginosa protein sequences from NCBI

(downloaded: Feb/2014). A P < 0.05 was used as the cutoff for accepting statistically

significant changes in protein expression level. False Discovery Rate (FDR) reports

were generated using a Detected Protein Threshold greater than 1.00 (equivalent to a

90% confidence level) and a ProtScore of 2.00. The mass spectrometry proteomics data

were deposited into the ProteomeXchange Consortium (Vizcaino et al., 2014) via the

PRIDE partner repository with the dataset identifier PXD002930.

Results

Core proteomes of Fe-limited and Fe-replete chemostat changes

The available protein sequences of M. aeruginosa PCC7806 (4923 sequences) and

M. aeruginosa NIES-843 (5989 sequences) were downloaded from BLAST and used to

construct the search database for the iTRAQ analysis. A total of 506 proteins from Fe-

limited cultures and 323 proteins from Fe-replete cultures were identified,

corresponding to proteome coverage of 9.7% and 6.2%, respectively (Table 3.1).

Proteins were categorized into functional groups according to CyanoBase

(http://genome.microbedb.jp/cyanobase, Figure 3.2), where the majority of identified

proteins belonged to the transcriptional and translational functional group (Fe-limited:

16.6%; Fe-replete: 19.8%) and the energy metabolism functional group (Fe-limited:

14.0%; Fe-replete: 14.9%). There was a large proportion of the identified proteome (Fe-

limited: 26%; Fe-replete: 22%) that grouped to hypothetical proteins or proteins with

unknown function.


concentration

59

Figure 3.2 Summary of the proteins identified in continuous cultures of M. aeruginosa PCC 7806 in (A) Fe-limited and (B) Fe-replete chemostats. Proteins were assigned into functional groups according to annotations on CyanoBase.

Table 3.1 M. aeruginosa iTRAQ overview from Fe-limited and Fe-replete chemostats.

Fe-limited (100 nM) Fe-replete (1000 nM)

Spectra identified 19495 15131

Total spectra (%) 94.2 90.2

Distinct peptides 4244 3421

Identified proteins 515 349

A

B


concentration

60

The ProteinPilot software used for analysis produces an automated list of detected

proteins, where the thresholds for peptide identification was already set to ≥ 95%

confidence, likewise the Unused ProtScore – for quantified proteins – was set to ≥ 1.3

(equivalent to ≥ 95% confidence, i.e. no protein in the list has more than 5% chance of

being incorrectly assigned). For the change in abundance to be considered significant,

the quantified protein must have a p-value ≤ 0.05 and have a ratio ≥ 1.2 (for higher

abundance) or ≤ 0.82 (for lower abundance) when compared to the reference condition

(iTRAQ T114). Although the changes to patterns of expression remain the same, the

ratio values which give the protein expression compared to control reported by

ProteinPilot can often be exaggerated, therefore proteins are considered to have a

significant fold change if the Log2 of the ratio were ≥ 0.263 for a significant increase in

abundance, or ≤ -0.286 for a significant decreased in abundance when compared to the

reference condition.

Under Fe-limited conditions, there were a total of 145 significantly differentially

regulated proteins relative to the highest dilution (or specific growth) rate (0.45 d-1

),

with 32, 107 and 78 changes observed in cultures grown at dilution rates of 0.30 d-1

,

0.15 d-1

and 0.07 d-1

, respectively (Table 3.2). Under Fe-replete conditions, only 13

proteins were differentially regulated in cultures grown at different dilution rates (Table

3.3), with 3, 6 and 8 changes observed in cultures grown at dilution rates of 0.30 d-1,

0.15 d-1

and 0.07 d-1

, respectively. Proteins that displayed a change in abundance within

Fe-replete conditions belonged solely to the energy metabolism and transport categories

(Figure 3.3). The full description of protein changes in Fe-limited and Fe-replete

chemostats is provided in Table 3.2 and Table 3.3 respectively.


concentration

61

Overview of the functional categories affected by growth rate at different

iron availabilities

Under iron limitation, the protein categories most affected by growth rate

belonged to photosynthesis and respiration; cellular and regulatory processes;

transcription and translation processes (Figure 3.3A). Proteins from these groups

showed a decrease in abundance at lower dilution rates towards 0.07 d-1

. Transport and

binding proteins was the only category where proteins have increased in abundance

across all dilution rates compared to the 0.45 d-1

, suggesting that cell permeability may

be increased under iron limitation to permit the exchange of nutrients and other possible

signal molecules during cell growth.

However under Fe-replete conditions, the protein categories affected across the

growth rates were not as evident as the Fe-limited condition since far fewer proteins

were observed to have significantly changed in abundance when compared to the

reference growth rate (D = 0.45 d-1

) (Figure 3.3 B). Likewise transporter and binding

proteins were not observed to have differed in expression under Fe-replete conditions

(Figure 3.3 B) may also provide partial explanation for the lack of detectable MCYST

in the external media as seen in Chapter 2.


concentration

62

Figure 3.3 Regulatory processes affected by growth rate in (A) Fe-limited and (B) Fe-replete chemostats. Box plots represent the distribution of proteins with significant fold changes for each growth rate compared to D = 0.45 d

-1 for each functional category.

Overall placement of the box above or below 0 conveys either increase or decrease in abundance of proteins from that functional category respectively. The extent of the whiskers represents the minimum and maximum fold change of the proteins for that sample. Note that data points have been included in B to reflect the fewer number of changes detected in the Fe-replete study.


concentration

63

Growth rate influenced protein changes

Under Fe-limited conditions, there were 145 significantly differentially regulated

proteins relative to the control (0.45 d-1

), where the most change was found in 0.15 d-1

with 110 proteins, followed by 0.07 d-1

with 79 proteins, and finally 0.30 d-1

with 33

proteins (Table 3.2). However in the Fe-replete iTRAQ experiment, only 13 proteins

were found to be significantly differentially expressed between the growth rates (Table

3.3) suggesting that less proteins are differentially regulated in Fe-replete growth of the

cell.

Energy metabolism proteins

Proteins within this category are related to the general metabolic pathways that

affect growth and respiration. The majority of protein changes within this category were

observed in cultures grown at the lower dilution rates (0.15 d-1

and 0.07 d-1

). Under Fe-

limited conditions, proteins from Photosystem I (PSI), Photosystem II (PSII) and

phycobilisomes were significantly down-regulated in cultures grown at lower dilution

rates compared to 0.45 d-1

condition (Figure 3.4; Table 3.2). Additionally, under Fe-

limited conditions, carbon fixation and glycolysis proteins were mostly down-regulated,

with the exception of PHA-specific acetyoacteyl-CoA reductase (PhaB) and

phosphoenolpyruvate synthase (PpsA) (Figure 3.4). Conversely, under Fe-replete

conditions, allophycocyanin (ApcB) and ATPase (AtpD) were the only proteins down-

regulated, but this was only observed in cultures grown at the 0.15 d-1

dilution rate.


concentration

64

Figure 3.4 Heat maps of Fe-limited and Fe-replete protein changes arranged into functional categories. Each column represents the dilution rates 0.07 d

-1, 0.15 d

-1 and

0.30 d-1

, respectively. The scale of this heat map is given as log2 fold change, ranging from -5 (red) to +5 (green) relative to 0.45 d

-1. Insignificant changes in protein abundance (P >

0.05) are coloured grey.


concentration

65

Amino acid metabolism

Proteins within this category are involved in the regulation of amino acid

bisynthesis. The majority of protein changes within this category were observed in Fe-

limited cultures grown at the 0.15 d-1

dilution rate (Figure 3.4). Under these conditions,

six of these proteins were up-regulated by at least 2-fold, including proteins involved in

aspartate, arginine, cysteine, glycine, isoleucine, and valine biosynthesis.

Cellular processes

Proteins within this category are mainly involved in redox regulation. The

majority of protein changes within this category were observed in Fe-limited cultures,

with distinct expression profiles observed for each dilution rate. Peroxiredoxins and the

universal stress protein (Usp) were down-regulated in Fe-limited cultures grown at the

0.07 d-1

dilution rate. Flavodoxin was the only protein in this category to be up-

regulated under the same growth conditions (Figure 3.4). Fe-limited cultures grown at a

dilution rate of 0.15 d-1

had increased levels of redox reaction and oxidative stress

recovery proteins, such as superoxide dismutase (SOD), stationary phase protection

protein (Dps) and thioredoxin. On the other hand, cultures grown at a dilution rate of

0.30 d-1

had increased levels of flavodoxin and decreased levels of the CBS-fused CP12

polypeptide.

Genetic information processing - transcription and translation proteins

The majority of proteins changes within this category were observed in Fe-limited

cultures, with both 30S and 50S ribosomal subunits heavily down-regulated in cultures

grown at the lower dilution rates. In particular, Fe-limited cultures grown at dilution

rates of 0.15 d-1

and 0.07 d-1

displayed the most marked reduction in ribosomal protein

abundance, with many ribosomal subunits down-regulated by over 3-fold. No


concentration

66

significant changes in the expression of ribosomal proteins were observed in Fe-replete

cultures (Figure 3.4).

GroS chaperone and RNA-binding proteins were up-regulated in Fe-limited

cultures grown under the 0.15 d-1

dilution rate, while proteases were down-regulated

under these conditions (Figure 3.4; Table 3.3). In Fe-replete cultures grown at dilution

rates of 0.07 d-1

and 0.30 d-1

, there was a 3-fold increase in DnaK (Figure 3.4; Table

3.3).

Transport and binding proteins.

Proteins within this category are involved in the transport of molecules across cell

membranes. The majority of protein changes within this category were observed in Fe-

limited cultures, with significant up-regulation occurring in cultures grown at the 0.15 d-

1 dilution rate compared to all other growth conditions (Figure 3.4). As shown in Table

3.2 these up-regulated transporter proteins included the nitrate permease (NrtA) from

the nitrate/nitrite transport system (increased in all Fe-limited cultures), an ABC-type

urea transporter (increased in cultures grown at the 0.15 d-1

dilution rate) and an Fe

transport protein (increased in cultures grown at 0.15 and 0.07 d-1

dilution rates). By

comparison, the Fe uptake protein was the only transporter protein that increased in

abundance in Fe-replete cultures grown at the 0.07 d-1

dilution rate (Table 3.3).

Other category proteins

Proteins that were included in this category usually have multiple functions such

as Gvp which not only for the structure of the cell but also controls the buoyancy of the

cell within the water column. Cyanophycin, a nitrogen-rich storage material found in

bacteria, was also down-regulated under iron limitation further supporting the

relationship between iron and nitrogen utilisation.


concentration

67

Hypothetical proteins

There were six hypothetical proteins denoted A to F (Table 3.2) that were

differentially expressed in the Fe-limited culture for which no homologues were found

in the NIES 843 genome. The amino acid sequences of these proteins were searched in

the Pfam database (http://pfam.xfam.org) to identify conserved domain features

belonging to any protein families. Of these unique hypothetical proteins, three were

found to contain conserved domains: Hypothetical protein A contained a Laminin G

domain which has a putative role in signal transduction, migration, and differentiation;

Hypothetical protein B contained Peptidase S47 domain which may act as molecular

chaperone; and Hypothetical protein E contained a PAP2 haloperoxidase domain which

is involved in the biosynthesis of halogenated natural products. Meanwhile in the Fe-

replete cultures, two hypothetical proteins were differentially expressed but Pfam

searches did not reveal any conserved domains within these proteins.

Discussion

Global proteomic and physiological response to Fe-limitation at different

growth rates

Past studies on Synechocystis have revealed that elements such as copper and iron

can alter the expression of primary metabolism proteins, as well general stress proteins

such as proteases, chaperones and sigma factors (Castielli et al., 2009). Recent studies

on Synechocystis and Anabaena have demonstrated that Fe limitation leads to the

expression of the iron stress induced protein (IsiA) and flavodoxin (IsiB), which act to

protect and support the cyanobacterial photosystem (Hernández-Prieto et al., 2012,

Latifi et al., 2005). Although this study identified IsiA in the Fe-limited core proteome,

http://pfam.xfam.org/


concentration

68

significant changes in its abundance was not observed at the different dilution rates.

This suggests that IsiA expression in M. aeruginosa PCC 7806 is a response to Fe

limitation and not a function of growth rate. Unsurprisingly, the IsiA protein was not

identified in the Fe-replete core proteome.

In order to alleviate the damaging effects of Fe limitation, photosynthetic

organisms activate flavodoxin proteins as an electron carrier substitute to the more Fe-

rich ferredoxin (Fromme et al., 2003). In line with down-regulation of ferredoxin

proteins and up-regulation of flavodoxin proteins was observed in the Fe-limited

chemostats. Similar results have been observed for previous Fe-limited batch cultures

during late-log to early-stationary growth phase (Alexova, 2010).

In Fe-limited chemostats, the largest number of proteomic changes occurred in

cultures grown at the lower dilution rates, which mimic the conditions of late growth

phase batch cultures. A significant reduction in the abundance of photosynthetic

proteins, including pigment and light-harvesting proteins, in these cultures compared to

Fe-limited cultures grown under higher dilution rates.

Thylakoid membrane remodeling is quite common during cell growth and

acclimation to the environment (Gan et al., 2014). In agreement with this, a reduction in

PSII protein expression was observed in Fe-limited cultures grown at low dilution rates

together with reductions in cellular Chl a concentration as well as cell density. The

down-regulation of photosynthesis proteins and pigments under Fe-limitation has a

negative impact on energy metabolism due to the reduction in light absorption (Wang et

al., 2010a).

Iron stress also has an indirect effect on growth as RuBisCo and glucose 6-

phosphate proteins, which form an integral part of the glycolysis pathway, are reduced


concentration

69

under Fe-limiting conditions (Fromme et al., 2003). We also observed this phenomenon

in Fe-limited M. aeruginosa chemostats. A reduction in GroEL chaperonin proteins is

likely to affect the folding of RuBisCo since the assembly process is dependent on these

chaperones (Liu et al., 2010). Taken together, these processes are likely to affect cell

growth and proliferation in chemostats in a comparable manner to the physiological

changes observed in batch cultures of M. aeruginosa under Fe and N limitation

(Alexova et al., 2011a, Alexova et al., 2016).

The majority of ribosomal proteins were down-regulated in our Fe-limited

cultures as previously observed in Synechocystis cells under N, P or Fe depletion

(Wegener et al., 2010). However, RNA-binding proteins were up-regulated under the

same conditions. These results suggest that energy resources are directed towards the

stabilization of mRNA transcripts or some other form of post-transcriptional control

rather than to the synthesis of new proteins (Takayama and Kjelleberg, 2000, Dressaire

et al., 2013).

Under nutrient replete conditions, proteins for nitrogen and carbon assimilation

generally follow the same pattern of regulation since these pathways are tightly

coordinated (Wang et al., 2010a); that is, they decline when N and C concentrations are

depleted. This was also observed in the Fe-limited chemostat cultures as they underwent

metabolic shutdown. The down-regulation of photosystem- and respiration-related

proteins under Fe limitation reduced the overall growth of the cultures compared to their

Fe-replete counterparts. These general housekeeping responses have been well

documented in other cyanobacterial studies in which the effects of light stress and

nutrient limitation were examined (Pandhal et al., 2007, Xing et al., 2008).


concentration

70

Changes to transporter proteins

Microcystis aeruginosa chemostat cultures also responded to Fe limitation by up-

regulating the expression of transporter proteins, with this response likely to lead to

increased import and export of molecules across cell membranes as needed to sustain

the cell. Interestingly, in this study N and Fe transporters were also up-regulated in Fe-

limited cultures, suggesting that these two nutrients interact and co-regulate

photosynthesis, transcriptional regulation and redox control pathways in M. aeruginosa

as they do in Anabaena (Lopez-Gomollon et al., 2007).

The observed presence of MCYSText in Fe-limited but not Fe-replete cultures in

Chapter 2 suggests the activation of a toxin export pathway under Fe limitation.

However, changes in the expression of the putative MCYST ABC transporter, McyH

(Pearson et al., 2004) were not identified. Interestingly, Fe-limited cultures grown at a

dilution rate of 0.15 d-1

had the highest level of MCYSText which corresponded with the

greatest overall increase in transporter proteins. These results suggest that an alternative

active transport pathway for the toxin may exist under certain growth conditions. While

there are presently no MCYST transporter candidates aside from McyH, this is an

interesting topic for future research. An alternative explanation for the high levels of

MCYSText observed in Fe-limited cultures relates to increased expression of the nitrate

transporter (NrtA) under these conditions. Up-regulation of NrtA is likely to raise the

intracellular levels of nitrate and nitrite, which could then be converted into

peroxynitrite via nitrate reductase (Chen et al., 2009b). This reactive species could have

damaging effects on the cell membrane, as well as the photosystem (Chen and Liu,

2015), thus possibly contributing to passive MCYST export.


concentration

71

Conclusion

This chapter followed the changes in the core proteome of M. aeruginosa PCC

7806 grown in Fe-limited and Fe-replete chemostats over a range of growth rates.

Under Fe-limited conditions transporter proteins were up-regulated, suggesting that the

toxin is actively transported across the membrane which may have an extracellular role

under Fe limitation.

Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron concentration

73

Table 3.2 Differentially expressed proteins in M. aeruginosa under Fe-limited chemostats at different dilution rates. Values highlighted in red represent down-regulation while green represent up-regulation of the protein relative to the 0.45 d

-1 (control) condition.

Accession Protein ID 0.07 d-1

P val Log2 fold

0.15 d-1

P val Log2 fold

0.30 d-1

P val Log2 fold

Energy metabolism (Photosynthesis)

MAE_10270 Allophycocyanin subunit alpha (apcA) 0.912 0.0377 -0.133

MAE_10260 Allophycocyanin subunit beta (apcB) 0.215 0.0348 -2.219

MAE_10240 Phycobilisome small core linker polypeptide (apcC)

0.209 0.0107 -2.259 0.146 0.0182 -2.771

MAE_49370 Phycobilisome core-membrane linker polypeptide (apcE)

0.209 0.0001 -2.259 0.256 0.0001 -1.967 0.483 0.0001 -1.050

MAE_21640 Phycobilisome core component (apcF) 0.497 0.0266 -1.010

MAE_24460 Phycocyanin alpha subunit PCA (cpcA1) 0.840 0.0430 -0.253

MAE_48340 Phycobilisome rod-core linker polypeptide (cpcG)

0.302 0.0204 -1.727 2.249 0.0003 1.169

MAE_10220 Photosystem II protein D1 Precursor (psbA1)

0.107 0.0195 -3.229 0.194 0.0118 -2.365

MAE_32990 Photosystem II core light harvesting protein (psbB)

0.078 0.0003 -3.681

MAE_44250 Photosystem II manganese-stabilizing polypeptide (psbO)

0.030 0.0011 -5.076

MAE_50080 Photosystem II extrinsic protein (psbQ) 4.055 0.0116 2.020

MAE_36490 Photosystem II complex extrinsic protein U (PsbU)

3.802 1.927


74

MAE_47560 Photosystem I P700 chlorophyll a apoprotein A1 (psaA)

0.145 0.0010 -2.790 0.132 0.0003 -2.923

MAE_47570 Photosystem I P700 chlorophyll a apoprotein A2 (psaB)

0.082 0.0048 -3.601 0.328 0.0422 -1.608

MAE_23300 Photosystem I subunit II (psaD) 0.078 0.0001 -3.681 0.083 0.0001 -3.588

MAE_47290 Photosystem I subunit III (psaF) 0.066 0.0050 -3.920 0.387 0.0475 -1.369

MAE_43690 Photosystem I subunit XI (psaL) 6.138 0.0441 2.618

MAE_09490 Photosystem I subunit XII (psaM) 0.209 0.0148 -2.259 0.047 0.0011 -4.398

MAE_19230 Apocytochrome f (petA) 2.128 0.0270 1.090

MAE_12570 Ferredoxin-NADP oxidoreductase (petH) 0.177 0.0033 -2.498 0.387 0.0058 -1.369

MAE_50160 F0F1 ATP synthase subunit alpha (atpA) 0.189 0.0004 -2.405

MAE_50150 F0F1 ATP synthase subunit delta (atpD) 0.347 0.0307 -1.528

MAE_50130 F0F1 ATP synthase subunit B' (atpG) 0.120 0.0015 -3.056

Energy metabolism (C-fixation and carbohydrate metabolism)

MAE_47890 Ribulose bisphosphate carboxylase large chain (RubisCo large subunit) (rbcL)

0.069 0.0001 -3.867 0.108 0.0062 -3.242 0.506 0.0029 -0.983

MAE_47870 Ribulose bisphosphate carboxylase small subunit (RubisCo small subunit) (rbcS)

0.055 0.0002 -4.186 0.492 0.0284 -1.023

MAE_25030 NAD(P)-dependent glyceraldehyde-3-phosphate dehydrogenase

0.409 0.0134 -1.289 0.147 0.0001 -2.764 0.479 0.0089 -1.063

MAE_38450 Phosphoribulokinase (prK) 0.126 0.0092 -2.990

MAE_47930 Carbon dioxide concentrating mechanism protein K (ccmK1)

4.488 0.0051 2.166


75

MAE_47910 Carbon dioxide concentrating mechanism protein (ccmM)

0.215 0.0433 -2.219

MAE_50050 PHA-specific acetoacetyl-CoA reductase (phaB)

5.346 0.0438 2.418 6.668 0.0146 2.737

MAE_02620 Phosphoenolpyruvate synthase (ppsA) 2.535 0.0084 1.342 1.380 0.0241 0.465 1.294 0.0276 0.372

MAE_54130 4-alpha-glucanotransferase 0.347 0.0332 -1.528

MAE_20180 Glycogen phosphorylase (glgP) 0.187 0.0001 -2.418 0.575 0.0158 -0.797

MAE_35090 Enolase phosphopyruvate hydratase (eno) 1.923 0.0021 0.943

MAE_34890 Glyceraldehyde 3-phosphate dehydrogenase, type 1 (gap1)

0.308 0.0069 -1.701 0.075 0.0000 -3.747

MAE_30020 Fructose-1,6-/sedoheptulose-1,7-bisphosphatase (glpX)

0.258 0.0003 -1.953

MAE_32470 Fructose-1,6-bisphosphate aldolase (fbaA) 0.340 0.0266 -1.555 0.322 0.0036 -1.634

MAE_52710 6-phosphofructokinase (pfkA1) 0.054 0.0370 -4.212

MAE_14970 Transketolase 0.132 0.0001 -2.923 0.466 0.0016 -1.103

MAE_61820 Transketolase 0.179 0.0146 -2.485 0.114 0.0010 -3.136 0.570 0.0377 -0.811

MAE_34870 D-xylulose 5-phosphate/D-fructose 6-phosphate phosphoketolase family protein

0.191 0.0203 -2.392

MAE_43640 Glucose 6-phosphate dehydrogenase (zwf) 0.084 0.0068 -3.574

MAE_14900 NADH-dependent glutamate synthase small subunit (gltD)

0.325 0.0390 -1.621

MAE_09050 Glutamate--ammonia ligase (glnN) 0.096 0.0083 -3.375

MAE_07560 NADH-dependent glutamate synthase large subunit (gltB)

0.116 0.0012 -3.109 0.1960 0.0042 -2.352


76


MAE_59440 Diaminopimelate epimerase (dapF) 0.847 0.0053 -0.239 0.705 0.0180 -0.505

MAE_01980 Aldehyde dehydrogenase (aldH) 0.189 0.0473 -2.405

MAE_50250 S-adenosyl-L-homocysteine hydrolase adenosylhomocysteinase

0.175 0.0000 -2.511 0.215 0.0000 -2.219

MAE_45970 S-adenosylmethionine synthetase (metK) 0.097 0.0322 -3.362

MAE_50420 Carbamoyl phosphate synthase large subunit (carB) pyrA?

0.461 0.0093 -1.116 0.766 0.0254 -0.385

MAE_35390 Aspartate aminotransferase (aspC) 5.702 0.0000 2.511 1.995 0.0463 0.997

MAE_15720 Acetylornithine aminotransferase (argD) 4.131 0.0023 2.046

MAE_60310 Cysteine syntase (cysK) 6.310 0.0144 2.656

MAE_62000 Leucyl aminopeptidase (pepA) 2.630 0.0055 1.395

MAE_32670 Glycine cleavage system protein H (gcvH) 5.916 0.0499 2.565

MAE_39110 Branched-chain amino acid aminotransferase (ilvE)

7.379 0.0026 2.883

MAE_28670 Dihydroxy-acid dehydratase (ilvD) 5.346 0.0000 2.418 1.871 0.0440 0.904

Cellular processes

MAE_46050 CP12 polypeptide 0.2560 0.0048 -1.967

MAE_62780 Putative peroxiredoxin 0.053 0.0450 -4.239

MAE_36510 Peroxiredoxin 0.157 0.0009 -2.671

MAE_48380 Universal stress protein UspA homolog 0.121 0.0452 -3.043

MAE_02790 Thioredoxin (trxA) 3.133 0.0014 1.648


77

MAE_22850 Delta-aminolevulinic acid dehydratase (hemB)

8.472 0.0152 3.083

MAE_62840 DNA starvation/stationary phase protection protein Dps / DNA-binding ferritin-like protein

5.650 0.0038 2.498

MAE_60930 Bacterioferritin comigratory protein 3.162 0.0001 1.661

MAE_53990 Iron/manganese superoxide dismutase (sodB)

5.248 0.0016 2.392

MAE_16920 Superoxide dismutase (sodB) 13.062 0.0197 3.707

gi|159028112 Flavodoxin (isiB) 3.162 0.0006 1.661 2.421 0.0057 1.276

Transport and binding proteins

MAE_39210 Chloroplastic outer envelope membrane protein homolog

3.531 0.0442 1.820 7.586 0.0013 2.923 4.246 0.0097 2.086

MAE_14800 Nitrate/nitrite transport protein (nrtA) 3.373 0.0002 1.754 7.586 0.0000 2.923 2.377 0.0121 1.249

MAE_06220 ABC-type urea transport system substrate-binding protein

15.704 0.0000 3.973

MAE_56680 Iron transport system substrate-binding protein

5.754 0.0000 2.525 8.551 0.0000 3.096 1.754 0.9975 0.811

MAE_47420 Extracellular solute-binding protein 2.911 0.0081 1.541

Genetic information processing - Transcription and translation proteins

MAE_46070 10 kDa chaperonin, co-chaperonin GroES (groS)

1.787 0.0431 0.837

gi|159027173 Metallothionein (smtA) 15.996 0.0014 4.000

MAE_02510 RNA-binding protein 8.954 0.0262 3.163 17.378 0.0028 4.119

MAE_45870 RNA-binding region protein (rbpF/A2) 14.859 0.0272 3.893 19.953 0.0190 4.319 9.550 0.0442 3.256


78

MAE_30540 Ribosome recycling factor (frr) 2.291 0.0256 1.196

MAE_03930 Aspartyl/glutamyl-tRNA amidotransferase subunit B (gatB)

0.123 0.0146 -3.030

MAE_62700 Trigger factor (tig) 0.227 0.0381 -2.139

MAE_61840 ClpB protein 0.738 0.0368 -0.439 0.718 0.0230 -0.478

MAE_57190 ATP-dependent Clp protease-like protein 0.139 0.0041 -2.844

MAE_46080 60 kDa chaperonin GroEL1 (groEL1) 0.146 0.0313 -2.777 0.425 0.0373 -1.236

MAE_03410 60 kDa chaperonin GroEL2 (groEL2) 0.229 0.0063 -2.126

MAE_62320 Bifunctional phosphoribosyl aminoimidazole carboxy formyl formyltransferase / inosinemonophosphate cyclohydrolase (purH)

0.297 0.0437 -1.754

MAE_13690 Transcriptional regulator (AbrB family) 0.223 0.0196 -2.166

MAE_54500 DNA-directed RNA polymerase beta subunit (rpoB)

0.143 0.0352 -2.804

MAE_11110 DNA-directed RNA polymerase subunit gamma (rpoC1)

0.116 0.0358 -3.109

MAE_42760 Elongation factor (tuf) 0.227 0.0187 -2.139 0.061 0.0000 -4.034 0.515 0.0248 -0.957

MAE_43910 30S ribosomal protein S1 0.311 0.0146 -1.688 0.194 0.0023 -2.365

MAE_57370 30S ribosomal protein S3 (rpsC) 0.077 -3.694

MAE_32430 30S ribosomal protein S4 (rpsD) 0.286 0.0031 -1.807

MAE_57270 30S ribosomal protein S5 (rpsE) 0.281 0.0073 -1.834 0.095 0.0009 -3.402

MAE_11310 30S ribosomal protein S6 0.313 0.0078 -1.674 0.182 0.0030 -2.458

MAE_57300 30S ribosomal protein S8 (rpsH) 0.207 0.0025 -2.272


79

MAE_52500 30S ribosomal protein S9 (rpsI) 0.087 0.0024 -3.521

MAE_06280 30S ribosomal protein S15 0.041 0.0000 -4.611


MAE_48050 30S ribosomal protein S18 0.219 0.3709 -2.193 0.069 0.0042 -3.853 0.718 0.3355 -0.478

MAE_43885 50S ribosomal protein L7/L12 0.328 0.0306 -1.608

MAE_36630 50S ribolsomal protein L1 (rplA) 0.080 0.0021 -3.641

MAE_57430 50S ribosomal protein L3 0.060 0.0032 -4.066


MAE_43870 50S ribosomal protein L10 0.063 0.0015 -4.000 0.550 0.0500 -0.864 0.291 0.0324 -1.781

MAE_36590 50S ribosomal protein L19 0.302 0.0285 -1.727 0.075 0.0013 -3.734 0.655 0.0455 -0.611

MAE_52530 50S ribosomal protein L17 (rplQ) 0.136 0.0049 -2.883

MAE_57330 50S ribosomal protein L14 0.261 0.0127 -1.940 0.175 0.0361 -2.511

MAE_57260 50S ribosomal protein L15 (rplO) 0.071 0.0009 -3.827 0.261 0.0036 -1.940


Other categories

MAE_04080 Heat shock protein (grpE) 2.249 0.0147 1.169

MAE_21600 Putative thylakoid-associated protein 3.565 0.0085 1.834 2.965 0.0098 1.568 4.920 0.0005 2.299

MAE_62060 Cell division protein FtsH (ftsH3) 7.244 0.0308 2.857

MAE_42350 Subtilisin-like protein peptidase S8 and S53

2.938 0.0161 1.555

MAE_50430 Putative modulator of DNA gyrase peptidase U62

7.047 0.0128 2.817

MAE_37620 Gas vesicle structural protein (gvpC) 1.803 0.0001 0.850 1.393 0.0019 0.478


80

MAE_61940 Plasma membrane protein 3.105 0.0080 1.634 1.977 0.2859 0.983

MAE_38380 Tic22-like protein 0.097 0.0153 -3.362 2.399 0.0018 1.262 0.745 0.4004 -0.425

MAE_54380 FKBP-type peptidyl-prolyl cis-trans isomerase (ytfC)

1.660 0.0315 0.731

MAE_18910 Orange carotenoid-binding protein /water-soluble carotenoid protein

0.520 0.0173 -0.943 0.2109 0.0001 -2.246 0.497 0.0071 -1.010

MAE_27460 Cyanophycin synthetase (cphA) 0.236 0.0020 -2.086

MAE_31270 S-layer region-like precursor protein 0.395 0.0198 -1.342 0.120 0.0031 -3.056

gi|169788458 Actin 0.076 0.0330 -3.721


gi|159027829 Hypothetical protein A 0.089 0.0032 -3.495 0.402 0.0032 -1.316 0.560 0.0045 -0.837

gi|159027827 Hypothetical protein B 2.188 0.0022 1.130 1.820 0.0183 0.864

gi|159030339 Hypothetical protein C 0.053 0.0000 -4.239

gi|159029460 Hypothetical protein D 11.803 0.0282 3.561

gi|159030907 Hypothetical protein E 4.966 0.0081 2.312

gi|159029624 Hypothetical protein F 2.780 0.0265 1.475

MAE_37770 Hypothetical protein 0.117 0.0028 -3.096

MAE_06000 Hypothetical protein 10.093 0.0000 3.335

MAE_47530 Hypothetical protein 18.880 0.0002 4.234 15.417 0.0004 3.947

MAE_11600 Hypothetical protein 0.068 0.0010 -3.880 0.425 0.011 -1.236 0.692 0.0254 -0.532

MAE_11610 Hypothetical protein 0.168 0.0441 -2.578 0.215 0.0035 -2.219




81









MAE_35080 Hypothetical protein 0.686 0.0428 -0.545 16.904 0.0084 4.079 3.631 0.0367 1.860



82

Table 3.3 Differentially expressed proteins in M. aeruginosa under Fe-replete chemostats at different dilution rates. Values highlighted in red represent down-regulation while green represent up-regulation of the protein relative to the 0.45 d

-1 (control) condition.


P val Log2 fold

0.15 d-1

P val Log2 fold

0.30 d-1

P val Log2 fold

Genetic information processing -Transcription and translation proteins

MAE_42760 Elongation factor Tu (tuf) 0.273 0.0419 -1.874

MAE_54740 AbrB family transcriptional regulator 0.263 0.0415 -1.927

MAE_49450 Molecular chaperone (dnaK) 9.638 0.0045 3.269 10.186 0.0182 3.349

gi|488826847 DNA-binding protein 0.334 0.0223 -1.581 0.227 0.0182 -2.139



gi|488836772 Iron uptake protein A1 2.858 0.0297 1.515

Energy metabolism

MAE_07560 NADH-dependent glutamate synthase large subunit (gltB)

0.299 0.0246 -1.741

MAE_10260 Allophycocyanin subunit beta (apcB) 0.453 0.0096 -1.143

MAE_50150 ATP synthase (atpD) 0.114 0.0044 -3.136

gi|488830534 Putative thylakoid-associated protein 0.196 0.0038 -2.352


83

Table 3.3 cont.


P val Log2 fold

0.15 d-1

P val Log2 fold

0.30 d-1

P val Log2 fold

Other categories

MAE_37620 Gas vesicle structural protein, GvpC 3.436 0.0049 1.781


gi|159030339 Hypothetical protein 0.092 0.0023 -3.442

gi|159030973 Hypothetical protein 0.242 0.0030 -2.0463 0.084 0.0118 -3.574 0.461 0.0410 -1.116

Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa

85

Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M.

aeruginosa

This chapter has been published as: Competitive Effects of Calcium and

Magnesium Ions on the Photochemical Transformation and Associated Cellular Uptake

of Iron by the Freshwater Cyanobacterial Phytoplankton Microcystis aeruginosa.

Manabu Fujii, Anna C. Y. Yeung, and T. David Waite. Environmental Science &

Technology 2015 49 (15), 9133-9142. DOI: 10.1021/acs.est.5b01583

Introduction

The impact of iron availability on the physiological and proteomic responses in

M. aeruginosa PCC7806 was explored in Chapters 2 and 3. However, iron

transformations in freshwater systems can also be affected by reactions with divalent

metal ions. This chapter discusses the physicochemical effects that calcium and

magnesium have on Fe transformations and the effect these cations have on Fe uptake

by M. aeruginosa.

Iron (Fe) is one of the important trace metal nutrients for the growth of


86

microorganisms including phytoplankton (Sunda, 2012, Crichton, 2009). In aerobic

natural surface waters at circumneutral pH, a majority of dissolved Fe is present as

organically complexed ferric iron (Fe[III]) (Rue and Bruland, 1995, Nagai et al., 2007,

Chen et al., 2009a, Laglera and van den Berg, 2009, Batchelli et al., 2010) due to the

low solubility of inorganic Fe(III) (e.g., ~10-11

M at pH 7.5 - 9 (Liu and Millero, 1999))

and rapid oxidation of ferrous iron (Fe[II]) (Pham and Waite, 2008). However,

organically complexed Fe is generally considered to be inaccessible for acquisition by

phytoplankton, except for those possessing transport systems that are specific for

particular Fe complexes including Fe(III)-siderophores (Hutchins et al., 1999, Ito and

Butler, 2005, Nicolaisen et al., 2008, Stevanovic et al., 2012) . Recent studies have

consistently suggested that Fe uptake in cyanobacteria may occur via siderophore-

independent processes due to the lack of siderophore-associated genes in many

prokaryotic phytoplankton (Hopkinson and Barbeau, 2012) and the predominance of the

uptake of unchelated iron by many species of freshwater and coastal cyanobacteria (e.g.,

Microcystis (Fujii et al., 2011a), Anabaena (Wirtz et al., 2010), Synechocystis (Jiang et

al., 2014, Kranzler et al., 2014) and Lyngbya (Salmon et al., 2006)), even under Fe-

stress. Therefore, the concentration of unchelated Fe species (Fe′), potentially in both

ferric (Fe(III)′) and ferrous (Fe(II)′) states, is likely a significant determinant of Fe

availability by cyanobacteria in surface natural waters.

There is now substantial accumulated evidence that reductive dissociation of

organically complexed Fe(III) to Fe(II)′ facilitates Fe uptake by phytoplankton in both

seawater (Maldonado et al., 2005, Shaked et al., 2005, Salmon et al., 2006, Maldonado

and Price, 2001, Hopkinson and Morel, 2009) and freshwaters (Kranzler et al., 2011,

Fujii et al., 2014b, Kranzler et al., 2014, Jiang et al., 2014). This process may include


87

the extracellular reduction via photochemical and biological processes mediated by

ligand-to-metal charge transfer (LMCT) (Fujii et al., 2011a, Kranzler et al., 2014,

Maldonado et al., 2005), cellular plasma-membrane reductase (Shaked et al., 2005,

Maldonado and Price, 2001) and superoxide (Salmon et al., 2006, Rose et al., 2005)

with the significance of these various processes possibly depending on the

phytoplankton species, type of Fe-binding ligand and other medium conditions. While

the reduction of Fe(III) generates Fe(II)′, the steady-state Fe(II)′ concentration achieved

is also influenced by other competing reactions including re-complexation by Fe-

binding ligands (Fujii et al., 2011a) and oxidation by oxygen (Sunda and Huntsman,

2003) when present. The oxidation of Fe(II)′ to Fe(III)′ by dissolved oxygen may be

critical in Fe acquisition by oceanic eukaryotic phytoplankton (Shaked et al., 2005,

Sunda, 2001).

Ethylenediaminetetraacetic acid (EDTA) is the most common organic ligand used

in the culturing of algae in both seawater and freshwater media (Andersen, 2005). This

trace metal buffer binds thermodynamically stable Fe(III) with a relatively high affinity

under freshwater conditions(Fujii et al., 2008) but only with moderate binding strength

in seawater(Hudson et al., 1992, Hering and Morel, 1989) with the lower binding

strength in seawater due to the presence of high concentrations of the divalent metals

(Me) calcium (Ca) and magnesium (Mg) which compete with Fe(III) for EDTA binding

sites (Morel and Hering, 1993). Specifically, the concentration of unchelated Fe(III) is

substantially higher in media exhibiting a high concentration ratio of Me relative to

EDTA (where most EDTA that is not bound to Fe is present as an EDTA-Me complex)

because the exchange reaction between Fe(III) and the EDTA-Me complex is very slow

compared to that for free EDTA (Hering and Morel, 1989, Fujii et al., 2008). In contrast


88

to EDTA, humic and fulvic acids, major Fe-binding ligands in freshwater (Tipping,

2002) and coastal seawaters (Laglera and van den Berg, 2009, Batchelli et al., 2010),

have less affinity for Ca and Mg than does EDTA (Fujii et al., 2008). Consequently, it

was suggested in a previous study (Fujii et al., 2008) that the rate of Fe(III)

complexation by Suwanee River fulvic acid (SRFA) at pH 8 only slightly decreases in

the presence of Ca and Mg, even at the high concentrations found in seawater. These

findings suggest that the effect of Ca and Mg (i.e. the elements most responsible for

water hardness) on Fe transformation kinetics may vary substantially depending on the

relative affinity of Me to the Fe-binding ligands present.

In addition to any effects on abiotic transformation kinetics, the presence of

competing metals may directly influence the uptake of iron and other nutrient metals by

phytoplankton. Previous studies by Sunda and Huntsman (1996, 1998), for example,

indicated that the uptake of Mn in a diatom and a green alga was inhibited by high

concentrations of the divalent metals Cu, Zn, and Cd. Metal transport in gram-negative

bacteria including cyanobacteria likely incorporates concentration gradient dependent

passive diffusion through non-specific trans-membrane channels (porins) in the outer-

membrane followed by intracellular transport processes (Kranzler et al., 2014, Nikaido,

2003, Katoh et al., 2001). Free or membrane-anchored periplasmic Fe-binding proteins

(FutA1 and FutA2) and membrane transporters (FutB, FutC and FeoB) are known to

involved in intracellular iron uptake (Katoh et al., 2001, Kranzler et al., 2014, Badarau

et al., 2008). While Fe uptake by many of these Fe transporters is likely to be highly

specific, the inhibitory effect of non-toxic levels of Cu on Fe uptake by the Gram-

negative proteobacterium (Helicobacter pylori) (Velayudhan et al., 2000) suggests that

competition with other metals may influence intracellular Fe transport. Although the


89

physiological and physicochemical processes involved remains unclear, the effect of

competing metals on cellular Fe uptake is likely an important consideration in

developing a comprehensive understanding of Fe uptake by cyanobacterial

phytoplankton.

Previous studies (Dang et al., 2012a, Fujii et al., 2014a, Fujii et al., 2011a) have

consistently suggested that Fe availability by M. aeruginosa is moderately or strongly

controlled by photo-reductive dissociation of organically complexed Fe(III) (Figure

4.1). However, limited studies have been undertaken to examine the impact of major

divalent metals (i.e., Ca and Mg) on either the photochemical transformations of Fe or

the associated uptake of Fe by phytoplankton. Given that hardness is an important

variable in natural waters, the effects of Ca and Mg on Fe uptake by the freshwater

cyanobacterium M. aeruginosa is investigated in this chapter.


90

Figure 4.1 Iron uptake model for Microcystis aeruginosa in the absence and presence of major divalent metals (Me). Under illuminated condition, the photochemical reductive dissociation of ferric-ligand complex (Fe

IIIL) generates unchelated Fe(II) (i.e.,

Fe(II)'). The generated Fe(II)' can be taken up by cells via the Fe transporter. In the EDTA system, the photochemical Fe(II)' generation (khv) is slower in the absence of Me (reaction depicted as blue arrow). In contrast, Fe(II)' generation (khv,Me) is facilitated in the presence of Me (reaction depicted as red arrow). In the fulvic acid system, Fe(II)' generation is relatively comparable in the absence and presence of Me. Regarding cellular Fe uptake, half saturation constant substantially increases in the presence of Me (i.e., KS,X < KS,MeX) due to the association of Me with plasma-membrane transporter, and the maximum Fe

uptake decreases (i.e.,

max

S,Xρ>

max

S,MeXρ) due possibly to the physiological or physicochemical

(adverse) effects of Me on the intracellular Fe transport. In the abiotic Fe transformation, Ferrozine (FZ) also significantly compete with Fe(II) complexation by L in both absence and presence of Me. Solid arrows represent major reactions, whereas dashed arrow shows relatively minor reactions. Note that, in the absence of FZ, the Fe

IIL formation becomes

significant reaction that influences steady-state Fe(II)' concentration. Kinetic rate constants depicted near the arrows correspond to those listed in Table 4.1.


91

Material and Methods

Strain and culturing condition

Cell culturing and photochemical and biological Fe uptake experiments were

performed as previously described in Fujii et al. (2011a, 2014a) but with some

modifications. A batch culture of M. aeruginosa PCC7806 was incubated in pH 8

Fraquil* medium (containing 26 μM EDTA and 100 nM Fe) at 27

oC in a 14h:10h light-

dark cycle, where chemical transformations of Fe (Fujii et al., 2014a, Fujii et al., 2011a)

and biological responses (Dang et al., 2012a) are well documented. In the

photochemistry and uptake experiments, Fraquil* was also prepared at different Fe,

ligand (EDTA or SRFA) and Me (Ca or Mg) concentrations. Further detailed

information including the methods for preparation of chemical stocks and the chemical

composition of culturing media is provided in Appendix A.

Photochemical Fe transformation

The photochemical experiments were conducted in 1 mL cuvettes using the

ferrozine (FZ) competitive assay (Fujii et al., 2011a). The formation of the purple

ferrous-ferrozine (FeIIFZ3) complex was monitored spectrophotometrically at 562 nm

following the addition of FZ stock to the Fraquil* medium containing equilibrated Fe-

ligand and Me. Final concentrations of chemicals in the reactions were 5 - 20 μM Fe, 40

μM EDTA, 50 mg.L-1

SRFA, 2 μM - 20 mM Me and 1 mM FZ.

In this assay, the rate of Fe(II)' formation due to the photolysis of organically

complexed Fe(III) was determined spectrophotometrically by measuring the time course

formation of ferrous-ferrozine (FeIIFZ3) complex concentration after mixing

equilibrated FeIII

L solution and FZ stock in Fraquil* media containing various

concentrations of Me.


92

Prior to the experiment, the Fe- and ligand-free Fraquil* media with various Me

concentrations were prepared by mixing CaCl2 and MgSO4 solutions with the Fe-,

ligand- and Me-free Fraquil* at the required concentrations. Then, the equilibrated

FeIII

EDTA or FeIII

SRFA solution was added into the Fe- and ligand-free Fraquil*. The

photochemical experiment was initiated by adding the FZ stock to the Fraquil* medium

containing equilibrated Fe-ligand and Me. Final concentrations of chemicals in the

samples were adjusted to 20 μM for Fe, 40 μM for EDTA, 2 μM -20 mM for Me and 1

mM for FZ in the EDTA system while in the SRFA system concentrations were

adjusted to 5 μM for Fe, 50 mg.L-1

for SRFA, 20 mM for Me and 1 mM for FZ. After

the addition of FZ stock, the absorbance of solution was monitored at a wavelength of

562 nm, where FeIIFZ3 complex absorbs most strongly (Stookey, 1970), by using a

Varian Cary 50 UV-vis spectrophotometer with 1 cm pathlength quartz cuvette. The

sample incubation was conducted under light or dark condition and the absorbance was

measured every 2 hours for up to 8 hours. The absorbance was converted to FeIIFZ3

concentration by using the molar absorptivity of 27,000 M-1

.cm-1

. The photochemical

experiments were conducted in a light- and temperature-controlled incubator, as above.

The effect of Fe contamination in the reagents on the FeIIFZ3 formation rate was

determined to be negligible by repeating the photochemical experiment with the

identical methods except that addition of Fe to the sample solution was omitted. While

fulvic acids typically absorb light in visible region, light absorbance of SRFA at 562 nm

is small. Thus, effect of SRFA (at 10 mg.L-1

concentration) on the determination of

FeIIFZ3 formation rate was determined to be negligible. Although it is well known that

Fe(III) is reduced to Fe(II) in the presence of fulvic acid (Pullin and Cabaniss, 2003,

Pham et al., 2012), concentration of Fe(II) initially present in the FeIII

SRFA stock (i.e.,


93

initial concentration of Fe(II) in the photochemical experiment) was estimated to be

negligibly small, as discussed in (Fujii et al., 2015).

Short-term iron uptake

The short-term Fe uptake incubational assays were initiated by spiking the pre-

equilibrated radiolabeled 55

Fe-ligand stock solution to the cell culture. Microcystis cells

in exponential phase (~ 106 cells.mL

-1) during daytime was collected (5000 × g, 15 min)

and resuspended into Fe- and ligand-free Fraquil* with different Me concentrations

ranging from 2 μM - 20 mM. The 55

Fe-ligand stock was added at final concentrations of

0.05 - 1 μM Fe, 20 μM EDTA and 10 mg.L-1

SRFA. The final cellular concentration

was adjusted to 2 × 106 cell.mL

-1. Cells were incubated for 2 h (where

55Fe

accumulation is linear with respect to time) in an incubator with the light source was

horizontally supplied by cool-white fluorescent tubes with total radiation intensity of

157 μmol.m-2

.s-1

(Fujii et al., 2011a).

After incubation, cells were vacuum-filtered on to 0.65 µm PVDF membrane

filters. The filters were washed three times with 1 mL of EDTA/oxalate chelate solution

to remove Fe (oxyhydroxides) adsorbed to the cell surface and three times with 1 mL of

2 mM NaHCO3 (Tang and Morel, 2006). Filters and cells were placed in glass

scintillation vials with 5 mL of scintillation cocktail (Beckman ReadyScint). Cellular

radioactivity was determined by a Packard TriCarb Liquid Scintillation Counter

(PerkinElmer). For the calibration purpose, 1 - 5 μM 55

Fe-ligand stocks were also

prepared in 5 mL scintillation cocktail and the scintillation counts of these stocks were

measured concurrently with sample measurement. The scintillation counts of sample

(disintegrations per minute) were then converted to moles of Fe by using the

scintillation counts of 55

Fe-ligand stocks. Process blanks were determined by repeating


94

the identical experiment except that Microcystis cells were omitted.

Kinetic and thermodynamic model for 55Fe uptake

Fe(II) formation in the photochemical experiment

The photochemical transformation of Fe(III)-ligand complexes ultimately

produces Fe(II)' and photo-oxidized ligand (Lox) most likely via ligand-to-metal charge

transfer (LMCT) (Barbeau, 2006, Sunda and Huntsman, 2003) and/or other redox

processes mediated by secondary generated entities during the photolysis, which may

include superoxide (Rose and Waite, 2006) and organic radicals (Faust and Zepp,

1993). While light-mediated Fe transformations are recognized to involve a number of

complex reactions, the photo-reductive dissociation of organically complexed Fe(III)

(FeIII

L) resulting in formation of Fe(II)′ can be empirically described by a pseudo-first-

order reaction (rate constant khv, s-1

) under constant illumination (Fujii et al., 2011a,

Sunda and Huntsman, 2003), as follows:

hvkIII

oxFe L Fe(II)' L , (1)

It should be noted that Fe(III) bound to SRFA is also continuously reduced even

in the dark, most likely due to the presence of redox-active moieties in fulvic acids (e.g.,

hydroquinones) as reported previously (Pullin and Cabaniss, 2003, Pham et al., 2012),

while thermal reduction of FeIII

EDTA is negligible under the conditions examined here.

Thus, the reduction rate in the photochemical experiment using SRFA includes the

thermal reduction which was estimated to account for ~30% of total reduction rate, as

noted in Appendix C.

The generated Fe(II)′ may subsequently form complexes with the ligand (L) and

FZ, when present.


95

f-Lk II

fFe(II)' L Fe L , (2)

f-FZk II

3Fe(II)' 3FZ Fe FZ , (3)

where kf-L (M-1

.s-1

) and kf-FZ (M-3

.s-1

) are rate constants for Fe(II)' complexation by L

and FZ, respectively. Lf indicates free ligand that is not bound to Fe and any other

metals. The steady-state Fe(II)' concentration is significantly affected by the oxidation

process in some conditions(Sunda and Huntsman, 2003), because Fe(II)' is oxidized at

appreciable rates primarily by dissolved oxygen (O2) in air-saturated and circumneutral

pH waters (Sunda and Huntsman, 2003, Pham and Waite, 2008). However, the effect of

oxidation on the Fe(II)' concentration is expected to be minimal under our experimental

conditions using freshwater medium, where the Fe(II)' oxidation rate is calculated to be

at least ~103 folds smaller than the rates of complexation of Fe(II)' by EDTA and FZ

(i.e., the reaction of Fe(II)' complexation by organic ligands outcompetes the reaction of

Fe(II)' oxidation), as described in Appendix C and in a previous study (Fujii et al.,

2011a).

In addition to the two complexation reactions, the photochemically generated

Fe(II)' can interact with ligand-Me complex (MeL) in the presence of Me, as follows:

f-MeLk IIFe(II)' + MeL Fe L+Me, (4)

where kf-MeL (M-1

.s-1

) is the rate constant for Fe(II) complexation by MeL. Given the

slower process of metal exchange (Hering and Morel, 1989, Fujii et al., 2008), the rate

of complexation between Fe(II)' and MeL is also expected to be slower than that

between Fe(II)' and Lf. Indeed, the Fe(II) complexation rate was determined to decrease

with increasing Me concentration. However, an observed sigmoidal increase in FeIIFZ3


96

formation with increase in Me concentration could not be solely accounted for by the

decreased rate of the FeII-L complexation reaction. Since the photochemical experiment

employed high concentration of FZ (i.e., FZ complexation was found to be the

dominant reaction in Fe(II)' removal in most cases where Me was present), the

reduction in extent of FeIIL formation as a result of Me competition for ligand binding

sites was calculated to be relatively small (discussed later). Therefore, to account for the

observed increase in FeIIFZ3 formation with increasing Me concentration, we introduced

the adjunctive metal-exchange reaction with this reaction becoming a significant factor

in FeIIFZ3 formation at higher Me, as follows:

hv,MekIII

oxFe L-Me Fe(II)' MeL , (5)

where khv,Me (s-1

) is the rate constant for FeIIIL photo-reduction in the presence of Me.

We assume that photochemical FeIIFZ3 formation is facilitated by the adjunctive

association of Me with the Fe-ligand complex to form a ternary complex (FeIII

L-Me),

though there is little evidence for the FeIII

L-Me ternary complex from previous studies

on Fe-ligand complexation in high Me containing media such as seawater (Sunda and

Huntsman, 2003, Hudson et al., 1992).

Regarding the interaction between Me and L, concentrations of MeL, Lf and Me

at given total Me and L concentrations were calculated by assuming a pseudo-

equilibrium (side) reaction between Me and L, as described by Me + Lf = MeL with

conditional stability constant of KMeL=[MeL]/[Me][Lf] (Fujii et al., 2008). Provided that

the concentrations of free ligand and its complex with Me ([L*] = [Lf] + [MeL]) are

constant over the duration of measurement (due to the relatively small changes in

concentrations of ligand complexes with Fe and other trace metals present in the


97

Fraquil* medium), the equilibrated concentrations of MeL, Lf and Me were determined

by KMeL with known total concentrations of Me ([Me]T) and [L*], where

*

MeL TK [MeL] / ([L ] [MeL])([Me] [MeL]) yielding:

2

* *

T T T

MeL MeL

1 1[L ]+[Me] + [L ]+[Me] + 4[L'][Me]

K K[MeL] =

2

, (6)

*

f[L ] [L ] [MeL] , (7)

MeL f

[MeL][Me] =

K [L ]. (8)

For the ternary complex FeIII

L-Me, conditional stability constant KFeL-Me =

[FeIII

L-Me]/([FeIII

L][Me]) was similarly introduced, yielding [FeIII

L-Me] = KFeL-

Me[Me][FeIII

L*]/(1+KFeL-Me[Me]) = αMe[FeIII

L*] and [FeIII

L] = [FeIII

L*] - [FeIII

L-

Me] = (1 - αMe)[FeIII

L*], where [FeIII

L*] is the total concentration for Fe(III) bound to

ligand (i.e., [FeIII

L*] = [FeIII

L] + [FeIII

L-Me]) and αMe is a fraction of the ternary

complex FeIII

L-Me relative to FeIII

L* (where this parameter is a function of [Me]) (

Me0 α 1 ).

At steady-state where the time-dependent change in Fe(II)′ concentration is

considered to be invariant (i.e., d[Fe(II)′]/dt ≈ 0), the rate law for FeIIFZ3 formation can

be written as:


98

II33

f-FZ SS

III III

hv hv,Me3

f-FZ 3

f-L f f-MeL f-FZ

hv Me hv,Me Me3 III *

f-FZ 3

f-L f f-MeL f-FZ

d[Fe FZ ]=k [FZ] [Fe(II)']

dt

k [Fe L]+k [Fe L-Me]k [FZ]

k [L ] k [MeL] k [FZ]

k (1-α )+k αk [FZ] [Fe L ]


, (9)

where [Fe(II)′]SS is the steady-state Fe(II)′ concentration. Under the given

conditions, the FeIIFZ3 formation can be further simplified with pseudo-first order rate

constant (k*hv, s-1

) as described below:

II* III *3hv

d[Fe FZ ]=k [Fe L ]

dt . (10)

Approximations of [FeIII

L*] ≈ [Fe]T – [FeIIFZ3] (where [Fe]T denotes total Fe

concentration in the system) due to the low [Fe(II)'] (e.g., [Fe(II)']/[ FeIIFZ3] < 1.4×10-7

in the presence of 1 mM FZ) and [FZ] ≈ [FZ]T due to the high [FZ]T (e.g., [FZ]T =1

mM >> 20 μM = [Fe]T) followed by integration yields the following relationship

between FeIIFZ3 concentration and time (t):

*ThvII

T 3

[Fe]ln k t

[Fe] [Fe FZ ]

. (11)

The detailed procedure of parameter determination in the photochemical Fe(II)'

generation process is described in Appendix C, Section 4. Briefly, by using time course

data of [FeIIFZ3] collected in the photochemical experiment, k

*hv was experimentally

determined from the slope of the linear regression line in the plot of time versus

ln([Fe]T/([Fe]T-[ FeIIFZ3])) (Figure C1). Subsequently, khv and khv,Me were determined

by substitutions of k*hv determined in the absence of Me (αMe =0) and in the presence

of excess Me (αMe =1), respectively, to eqs 9 and 10. Then, KFeL-Me was determined


99

from best fit of the model (eqs 9 and 10) to the k*hv data as a function of Me

concentration, where concentrations of MeL, Lf and Me were determined by using eqs

6-8 with reported values of KMeL (Fujii et al., 2008) (Table 4.1).

Cellular Fe uptake

A number of previous studies on trace metal (including Fe) uptake by

phytoplankton (Sunda, 2012, Fujii et al., 2010a) have consistently suggested that

cellular uptake follows Michaelis-Menten-type saturation theory:

max

SS

S

ρ [S]ρ =

K +[S], (12)

where [S] indicates the steady-state concentration of the biologically available portion

of Fe in the extracellular environment (i.e., [Fe(II)′]SS in our system) (Fujii et al.,

2011a), and KS and max

Sρ represent the half saturation constant and the maximum uptake

rate under the conditions examined, respectively. max

Sρ can be described by a product of

the first-order rate constant for Fe transport and the total concentration of Fe transporter.

In this study, we define the term “Fe uptake” as an intracellular accumulation of Fe

which is not removed from the cells by the EDTA/oxalate wash. In contrast, “Fe

transport” is used to refer to the intracellular specific transport process, which represents

the Fe transport from periplasmic to cytoplasmic spaces by free or membrane-anchored

periplasmic Fe-binding proteins (e.g., FutA1 and FutA2) and membrane transporters

(FutB, FutC and FeoB) (Katoh et al., 2001, Kranzler et al., 2014, Badarau et al., 2008).

Intracellular transport may follow concentration gradient dependent passive diffusion of

Fe from the extracellular environment into the periplasmic space through trans-


100

membrane channels in the outer-membrane (Nikaido, 2003). The Michaelis-Menten

theory is only applicable when uptake is not limited by the diffusive flux of available

metals (Sunda, 2012). However, given that the diffusion layer thickness of metal

complexes in aqueous solution is generally on the order of tens of micrometers (Buffle

et al., 2009), it is likely that the effect of physical diffusion on the metal flux in

proximity of the cell surface is relatively small for small sized phytoplankton such as M.

aeruginosa (cellular radius is ~3 μm). Under such conditions, the substrate

concentration at the outer surface of the cellular membrane can be approximated to that

of the bulk environment.

According to the observations described below (Section 4.2), Me present in the

culture medium can effectively compete with Fe for cellular uptake. This effect is best

described by a reduced affinity of the plasma-membrane transporters for Fe when the

transporter forms a complex with Me, as follows:

X + Me = MeX, KMeX = [MeX]/[X][Me]. (13)

where X represents free Fe transporters that are not bound to Me, MeX represents the

Me-transporter complex and KMeX is the conditional stability constant for complexation

between X and Me. Given that total concentration of transporter ([X]T) is a sum of X

and MeX concentrations (i.e., [X]T = [X] + [MeX]), [X] and [MeX] can be described as

[X] =(1-βMe)[X]T and [MeX] = βMe[X]T, where, similar to the photochemical model,

βMe (= KMeX[Me]/(1+ KMeX[Me])) is the fraction of [MeX] relative to total transporter

concentration (0 ≤ βMe ≤ 1).

Assuming that Fe transport is mediated by concurrently-occurring reactions

between Fe(II)′ and X or MeX, the total Fe uptake in the presence of Me may be

described as below:


101

max max

S,X S,MeX

S

S,X S,MeX

up,X up,MeX

S,X S,MeX

up,X Me up,MeX Me

T

S,X S,MeX

ρ [S] ρ [S]ρ =

K +[S] K +[S]

k [X][S] k [MeX][S]

K +[S] K +[S]

k (1 β )[S] k β [S][X]

K +[S] K +[S]

(14)

where KS,X and KS,MeX are half-saturation constants for X and MeX, respectively.

max

S,Xρ

(=kup,X[X]) and

max

S,MeXρ (= kup,MeX[MeX]) represent rates of maximum Fe uptake in the

absence and presence of Me, respectively. kup,X and kup,MeX are first-order rate constants

for Fe uptake in the absence and presence of Me, respectively. To satisfactorily describe

the experimental observation in Section 4.2, the latter term of eq. 14 needs to dominate

at high concentrations of Me (i.e., βMe = 1), while the value of

max

S,MeXρ is lower than

max

S,Xρ (i.e., the maximum uptake occurs at a slower rate at high [Me]). Under saturated

uptake (i.e., KS,X, KS,MeX << [S]), the total Fe uptake rate can be described by the

maximum Fe uptake rate:

max max

S S,X S,MeX up,X Me up,MeX Me Tρ =ρ ρ k (1 β ) k β [X] (15)

Detailed description of the procedure used in parameter determination is described

in Appendix C. Briefly, in the Fe uptake model, five parameters (KS,X, KS,MeX,

max

S,Xρ,

max

S,MeXρ and KMeX) were considered to be fitting parameters. The first two parameters

KS,X and KS,MeX were determined from a non-linear fit of the Michaelis-Menten

equation to the 55Fe uptake data measured over a range of Fe(II)′ concentrations in the


102

absence of Me (βMe = 0) and presence of excess Me (βMe = 1), respectively. Fe(II)′

concentrations was calculated according to the procedure described in AppendixC. The

maximum Fe uptake rates in the absence and presence of excess Me (i.e.,

max

S,Xρ and

max

S,MeXρ , respectively, in eq. 15) were determined from the

55Fe uptake data in the SRFA

system where Fe uptake rate is saturated. The affinity of transporter to Me (KMeX) was

determined by fitting eq. 15 to the 55

Fe uptake data for all Me concentrations in the

SRFA system. To this end, values of βMe and [Me] were calculated by βMe =

KMeX[Me]/(1+ KMeX[Me])) and eqs. 6-8, respectively.

The detailed calculation procedure of substrate concentration including sensitivity

analysis (Appendix C), comprehensive reaction set of Fe transformation kinetics (Table

C2 and Table C3) and definitions of all the parameters used in this study (Table C8) are

provided in the Supporting Information. The significant reactions in the Fe uptake

assay, extracted via the sensitivity analysis (Appendix C, Section 5), are depicted in

Figure 4.1.

Results and Discussion

Photochemical Fe(II) formation

The photochemical experiment revealed that FeIIFZ3 formation from the

FeIII

EDTA complex was significantly affected by Me concentration (Figure 4.2A). As

Me concentration increases, the FeIIFZ3 formation rate (k

*hv) increased sharply (up to

~50-fold) and reached a constant maximum value when the Me concentration reaches a

concentration a little higher than the concentration of EDTA that is not bound to Fe

(i.e., 20 μM).


103

Figure 4.2 Effects of Me concentration on the photochemical FeIIFZ3 formation in

Fraquil* buffered by (A) EDTA (Ca: black-coloured square, Mg: grey-coloured triangle, no Me: open diamond) and (B) SRFA. The photochemical experiments were performed under the conditions of total concentrations of 20 μM for Fe, 40 μM for EDTA and 0 - 20 mM for Ca and Mg in the EDTA system and 5 μM for Fe, 50 mg.L

-1 SRFA and 0

- 20 mM for Ca and Mg in the SRFA system. By assuming the first-order reaction as described by [Fe

IIFZ3]/dt = k*hv[Fe

IIIL*] (eq.10), the photochemical FeIIFZ3 formation rate

constant (k*hv, s-1

) was determined via linear regression analysis in a plot of ln([Fe]T/([Fe]T - [Fe

IIFZ3])) versus time (where [Fe]T [Fe

IIIL] and [Fe

IIFZ3] is a time course data of Fe

IIFZ3

concentration). Symbols and error bars represent average value and standard deviation from triplicate experiments. In panel A, solid and dotted lines indicate model fits (eq. 9) to the data for the Ca and Mg cases, respectively. In the EDTA case, data plotted for log [Me] = -7 was used for the “no Me” case, while data plotted for log [Me] > -4 was considered as the “excess Me” case.

-7.5

-7

-6.5

-6

-5.5

-5

-4.5

-7 -6 -5 -4 -3 -2 -1

Loga

rith

m o

f p

ho

toch

em

ical

Fe

(II)

FZ

form

atio

n r

ate

co

nst

ant

(k*

hv,

s-1

)

Logarithm of Me concentrations (M)

+ Ca

+ Mg

no Me

-6

-5.5

-5

-4.5

-4

-3.5

-3

no Me 20 mM Ca 20 mM Mg

Lo

ga

rith

m o

f p

ho

toch

em

ical F

e(I

I)F

Z

form

atio

n r

ate

co

nsta

nt (k

* hv, s

-1) C

A

B


104

The large increase in FeIIFZ3 formation (k*hv) around the threshold values is

primarily due to the higher net generation of Fe(II)′, given that (i) the FZ concentration

was kept constant over the range of Me concentrations used, and (ii) the effects of

hardness cations on the rate of Fe(II) complexation by FZ is negligible (Thompsen and

Mottola, 1984, Lin and Kester, 1992). The higher rate of Fe(II)′ generation can be

associated with (i) the masking effect of Me on re-complexation of generated Fe(II)′ by

EDTA and/or (ii) the increased photo-reduction rate due to the competitive effect of Me

on dissociation of the photochemically-generated Fe(II)-ligand complex as described by

Fujii et al. (2015). However, the former reaction is likely to have a minor effect on the

steady-state Fe(II)′ concentration under the condition examined (i.e., [FZ]T = 1 mM,

[L]T = 20 μM and [Me]T = 0 - 20 mM) because the third term in the denominator of eq.

9 (i.e., 3

f-FZk [FZ]= 310 s

-1) is calculated to be higher than the sum of the first and second

terms (i.e., *

f-Lk [L ]+ f-MeLk [MeL]

= 5.3-163 s-1

). Thus, the increase in FeIIFZ3 formation

due to the masking effect of Me on re-complexation of Fe(II)′ and ligand was

determined to be small (e.g., by 1.5-fold at maximum) as Me increases from 0 to 20

mM, regardless of the facts that (i) thermodynamic calculations using the stability

constants listed in Table 1 indicated that almost all of the free EDTA (>99%) forms

complexes with Me at concentrations greater than 21 μM for Ca and 70 μM for Mg

(Figure C2 A and B), and (ii) an independent experiment suggests that FeIIEDTA

complexation decreased by 15-26-fold in the presence of excess Me (Figure C3 A).

It is more likely that the latter reaction (i.e., enhanced photo-reduction)

substantially contributed to the observed increase in FeIIFZ3 formation. As described in

eq. 5, the presence of the ternary complex (FeIII

L-Me) was introduced to account for the

Me-promoted FeIIFZ3 formation at higher Me concentrations with assumptions that (i)


105

reductive dissociation of Fe from FeIII

L-Me is faster than FeIIIL complex formation and

(ii) its fraction relative to FeIII

L increases with increasing Me concentration. Under this

assumption, the photochemical reduction rates were determined to be khv = 2.5 × 10-7

s-1

for FeIII

EDTA and khv,Me = 5.3 - 6.0 × 10-6

s-1

for the FeIII

EDTA-Me complex by

substituting the time-course data of FeIIFZ3 formation in the absence of Me (i.e.,αMe =

0) and presence of excess Me (αMe = 1) in eq. 9. The results indicate that the reduction

rate for the FeIII

EDTA-Me complex was an order of magnitude greater (by 21-24 fold)

than that for FeIII

EDTA (Appendix C, Figure C3 B).

Furthermore, the model fit (eq., 9) to all the data shown in Figure 4.2A yielded

stability constants for the ternary complexes (KFeL-Me) that are one or two orders of

magnitude lower than the stability constant of the MeL complex (KMeL, Table 4.1). The

relatively lower value of KFeL-Me is consistent with the notion that the metal-binding

ligand in the ternary complex has a smaller number of sites available for coordination

with incoming metals (i.e., Me) (Fujii et al., 2008, Hering and Morel, 1988). In addition,

the lower stability of the ternary complex suggests that FeEDTA has a significant

interaction with excess Me only when free EDTA is saturated with Me (i.e., [Me]T >

[Lf], otherwise Me preferentially binds to free EDTA; also see Appendix C, Figure C2

C and D. Overall, the proposed model provided reasonable fits to the observed data over

the range of Ca and Mg concentrations examined (Figure 4.2 A). Furthermore, the

greater sensitivity of photochemical FeIIFZ3 formation for Ca compared to that for Mg

is consistent with the thermodynamically higher affinity of Ca for EDTA (Table 4.1).

In contrast to EDTA, Me-promoted FeIIFZ3 formation was not observed in the

system buffered by SRFA (Figure 4.2 B), suggesting that (i) the rate of metal exchange

between Fe(II)′ and Me complexed by SRFA is comparable to that for free SRFA and/or


106

(ii) Me does not competitively bind to the Fe-binding sites of SRFA. Thermodynamic

calculations (using KMeL values shown in Table 4.1) indicated that Me complexes with

fulvic acids account for only a small portion of total fulvic acids, even at high

concentrations of Me (e.g., <3% and <24% at 2 mM and 20 mM Me; also see Appendix

C, Figure C2 E and F). Therefore, it is likely that the negligible effect of Me on the

FeIIFZ3 formation is associated with the lower degree of Me-coordination with Fe-

binding sites in fulvic acid.


107

Table 4.1 Kinetic and thermodynamic rate constants used in this study.

Parameters Unit EDTA SRFA

FZ Related

equation a no Me Ca Mg no Me Ca Mg

i) Fe transformation kinetics

k*hv s

-1 1.6×10

-7 b,c 5.9×10

-6 b,c 5.2×10

-6 b,c 3.1×10

-5 b 3.1×10

-5 c,d 3.1×10

-5 c,d Eqs. 10, 11

6.4×10-6

e 1.1×10-5

b 2.9×10-5

b

2.9×10-5

e

khv, khv,Me s-1

2.5×10-7

f 6.0×10-6

f 5.3×10-6

f 3.1×10-5

f N.D. g N.D. g Eqs. 1, 5, 9

kf-L, kf-MeL M-1

.s-1

7.1×106 c, h 2.7×10

5 c,h 2.7×10

5 c 4.5×10

4 i 4.5×10

4 d 4.5×10

4 d 3.1×10

11 d, j Eqs. 2, 3, 4, 9

2.1×106 k 4.8×10

5 h

KMeL M-1

1.3×108 l 2.0×10

6 l 4.7 l 16 l Eqs. 6,7,8,9

KFeL-Me M-1

1.0×107 m 5.0×10

4 m N.D. g N.D. g Eq. 9

ii) Cellular Fe uptaken

max

S,Xρ,

max

S,MeXρ

zmol.cell-1

h-1

660 o 120 p 36 p 660 o 120 p 36 p Eqs. 14,15

KS,X, KS,MeX M-1

1.0×10-14

o 4.1 × 10-13

o 4.1×10-13

o 1.0×10-14

o 4.1×10-13

o 4.1×10-13

o Eq. 14

KMeX M-1

3.4 × 104 q 5.9×10

3 q 3.4×10

4 q 5.9×10

3 q Eq. 13

a Equations described in the text.

b k*hv values were determined by fitting Eq. 11 to the Fe

IIFZ3 time course data in the absence of Me and presence of excess Me (Figure C1).

c Values used in this study as these values provided the best fit to the experimentally determined data.


108

d Effect of Me on the complexation of Fe(II) by fulvic acid and FZ were assumed to be negligible under the conditions examined.

e Reported photoreduction rate constant (Fujii et al., 2011a) determined in Fraquil* (pH 8) containing Ca and Mg concentrations of 1.5×10-4

M and 1.0×10-3

M respectively at constant illumination of 157 μmol.m

-2.s

-1.

f khv and khv,Me values were determined from eq. 9 in the absence of Me (αMe = 0) and presence of excess Me (αMe = 1), respectively. Associated parameters and Fe

IIFZ3 time course data at given conditions were used for the calculation.

g Values were not determined due to the negligible association of Me and fulvic acid.

h Values were independently determined in this study by using ligand competition methods as described in Appendix C, Section 1. In the calculation of steady-state Fe(II) concentration using eq. 9, the Fe-binding capacity of 260 nmol.mg

-1 for SRFA (Rose and Waite, 2003) was used.

i Reported value (Bligh and Waite, 2010).

j Reported value (Thompsen and Mottola, 1984) with unit of M-3

.s-1

.

k Value reported in previous work (Fujii et al., 2011a) at Fraquil* (pH 8) containing Ca and Mg concentrations of 1.5×10-4

M and 1.0×10-3

M, respectively.

l Reported values (Fujii et al., 2008).

m Values from best-fit of model (eqs. 9 and 10) to the experimental data shown in Figure 4.2 A.

n The uptake parameters are identical in the EDTA- and SRFA-buffered systems.

o The values were determined from best-fit of model to the 55

Fe uptake data in Figure 4.3B via non-linear regression using software R. The value for Mg was assumed to be equal to that for Ca.

p The values were determined by using 55

Fe uptake rate in the SRFA system containing 20 mM Me (Figure 4.3 B), where Fe uptake is assumed to be saturated.

q Values from best-fits to the 55

Fe uptake data in the SRFA system (Figure 4.3 C).


109

Cellular Fe uptake

Similar to the photochemical experiment, 55

Fe uptake in the EDTA system

generally increased as Me concentrations increased (Figure 4.3A). However, the

magnitude of increase was smaller (up to 2.2 to 2.8-fold) compared to the

photochemical FeIIFZ3 formation (up to ~50-fold). In addition, while

55Fe uptake rates

in the Mg case monotonically increased with increasing Mg concentration, 55

Fe uptake

in the Ca case displayed the highest value at 2 mM Ca followed by a slight decrease at

20 mM Ca. In the SRFA system, 55

Fe uptake rates were determined to be higher (by up

to ~10-fold) than observed in the EDTA system, particularly at lower Me concentration

(Figure C4). The uptake rate, however, monotonically decreased with increasing Me

concentration by 5-fold for Ca and 18-fold for Mg compared to the rate observed in the

absence of Me.

As noted below, the 55

Fe uptake rates in the EDTA system were in most cases

calculated to be below the saturated rate of uptake (e.g., by 1.3 to 12-fold for the Ca

system, depending on the Me concentration), whereas the Fe uptake in the SRFA

system is expected to be saturated. The Michaelis-Menten-type uptake theory indicates

that uptake rate increases proportionally as substrate concentration increases in cases

where [S] << Ks (e.g. S1 S2 1 2ρ /ρ =[S ]/[S ], where

max

S S Sρ =(ρ /K )[S]), unless the Fe uptake

parameters vary otherwise. Therefore, the relatively small increase in the cellular iron

uptake rate compared to the increase in the Fe(II) formation rate (in the non-saturated

EDTA system) in addition to the decreased uptake at the higher Me concentration (in

the saturated SRFA system) suggest an adverse effect of Me on Fe transport parameters

(i.e., maximum uptake rate and half-saturation constant).


110

Figure 4.3 (A) 55

Fe uptake rate in a range of Me concentration in EDTA-buffered

0

100

200

300

400

500

600

700

800

900

1000

No Me 0.02 mM 0.2 mM 20 mM

55Fe

up

take

rat

e (

zmo

l/ce

ll/h

)

Me concentration

+Ca

+Mg

B

0

20

40

60

80

100

120

140

160

180

No Me 0.02 mM 0.2mM 2mM 20mM

55Fe

up

take

rat

e (

zmo

l/ce

ll/h

)

Me concentration

+Ca

+MgA

0

0.5

1

1.5

2

2.5

3

-18 -17 -16 -15 -14 -13 -12 -11 -10 -9

Loga

rith

m o

f 5

5Fe

up

take

rat

e

(zm

ol/

cell/

h)

Logarithm of Fe(II)' concentration (M)

0

100

200

300

400

500

600

700

800

-7 -6 -5 -4 -3 -2 -1 0

55Fe

up

take

rat

e (

zmo

l/ce

ll/h

)

Logarithm of Me concentration (M)

+Ca

+Mg

no Me

B

C


111

Fraquil*. 55

Fe uptake rates were measured in the absence and presence of Me (Ca: black

bars, Mg: grey bars). Total concentrations were adjusted to 0.5 μM for 55

Fe, 20 μM for

EDTA, 0 - 20 mM for Me and ~2 × 106 cell.mL

-1 for cells. Averaged data with standard

deviation from triplicate runs were shown. (B) 55

Fe uptake rate as a function of

unchelated Fe(II) concentration in EDTA-buffered Fraquil*. 55

Fe uptake assays were

conducted in the absence of Me (open diamond) and presence of excess Ca (total Ca

concentration of 200 μM, open triangle). Total concentrations were adjusted to 0.05 - 1 μM

for 55

Fe, 20 μM for EDTA and ~2 × 106 cell.mL

-1 for cells. In addition,

55Fe uptake rates

measured in the SRFA-buffered system (0.5 μM for 55

Fe and 10 mg.L-1

for SRFA) were

also plotted as indicated by closed symbols. The closed diamond and closed triangle

represent Fe uptake rates for SRFA systems in the absence Ca and presence of excess

Ca (total Ca concentration of 200 μM), respectively. Symbols and error bars indicate

average and standard deviation from triplicate experiment. Solid and dotted lines represent

model fits (eq. 14) to the data measured in the absence and presence Me, respectively.

Fe(II)' concentrations was determined by the balance of light mediated-reduction of FeIIIL

(including thermal reduction in case of SRFA) and complexation of photo-generated Fe(II)'

by the ligand. (C) Maximum Fe uptake as a function of Me concentration in SRFA-

buffered Fraquil*. 55

Fe uptake rates were measured in the absence (open diamond) and

presence (Ca: black-colored square, Mg: grey-colored triangle) of Me. Total concentrations

were adjusted to 0.5 μM for 55

Fe, 10 mg.L-1

for SRFA, 0 - 20 mM for Me and ~2 × 106

cell.mL-1

for cells. Symbols and error bars represent average and standard deviation from

triplicate runs. Solid and dotted lines represent model fits (eq. 15) to the data for the Ca and

Mg cases, respectively. Arrows indicate the ion concentrations of Ca (grey) and Mg (black)

in the Fraquil* medium.

To obtain further insight into the mechanisms involved in the interaction between

Fe uptake and Me, 55

Fe uptake was examined as a function of Fe(II)' concentration in

the absence of Ca and presence of excess Ca (Figure 4.3B). Between these two extreme

cases, response of cellular 55

Fe uptake to the Fe(II)' concentration varied markedly.

Notably, the Fe(II)' concentrations at which Fe uptake starts to decline differed by an

order of magnitude. More quantitatively, the non-linear regression analyses yielded

half-saturation constants (i.e., KS in eq. 12) of 1.0 × 10-14

M for the no Ca case and 4.1 ×

10-13

M for the excess Ca case, which correspond to KS,X and KS,MeX in eq. 14

respectively (Table 4.1). This large decrease of uptake affinity in the presence of excess

Ca suggests that the association of Ca with the Fe transporter (eq. 13) results in

reduction of the transporter affinity for Fe.


112

The 55

Fe uptake rates determined in the SRFA system lay in the higher range of

Fe(II)' concentration (10-9.8

M) where uptake is predicted to be independent of Fe(II)'

concentration (closed symbols in Figure 4.3B). This indicates that Fe uptake in the

SRFA-buffered system employed in this study was saturated and equal to the maximum

uptake. In addition, our model results indicate that the Fe(II)' concentration in the SRFA

system is constant at 10-9.8

M over a range of Me concentrations due to the minor

association of Me with SRFA. Therefore, it appears reasonable to consider that all

uptake rates measured in the SRFA systems are equal to the saturated uptake (note that

Fe(II) uptake rates were determined by assuming that Fe(II) uptake accounts for 60% of

total uptake as indicated in the previous 55

Fe uptake assay using FZ treatment (Fujii et

al., 2014b)). If this is the case, the monotonic decrease in Fe uptake as Me concentration

increases (in the SRFA system) indicates that maximum uptake also decreases in the

presence of Me. Me-dependent maximum uptake in Figure 4.3C yielded

max

S,Xρ and

max

S,MeXρ in eq. 15 (Table 4.1), suggesting that the maximum Fe uptake decreased by 6-18-

folds in the presence of excess Me. In addition, by fitting eq. 15 to the 55Fe uptake data

for all Me concentrations in Figure 4.3C, the affinity of transporter to Me (KMeX) was

determined, indicating that the transporter affinity for Mg was comparable or a little

higher than that for Ca (by ~1.7-fold, Table 4.1).

The observation here that Fe uptake in the SRFA system decreases as Me

concentration increases suggests that maximum Fe uptake rate varies depending on Me

concentration in the bulk environment. According to the Michaelis-Menten-type

equation, the maximum rate of Fe uptake is mathematically described by the product of

total number of transporter sites and rate constant for translocation of Fe complexed by


113

the transporter (i.e., max

S,X up,Xρ k [X]). The maximum uptake rate of trace metal may vary

depending on trace metal availability and intracellular quota (Sunda, 2012). Indeed,

previous studies (Dang et al., 2012b, Alexova et al., 2011b) on M. aeruginosa

consistently indicated that Fe uptake by this organism is regulated by a negative

feedback response, suggesting that transporter synthesis, rate of plasma-membrane

transport or both factors are facilitated under substrate limitation. However, given the

fact that Microcystis cells sacrificed for the short-term (2 h) Fe uptake assay in this

study were acclimated under identical pre-incubation conditions including medium

nutrient concentrations, it is likely that regulation of the Fe transport system is constant

among the treatments. At least in the initial stage of assay, it would be reasonable to

assume that total number of transporters available for Fe transport is comparable among

the cells tested.

One of the explanations for the observed decrease in Fe uptake rate at the higher

Me concentrations is the reduced rate constant for Fe transport into the cytoplasm after

an Fe complex with the plasma-membrane transporter is formed (e.g., kup,MeX). Given

that cyanobacterial Fe transport is an energy-dependent process (Kranzler et al., 2014,

Nikaido, 2003, Katoh et al., 2001), salt stress including high osmotic pressures resulting

from these higher Me concentrations may have an adverse effect on the basal cellular

metabolism of M. aeruginosa (e.g., ionic strengths of Fraquil* in the absence of Me and

presence of excess Me are 1.6 mM and 50 - 80 mM, respectively) and, as such,

negatively affect the generation of energy required for the translocation of Fe. Yet, the

maximum uptake rate begins to decrease with increasing Ca and Mg at concentrations

less than those in the Fraquil* medium where cells were initially acclimated (i.e., 0.26

mM for Ca and 0.15 mM for Mg, Figure 4.3C). This result may suggest that the initial


114

decreases are not due to the osmotic pressure or any other effects including Ca/Mg-

associated metabolic inhibition. While the mechanism behind this adverse effect

remains unclear, alternative explanations may include that Fe(II) is transported by the

same mechanism as Ca and Mg. For example, a non-specific divalent metal transport

system can transport a variety of divalent metals including Fe(II) with this system

recognized to occur in phytoplankton (Lane et al., 2008, Sunda and Huntsman, 2000).

The redox state of periplasmic Fe is perhaps tightly associated with the activity of

oxidoreductase enzymes such as alternate respiratory terminal oxidase (Kranzler et al.,

2014), multi-copper oxidase (Maldonado et al., 2006), flavin proteins (Coves and

Fontecave, 1993) or secondary produced reactive oxygen species (Salmon et al., 2006).

Subsequent intracellular Fe(II) and Fe(III) transport may well involve different transport

systems (e.g. FeoB for Fe(II) and FutB/FutC for Fe(III)) (Kranzler et al., 2014). The

presence of high Me concentration might alter the redox dynamics and transport of Fe

due to either direct or indirect associations of Me with Fe redox moieties, though the

redox state of intracellular periplasmic Fe and associated cellular mechanisms remain

largely unclear. However, further studies are needed to develop a full understanding of

the molecular mechanisms associated with Fe transport and the impact of divalent

cations on these mechanisms.

Conclusion

In this chapter, two divalent cations (Ca and Mg) and two different Fe-binding

ligands (EDTA and fulvic acid) were used to demonstrate their influence on the

bioavailability of Fe in freshwater systems. EDTA is one of the most commonly used

trace metal buffers in phytoplankton culturing media, with Ca and Mg concentrations


115

typically in the range of 10-5

to 10-3

M. Under conditions where divalent metal

concentrations are higher or comparable to the concentration of EDTA, the rate of

photochemical reduction of Fe(III) present in FeIII

EDTA in the culture would be

comparable to that measured in the presence of excess divalent metals in this study.

However, if the culture media contained major divalent metals at concentrations less

than the EDTA concentration, the light-induced reductive formation of Fe(II) will be

retarded. In such cases, the effect of co-existing divalent metals should be taken into

account when determining the rate of formation of bioavailable Fe.

In natural freshwaters, the major Fe-binding ligands include fulvic acids whereas

hardness generally varies from ~1.0 to ~100 mg.L-1

(corresponding to [Ca] = ~2.5 ×

10-4

to ~2.5 × 10-3

M) depending on geological, climatic and other environmental

circumstances. Based on the present results, it is expected that the variation of hardness

would have little effect on the photo-reductive dissociation of Fe(III) complexed by

fulvic acid due to the relatively lower affinities of fulvic acid for Ca and Mg.

While the presence of divalent cations had little effect on the rate of reduction of

fulvic acid-complexed Fe(III), these cations were found to significantly hinder cellular

Fe uptake. These findings indicate that the high concentration of Ca and Mg decreases

both transporter affinity for Fe and maximum Fe uptake rate. It is likely that the

competition between divalent metals and Fe for binding by transporter reduces the

transporter affinity for Fe. However, the physicochemical or physiological mechanisms

associated with the reduction of maximum Fe uptake remain unclear. The cellular Fe

uptake systems (as evident from the maximum uptake rate and affinity) were found to

be sensitive to the divalent cation concentrations even in the lower concentration range

(e.g., 10-5

- 10-4

M). These results suggest that water hardness should be considered an


116

important determinant of Fe availability in natural waters, although its effect on the

photochemical formation of bioavailable Fe is likely less pronounced.

Overall this chapter demonstrated the importance of the divalent metals, calcium

and magnesium, in their influence of the bioavailability of iron. Furthermore the nature

of the Fe-binding ligand also played a role in the subsequent uptake of iron. From this

study, it can be concluded that Fe bioavailability in freshwater may be further limited by

the hardness of the water and the interactions with divalent metals. The results here

suggested that photochemical Fe(II) formation and associated Fe uptake by M.

aeruginosa is substantially influenced by the concentration of Ca and Mg present and

the relative affinity of these cations for Fe-binding ligands and cellular transporters.

Chapter 5: The physiological responses of two closely related strains of Cylindrospermopsis

raciborskii to differing iron availability under nitrogen-fixing conditions

117

Chapter 5: The physiological responses of two closely related strains of

Cylindrospermopsis raciborskii to differing iron availability under nitrogen-

fixing conditions

Introduction

Cylindrospermopsis raciborskii ((Woloszynska) (Seenayya and Raju, 1972)) is a

filamentous species of freshwater cyanobacteria. Though initially regarded as a tropical

species originating from Indonesia, it has since become ubiquitous across multiple

continents, making it a truly cosmopolitan species (Sinha et al., 2012, Antunes et al.,

2015). As a result of climate change, the rise in water temperatures together with the

highly adaptable nature of C. raciborskii has enabled the species to grow in diverse

environmental conditions (Bonilla et al., 2012, Sinha et al., 2012). Recent C. raciborskii

blooms have been found in temperate regions such as Australia and New Zealand

(McGregor and Fabbro, 2000), northern Europe (Briand et al., 2004, Hong et al., 2006)

and north America (Messineo et al., 2010). However, the blooms are often difficult to

detect as C. raciborskii rarely form surface blooms (McGregor and Fabbro, 2000).

Furthermore, their low chlorophyll content often leads to an underestimation of the cell

concentration therefore manual methods of monitoring are still required (McGregor and

Fabbro, 2000).



118

The current state of warming climates may prove to be advantageous for C.

raciborskii since its growth rate increases at warmer temperatures, although it has been

found in temperature ranges as low as 11 °C (Bonilla et al., 2012) up to 35 °C (Briand et

al., 2004). This freshwater species is also exceptional at phosphorous uptake and storage

(Bai et al., 2014) which, combined with its capacity to utilise multiple N sources and

diazotrophy (i.e. ability to convert dinitrogen (N2) from the atmosphere into ammonia

(NH3) for assimilation) makes C. raciborskii a highly competitive species in the ever

changing environment (Burford et al., 2006, Willis et al., 2016).

Past ecophysiology studies of C. raciborskii have primarily focussed on

temperature and light (Briand et al., 2004, Bonilla et al., 2012, Messineo et al., 2010),

salinity (Moisander et al., 2002) and macronutrient (N and P) availability (Burford et

al., 2006, Sprőber et al., 2003, Willis et al., 2016). Aside from the study by Dufour et al

(2006), there has been no other C. raciborskii study which examined iron, despite its

importance in the biosynthesis of the nitrogenase enzyme required for nitrogen fixation

(N2-fixation). Nitrogenase is made up of two component proteins: dinitrogenase – a

large heteromeric protein to bind N2; and dinitrogenase reductase – a smaller

homomeric protein that acts as electron donor. Iron and molybdenum form the essential

cofactors for the dinitrogenase component in the reduction of N2 into NH3, allowing

diazotrophs such as C. raciborskii to be more competitive than non-diazotrophs under

N-depleted environments. However, N2-fixation is Fe intensive, requiring between 25 to

39 molecules of Fe for the synthesis of the nitrogenase enzyme (Postgate, 1998). This is

consistent with the higher Fe requirement reported for phototrophic diazotrophs relative

to non-diazotrophs (Tuit et al., 2004, Kustka et al., 2003a) and common limitations of

N2-fixation due to the lower availability of Fe and other nutrients (e.g., phosphorous) in



119

oceanic and inland waters (Sanudo-Wilhelmy et al., 2001, Whittaker et al., 2011,

Berman-Frank et al., 2007b).

In this chapter, the physiological response to combined nitrogen and iron stress is

examined in two C. raciborskii strains with different toxicity profiles. Iron requirement

is expected to increase during N2-fixation for the proper functioning of the nitrogenase

enzyme. The physiological characteristics examined include growth rate, trichome

length and number of heterocysts, chlorophyll content, nitrogenase activity, and iron

uptake.

Material and Methods

Strains and culturing conditions

Both C. raciborskii strains used in this study originated from North Queensland,

Australia, but differ in cell morphology and toxigenicity (Saker and Neilan, 2001).

Strain CS-506 has coiled trichomes and produces cylindrospermopsins (CYN+) while

strain CS-509 has straight trichomes and does not produce cylindrospermopsins (CYN-).

Both strains were maintained in JM medium (Appendix A) at 27 °C under a 14:10 h

light:dark cycle at 157 µmol photons m-2

s-1

.

For the N2-fixing conditions, JM was modified to JM* by removing all combined

nitrogen sources, therefore replacing Ca(NO3)2·4H2O with CaCl2·2H2O,

(NH4)6Mo7O24·4H2O with Na2MoO4·2H2O, and NaNO3 with NaCl at equivalent

concentrations. Iron was supplied in the form of FeCl3·6H2O complexed with EDTA

only. Media was mixed and equilibrated for two days prior to inoculation.

Triplicate batch cultures under the conditions: JM* + 1000 nM Fe (-N1000, Fe

replete); JM* + 200 nM Fe (-N200, Fe limited); JM* + 50 nM Fe (-N50, Fe starved);



120

and JM + 1000 nM Fe (+N1000, control) were set up for each strain. Cultures were

incubated as before. Placement within the incubator was randomised to minimise

shading from light source and agitated daily to maintain a homogeneous culture.

Physiological characterisations

The density of the C. raciborskii cultures was monitored using a

spectrophotometer (Cary 50 UV-Vis, Varian Inc.) at λ = 750 nm (OD750) over the

culturing period of 16 days. Cultures were inspected under the microscope (Leica) at

400x magnification with a Sedgwick-Rafter counting chamber to determine trichome

length, the number of heterocysts and vegetative cells trichome-1

from a minimum of 50

trichomes. Linear regression was fitted to determine the relationship of cells mL-1

to

OD750 (R2 = 0.93); OD750 converted to cells mL

-1 (R

2 = 0.93) was used to calculate

growth rates (µ) at exponential phase (days 4 - 8) and stationary phase (days 10 – 14)

using the formula µ (d-1

) = [ln(k2/k1)/(Δt)].

Cells were collected (1 mL, 14 000 × g, 5 min) and 1.5 mL of 90% (v/v) methanol

with 0.5 mm zirconium silicate beads (50 µL). Chlorophyll (Chl a) was extracted using

a cell disrupter (FastPrep FP120, Thermo Savant) at top speed for 45 s, then placed in

the dark for 1 h. After centrifugation (14000 × g, 5 min), 1 mL of the extract was

transferred into a cuvette and measured with a spectrophotometer at λ = 665 nm (Cary

50 UV-Vis, Varian Inc.) to estimate Chl a content, Chl a (µg mL-1

) = OD665 × 12.7

(Meeks and Castenholz, 1971).

Acetylene reduction assay

Nitrogenase activity (hence nitrogen fixation) was indirectly measured using the

acetylene reduction assay (ARA) in a similar procedure as described by Plominsky et al.



121

(2013). CYN+ and CYN

- were subcultured twice into JM* supplemented with 50 nM,

200 nM and 1000 nM Fe prior to the ARA to examine the effects of Fe on nitrogenase

activity.

Triplicate cultures (50 mL) were collected at mid-exponential phase (8000 × g, 15

min). Cells were resuspended into 100 µL of fresh medium (JM or JM*) in their

respective Fe treatments then transferred into 3 mL glass vials fitted with Teflon/silicon

septa (Exetainer®, Labco). A gas-tight syringe was used to remove 300 µL from the

headspace of the vial and replaced with an equal volume of acetylene, making the final

concentration in the vial 10% (v/v). Cultures were incubated at 27 °C under 157 µmol

photons m-2

s-1

.

Ethylene (C2H4) measurements were taken at 1, 4, 8 and 24 h after initial

acetylene injection. At each sampling point, a gas-tight syringe was used to withdraw 20

µL from the headspace and injected into an Agilent 7890A GC System equipped with a

HP-PLOT Q column (Agilent, 30 m × 0.53 mm × 40 µm) and a flame ionised detector

(90 °C, with N2 flow of 20 mL min-1

). Standard curve for ethylene was prepared by

serial dilution of ethylene standard (4.12 nM to 4120 nM, R2 = 0.99).

At the end of time course, the sample vials were opened and 1.5 mL of 90% (v/v)

methanol was added. The entire volume was transferred into 2 mL cryovials with 50 µL

of 0.5 mm zirconium silicate beads. Cryovials were placed into a FastPrep FP120 Cell

Disrupter (Thermo Savant, Carlsbad, USA) to extract Chl a as described above.

Short term iron uptake

The effect of nitrogen availability on iron uptake was examined by short term iron

uptake using radiolabelled iron (55

Fe) as described in Chapter 4 (page 93).



122

Briefly, 55

Fe-EDTA stock solutions were prepared 24 h in advance by spiking

FeCl3 (1 mM, pH 2) with 1 µL of 55

FeCl3 (5 mCi), then mixed with EDTA (26 mM) in

different ratios to create different 55

Fe-ligand stocks. Bicarbonate buffer (2 mM, pH 8)

was added to maintain the 55

Fe-EDTA solution at pH 8. 55

Fe-EDTA stock solutions

were equilibrated in the dark at ambient temperature.

Batch cultures of CYN+ and CYN

- at exponential growth in different N- and Fe-

treatments were collected during the light cycle (8000 × g, 10 min). Cells were washed

twice with Fe/EDTA-free JM*, resuspended in Fe/EDTA-free JM* then distributed

(100 µL) into 96-well microplates. The Fe uptake experiment was initiated by adding 6

µL of equilibrated 55

Fe-EDTA solutions (final concentrations: 200 nM 55

Fe(III), 3.5 –

200 µM EDTA) to each well. Controls of JM* media plus 55

Fe-EDTA without

cyanobacterial cells were used to determine background 55

Fe measurements.

Microplates were incubated for 3 h at 27 ºC under 157 µmol photons m-2

s-1

. For dark

uptake, microplates were first wrapped in aluminium foil then placed into the incubator.

After incubation, cells were vacuum-filtered onto 1.2 µm PVDF membrane filter

microplates (Millipore). Filters were washed three times each with 200 µL of

EDTA/oxalate solution and 200 µL of 2 mM NaHCO3 solution (total washing time was

approximately 10 min). Each filter along with cells were removed and transferred into

glass scintillation vials with 5 mL of scintillation cocktail (Beckman ReadyScint).

Radioactivity was measured using a liquid scintillation counter (Packard TriCarb).



123

Results

Physiological characterisations

Figure 5.1 Growth curves of (A) CYN+ and (B) CYN

– C. raciborskii in different N and

Fe treatments. Filled symbols indicate CYN+ strain whereas open symbols indicate the

CYN– strain. N2-free culture conditions are represented by –N, while nitrate-supplied

cultures are indicated by +N. All measurements are mean ±SD with n = 3, when not visible, the size of error bars do not exceed the size of the symbol. Note that the y-axis has different scales for the upper and lower parts of the axis.

Cylindrospermopsis raciborskii CYN+ and CYN

- absorbance values were

converted to cell concentration (R2 = 0.93). Both strains grew to the highest

concentration in the control condition where nitrate and iron were supplied in excess

(+N 1000 nM Fe). However, cell concentration reduced significantly (P < 0.05) when

nitrate was removed, with further differences in final yields observed depending on Fe

concentrations (Figure 5.1). Overall, CYN+ yield remained high even in –N 1000 nM Fe

and was only affected when Fe concentrations fell to 50 nM. However, different Fe

concentrations had similar effects on final yields when CYN- was cultured in –N

conditions (Figure 5.1).

At exponential phase, CYN+ growth rates (µ) increased with increasing Fe

availability, where µ = 0.03, 0.04 and 0.06 d-1

were observed respectively for conditions



124

50, 200 and 1000 nM Fe (

Table 5.1). In contrast, CYN- growth rates were similar between the Fe treatments

with 50 and 200 nM Fe conditions both at 0.03 d-1

while 1000 nM Fe had a growth rate

of 0.04 d-1

(

Table 5.1). However, under control (+N 1000 nM Fe) conditions both strains had

similar growth rates, 0.16 d-1

for CYN+ and 0.14 d

-1 for the CYN

- strain.

Table 5.1 Physiological changes in C. raciborskii under different Fe concentrations. Physiological parameters were observed by light microscopy (n ≥ 50 trichomes).

CYN+ CS-506 CYN

- CS-509

[Fe] (nM)

Trichome (µm)

Cells Het Chl a (µg.mL

-1)

µ

(d-1

)

Trichome (µm)

Cells Het Chl a (µg.mL

-1)

µ

(d-1

)

+N

1000

240-360 6012 26 2.25 0.16 398-450 818 17 2.62 0.14

-N

1000

250-287 5420 98 1.42 0.06 230-400 6317 95 1.41 0.04

-N

200

170-200 378 41 1.38 0.05 260-350 619 82 1.41 0.03

-N

50

63-150 239 43 1.33 0.03 50-120 177 75 1.40 0.03

Het: heterocysts

From observations under the microscope, the number of heterocysts increased

when C. raciborskii was cultured without a fixed nitrogen source (e.g. in –N medium),

even though heterocysts were still present in the nitrate supplied (+N) cultures.

Heterocysts were also more frequently observed on both ends of the trichomes as Fe

concentration increased. Under –N conditions, the trichome length and number of cells

per trichome increased with Fe availability in the culturing medium, though were unable

to match the trichome lengths of +N cultures (



125

Table 5.1).

Figure 5.2 C. raciborskii CYN+ (Left) and CYN

- (Right) culture in different nitrogen and

iron conditions. Strains were cultured in the presence (+N) or absence (–N) of nitrate combined with different Fe concentrations. Visual inspection shows chlorosis in CYN

- strain

however, Chl a measurements were similar between the strains.

Chlorophyll (Chl a) content was almost two times higher in +N conditions which

was also reflected by the visibly greener cultures (Figure 5.2). Visual inspection also

suggested that chlorosis had occurred in the –N CYN-

cultures, yet the CYN+ strain

remained largely unaffected. Despite the difference in appearance, both strains had

similar Chl a measurements across the culturing conditions. Chl a was higher in +N

cultures compared to –N cultures which was also reflected by the visibly greener

cultures (Figure 5.2).

CYN+ CYN-



126

Nitrogenase activity

Figure 5.3 Ethylene production by (A) CYN+ and (B) CYN

- strains of C. raciborskii

during the ARA experiment. Ethylene production was measured by a gas chromatographer and quantified against a 5 point ethylene standard curve, R

2 = 0.9998.

The effect of Fe limitation on nitrogenase activity was estimated using ARA by

measuring C2H4 production over the course of 24 h. The trend for C2H4 production was

similar for both with C2H4 production increasing linearly with time and the final yield

of C2H4 was higher in CYN+ than CYN

- cultures (Figure 5.3). Interestingly, in the

presence of a fixed-nitrogen source, both strains displayed a basal nitrogenase activity

level since ethylene production was detected throughout the experiment (Figure 5.3).

Nitrogenase activity was higher in the CYN- strain compared to the CYN

+ strain (Table

5.2). Generally, nitrogenase activity increased with increasing Fe availability, where

nitrogenase performed better in –N 1000 nM Fe than any other Fe concentrations.

However, the nitrogenase responses between the two strains were different throughout

the experiment (Table 5.2).



127

Table 5.2 Nitrogenase activity in (A) CYN+ and (B) CYN

- strains of C. raciborskii

relative to chlorophyll content.

(A) Nitrogenase activity in CYN+ strain (nmoles C2H4

µg Chl a ml

-1 h

-1)

[Fe] 2h 4h 8h 24h

+N 1000 nM 2.48 ± 0.26 1.94 ± 0.13 2.50 ± 0.20 1.10 ± 0.13

-N 1000 nM 1.84 ± 0.19 1.91 ± 0.08 1.85 ± 0.20 3.51 ± 0.32

-N 200 nM 1.58 ± 0.10 1.79 ± 0.21 1.69 ± 0.28 4.06 ± 0.65

-N 50 nM 1.40 ± 0.10 1.58 ± 0.15 1.37 ± 0.26 1.91 ± 0.16

(B) Nitrogenase activity in CYN- strain (nmoles C2H4

µg Chl a ml

-1 h

-1)

[Fe] 2h 4h 8h 24h

+N 1000 nM 1.18 ± 0.26 2.88 ± 0.29 0.81 ± 0.26 0.87 ± 0.31

-N 1000 nM 5.46 ± 0.25 11.25 ± 2.13 11.90 ± 2.26 12.20 ± 1.46

-N 200 nM 1.65 ± 0.12 0.75 ± 0.06 8.39 ± 1.26 8.45 ± 1.37

-N 50 nM 3.77 ± 0.11 2.93 ± 0.26 9.3 ± 1.16 8.66 ± 1.04

Short term 55Fe uptake

Figure 5.4 Preliminary 55

Fe uptake by C. raciborskii in the presence and absence of light. CYN

- cells were grown in +Fe or –Fe medium and incubated with

55Fe under Light

and Dark conditions. 55

Fe accumulation in cells was measured by liquid scintillation.

R² = 0.9312

R² = 0.9706

R² = 0.6622 R² = 0.6622

-1

1

3

5

7

9

11

13

15

0 2 4 6 8

Acc

um

ula

ted

55Fe

(zm

ol c

ell

-1)

x 1

00

00

Time (h)

+Fe, Light

-Fe, Light

+Fe, Dark

-Fe, Dark



128

To verify that the 55

Fe uptake assay used previously for M. aeruginosa (Fujii et

al., 2011a) could also be applied to C. raciborskii, a preliminary experiment was

conducted on CYN- strain cultured in +Fe or –Fe medium.

55Fe uptake was linear over

the time course with the highest uptake by –Fe cultures (Figure 5.4). The preliminary

study also showed that 55

Fe uptake occurred in the presence of light as cultures

incubated in dark conditions showed minimal 55

Fe uptake (Figure 5.4).

In a subsequent experiment, 55

Fe uptake was compared between CYN+ and CYN

-

strains and to test the hypothesis of whether Fe requirement is greater under N2-fixing

conditions. Although the preliminary results already showed higher Fe uptake in –Fe

cells compared to +Fe cells (Figure 5.4), Fe cannot be excluded from the culture

medium as Fe is essential for nitrogenase activity. Therefore the culturing medium was

supplemented with 50 nM Fe either with or without nitrate to stimulate N2-fixation in

the C. raciborskii strains.



129

Figure 5.5 55

Fe uptake by C. raciborskii strains in the presence or absence of combined nitrogen. Filled symbols represent CYN

+ strain while unfilled symbols represent

the CYN- strain. Cultures were incubated in JM* supplemented with 50 nM Fe, either with

(+N) or without (-N) nitrate.

When cultured in the presence of nitrate, CYN- showed significantly higher

55Fe

uptake than CYN+

which remained low throughout the experiment (Figure 5.5). Yet

under N2-fixing conditions, both strains showed similarly low levels of Fe uptake with

the CYN+ strain slightly more active than CYN

- (Figure 5.5). Unexpectedly, these

results do not support the hypothesis of increased Fe requirement during diazotrophy.

Discussion

Physiological responses to different Fe availability under N2-fixation

Under N2-fixing conditions, the trichome lengths of CYN+ reduced by 10 – 64 %

whereas 30 – 80 % reduction was observed for CYN-. Furthermore, reduced Fe

availability also produced shorter trichomes, which has been reported previously in

R² = 0.9706

R² = 0.7971

R² = 0.4256

R² = -0.248 0

100

200

300

400

500

600

0 2 4 6 8

Acc

um

ula

ted

55Fe

in c

ell (

µm

ol c

ell-1

)

Time (h)

NT +N50

Tox -N50

NT -N50

Tox +N50

CYN-, +N

CYN+, -N

CYN-, -N

CYN+, +N



130

filamentous cyanobacteria as a stress response to Fe deficiencies (Küpper et al., 2008)

and increased light intensities (Wojciechowski et al., 2016). Shorter trichomes increases

surface area to volume ratios which is likely to maximise the exchange of molecules

(such as nutrients, trace metals) allowing cells to survive under unfavourable conditions.

N2-fixing conditions led to chlorosis in CYN- cultures but not in CYN

+ cultures.

Despite the visibly greener appearance of CYN+ cultures, Chl a measurements were still

higher in the nontoxic strain. The presence of other pigments (e.g. carotenoids) in the

methanol extracts may have interfered with the absorbance measurements thus

contributed to the anomaly. Generally speaking, chlorosis is an indication of damage to

the photosystem resulting in reduced photosynthetic abilities which can be brought

about by N depletion (Sauer et al., 2001). Although PSII is lost in heterocysts, PSI is

still available to harvest light to provide ATP for N2-fixation (Stal, 2001). The

resistance to bleaching under N2-fixing and Fe-limiting conditions may be characteristic

of CYN-producers or may be a strain-specific characteristic as demonstrated by M.

aeruginosa (Alexova et al., 2011a).

Effects of Fe on nitrogenase activity

A common perception is that N2-fixation and N-assimilation occur independently,

however, as shown this study, both CYN+ and CYN

- strains retained low levels of

nitrogenase activity in the +N medium. This response mirrored previous studies in

which nitrogenase activity was still detected in C. raciborskii at ammonium

concentrations up to 10 µg L-1

(Sprőber et al., 2003) or in Trichodesmium with 2 mM

nitrate (Ohki et al., 1991). It is more likely that both processes occur simultaneously in



131

response to N availability (Willis et al., 2016). The results also suggest that N2-fixation

occurs during day time otherwise it would be expected that the 24 h ethylene

measurement would be much higher.

To minimise the competition for Fe between C-fixation and N2-fixation processes,

diazotrophs may alternate the two processes by day and night cycles (temporally), or

physical separation of vegetative cells and heterocysts (spatially), or a combination of

the two (Berman-Frank et al., 2007a). Crocosphaera utilises the temporal strategy such

that photosynthesis occurs in the day while N2-fixation occurs at night (Barnett et al.,

2012). However, the current Cylindrospermopsis study suggests that photosynthesis and

N2-fixation occur simultaneously. Therefore Fe requirement is likely to increase in order

to reduce the competition for Fe between these key biological processes. In

Trichodesmium, Fe requirement increased by up to 5-fold during N2-fixation (Kustka et

al., 2003b); surprisingly, the opposite effect was found in this study. Under N2-fixation,

55Fe uptake in CYN

- cultures was five-times lower than +N conditions, whereas Fe

uptake remained unchanged by the N2 treatment in the CYN+ cultures. The

unexpectedly lower Fe uptake under diazotrophy may be a result of cells requiring time

to adapt to Fe stress (e.g. synthesise Fe transporters) (Dang et al., 2012a) to meet the Fe

demands of N2-fixation. Furthermore, we speculate that coordinating daytime N2-

fixation with light-assisted Fe uptake may be a strategy to lower Fe requirement while

providing enough Fe to the nitrogenase enzyme. It was surprising that Fe uptake by the

nontoxic C. raciborskii strain was more efficient than the CYN+ strain given that

toxigenic strains are usually more competitive under unfavourable conditions as shown

previously by the higher Fe uptake in the MCYST-producing Microcystis strain

compared to nontoxigenic strains (Fujii et al., 2011b).



132

Competition between CYN+ and CYN- under combined N and Fe limitation

Overall, the growth of CYN+ in N2-fixing conditions appeared to be unaffected by

Fe except when concentrations became too low (e.g. at 50 nM Fe). In contrast, CYN-

growth in N2-fixing conditions was similar between the different Fe treatments. On the

basis of growth alone, the results suggest that the CYN+ strain is likely to dominate in

N2-fixing conditions where Fe concentrations are high. However, if Fe concentration is

limited under N2-fixing conditions, both strains are likely to compete and other factors

should be considered. Another factor to consider is salinity of the environment. In this

study, 1 M NaCl was used to replace the 1 M NaNO3 in the culturing medium which

may have negatively affected growth, especially since C. raciborskii is more sensitive

to salinity changes compared to other diazotrophs, where 0.03 M salt has been shown to

affect photosynthesis and growth rate (Moisander et al., 2002). Although this study

focused on characteristics directly comparable between the strains, it is reasonable to

speculate that CYN production may also influence the growth of the CYN+ strain under

unfavourable conditions, just as MCYST has done for Microcystis (Zilliges et al., 2011,

Yeung et al., 2016) and will therefore improve its competitiveness in the bloom

population.

Conclusion

This chapter examined the physiological changes of C. raciborskii strains with

differing toxigenicity in response to combined N and Fe limitation. CYN+ growth

during N2-fixation remained relatively unaffected provided that the Fe concentration in

the environment is high. On the other hand, CYN- growth was similar regardless of Fe



133

concentration during diazotrophy. This study showed that nitrogenase activity in C.

raciborskii increase with Fe availability. Contrary to expectations, Fe uptake by CYN+

and CYN- did not increase under N2-fixation yet cultures were able to maintain

nitrogenase activity. Instead, N2-fixation is proposed to occur in the daytime in order to

take advantage of light-induced reduction of complexed Fe(III) in the external medium,

thereby assisting in meeting the Fe demands of the nitrogenase enzyme.

Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in

response to iron under N2-fixing conditions

135

Chapter 6: Comparative proteomics of C. raciborskii strains with different

toxigenicity in response to iron under N2-fixing conditions

Introduction

There are numerous reports that have documented the spread of

Cylindrospermopsis raciborskii on a global scale (Briand et al., 2004, Burford et al.,

2006, Dufour et al., 2006, Sinha et al., 2012), with its success owing to its ability to

adapt to a wide range of environments (Bonilla et al., 2012). To date,

cylindrospermopsin (CYN) producing strains of C. raciborskii have only been recorded

in Australia and Asia (Rzymski and Poniedzialek, 2014, Burford and Davis, 2011). This

potent alkaloid cytotoxin is water soluble and stable across a wide temperature, light

and pH range (Chiswell et al., 1999).

In order to understand and appreciate the adaptable nature of C. raciborskii to

environmental stimuli, we must look into what drives these adaptations at a molecular

level. The genomes of the toxigenic CS-506 (CYN+) and non-toxigenic CS-509 (CYN

-)

Cylindrospermopsis raciborskii strains were recently published (Sinha et al., 2014). The

study compared the similarities of these C. raciborskii strains amongst other N2-fixing

strains including Raphidiopsis and concluded that the genetic differences were likely a

consequence of environmental niche selectivity. More importantly, the study confirmed

the importance of the cyr gene cluster in determining the toxigenic phenotype and



136

furthermore that CYN production could be linked to physiological processes (Sinha et

al., 2014).

Utilising these newly available genomes and to complement the physiological

studies conducted in Chapter 5, the proteomic responses to Fe availability under N2-

fixing conditions will be examined in this chapter. This is the first comparative

proteomic study of C. raciborskii with different toxigenic capabilities in relation to N

and Fe stress. It is expected that the protein changes in response to Fe will be specific to

each strain. The changes are documented by the use of iTRAQ labelled mass

spectrometry and matched to available protein sequences in the database for the CYN+

and CYN- strains and the model C. raciborskii CS-505.



137

Materials and methods

Experimental design

Figure 6.1 Experimental design for comparative proteomics of C. raciborskii strains with different toxigenicity. 1. Triplicate CYN

+ and CYN

- cultures were harvested at

exponential and stationary phases. 2. Protein extraction was performed and extracts were labelled with iTRAQ tags. 3. Clean up steps were performed on iTRAQ sample and submitted individually to tandem mass spectrometry and analysed using ProteinPilot software. See in text for details.

Toxigenic and nontoxigenic strains of C. raciborskii were cultured in nitrate-free

medium with different Fe concentrations to investigate the global proteomic response to

Fe limitation under N2-fixing conditions (Figure 6.1). Protein extractions were

performed at mid-exponential and stationary phases of growth and iTRAQ-labelled

tandem mass spectrometry was performed on the samples. The spectra and sequence

data were matched against composite library of available C. raciborskii CS-505

sequences on NCBI and protein sequences of the respective strain available on RAST

then analysed using ProteinPilot software V4.5.



138

Strains and culturing conditions

C. raciborskii CS-509 (CYN-) and C. raciborskii CS-506 (CYN

+) were

maintained in Jarworski Medium (Appendix A) and sub-cultured three times into

Modified JM (JM*) where NaNO3 was replaced with NaCl for N-free studies and Fe

was supplied in the form of FeCl3·6H2O complexed with EDTA only. Cultures were

incubated in a refrigerated incubator (Thermoline Scientific, Australia) at 27 °C under a

14: 10 h light:dark regime at 157 µmol photons m-2

s-1

to mimic the natural photoperiod

in nature. Cultures were manually agitated daily to maintain homogeneity and

placement within the incubator was randomised to eliminate bias from the light source.

Protein extraction and visualisation

At selected collection time points, 50 mL of C. raciborskii cultures were collected

by centrifugation (5000 x g, 20 min) and protein extracted as described in Chapter 3

(page 55). Protein extracts were visualised by SDS-PAGE on pre-cast NuPAGE 4-12%

Bis-Tris gradient gels (Invitrogen, USA). Gel electrophoresis was performed according

to Invitorgen. Gels were stained with colloidal coomassie [0.02% (w/v) Coomassie

Brilliant Blue G-250, 5% (w/v) aluminium sulfate-(14-18)-hydrate, 10% (w/v) ethanol

(96%), 2% (v/v) orthophosphoric acid (85%)] for 2 h (Dyballa and Metzger, 2009).

Gels were rinsed twice with MQ before placing in destaining solution [10% (v/v)

ethanol (96%), 2% (v/v) orthophosphoric acid (85%)] for 1 h. Gel shrinkage can occur

during destaining procedure, rinse gels with MQ to return gels to original thickness.



139

iTRAQ labelling

Exponential phase samples from each Fe treatment was labelled with unique

iTRAQ tags: T113 for 50 nM Fe, T114 for 200 nM Fe and T115 for 1000 nM Fe.

Similarly, tags T116, T117 and T118 were used for stationary phase conditions 50 nM,

200 nM and 1000 nM Fe respectively. Samples were labelled as previously described

(page 56).

Sample preparation and mass spectrometry analysis

iTRAQ samples were prepared as previously described (see page 57). 2D

LC/MS/MS was performed by Dr Anne Poljak (Biomolecular Mass Spectrometry

Facility, UNSW, Australia) on an API QStar Elite hybrid tandem mass spectrometer

(Applied Biosystems, Foster City, CA). Spectral data were analysed with ProteinPilot

software V4.5 against a composite database library constructed from available

sequences for C. raciborskii strains CS-505, CS-506 and CS-509. Protein sequences for

C. raciborskii CS-505 were downloaded from UniProt (October 2014) while CS-506

and CS-509 were obtained from Rapid Annotations using Subsystems Technology

(RAST: http://rast.nmpdr.org/) server under sequencing jobs #22519 and #22520

respectively.

http://rast.nmpdr.org/



140

Results

Effects of Fe availability on growth under N2-fixing conditions

Figure 6.2 Growth curves of CYN+ (left) and CYN

- (right) in N-free media with varying

Fe concentrations. Growth was monitored at 750 nm by UV spectrophotometry over the course of the experiment. Protein extraction was performed on Day 7 and Day 14 as indicated by red arrows for exponential and stationary phase studies respectively. C. raciborskii were cultured in N-free conditions with iron concentrations 50nM Fe (), 200 nM Fe () and 1000 nM Fe (▲).

The growth of CYN+ and CYN

- strains in N2-fixing conditions was compared

between 50 nM, 200 nM and 1000 nM Fe concentrations. Cell concentration at the end

of the experiment was highest at 1000 nM Fe condition with the CYN+ strain growing

to OD750 = 0.045 whereas the CYN- strain grew to OD750 = 0.035 (Figure 6.2). Similarly

CYN+

growth was higher than CYN- in the 200 nM Fe condition. However, the 50 nM

Fe condition affected the growth of both strains equally with the OD750 falling to 0.028

for CYN+ compared to 0.025 for CYN

- (Figure 6.2). Cultures were harvested on Day 7

(exponential phase) and Day 14 (stationary phase) for protein extraction.



141

Comparative proteome analysis

Figure 6.3 Representative SDS PAGE gels of C. raciborskii CYN+ (left) and CYN

-

(right) at exponential phase and stationary phrase. For each sample, 15 µg of protein

was separated by electrophoresis on 4-12% Bis-Tris gel (Invitrogen). Ladder: Broadrange

Protein Marker (BioRad). 50: 50 nM Fe; 200: 200 nM Fe; 1000: 1000 nM Fe.

Protein samples were visualised by SDS PAGE to evaluate the extraction

procedure prior to iTRAQ labelling for proteomic analysis. Although the protein

banding patterns were similar between different Fe concentrations in CYN+, the

intensity of the bands differed despite loading equivalent amount of protein to each

lane (Figure 6.3). A second BCA was performed for CYN+ samples and protein extracts

were normalised to the sample with the lowest amount of protein to ensure equivalent

quantities were supplied for iTRAQ labelling.



142

Figure 6.4 Distribution of identified proteins in functional groups from CYN+ (Top)

and CYN- (Bottom). Proteins were categorised according to their annotations on RAST.

C S -5 0 6 (C Y N+)

8 .5 7 % A m in o a c id s a n d d e riv a tive s

1 2 .7 0 % C -fixa tio n a n d ca rb o n m e ta b o lism

2 .5 4 % C e ll d iv is io n a n d re g u la to ry p ro c e s s e s

3 .4 9 % C o fa c to rs , V ita m in s , P ro s th e tic G ro u p s , P ig m e n ts

4 .1 3 % D N A a n d R N A M e tab o lism

1 .2 7 % F a tty A c id s , L ip id s , a n d Iso p re n o id s

1 8 .4 1 % H yp o th e tic a l

3 .8 1 % O th e r c a te g o r ie s (M is ce lla n e o u s )

1 3 .6 5 % P h o to s yn th e s is a n d re sp ira tio n

0 .3 2 % P h o s p h o ru s M e ta b o lism

1 3 .3 3 % P ro te in M e ta b o lism

1 .9 0 % R e g u la tio n a n d C e ll s ig n a lin g

0 .6 3 % R e d o x p ro te in s

4 .7 6 % S tre s s R e s p o n s e

T o ta l = 3 1 5

6 .0 3 % T ra n s p o rt a n d b in d in g p ro te in s

1 .9 0 % N itro g e n M e ta b o lism

2 .5 4 % T ra n sp c rip tio n a n d tra n s la t io n

C S -5 0 9 (C Y N-)

4 .0 4 % A m in o A c id s a n d D e riv a tive s

1 0 .0 0 % C -fixa tio n a n d ca rb o n m e ta b o lism

4 .2 6 % C e ll D iv is io n a n d re g u la to ry p ro ce s s e s

4 .0 4 % C o fa c to rs , V ita m in s , P ro s th e tic G ro u p s , P ig m e n ts

7 .4 5 % D N A a n d R N A m e ta b o lism

1 .4 9 % F a tty A c id s , L ip id s , a n d Iso p re n o id s

2 2 .1 3 % H yp o th e tic a l

4 .8 9 % O th e r c a te g o r ie s (m is c e lla n e o u s )

2 .1 3 % N itro g e n m e ta b o lism

0 .8 5 % P h o s p h o ru s M e ta b o lism

1 4 .6 8 % P ro te in m e ta b o lism

2 .3 4 % R e g u la tio n a n d C e ll s ig n a lin g

2 .9 8 % S tre s s re s p o n s e

2 .5 5 % T ra n s c rip t io n a n d T ra n s la t io nT o ta l = 4 7 0

4 .6 8 % T ra n s p o rt a n d b in d in g p ro te in s

1 0 .6 4 % P h o to s yn th e s is a n d re sp ira tio n

0 .8 5 % S u lfu r m e ta b o lism



143

A total of 315 proteins from CYN+ and 470 proteins from CYN

- were identified in

the iTRAQ-506 and iTRAQ-509 runs respectively. These account for 10% and 14% of

the proteome coverage for the CYN+ and CYN

- strains respectively. The identified

proteins were categorised into 18 functional groups as annotated in RAST (Figure 6.4).

For both strains, proteins mainly grouped to carbon fixation and carbon metabolism

(12.7% in CYN+, 10% in CYN

-), protein metabolism (13% in CYN

+, 15% in CYN

-),

photosynthesis related (13.7% in CYN+ and 10.6% in CYN

-) and hypothetical (18% in

CYN+, 22% in CYN

-) functional categories. Overall, the protein categories were

similarly distributed between the two Cylindrospermopsis strains. For each strain, the

1000 nM Fe condition produced the highest culture yield as the conditions were non-

limiting (Figure 6.2), hence this was used as the control condition for all protein

expression comparisons in each iTRAQ experiment. For each study, data analysis was

further separated into exponential and stationary phases to account for differences in

biomass at the time of harvesting.

Effects of Fe availability on protein expression in CYN+ strain

During exponential phase, 22 proteins were differentially expressed in the 200 nM

Fe condition while 16 proteins were differentially expressed in the 50 nM Fe condition

relative to control condition (1000 nM Fe). The majority of these proteins belonged to

energy metabolism (e.g. carbon metabolism and photosynthesis related proteins),

membrane transport and amino acid metabolism functional categories (Table 6.1, Figure

6.5). Three transport proteins were down-regulated in both Fe conditions including S-

layer protein-like protein, sodium/hydrogen exchanger, and extracellular ligand-binding

receptor (Table 6.1). However, a putative porin protein was strongly up-regulated by

6.5-fold under both Fe conditions. Furthermore, Fe starvation likely affected nitrogen



144

assimilation as nitrogenase reductase was down-regulated by 0.85-fold only in the 50

nM Fe but not the 200 nM Fe condition (Table 6.1).

During stationary phase, 26 proteins were differentially expressed in 200 nM Fe

and 33 changes occurring in 50 nM Fe compared to the control (Table 6.2; Figure 6.6).

Again, functional categories most affected by reduced Fe availability included amino

acid metabolism, transport and binding proteins and transcription/translations proteins.

In particular, transport proteins such as the bicarbonate transporter and periplasmic

substrate-binding protein were down-regulated by between 2 to 4 -fold in both Fe

conditions. Proteins were rarely up-regulated and did not appear to follow a particular

pattern of expression under Fe limitation. For example, phycocyanin alpha subunit

(CpcA) was up-regulated by 1.7-fold in 200 nM Fe only, while elongation factor Ts was

up-regulated by 1-fold in 50 nM Fe. However, protective antigen (Oma87) was up-

regulated 4-fold in both Fe conditions (Table 6.2).

Effects of Fe availability on protein expression in CYN- strain

During exponential phase, the majority of the changes to protein expression were

observed for the 50 nM Fe case with changes in 32 proteins, while 10 proteins were

differentially regulated in the 200 nM Fe case (Table 6.3). The CYN- strain responded

to Fe starvation by down-regulating proteins across some major protein categories

including energy metabolism as well as transcription and translation proteins. Energy

metabolism proteins involved in carbon fixation and photosynthesis-related categories

were mostly down-regulated in the 50 nM Fe cultures. Likewise transcription and

translation proteins from the 50 nM Fe condition were also strongly down-regulated

relative to 1000 nM Fe. In particular, peptidyl-prolyl cis-trans isomerase (PPIase) which

is required for the correct protein folding was down-regulated by 6.5-fold; ribosomal



145

proteins L7 and L10 were down-regulated by 2.3-fold and 4.7-fold respectively (Table

6.3). Hypothetical proteins were also reduced between -1.8-fold to -4.3-fold.

During stationary phase, six proteins were differentially regulated in the 200 nM

Fe condition and seven proteins differentially regulated in 50 nM Fe compared to the

control condition (Table 6.4). However, the majority of the protein expression changes

were up-regulated. For example, twin-arginine translocation pathway signal protein was

up-regulated by 2.4-fold and 1.5-fold in 50 nM and 200 nM Fe conditions respectively.

Transporter proteins and the putative DNA binding protein, DevH, were found to

be exclusively up-regulated in the 50 nM Fe condition at stationary phase while the

chaperone protein, GroEL, was exclusively up-regulated in 200 nM Fe stationary phase

(Table 6.4). Phosphorus metabolism related proteins, inorganic pyrophosphatase and 2-

phosphosulfonlactate phosphatase, were also down-regulated for both Fe conditions

during stationary phase.

Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in response to iron under N2-fixing conditions

146

Table 6.1 Differentially expressed proteins in CYN+ CS-506 at exponential phase. Proteins were annotated using a composite search library

containing amino acid sequences for C. raciborskii CS-505 available from UniProt (www.uniprot.org) and sequences for C. raciborskii CS-506 available from RAST. Positive values (green) indicate increase expression relative to the control condition (1000 nM Fe) while negative values (red) denote decrease expression relative to control conditions. Gene names are given in italics.

Accession Protein ID 50 vs 1000

PVal Log2 Fold

200 vs 1000

Pval Log2 Fold


533241.6.peg.1906 Serine hydroxymethyltransferase 0.131 0.003 -2.937

D4THV1_9NOST Acetylglutamate kinase (argB) 0.625 0.003 -0.678

D4TD09_9NOST LL-diaminopimelate aminotransferase (dapL) 0.011 0.016 -6.498

533241.6.peg.2565 Adenylosuccinate synthetase 4.571 0.036 2.192 3.251 0.043 1.701

533241.6.peg.863 2-keto-3-deoxy-D-arabino-heptulosonate-7-phosphate (DAHP) synthase I beta

1.786 0.036 0.837

Cellular processes

533241.6.peg.1270 Superoxide dismutase [Fe] 4.656 0.028 2.219

533241.6.peg.1302 BioD-like N-terminal domain of phosphotransacetylase 0.011 0.018 -6.498 0.011 0.018 -6.498

Energy metabolism (Carbohydrate metaboilsm and carbon fixation)

533241.6.peg.2340 4-alpha-glucanotransferase (amylomaltase) 0.673 0.005 -0.571

533241.6.peg.2476 Glycogen synthase ADP-glucose transglucosylase 0.637 0.003 -0.651

D4TD39_9NOST Glutamine--fructose-6-phosphate aminotransferase -isomerizing 3.048 0.049 1.608

533241.6.peg.3197 Lactoylglutathione lyase 0.780 0.031 -0.359

533241.6.peg.1767 Malonyl CoA-acyl carrier protein transacylase 0.011 0.017 -6.484

Energy metabolism (Photosynthesis and respiration)

533241.6.peg.466 Allophycocyanin alpha chain 5.248 0.013 2.392 2.559 0.034 1.355

533241.6.peg.467 Allophycocyanin beta chain 2.729 0.038 1.448

533241.6.peg.3117 Photosystem II 12 kDa extrinsic protein (psbU) 2.228 0.026 1.156

http://www.uniprot.org/


147

Table 6.1 cont.


PVal Log2 Fold

200 vs 1000

Pval Log2 Fold

Genetic information (Transcription and translation proteins)

D4TD75_9NOST Transcriptional regulator AbrB 0.011 0.019 -6.484

D4TDS6_9NOST HAD-superfamily hydrolase, subfamily IA, variant 1 0.011 0.019 -6.484 0.011 0.019 -6.484

533241.6.peg.2139 Nuclease A inhibitor-like 0.180 0.034 -2.472

D4TK12_9NOST Two Component Transcriptional Regulator, LuxR family 0.275 0.003 -1.860

D4THJ6_9NOST DNA-directed RNA polymerase (rpoC1) 0.955 0.040 -0.066

533241.6.peg.1482 ATP-dependent Clp protease proteolytic subunit 0.904 0.039 -0.146

Nitrogen metabolism

533241.6.peg.2707 Nitrogenase (Mo-Fe) reductase and maturation protein (nifH) 0.555 0.030 -0.850


D4TGR8_9NOST S-layer region protein-like protein 0.099 0.016 -3.335

D4TK17_9NOST S-layer region protein-like protein 0.912 0.005 -0.133 0.946 0.014 -0.080

D4TDZ_9NOST Extracellular ligand-binding receptor 0.111 0.000 -3.176 0.275 0.000 -1.860

D4TJZ5_9NOST Sodium/hydrogen exchanger 0.126 0.001 -2.990 0.219 0.002 -2.192

D4TCY9_9NOST ABC transporter substrate-binding protein 0.053 0.032 -4.225

533241.6.peg.682 Possible porin 87.902 0.048 6.458 87.902 0.045 6.458


D4TL32_9NOST Hypothetical protein 0.655 0.049 -0.611

533241.6.peg.1265 Hypothetical protein 1.057 0.008 0.080


148

Table 6.2 Differentially expressed proteins in CYN+ CS-506 at stationary phase. Proteins were annotated using a composite search library

containing amino acid sequences for C. raciborskii CS-505 available from UniProt (www.uniprot.org) and sequences for C. raciborskii CS-506 available from RAST. Positive values (green) indicate increase expression relative to the control condition (1000 nM Fe) while negative values (red) denote decrease expression relative to control conditions. Gene names are given in italics.

Accession Protein ID 50 Fe vs 1000

Pval Log2 Fold

200 Fe vs 1000

Pval Log2 Fold

Amino acids and derivatives

533241.6.peg.2111 Dihydroxy-acid dehydratase (ilvD) 0.296 0.032 -1.754

533241.6.peg.1906 Serine hydroxymethyltransferase (glyA) 0.302 0.003 -1.727 0.231 0.003 -2.113

533241.6.peg.1900 Argininosuccinate synthase (argG) 0.192 0.040 -2.379

D4THV1_9NOST Acetylglutamate kinase (argB) 2.443 0.015 1.289 0.291 0.007 -1.781

D4TGT5_9NOST Valine--tRNA ligase (valS) 0.011 0.018 -6.498 0.011 0.018 -6.498

D4TE84_9NOST Aminotransferase, class V 81.658 0.045 6.352

Cellular process

533241.6.peg.2885 Mo-cofactor of nitrate reductase (moaD) 0.625 0.004 -0.678

533241.6.peg.2027 Ubiquinone biosynthesis monooxygenase (ubiB) 0.194 0.018 -2.365 1.169 0.040 0.226

533241.6.peg.385 Sugar-non-specific nuclease NucA homolog 0.139 0.001 -2.844

533241.6.peg.1270 Superoxide dismutase [Fe] 0.161 0.008 -2.631

533241.6.peg.2225 Thioredoxin (trxA) 0.136 0.002 -2.883

533241.6.peg.1671 Outer membrane protein/protective antigen OMA87 18.535 0.009 4.212 26.792 0.006 4.744

533241.6.peg.2028 Alkyl hydroperoxide reductase subunit C-like protein 1.086 0.004 0.120



149

Table 6.2 cont.


Pval Log2 Fold

200 Fe vs 1000

Pval Log2 Fold

Energy metabolism (Carbohydrate metabolism and carbon fixation)

533241.6.peg.2877 Ribulose bisphosphate carboxylase large chain (rbcL) 2.014 0.042 1.010

533241.6.peg.968 Triosephosphate isomerase (tpiA) 0.453 0.002 -1.143

533241.6.peg.2340 4-alpha-glucanotransferase (amylomaltase) 0.991 0.010 -0.013

533241.6.peg.668 Galactose mutarotase and related enzymes 0.151 0.031 -2.724

533241.6.peg.2476 Glycogen synthase ADP-glucose transglucosylase 0.637 0.044 -0.651

Energy metabolism (Photosyntheiss and respiration)

D4TI18_9NOST Phycocyanin, alpha subunit (cpcA) 3.373 0.014 1.754

533241.6.peg.295 NADPH-dependent FMN reductase 0.172 0.033 -2.538

D4TFJ9_9NOST ATP synthase subunit beta 7.943 0.027 2.990


D4TG92_9NOST 50S ribosomal protein L3 (rplC) 0.011 0.017 -6.498

533241.6.peg.1894 SSU ribosomal protein S2p 0.229 0.011 -2.126 6.546 0.026 2.711

D4TCX1_9NOST Twin-arginine translocation pathway signal 0.421 0.048 -1.249 0.244 0.027 -2.033

533241.6.peg.714 Cell division trigger factor 0.119 0.003 -3.069

533241.6.peg.2820 Cell division protein FtsH 0.692 0.029 -0.532

533241.6.peg.2139 Nuclease A inhibitor-like 0.325 0.032 -1.621

533241.6.peg.513 Nucleoside diphosphate kinase 0.398 0.027 -1.329

D4TCD4_9NOST Elongation factor Ts 2.148 0.049 1.103

D4THJ6_9NOST DNA-directed RNA polymerase (rpoC1) 1.330 0.048 0.412


150

Table 6.2 cont.


Pval Log2 Fold

200 Fe vs 1000

Pval Log2 Fold


D4TK17_9NOST S-layer region protein-like protein 0.879 0.001 -0.186 0.895 0.001 -0.159

D4TGR8_9NOST S-layer region protein-like protein 0.251 0.000 -1.993 0.356 0.000 -1.488

D4TDZ7_9NOST Extracellular ligand-binding receptor 0.179 0.000 -2.485 0.164 0.000 -2.604

533241.6.peg.720 Branched-chain amino acid/ABC transporter amino acid-binding protein

0.044 0.000 -4.505 0.313 0.001 -1.674

533241.6.peg.1686 Bicarbonate transporter bicarbonate binding protein 0.158 0.021 -2.658 0.119 0.018 -3.069

D4TJZ5_9NOST Sodium/hydrogen exchanger 0.215 0.002 -2.219

D4TCY9_9NOST ABC transporter, periplasmic substrate-binding protein 0.051 0.033 -4.292 0.116 0.035 -3.109

D4THG2_9NOST ABC transporter, transmembrane region protein 0.011 0.019 -6.445

Hypothetical Proteins

533241.6.peg.1595 Hypothetical protein 0.207 0.024 -2.272 0.121 0.021 -3.043

533241.6.peg.2658 Hypothetical protein 0.525 0.030 -0.930

533241.6.peg.3071 Hypothetical protein 1.923 0.030 0.943





151

Table 6.3 List of significantly differentiated proteins in CYN- CS-509 at exponential phase. Proteins were annotated using a composite search

library containing amino acid sequences for C. raciborskii CS-505 available from UniProt (www.uniprot.org) and sequences for C. raciborskii CS-509

available from RAST. Positive values (green) indicate increase expression relative to the control condition (1000 nM Fe) while negative values (red)

denote decrease expression relative to control conditions. Gene names are given in italics.


Pval Log 2 Fold

200 vs 1000

Pval Log 2 Fold


D4TD12_9NOST Ornithine carbamoyltransferase 0.043 0.042 -4.544

Cellular processes

D4TE15_9NOST ThiJ/PfpI domain protein-containing protein 0.286 0.048 -1.807

D4TDK9_9NOST Alkyl hydroperoxide reductase subunit C-like protein 0.421 0.028 -1.249

D4TL38_9NOST Chemotaxis signal transduction protein (cheW) 0.014 0.026 -6.179

Energy metabolism (Carbohydrates metabolism and carbon fixation)

D4TFV3_9NOST Phosphoenolpyruvate synthase 1.028 0.005 0.040

D4TFW2_9NOST Glucokinase 1.009 0.008 0.013

533244.4.peg.2520 Probable glycosyl transferase 0.012 0.027 -6.338

D4TFL7_9NOST D-3-phosphoglycerate dehydrogenase 0.011 0.026 -6.498

Energy metabolism (Photosynthesis and respiration)

D4TI17_9NOST Phycocyanin beta chain 0.145 0.022 -2.790

D4TJC0_9NOST Allophycocyanin alpha subunit (apcA) 0.384 0.011 -1.382 0.667 0.008 -0.585

D4TF75_9NOST Plastocyanin precursor (petE) 0.305 0.016 -1.714

D4TCV1_9NOST Photosystem I subunit II (psaD) 0.177 0.020 -2.498

D4TIZ0_9NOST Photosystem II CP47 protein (psbB) 0.506 0.042 -0.983



152

Table 6.3 cont.


Pval Log 2 Fold

200 vs 1000

Pval Log 2 Fold

Energy metabolism (Photosynthesis and respiration) cont.

D4TJF2_9NOST ATP synthase alpha chain 0.166 0.031 -2.591

D4TJE9_9NOST ATP synthase B chain 0.011 0.023 -6.498

D4TJ74_9NOST NADPH-dependent FMN reductase 0.103 0.020 -3.282

D4TIV3_9NOST NADPH-quinone oxidoreductase chain H 0.839 0.007 -0.252

Genetic information processing (Transcription and translation proteins)

D4TCM4_9NOST RNA-binding protein 0.334 0.001 -1.581

533244.4.peg.2779 Ribonuclease I precursor 0.112 0.042 -3.162

D4TJF5_9NOST Peptidyl-prolyl cis-trans isomerase 0.011 0.024 -6.484

D4THE1_9NOST Two-component response regulator 0.261 0.028 -1.940

gi|282901474 tRNA synthetase, class II (G, H, P and S) 0.409 0.032 -1.289

D4TE60_9NOST Ribosomal protein L7/L12 0.209 0.017 -2.259

D4TE59_9NOST Ribosomal protein L10 0.040 0.044 -4.651

D4TF59_9NOST Peptidase U62, modulator of DNA gyrase 0.597 0.048 -0.744

D4TFB3_9NOST Aminotransferase, class I and II 0.550 0.045 -0.864 0.191 0.032 -2.392

D4TK45_9NOST Ribonuclease H 0.938 0.009 -0.093

D4TLW0_9NOST Chaperone protein DnaJ 0.887 0.643 -0.173

533244.4.peg.3184 ATP-dependent Clp protease proteolytic subunit 0.603 0.046 -0.731


533244.4.peg.963 ABC-type transport systems, periplasmic components 4.285 0.020 2.099

533244.4.peg.3090 Urea ABC transporter, urea binding protein 0.172 0.011 -2.538 0.360 0.014 -1.475

533244.4.peg.2559 Zinc-regulated outer membrane porin 0.233 0.004 -2.099


153

Table 6.3 cont.


Pval Log 2 Fold

200 vs 1000

Pval Log 2 Fold

Phosphorus metabolism

D4THF7_9NOST Inorganic pyrophosphatase 0.824 0.006 -0.279

Hypothetical proteins gi|282900920 Hypothetical protein 0.268 0.006 -1.900

gi|282900833 Hypothetical protein 0.278 0.003 -1.847





154

Table 6.4 List of significantly differentiated proteins in CYN- CS-509 at stationary phase. Proteins were annotated using a composite search

library containing amino acid sequences for C. raciborskii CS-505 available from UniProt (www.uniprot.org) and sequences for C. raciborskii CS-509

available from RAST. Positive values (green) indicate increase expression relative to the control condition (1000 nM Fe) while negative values (red)

denote decrease expression relative to control conditions. Gene names are given in italics.


Pval Log 2 Fold

200 vs 1000

Pval Log 2 Fold

Cellular processes

D4TI85_9NOST Two-component response regulator 1.770 0.034 0.824

D4THE1_9NOST Twin-arginine translocation pathway signal 5.445 0.001 2.445 2.780 0.001 1.475

D4TH04_9NOST Glutathione S-transferase family protein 1.570 0.032 0.651

D4TKA3_9NOST Universal stress protein A (uspA) 0.225 0.048 -2.153


D4TK15_9NOST Heat shock protein 60 family chaperone GroEL 1.675 0.024 0.744

D4TKW8_9NOST Putative DNA binding protein (devH) 3.597 0.021 1.847

D4TK72_9NOST Ribosomal RNA small subunit methyltransferase B 0.766 0.006 -0.385


533244.4.peg.3090 Urea ABC transporter, urea binding protein 2.070 0.009 1.050

533244.4.peg.846 Outer membrane protein 2.051 0.004 1.036

Phosphorus metabolism

D4THF7_9NOST Inorganic pyrophosphatase 0.698 0.004 -0.518

D4TD05_9NOST 2-phosphosulfolactate phosphatase 0.417 0.037 -1.262

Hypothetical protein

gi|282900548 Hypothetical protein 1.738 0.000 0.797




155

Figure 6.5 Heat map of

differentially

expressed proteins

from exponential

phase arranged by

functional

categories.Proteins are

coloured by fold

changes relative to 1000

nM Fe condition. CYN+

is shown at the top

panel and CYN- is at the

bottom panel. Red

represents reduced

expression and green

for increased

expression. Boxes are

coloured grey where the

protein was not

detected.



156

Figure 6.6 Heat map of differentially expressed proteins from stationary phase arranged by functional groups. Proteins are mapped by fold change differences relative to 1000 nM Fe. CYN

+ is shown at the top panel and CYN

- is at the bottom panel. Green

boxes represent increased expression; red boxes indicate reduced expression. Boxes are coloured grey when the protein is not detected.



157

Discussion

Diazotrophy enables C. raciborskii to utilise nitrogen (N2) from the atmosphere

when combined nitrogen sources become depleted in the medium. However, since Fe is

required for the synthesis of nitrogenase plus multiple other cellular processes, it is

expected that the co-limitation of N and Fe would affect multiple protein pathways.

During exponential phase, when Fe concentration the medium was reduced to 200

nM Fe, CYN+

responded by increasing expression of energy metabolism functional

categories, specifically allophycocyanin and PsbU proteins which are involved in light

harvesting and PSII stability respectively (Kashino et al., 2002, Fromme et al., 2003).

Conversely, CYN- was severely affected by Fe limitation and a wide range of proteins

were down-regulated, as if undergoing metabolic shutdown by decreasing the

expression of primary metabolism proteins (Figure 6.5).

As cell growth continued on to stationary phase, primary metabolism functional

groups decreased in expression as expected, indicative of the cells preparing for

stationary phase (Chubukov and Sauer, 2014). This expected response was observed in

CYN+

strain, in contrast, primary metabolism proteins in CYN- were already down-

regulated at exponential phase instead, and stress response and chaperone proteins were

up-regulated during stationary phase.

Transport and binding proteins appeared to be the only category affected at

exponential phase under Fe starvation (50 nM) as no other categories received as many

differentially expressed proteins. The twin-arginine translocation (Tat) pathway signal

protein was differentially expressed in the CYN- strain only, furthermore the regulation

of this protein is likely to be related to Fe availability since increased expression was



158

found in conditions for reduced Fe availability (e.g. 50 nM vs 200 nM Fe). The Tat

pathway is involved in protein translocation across the cytoplasmic and thylakoid

membrane and, while this pathway is well studied in E. coli (Lee et al., 2006), its role in

cyanobacteria is less clearly defined. A recent review by Barnett and colleagues (2011),

the authors described the involvement of the Tat pathway in the biosynthesis of

metalloproteins, such as the PetC (containing FeS cluster and superoxide dismutase),

where metal cofactors are added to binding sites before translocation.

The putative DNA binding protein, DevH, is a protein closely related to the global

nitrogen regulator (NtcA) and is also required for heterocysts activation (Ramírez et al.,

2005). Its exclusive up-regulation during Fe starvation in the CYN- strain supports the

link between Fe and N regulation. On the other hand, the chaperone protein, GroEL,

was exclusively up-regulated in 200 nM Fe stationary phase may increase the stability

of the RuBisCo protein (Liu et al., 2010).

It is becoming increasingly clear that toxigenic and nontoxigenic strains of a

species behave differently to environmental stimuli (Alexova et al., 2016, D'Agostino et

al., 2016). This study supports this as the differentially expressed proteins were mainly

strain specific. The pathways activated or deactivated also differ between the strains.

Overall, the CYN+ strain responded to Fe availability by up-regulating photosynthesis

and nitrogen assimilation pathways. However the transcription and translation pathway

are altered in CYN- in response to Fe.



159

Conclusion

Through this chapter, the response of toxigenic and nontoxigenic strains of C.

raciborskii to combined N and Fe limitation was examined from a molecular

perspective, specifically by comparing the global expression changes of proteins in

response to total Fe concentration in the medium under N2-fixation. The different

proteomic responses reflected the strain specificities and sensitivity to Fe availability. In

this chapter, CYN- appeared to have a higher Fe requirement and this was shown by the

down regulation of multiple primary metabolism pathways during the early stages of

growth. Conversely, CYN+ may be more persistent in environments where Fe may be

limiting as the differentially expressed proteins were not to do with growth but with

membrane transport.

Chapter 7: Summary and future work

161


This chapter is an overview of the main findings from each major chapter and

answers the questions posed at the beginning of the thesis. It also shares some insights

on the potential future work that relates to these conclusions.

Summary

This thesis provides new insight in the growth response of two cosmopolitan

freshwater species of bloom-forming cyanobacteria, M. aeruginosa and C. raciborskii,

to iron availability. This new understanding enables managing authorities to prepare for

and mitigate control strategies to treat future algal blooms in freshwater systems.

The physiological response to Fe availability was explored in Chapter 2, where

chemostat systems with different Fe availabilities were used to examine the

physiological adaptations in the MCYST-producing M. aeruginosa were compared at

different growth rates. Decreases in cell size and chlorophyll content in Fe-limited

cultures were indicative of its role in growth and photosynthesis. Comparison of

MCYST content between the Fe conditions produced some unexpected results with

equally high MCYST levels recorded across all Fe-limited cultures whereas high

MCYST levels were only recorded in slow growing Fe-replete cultures. Additionally,

extracellular MCYST was detected at increasing levels in Fe-limited conditions but not

detected when replete concentration of Fe was used in the medium. The higher MCYST


162

concentration also increased the cells’ resilience to ROS. Taken together, the results of

this chapter have strong implications for increased fitness of the MCYST-producing

strain under Fe-limiting conditions with the possibility of increased exposure to

cyanotoxins under these conditions when cells release MCYST into surroundings.

In Chapter 3, proteomic analysis was carried out on the same M. aeruginosa

chemostat cultures to view the adaptions to iron availability on a molecular level. It was

discovered that Fe-limited cultures have increased expression of transporter proteins

which is likely to increase exchange between cell membranes and may contribute to the

increase in extracellular MCYST detected in the Fe-limited samples of Chapter 2.

Furthermore, the affected functional categories differed depending on Fe availability in

the medium with increased expression of proteins for oxidative stress protection. As

expected, reduced Fe availability affected primary metabolism processes such as carbon

fixation, photosynthesis and protein metabolism, strengthening the links between Fe

availability and growth and succession of bloom-forming M. aeruginosa.

Delving deeper into the complexities of Fe bioavailability in the aquatic

environment, Chapter 4 explored the impact that major cations, magnesium and

calcium, have on photochemical Fe(II) formation and subsequently how they affect Fe

uptake by M. aeruginosa. The Fe(II) formation was studied using two different metal

binding ligands: EDTA – commonly used in phytoplankton culturing medium, and

fulvic acid – major Fe-binding ligand in natural waters. In the presence of excess

divalent metals, Fe uptake rate was found to increase significantly in the EDTA system

as the cations competitively bind EDTA, Fe(III) is released from the complex.

However, in the fulvic acid buffered system, these divalent cations had little effect on

the ligand and actually hindered Fe uptake by up to 5-fold. From this study, it is clear


163

that calcium and magnesium concentrations (major indicators of water hardness)

together with ligand type can significantly influence the bioavailability of Fe in natural

waters. As discussed in earlier chapters Fe limitation could result in selection of the

resilient toxin-producing cyanobacteria and further affect the success of the species in

bloom situations.

In Chapters 5 and 6, C. raciborskii is introduced as a rising concern for modern-

day cyanobacterial blooms due to their invasion from tropical into temperate regions.

Furthermore, Australian strains are known to produce cylindrospermopsin, another

potent hepatotoxin responsible for the 1979 hepatoenteritis outbreak on Palm Island in

Queensland, Australia. In contrast to earlier chapters, C. raciborskii is capable of

diazotrophy which enables it to ‘fix’ dinitrogen from the atmosphere to supplement its

needs at times when combined N sources are limited. However, Fe plays a large role in

the N2-fixation process and might be expected to strongly influence the expansion of

N2-fixing cyanobacteria.

In chapter 5, batch cultures of CYN+ and CYN

- strains were cultured in medium

devoid of combined N sources. Iron was added at different concentrations to the

cultures to examine the differences in physiological response between the two strains.

Overall CYN+ strain had higher growth than CYN

- under N2-fixing conditions however,

growth was equally affected when Fe concentrations were reduced to 50 nM. Looking at

the effect of Fe concentration on N2-fixation, the study found that nitrogenase activity

generally increased with the availability of Fe. Surprisingly though, the rate of Fe

uptake rate did not increase in N2-fixing conditions. This may be attributed the lack of

Fe transporters in the cells, hence a lag in the Fe uptake response at the time of the

experiment. From the results, it is predicted that the CYN+ strain would outcompete the


164

CYN- strain in N2-fixing conditions where Fe is not limiting. However, under N2-fixing

conditions where Fe concentrations are starved, both strains are likely to co-exist and

other environmental factors should be considered.

Using the same N2 and Fe growth conditions, Chapter 6 focussed on the

adaptation and regulation of CYN+ and CYN

- strains to Fe limitation at a protein level.

Using iTRAQ-labelled tandem mass spectrometry, the protein categories affected by Fe

were found to be strain specific. In agreement with the physiological results in Chapter

5, the increased expression of photosynthesis, nitrogen metabolism, and membrane

transport proteins in CYN+ are likely to be crucial in maintaining growth during Fe

limitation. For the CYN- strain however, the primary metabolism pathways were down-

regulated, with up-regulation mainly seen in chaperone and stress response type

proteins, suggesting that reducing oxidative stress and improving stability of proteins

may be the main strategies of survival for CYN-.

Future work

As laboratory experiments aim to replicate situations in nature in a controlled

manner, it becomes apparent to build on single parameter experimental setups to

examine interacting drivers. We began doing this in the Cylindrospermopsis chapters by

studying the links between N and Fe requirement – or “co-limiting” environments.

In nature, algal blooms do not exist as monocultures but as mixed communities

with different genus and strains. It would be valuable for future studies to include

microcosm experiments to examine the interactions between bloom forming strains.

This could be achieved through co-culture studies using vessels separated by permeable


165

membranes which allow for the exchange of nutrients and other small molecules, while

still keeping testing strains separate.

References

167

References

AL-TEBRINEH, J., MERRICK, C., RYAN, D., HUMPAGE, A., BOWLING, L. &

NEILAN, B. A. 2012. Community composition, toxigenicity, and environmental

conditions during a cyanobacterial bloom occurring along 1,100 kilometers of

the Murray River. Appl Environ Microbiol, 78, 263-72.

ALEXOVA, R. 2010. The regulation of toxin synthesis in Microcystis aeruginosa. PhD

Thesis, The University of New South Wales.

ALEXOVA, R., DANG, T. C., FUJII, M., RAFTERY, M. J., WAITE, T. D.,

FERRARI, B. C. & NEILAN, B. A. 2016. Specific global responses to N and Fe

nutrition in toxic and non-toxic Microcystis aeruginosa. Environ Microbiol, 18,

401-13.

ALEXOVA, R., FUJII, M., BIRCH, D., CHENG, J., WAITE, T. D., FERRARI, B. C.

& NEILAN, B. A. 2011a. Iron uptake and toxin synthesis in the bloom-forming

Microcystis aeruginosa under iron limitation. Environ Microbiol, 13, 1064-77.

ALEXOVA, R., FUJII, M., BIRCH, D., CHENG, J., WAITE, T. D., FERRARI, B. C.

& NEILAN, B. A. 2011b. Iron uptake and toxin synthesis in the bloom-forming

Microcystis aeruginosa under iron limitation. Environmental Microbiology, 13,

1064-1077.

ALEXOVA, R., HAYNES, P. A., FERRARI, B. C. & NEILAN, B. A. 2011c.

Comparative protein expression in different strains of the bloom-forming

cyanobacterium Microcystis aeruginosa. Mol Cell Proteomics, 10, M110

003749.

ANDERSON, R. A. 2005. Algal culturing techniques, Burlington, Massachusetts,

Academic Press.

ANTUNES, J. T., LEÃO, P. N. & VASCONCELOS, V. M. 2015. Cylindrospermopsis

raciborskii: review of the distribution, phylogeography, and ecophysiology of a

global invasive species. Frontiers in Microbiology, 6, 473.

APELDOORN, M. E. V., EGMOND, H. P. V., SPEIJERS, G. J. A. & BAKKER, G. J.

I. 2007. Toxins of cyanobacteria. Molecular Nutrition & Food Research, 51.

BABICA, P., BLÁHA, L. & MARŠÁLEK, B. 2006. Exploring the natural role of

microcystins - A review of effects on photoautorophic organisms Journal of

Phycology, 42, 9-20.

BADARAU, A., FIRBANK, S. J., WALDRON, K. J., YANAGISAWA, S.,

ROBINSON, N. J., BANFIELD, M. J. & DENNISON, C. 2008. FutA2 is a

ferric binding protein from Synechocystis PCC 6803. Journal of Biological

Chemistry, 283, 12520-12527.

BAGU, J. R., SYKES, B. D., CRAIG, M. M. & HOLMES, C. F. B. 1997. A molecular

basis for different interactions of marine toxins with protein phosphatase-1.

Journal of Biological Chemistry, 272, 5087-5097.

BAI, F., LIU, R., YANG, Y., RAN, X., SHI, J. & WU, Z. 2014. Dissolved organic

phosphorus use by the invasive freshwater diazotroph cyanobacterium,

Cylindrospermopsis raciborskii. Harmful Algae, 39, 112-120.

References

168

BANTSCHEFF, M., LEMEER, S., SAVITSKI, M. & KUSTER, B. 2012. Quantitative

mass spectrometry in proteomics: critical review update from 2007 to the

present. Analytical and Bioanalytical Chemistry, 404, 939-965.

BAPTISTA, M. S. & VASCONCELOS, M. T. 2006. Cyanobacteria metal interactions:

requirements, toxicity, and ecological implications. Crit Rev Microbiol, 32, 127-

37.

BAR-YOSEF, Y., SUKENIK, A., HADAS, O., VINER-MOZZINI, Y. & KAPLAN, A.

2010. Enslavement in the water body by toxic Aphanizomenon ovalisporum,

inducing alkaline phosphatase in phytoplanktons. Current Biology, 20, 1557-

1561.

BARBEAU, K. 2006. Photochemistry of organic iron(III) complexing ligands in

oceanic systems. Photochemistry and Photobiology, 82, 1505-1516.

BARBEAU, K., RUE, E. L., BRULAND, K. W. & BUTLER, A. 2001. Photochemical

cycling of iron in the surface ocean mediated by microbial iron(III)-binding

ligands. Nature, 413, 409-413.

BARNETT, J. P., ROBINSON, C., SCANLAN, D. J. & BLINDAUER, C. A. 2011. The

Tat protein export pathway and its role in cyanobacterial metalloprotein

biosynthesis. FEMS Microbiology Letters, 325, 1-9.

BARNETT, J. P., SCANLAN, D. J. & BLINDAUER, C. A. 2012. Protein fractionation

and detection for metalloproteomics: Challenges and approaches. Analytical and

Bioanalytical Chemistry, 402, 3311-3322.

BARRIOS-LLERENA, M. E., CHONG, P. K., GAN, C. S., SNIJDERS, A. P. L.,

REARDON, K. F. & WRIGHT, P. C. 2006. Shotgun proteomics of

cyanobacteria—applications of experimental and data-mining techniques.

Briefings in Functional Genomics & Proteomics, 5, 121-132.

BATCHELLI, S., MULLER, F. L. L., CHANG, K. C. & LEE, C. L. 2010. Evidence for

strong but dynamic iron-humic colloidal associations in humic-rich coastal

waters. Environmental Science & Technology, 44, 8485-8490.

BATTCHIKOVA, N., VAINONEN, J. P., VORONTSOVA, N., KERANEN, M.,

CARMEL, D. & ARO, E. M. 2010. Dynamic changes in the proteome of

Synechocystis 6803 in response to CO2 limitation revealed by quantitative

proteomics. J Proteome Res, 9, 5896-912.

BERMAN-FRANK, I., QUIGG, A., FINKEL, Z. V., IRWIN, A. J. & HARAMATY, L.

2007a. Nitrogen-fixation strategies and Fe requirements in cyanobacteria.

Limnol. Oceanogr., 52, 2260-2269.

BERMAN-FRANK, I., QUIGG, A., FINKEL, Z. V., IRWIN, A. J. & HARAMATY, L.

2007b. Nitrogen-fixation strategies and Fe requirements in cyanobacteria.

Limnology and Oceanography, 52, 2260-2269.

BIELSKI, B. H. J., CABELLI, D. E., ARUDI, R. L. & ROSS, A. B. 1985. Reactivity of

HO2/O2- radicals in aqueous-solution. Journal of Physical and Chemical

Reference Data, 14, 1041-1100.

BLIGH, M. W. & WAITE, T. D. 2010. Role of heterogeneous precipitation in

determining the nature of products formed on oxidation of Fe(II) in seawater

containing natural organic matter. Environmental Science & Technology, 44,

6667-6673.

BONILLA, S., AUBRIOT, L., SOARES, M. C. S., GONZÁLEZ-PIANA, M., FABRE,

A., HUSZAR, V. L. M., LÜRLING, M., ANTONIADES, D., PADISÁK, J. &

KRUK, C. 2012. What drives the distribution of the bloom-forming

References

169

cyanobacteria Planktothrix agardhii and Cylindrospermopsis raciborskii? FEMS

Microbiology Ecology, 79, 594-607.

BOON, P. I., BUNN, S. E., GREEN, J. D. & SHIEL, R. J. 1994. Consumption of

cyanobacteria by freshwater zooplankton: Implications for the success of “Top-

down” control of cyanobacterial blooms in Australia. Australian Journal of

Marine and Freshwater Research, 45, 875-887.

BRIAND, J.-F., LEBOULANGER, C., HUMBERT, J.-F., BERNARD, C. & DUFOUR,

P. 2004. Cylindrospermopsis raciborskii (Cyanobacteria) invasion at mid-

latitudes: selection, wide physiological tolerance, or global warming? Journal of

Phycology, 40, 231-238.

BUFFLE, J., WILKINSON, K. J. & VAN LEEUWEN, H. P. 2009. Chemodynamics

and Bioavailability in Natural Waters. Environmental Science & Technology,

43, 7170-7174.

BURFORD, M. A. & DAVIS, T. W. 2011. Physical and chemical processes promoting

dominance of the toxic cyanobacterium Cylindrospermopsis raciborskii.

Chinese Journal of Oceanology and Limnology, 29, 883-891.

BURFORD, M. A., MCNEALE, K. L. & MCKENZIE-SMITH, F. J. 2006. The role of

nitrogen in promoting the toxic cyanophyte Cylindrospermopsis raciborskii in a

subtropical water reservoir. Freshwater Biology, 51, 2143-2153.

BURJA, A. M., DHAMWICHUKORN, S. & WRIGHT, P. C. 2003. Cyanobacterial

postgenomic research and systems biology. TRENDS in Biotechnology, 21, 504-

511.

CARMICHAEL, W. W. 2001. Health effects of toxin-producing cyanobacteria: "The

CyanoHABs". Human and Ecological Risk Assessment, 7, 1393-1407.

CASTIELLI, O., DE LA CERDA, B., NAVARRO, J. A., HERVÁS, M. & DE LA

ROSA, M. A. 2009. Proteomic analyses of the response of cyanobacteria to

different stress conditions. FEBS Letters, 583, 1753-1758.

CHEN, B. Z., LIU, H. B., LANDRY, M. R., CHEN, M., SUN, J., SHEK, L., CHEN, X.

H. & HARRISON, P. J. 2009a. Estuarine nutrient loading affects phytoplankton

growth and microzooplankton grazing at two contrasting sites in Hong Kong

coastal waters. Marine Ecology Progress Series, 379, 77-90.

CHEN, W. M. & LIU, H. 2015. Intracellular nitrite accumulation: The cause of growth

inhibition of Microcystis aeruginosa exposure to high nitrite level. Phycological

Research, 63, 197-201.

CHEN, W. M., ZHANG, Q. M. & DAI, S. G. 2009b. Effects of nitrate on intracellular

nitrite and growth of Microcystis aeruginosa. Journal of Applied Phycology, 21,

701-706.

CHISWELL, R. K., SHAW, G. R., EAGLESHAM, G.,

SMITH, M.J.,, NORRIS, K. R., SEAWRIGHT, A. A. & MOORE, M. R. 1999. Stability

of cylindrospermopsin, the toxin from the cyanobacterium, Cylindrospermopsis

raciborskii: Effect of pH, temperature and sunlight on decomposition. Environmental

Toxicology, 14.

CHOE, L. H., AGGARWAL, K., FRANCK, Z. & LEE, K. H. 2005. A comparison of

the consistency of proteome quantitation using two-dimensional electrophoresis

and shotgun isobaric tagging in Escherichia coli cells. ELECTROPHORESIS,

26, 2437-2449.

CHRISTIANSEN, G., MOLITOR, C., PHILMUS, B. & KURMAYER, R. 2008.

Nontoxic strains of cyanobacteria are the results of major gene deletion events

References

170

induced by a transposable element. Molecular Biology Evolution, 25, 1695-

1704.

CHUBUKOV, V. & SAUER, U. 2014. Environmental Dependence of Stationary-Phase

Metabolism in Bacillus subtilis and Escherichia coli. Applied and Environmental

Microbiology, 80, 2901-2909.

CODD, G., STEFFENSEN, D., BURCH, M. & BAKER, P. 1994. Toxic blooms of

cyanobacteria in Lake Alexandrina, South Australia - Learning from history.

Australian Journal of Marine and Freshwater Research, 45, 731-736.

CODD, G. A. 2000. Cyanobacterial toxins, the perception of water quality, and the

prioritisation of eutrophication control. Ecological Engineering, 16, 51-60.

CODD, G. A., MORRISON, L. F. & METCALF, J. S. 2005. Cyanobacterial toxins: risk

management for health protection. Toxicol Appl Pharmacol, 203, 264-72.

COVES, J. & FONTECAVE, M. 1993. Reduction and mobilization of iron by a

NAD(P)H - flavin oxidoreductase from Escherichia coli. European Journal of

Biochemistry, 211, 635-641.

CRICHTON, R. R. 2009. Inorganic biochemistry of iron metabolism : from molecular

mechanisms to clinical consequences, Chichester, West Sussex, U.K. ; Hoboken,

John Wiley & Sons.

D'AGOSTINO, P. M., SONG, X., NEILAN, B. A. & MOFFITT, M. C. 2016.

Proteogenomics of a saxitoxin-producing and non-toxic strain of Anabaena

circinalis (cyanobacteria) in response to extracellular NaCl and phosphate

depletion. Environmental Microbiology, 18, 461-476.

D’AGOSTINO, P. M., SONG, X., NEILAN, B. A. & MOFFITT, M. C. 2014.

Comparative proteomics reveals that a saxitoxin-producing and a nontoxic strain

of Anabaena circinalis are two different ecotypes. Journal of Proteome

Research, 13, 1474-1484.

DANG, T. C., FUJII, M., ROSE, A. L., BLIGH, M. & WAITE, T. D. 2012a.

Characteristics of the freshwater cyanobacterium Microcystis aeruginosa grown

in iron-limited continuous culture. Appl Environ Microbiol, 78, 1574-83.

DANG, T. C., FUJII, M., ROSE, A. L., BLIGH, M. & WAITE, T. D. 2012b.

Characteristics of the freshwater cyanobacterium Microcystis aeruginosa grown

in iron-limited continuous culture. Applied and Environmental Microbiology,

78, 1574-1583.

DAVIS, J. R. & KOOP, K. 2006. Eutrophication in Australian Rivers, Reservoirs and

Estuaries – A Southern Hemisphere Perspective on the Science and its

Implications. Hydrobiologia, 559, 23-76.

DE LA CERDA, B., CASTIELLI, O., DURÁN, R. V., NAVARRO, J. A., HERVÁS,

M. & DE LA ROSA, M. A. 2007. A proteomic approach to iron and copper

homeostasis in cyanobacteria. Briefings in Functional Genomics & Proteomics,

6, 322-329.

DITTMANN, E., ERHARD, M., KAEBERNICK, M., SCHELER, C., NEILAN, B. A.,

VON DOHREN, H. & BORNER, T. 2001. Altered expression of two light-

dependent genes in a microcystin-lacking mutant of Microcystis aeruginosa

PCC 7806. Microbiology-Sgm, 147, 3113-3119.

DITTMANN, E., NEILAN, B. A., ERHARD, M., VON DÖHREN, H. & BÖRNER, T.

1997. Insertional mutagenesis of a peptide synthetase gene that is responsible for

hepatotoxin production in the cyanobacterium Microcystis aeruginosa PCC

7806. Molecular Microbiology, 26, 779-787.

References

171

DOWNING, T. G., SEMBER, C. S., GEHRINGER, M. M. & LEUKES, W. 2005.

Medium N:P Ratios and Specific Growth Rate Comodulate Microcystin and

Protein Content in Microcystis aeruginosa PCC7806 and M. aeruginosa UV027.

Microbial Ecology, 49, 468-473.

DRESSAIRE, C., PICARD, F., REDON, E., LOUBIÈRE, P., QUEINNEC, I.,

GIRBAL, L. & COCAIGN-BOUSQUET, M. 2013. Role of mRNA Stability

during Bacterial Adaptation. PLoS ONE, 8, e59059.

DUFOUR, P., SARAZIN, G., QUIBLIER, C., SANE, S. & LEBOULANGER, C. 2006.

Cascading nutrient limitation of the cyanobacterium Cylindrospermopsis

raciborskii in a Sahelian lake (North Senegal). Aquatic Microbial Ecology, 44,

219-230.

DYBALLA, N. & METZGER, S. 2009. Fast and sensitive colloidal coomassie G-250

staining for proteins in polyacrylamide gels. J Vis Exp, 1431.

ESPINOSA, J. & FORCHHAMMER, K. 2006. Interaction network in cyanobacterial

nitrogen regulation: PipX, a protein that itneracts in a 2-oxoglutarate dependent

manner with PII and NtcA. Molecular Mirobiology, 61, 457-469.

FALCONER, I. R. 2005. Is there a human health hazard from microcystins in the

drinking water supply? Acta hydrochimica et hydrobiologica, 33, 64-71.

FALCONER, I. R. & HUMPAGE, A. R. 2006. Cyanobacterial (Blue-Green Algal)

toxins in water supplies: Cylindrospermopsins. Environmental Toxicology, 21,

299-304.

FAUST, B. C. & ZEPP, R. G. 1993. Photochemistry of aqueous iron(III)

polycarboxylate complexes - Roles in the chemistry of atmospheric and surface

waters. Environmental Science & Technology, 27, 2517-2522.

FRANGEUL, L., QUILLARDET, P., CASTETS, A.-M., HUMBERT, J.-F.,

MATTHIJS, H., CORTEZ, D., TOLONEN, A., ZHANG, C.-C., GRIBALDO,

S., KEHR, J.-C., ZILLIGES, Y., ZIEMERT, N., BECKER, S., TALLA, E.,

LATIFI, A., BILLAULT, A., LEPELLETIER, A., DITTMANN, E.,

BOUCHIER, C. & TANDEAU DE MARSAC, N. 2008. Highly plastic genome

of Microcystis aeruginosa PCC 7806, a ubiquitous toxic freshwater

cyanobacterium. BMC Genomics, 9, 274.

FROMME, P., MELKOZERNOV, A., JORDAN, P. & KRAUSS, N. 2003. Structure

and function of photosystem I: interaction with its soluble electron carriers and

external antenna systems. FEBS Lett, 555, 40-4.

FUJII, M., DANG, T. C., BLIGH, M. W., ROSE, A. L. & WAITE, T. D. 2014a. Effect

of natural organic matter on iron uptake by the freshwater cyanobacterium

Microcystis aeruginosa. Environ Sci Technol, 48, 365-74.

FUJII, M., DANG, T. C., BLIGH, M. W., ROSE, A. L. & WAITE, T. D. 2014b. Effect

of Natural Organic Matter on Iron Uptake by the Freshwater Cyanobacterium

Microcystis aeruginosa. Environmental Science & Technology, 48, 365-74.

FUJII, M., DANG, T. C., BLIGH, M. W. & WAITE, T. D. Submitted. Cellular

characteristics and growth behaviour of iron-limited Microcystis aeruginosa in

eutrophic and oligotrophic chemostat systems. Limnology and Oceanography.

FUJII, M., DANG, T. C., ROSE, A. L., OMURA, T. & WAITE, T. D. 2011a. Effect of

Light on Iron Uptake by the Freshwater Cyanobacterium Microcystis

aeruginosa. Environmental Science & Technology, 45, 1391-1398.

References

172

FUJII, M., IMAOKA, A., YOSHIMURA, C. & WAITE, T. D. 2014c. Effects of

Molecular Composition of Natural Organic Matter on Ferric Iron Complexation

at Circumneutral pH. Environmental Science & Technology, 48, 4414-4424.

FUJII, M., ROSE, A. L., OMURA, T. & WAITE, T. D. 2010a. Effect of Fe(II) and

Fe(III) transformation kinetics on iron acquisition by a toxic strain of

Microcystis aeruginosa. Environmental Science & Technology, 44, 1980-1986.

FUJII, M., ROSE, A. L. & WAITE, T. D. 2011b. Iron uptake by toxic and nontoxic

strains of Microcystis aeruginosa. Appl Environ Microbiol, 77, 7068-71.

FUJII, M., ROSE, A. L., WAITE, T. D. & OMURA, T. 2008. Effect of divalent cations

on the kinetics of Fe(III) complexation by organic ligands in natural waters.

Geochimica Et Cosmochimica Acta, 72, 1335-1349.

FUJII, M., ROSE, A. L., WAITE, T. D. & OMURA, T. 2010b. Oxygen and superoxide-

mediated redox kinetics of iron complexed by humic substances in coastal

seawater. Environmental Science & Technology, 44, 9337-9342.

FUJII, M., YEUNG, A. C. & WAITE, T. D. 2015. Competitive effects of calcium and

magnesium ions on the photochemical transformation and associated cellular

uptake of iron by the freshwater cyanobacterial phytoplankton Microcystis

aeruginosa. Environ Sci Technol, 49, 9133-42.

FULDA, S., MIKKAT, S., HUANG, F., HUCKAUF, J., MARIN, K., NORLING, B. &

HAGEMANN, M. 2006. Proteome analysis of salt stress response in the

cyanobacterium Synechocystis sp. strain PCC 6803. Proteomics, 6, 2733-45.

GAN, F., ZHANG, S., ROCKWELL, N. C., MARTIN, S. S., LAGARIAS, J. C. &

BRYANT, D. A. 2014. Extensive remodeling of a cyanobacterial photosynthetic

apparatus in far-red light. Science, 345, 1312-7.

GAN, N., XIAO, Y., ZHU, L., WU, Z., LIU, J., HU, C. & SONG, L. 2012. The role of

microcystins in maintaining colonies of bloom-forming Microcystis spp.

Environ Microbiol, 14, 730-42.

GARG, S., ROSE, A. L., GODRANT, A. & WAITE, T. D. 2007. Iron uptake by the

ichthyotoxic Chattonella marina (Raphidophyceae): Impact of superoxide

generation. Journal of Phycology, 43, 978-991.

GARG, S., ROSE, A. L. & WAITE, T. D. 2011. Photochemical production of

superoxide and hydrogen peroxide from natural organic matter. Geochimica Et

Cosmochimica Acta, 75, 4310-4320.

GATLIN, C. L., KLEEMANN, G. R., HAYS, L. G., LINK, A. J. & YATES, J. R. 1998.

Protein identification at the low femtomole level from silver-stained gels using a

new fritless electrospray interface for liquid chromatography-microspray and

nanospray mass spectrometry. Anal Biochem 263, 93-101.

GINN, H. P., PEARSON, L. A. & NEILAN, B. A. 2009. Hepatotoxin biosynthesis and

regulation in cyanobacteria - the putative involvement of nitrogen and iron

hmeostasis mechanisms. Chiang Mai Journal of Science, 36, 200-223.

GINN, H. P., PEARSON, L. A. & NEILAN, B. A. 2010. NtcA from Microcystis

aeruginosa PCC 7806 Is Autoregulatory and Binds to the Microcystin Promoter.

Applied and Environmental Microbiology, 76, 4362-4368.

GOLDMAN, S. J., LAMMERS, P. J., BERMAN, M. S. & SANDERS-LOEHR, J.

1983. Siderophore-mediated iron uptake in different strains of Anabaena sp.

Journal of Bacteriology, 156, 1144-1150.

GUO, J., NGUYEN, A. Y., DAI, Z., SU, D., GAFFREY, M. J., MOORE, R. J.,

JACOBS, J. M., MONROE, M. E., SMITH, R. D., KOPPENAAL, D. W.,

References

173

PAKRASI, H. B. & QIAN, W.-J. 2014. Proteome-wide Light/Dark Modulation

of Thiol Oxidation in Cyanobacteria Revealed by Quantitative Site-Specific

Redox Proteomics. Molecular & Cellular Proteomics.

HAANDE, S., ROHRLACK, T., BALLOT, A., RØBERG, K., SKULBERG, R.,

BECK, M. & WIEDNER, C. 2008. Genetic characterisation of

Cylindrospermopsis raciborskii (Nostocales, Cyanobacteria) isolates from

Africa and Europe. Harmful Algae, 7, 692-701.

HERBERT, B. R., GRINYER, J., MCCARTHY, J. T., ISAACS, M., HARRY, E. J.,

NEVALAINEN, H., TRAINI, M. D., HUNT, S., SCHULZ, B., LAVER, M.,

GOODALL, A. R., PACKER, J., HARRY, J. L. & WILLIAMS, K. L. 2006.

Improved 2-DE of microorganisms after acidic extraction. Electrophoresis, 27,

1630-40.

HERING, J. G. & MOREL, F. M. M. 1988. Kinetics of Trace-Metal Complexation -

Role of Alkaline-Earth Metals. Environmental Science & Technology, 22, 1469-

1478.

HERING, J. G. & MOREL, F. M. M. 1989. Slow Coordination Reactions in Seawater.


HERNÁNDEZ-PRIETO, M. A., SCHÖN, V., GEORG, J., BARREIRA, L., VARELA,

J., HESS, W. R. & FUTSCHIK, M. E. 2012. Iron Deprivation in Synechocystis:

Inference of Pathways, Non-coding RNAs, and Regulatory Elements from

Comprehensive Expression Profiling. G3: Genes|Genomes|Genetics, 2, 1475-

1495.

HERRERO, A., MURO-PASTOR, A. M. & FLORES, E. 2001. Nitrogen control in

cyanobacteria. Journal of Bacteriology, 183, 411-425.

HESSE, K., DITTMANN, E. & BÖRNER, T. 2001. Consequences of impaired

microcystin production for light-dependent growth and pigmentation of

Microcystis aeruginosa PCC 7806. FEMS Microbiology Ecology, 37, 39-43.

HONG, Y., STEINMAN, A., BIDDANDA, B., REDISKE, R. & FAHNENSTIEL, G.

2006. Occurrence of the Toxin-producing Cyanobacterium Cylindrospermopsis

raciborskii in Mona and Muskegon Lakes, Michigan. Journal of Great Lakes

Research, 32, 645-652.

HOPKINSON, B. M. & BARBEAU, K. A. 2012. Iron transporters in marine

prokaryotic genomes and metagenomes. Environmental Microbiology, 14, 114-

28.

HOPKINSON, B. M. & MOREL, F. M. M. 2009. The role of siderophores in iron

acquisition by photosynthetic marine microorganisms. Biometals, 22, 659-669.

HUDSON, R. J. M., COVAULT, D. T. & MOREL, F. M. M. 1992. Investigations of

Iron Coordination and Redox Reactions in Seawater Using Fe-59 Radiometry

and Ion-Pair Solvent-Extraction of Amphiphilic Iron Complexes. Marine

Chemistry, 38, 209-235.

HUTCHINS, D. A., WITTER, A. E., BUTLER, A. & LUTHER, G. W. 1999.

Competition among marine phytoplankton for different chelated iron species.

Nature, 400, 858-861.

IANNI, J. C. 2002. Kintecus v3.0, Windows Version. http://www.kintecus.com.

IHSS International humic substance society homepage database

(http://www.humicsubstances.org/index.html).

http://www.kintecus.com/

http://www.humicsubstances.org/index.html

References

174

ITO, Y. & BUTLER, A. 2005. Structure of synechobactins, new siderophores of the

marine cyanobacterium Synechococcus sp PCC 7002. Limnology and

Oceanography, 50, 1918-1923.

JIANG, F., MANNERVIK, B. & BERGMAN, B. 1997. Evidence for redox regulation

of the transcription factor NtcA, acting both as an activator and a repressor, in

the cyanobacterium Anabaena PCC 7120. Biochemical Journal, 327, 513-517.

JIANG, H.-B., LOU, W.-J., KE, W.-T., SONG, W.-Y., PRICE, N. M. & QIU, B.-S.

2014. New insights into iron acquisition by cyanobacteria: an essential role for

ExbB-ExbD complex in inorganic iron uptake. ISME Journal.

JIN, X.-C., CHU, Z.-S., YI, W.-L. & HU, X.-Z. 2005. Influence of phosphorus on

Microcystis growth and the changes of other environmental factors. Journal of

Environmental Sciences (IOS Press), 17, 937-941.

JOCHIMSEN, E. M., CARMICHAEL, W. W., AN, J., CARDO, D. M., COOKSON, S.

T., HOLMES, C. E. M., ANTUNES, M. B., DE MELO FILHO, D. A., LYRA,

T. M., BARRETO, V. S. T., AZEVEDO, S. M. F. O. & JARVIS, W. R. 1998.

Liver Failure and Death after Exposure to Microcystins at a Hemodialysis

Center in Brazil. New England Journal of Medicine, 338, 873-878.

KAEBERNICK, M. & NEILAN, B. A. 2001. Ecological and molecular investigations

of cyanotoxin production. FEMS Microbiology Ecology, 35, 1-9.

KAEBERNICK, M., NEILAN, B. A., BORNER, T. & DITTMANN, E. 2000. Light

and the transcriptional response of the microcystin biosynthesis gene cluster.

Appl Environ Microbiol, 66, 3387-92.

KARLSSON, T. & PERSSON, P. 2010. Coordination chemistry and hydrolysis of

Fe(III) in a peat humic acid studied by X-ray absorption spectroscopy.


KASHINO, Y., LAUBER, W. M., CARROLL, J. A., WANG, Q., WHITMARSH, J.,

SATOH, K. & PAKRASI, H. B. 2002. Proteomic Analysis of a Highly Active

Photosystem II Preparation from the Cyanobacterium Synechocystis sp. PCC

6803 Reveals the Presence of Novel Polypeptides†. Biochemistry, 41, 8004-

8012.

KATOH, H., HAGINO, N., GROSSMAN, A. R. & OGAWA, T. 2001. Genes essential

to iron transport in the cyanobacterium Synechocystis sp strain PCC 6803.

Journal of Bacteriology, 183, 2779-2784.

KINNEAR, S. 2010. Cylindrospermopsin: A decade of progress on bioaccumulation

reasearch. Marine Drugs, 8, 542-564.

KLEIN, A. R., BALDWIN, D. S. & SILVESTER, E. 2013. Proton and iron binding by

the cyanobacterial toxin microcystin-LR. Environ Sci Technol, 47, 5178-84.

KRANZLER, C., LIS, H., FINKEL, O. M., SCHMETTERER, G., SHAKED, Y. &

KEREN, N. 2014. Coordinated transporter activity shapes high-affinity iron

acquisition in cyanobacteria. Isme Journal, 8, 409-417.

KRANZLER, C., LIS, H., SHAKED, Y. & KEREN, N. 2011. The role of reduction in

iron uptake processes in a unicellular, planktonic cyanobacterium.

Environmental Microbiology, 13, 2990-2999.

KRÜGER, G. H. J. & ELOFF, J. N. 1981. The effect of physico-chemical factors on

growth relevant to the mass culture of axenic Microcystis. In: CARMICHAEL,

W. W. (ed.) The Water Environment: Algal Toxins and Health. Boston, MA:

Springer US.

References

175

KUCHAROVA, V. & WIKER, H. G. 2014. Proteogenomics in microbiology: Taking

the right turn at the junction of genomics and proteomics. Proteomics, 14, 2360-

675.

KÜPPER, H., ŠETLÍK, I., SEIBERT, S., PRÁŠIL, O., ŠETLIKOVA, E.,

STRITTMATTER, M., LEVITAN, O., LOHSCHEIDER, J., ADAMSKA, I. &

BERMAN-FRANK, I. 2008. Iron limitation in the marine cyanobacterium

Trichodesmium reveals new insights into regulation of photosynthesis and

nitrogen fixation. New Phytologist, 179, 784-798.

KUSTKA, A., SANUDO-WILHELMY, S., CARPENTER, E. J., CAPONE, D. G. &

RAVEN, J. A. 2003a. A revised estimate of the iron use efficiency of nitrogen

fixation, with special reference to the marine cyanobacterium Trichodesmium

spp. (Cyanophyta). Journal of Phycology, 39, 12-25.

KUSTKA, A. B., SAÑUDO-WILHELMY, S. A., CARPENTER, E. J., CAPONE, D.,

BURNS, J. & SUNDA, W. G. 2003b. Iron requirements for dinitrogen- and

ammonium-supported growth in cultures of Trichodesmium (IMS 101):

Comparison with nitrogen fixation rates and iron: carbon ratios of field

populations. Limnology and Oceanography, 48, 1869-1884.

LAGLERA, L. M. & VAN DEN BERG, C. M. G. 2009. Evidence for geochemical

control of iron by humic substances in seawater. Limnology and Oceanography,

54, 610-619.

LANE, E. S., JANG, K., CULLEN, J. T. & MALDONADO, M. T. 2008. The

interaction between inorganic iron and cadmium uptake in the marine diatom

Thalassiosira oceanica. Limnology and Oceanography, 53, 1784-1789.

LATIFI, A., JEANJEAN, R., LEMEILLE, S., HAVAUX, M. & ZHANG, C. C. 2005.

Iron starvation leads to oxidative stress in Anabaena sp. strain PCC 7120. J

Bacteriol, 187, 6596-8.

LATIFI, A., RUIZ, M. & ZHANG, C. C. 2009. Oxidative stress in cyanobacteria.

FEMS Microbiol Rev, 33, 258-78.

LEBLANC, S., PICK, F. R. & ARANDA-RODRIGUEZ, R. 2005. Allelopathic effects

of the toxic cyanobacterium Microcystis aeruginosa on duckweed, Lemna gibba

L. Environmental Toxicology, 20, 67-73.

LEE, P. A., TULLMAN-ERCEK, D. & GEORGIOU, G. 2006. The Bacterial Twin-

Arginine Translocation Pathway. Annual review of microbiology, 60, 373-395.

LI, H. L., MURPHY, T., GUO, J., PARR, T. & NALEWAJKO, C. 2009. Iron-

stimulated growth and microcystin production of Microcystis novacekii UAM

250. Limnologica, 39, 255-259.

LIN, J. & KESTER, D. R. 1992. The Kinetics of Fe(II) Complexation by Ferrozine in

Seawater. Marine Chemistry, 38, 283-301.

LIU, C., YOUNG, A. L., STARLING-WINDHOF, A., BRACHER, A.,

SASCHENBRECKER, S., RAO, B. V., RAO, K. V., BERNINGHAUSEN, O.,

MIELKE, T., HARTL, F. U., BECKMANN, R. & HAYER-HARTL, M. 2010.

Coupled chaperone action in folding and assembly of hexadecameric Rubisco.

Nature, 463, 197-202.

LIU, X. W. & MILLERO, F. J. 1999. The solubility of iron hydroxide in sodium

chloride solutions. Geochimica Et Cosmochimica Acta, 63, 3487-3497.

LONG, B. M., JONES, G. J. & ORR, P. T. 2001. Cellular microcystin content in N-

limited Microcystis aeruginosa can be predicted from growth rate. Appl Environ

Microbiol, 67, 278-83.

References

176

LOPEZ-GOMOLLON, S., HERNANDEZ, J. A., PELLICER, S., ANGARICA, V. E.,

PELEATO, M. L. & FILLAT, M. F. 2007. Cross-talk between iron and nitrogen

regulatory networks in Anabaena (Nostoc) sp PCC 7120: Identification of

overlapping genes in FurA and NtcA regulons. Journal of Molecular Biology,

374, 267-281.

LUKAC, M. & AEGERTER, R. 1993. Influence of trace metals on growth and toxin

production of Microcystis aeruginosa. Toxicon, 31, 293-305.

LYCK, S. 2004. Simultaneous changes in cell quotas of microcystin, chlorophyll a,

protein and carbohydrate during different growth phases of a batch culture

experiment with Microcystis aeruginosa. Journal of Plankton Research, 26,

727-736.

MAKOWER, A. K., SCHUURMANS, J. M., GROTH, D., ZILLIGES, Y., MATTHIJS,

H. C. & DITTMANN, E. 2015. Transcriptomics-aided dissection of the

intracellular and extracellular roles of microcystin in Microcystis aeruginosa

PCC 7806. Appl Environ Microbiol, 81, 544-54.

MALDONADO, M. T., ALLEN, A. E., CHONG, J. S., LIN, K., LEUS, D.,

KARPENKO, N. & HARRIS, S. L. 2006. Copper-dependent iron transport in

coastal and oceanic diatoms. Limnology and Oceanography, 51, 1729-1743.

MALDONADO, M. T. & PRICE, N. M. 2001. Reduction and transport of organically

bound iron by Thalassiosira oceanica (Bacillariophyceae). Journal of

Phycology, 37, 298-309.

MALDONADO, M. T., STRZEPEK, R. F., SANDER, S. & BOYD, P. W. 2005.

Acquisition of iron bound to strong organic complexes, with different Fe

binding groups and photochemical reactivities, by plankton communities in Fe-

limited subantarctic waters. Global Biogeochemical Cycles, 19, GB4S23.

MARTIN-LUNA, B., SEVILLA, E., HERNANDEZ, J. A., BES, M. T., FILLAT, M. F.

& PELEATO, M. L. 2006. Fur from Microcystis aeruginosa binds in vitro

promoter regions of the microcystin biosynthesis gene cluster. Phytochemistry,

67, 876-881.

MASH, H. E., CHIN, Y. P., SIGG, L., HARI, R. & XUE, H. B. 2003. Complexation of

copper by zwitterionic aminosulfonic (good) buffers. Analytical Chemistry, 75,

671-677.

MCGREGOR, G. B. & FABBRO, L. D. 2000. Dominance of Cylindrospermopsis

raciborskii (Nostocales, Cyanoprokaryota) in Queensland tropical and

subtropical reservoirs: Implications for monitoring and management. Lakes &

Reservoirs: Research & Management, 5, 195-205.

MEEKS, J. C. & CASTENHOLZ, R. W. 1971. Growth and photosynthesis in an

extreme thermophile, Synechococcus lividus (Cyanophyta). Arch Mikrobiol, 78,

25-41.

MEISSNER, S., FASTNER, J. & DITTMANN, E. 2013. Microcystin production

revisited: conjugate formation makes a major contribution. Environmental


MESSINEO, V., MELCHIORRE, S., DI CORCIA, A., GALLO, P. & BRUNO, M.

2010. Seasonal succession of Cylindrospermopsis raciborskii and

Aphanizomenon ovalisporum blooms with cylindrospermopsin occurrence in the

volcanic Lake Albano, Central Italy. Environmental Toxicology, 25, 18-27.

MIHALI, T. K., KELLMANN, R., MUENCHHOFF, J., BARROW, K. D. & NEILAN,

B. A. 2008. Characterization of the gene cluster responsible for

References

177

cylindrospermopsin biosynthesis. Applied and Environmental Microbiology, 74,

716-722.

MILLER, C. J., ROSE, A. L. & WAITE, T. D. 2009. Impact of natural organic matter

on H2O2-mediated oxidation of Fe(II) in a simulated freshwater system.


MILLERO, F. J. & SOTOLONGO, S. 1989. The oxidation of Fe(II) with H2O2 in

seawater. Geochimica Et Cosmochimica Acta, 53, 1867-1873.

MOISANDER, P. H., MCCLINTON, E. & PAERL, H. W. 2002. Salinity Effects on

Growth, Photosynthetic Parameters, and Nitrogenase Activity in Estuarine

Planktonic Cyanobacteria. Microbial Ecology, 43, 432-442.

MOREL, F. & HERING, J. G. 1993. Principles and applications of aquatic chemistry,

New York, Wiley.

MORISAWA, H., HIROTA, M. & TODA, T. 2006. Development of an open source

laboratory information management system for 2-D gel electrophoresis-based

proteomics workflow. BMC Bioinformatics, 7, 430.

NAGAI, T., IMAI, A., MATSUSHIGE, K., YOKOI, K. & FUKUSHIMA, T. 2007.

Dissolved iron and its speciation in a shallow eutrophic lake and its inflowing

rivers. Water Research, 41, 775-784.

NICOLAISEN, K., MOSLAVAC, S., SAMBORSKI, A., VALDEBENITO, M.,

HANTKE, K., MALDENER, I., MURO-PASTOR, A. M., FLORES, E. &

SCHLEIFF, E. 2008. Alr0397 is an outer membrane transporter for the

siderophore Schizokinen in Anabaena sp strain PCC 7120. Journal of

Bacteriology, 190, 7500-7507.

NIKAIDO, H. 2003. Molecular basis of bacterial outer membrane permeability

revisited. Microbiology and Molecular Biology Reviews, 67, 593-+.

OH, H. M., LEE, S. J., JANG, M. H. & YOON, B. D. 2000. Microcystin production by

Microcystis aeruginosa in a phosphorus-limited chemostat. Appl Environ

Microbiol, 66, 176-9.

OHKI, K., ZEHR, J. P., FALKOWSKI, P. G. & FUJITA, Y. 1991. Regulation of

nitrogen-fixation by different nitrogen sources in the marine non-heterocystous

cyanobacterium Trichodesmium sp. NIBB1067. Archives of Microbiology, 156,

335-337.

OLIVER, R. L. 1994. Floating and sinking in gas-vacuolate cyanobacteria. Journal of

Phycology, 30, 161-173.

ORR, P. T. & JONES, G. J. 1998. Relationship between microcystin production and

cell division rates in nitrogen-limited Microcystis aeruginosa cultures.

Limnology and Oceanography, 43, 1604-1614.

OSANAI, T. & TANAKA, K. 2007. Keeping in touch with PII: PII-interacting proteins

in unicellular cyanobacteria. Plant Cell Physiology, 48, 908-914.

OSTERMAIER, V. & KURMAYER, R. 2009. Distribution and Abundance of Nontoxic

Mutants of Cyanobacteria in Lakes of the Alps. Microbial Ecology, 58, 323-333.

OU, M.-M., WANG, Y., ZHOU, B.-X. & CAI, W.-M. 2006. Effects of iron and

phosphorus on Microcystis physiological reactions. Biomed Environ Sci, 19,

399-404.

OU, M.-M., ZHOU, B.-X., XIE, W.-J., JIANG, J.-H. & CAI, W.-M. 2004. Effects of

nutrients on Microcystis growth more easily forming bloom. Journal of

Environmental Sciences, 16, 934-937.

References

178

OW, S. Y. & WRIGHT, P. C. 2009. Current trends in high throughput proteomics in

cyanobacteria. FEBS Letters, 583, 1744-1752.

OW, S. Y. & WRIGHT, P. C. 2011. High-Throughput Cyanobacterial Proteomics:

Systems-Level Proteome Identification and Quantitation. Handbook of

Molecular Microbial Ecology I. John Wiley & Sons, Inc.

PAERL, H. W. & HUISMAN, J. 2009. Climate change: a catalyst for global expansion

of harmful cyanobacterial blooms. Environ Microbiol Rep, 1, 27-37.

PANDHAL, J., OW, S. Y., WRIGHT, P. C. & BIGGS, C. A. 2008. Comparative

Proteomics Study of Salt Tolerance between a Nonsequenced Extremely

Halotolerant Cyanobacterium and Its Mildly Halotolerant Relative Using in vivo

Metabolic Labeling and in vitro Isobaric Labeling. Journal of Proteome

Research, 8, 818-828.

PANDHAL, J., WRIGHT, P. C. & BIGGS, C. A. 2007. A quantitative proteomic

analysis of light adaptation in a globally significant marine cyanobacterium

Prochlorococcus marinus MED4. J Proteome Res, 6, 996-1005.

PEARSON, L., MIHALI, T., MOFFITT, M., KELLMANN, R. & NEILAN, B. 2010.

On the chemistry, toxicology and genetics of the cyanobacterial toxins,

microcystin, nodularin, saxitoxin and cylindrospermopsin. Marine Drugs, 8,

1650-1680.

PEARSON, L. A., HISBERGUES, M., BORNER, T., DITTMANN, E. & NEILAN, B.

A. 2004. Inactivation of an ABC transporter gene, mcyH, results in loss of

microcystin production in the cyanobacterium Microcystis aeruginosa PCC

7806. Appl Environ Microbiol, 70, 6370-8.

PFLUGMACHER, S. 2002. Possible allelopathic effects of cyanotoxins, with reference

to microcystin-LR, in aquatic ecosystems. Environmental Toxicology, 17, 407-

413.

PHAM, A. N., ROSE, A. L., FEITZ, A. J. & WAITE, T. D. 2006. Kinetics of Fe(III)

precipitation in aqueous solutions at pH 6.0-9.5 and 25 degrees C. Geochimica

Et Cosmochimica Acta, 70, 640-650.

PHAM, A. N., ROSE, A. L. & WAITE, T. D. 2012. Kinetics of Cu(II) Reduction by

Natural Organic Matter. Journal of Physical Chemistry A, 116, 6590-6599.

PHAM, A. N. & WAITE, T. D. 2008. Oxygenation of Fe(II) in natural waters revisited:

Kinetic modeling approaches, rate constant estimation and the importance of

various reaction pathways. Geochimica Et Cosmochimica Acta, 72, 3616-3630.

PHELAN, R. R. & DOWNING, T. G. 2014. The localization of exogenous microcystin

LR taken up by a non-microcystin producing cyanobacterium. Toxicon, 89, 87-

90.

PLOMINSKY, Á. M., LARSSON, J., BERGMAN, B., DELHERBE, N., OSSES, I. &

VÁSQUEZ, M. 2013. Dinitrogen fixation is restricted to the terminal

heterocysts in the invasive cyanobacterium Cylindrospermopsis raciborskii CS-

505. PLoS ONE, 8, e51682.

PLOMINSKY, Á. M., SOTO-LIEBE, K. & VÁSQUEZ, M. 2009. Optimization of 2D-

PAGE protocols for proteomic analysis of two nonaxenic toxin-producing

freshwater cyanobacteria: Cylindrospermopsis raciborskii and Raphidiopsis sp.

Letters in Applied Microbiology, 49, 332-337.

POSTGATE, J. 1998. Nitrogen fixation-Third edition, Cambridge University Press.

PULLIN, M. J. & CABANISS, S. E. 2003. The effects of pH, ionic strength, and iron-

fulvic acid interactions on the kinetics of nonphotochemical iron

References

179

transformations. I. Iron(II) oxidation and iron(III) colloid formation. Geochimica

Et Cosmochimica Acta, 67, 4067-4077.

RAMÍREZ, M. E., HEBBAR, P. B., ZHOU, R., WOLK, C. P. & CURTIS, S. E. 2005.

Anabaena sp. Strain PCC 7120 Gene devH Is Required for Synthesis of the

Heterocyst Glycolipid Layer. Journal of Bacteriology, 187, 2326-2331.

RASTOGI, R. P., SINGH, S. P., HAIDER, D.-P. & SINHA, R. P. 2010. Detection of

reactive oxygen species (ROS) by the oxidant-sensing probe 2',7'-

dichlorodihydrofluorescein diacetate in the cyanobacterium Anabaena variabilis

PCC 7939. Biochemical and Biophysical Research Communications, 397, 603-

607.

REISNER, M., CARMELI, S., WERMAN, M. & SUKENIK, A. 2004. The

cyanobacterial toxin cylindrospermopsin inhibits pyrimidine nucleotide

synthesis and alters cholesterol distribution in mice. Toxicological Sciences, 82,

620-627.

REYNOLDS, C. S. 1998. The state of freshwater ecology. Freshwater Biology, 39,

741-753.

ROSE, A. L., SALMON, T. P., LUKONDEH, T., NEILAN, B. A. & WAITE, T. D.

2005. Use of superoxide as an electron shuttle for iron acquisition by the marine

cyanobacterium Lyngbya majuscula. Environmental Science & Technology, 39,

3708-3715.

ROSE, A. L. & WAITE, D. 2006. Role of superoxide in the photochemical reduction of

iron in seawater. Geochimica Et Cosmochimica Acta, 70, 3869-3882.

ROSE, A. L. & WAITE, T. D. 2003. Kinetics of iron complexation by dissolved natural

organic matter in coastal waters. Marine Chemistry, 84, 85-103.

ROSE, A. L. & WAITE, T. D. 2005. Reduction of organically complexed ferric iron by

superoxide in a simulated natural water. Environmental Science & Technology,

39, 2645-2650.

RUE, E. L. & BRULAND, K. W. 1995. Complexation of iron(III) by natural organic-

ligands in the central North Pacific as determined by a new competitive ligand

equilibration adsorptive cathodic stripping voltammetric method. Marine

Chemistry, 50, 117-138.

RUSH, J. D. & BIELSKI, B. H. J. 1985. Pulse radiolytic studies of the reactions of

HO2/O2- with Fe(II)/Fe(III) ions - the reactivity of HO2/O2

- with ferric ions and

its implication on the occurrence of the Haber-Weiss reaction. Journal of

Physical Chemistry, 89, 5062-5066.

RYAN, N. J., DABOVIC, J., BOWLING, L., DRIVER, B. & BARNES, B. 2009. The

Murray River algal bloom: evaluation and recommendations for the furture of

management of major outbreaks. NSW Office of Water.

RZYMSKI, P. & PONIEDZIALEK, B. 2014. In search of environmental role of

cylindrospermopsin: A review on global distribution and ecology of its

producers. Water Research, 66, 320-337.

SAKER, M. L. & NEILAN, B. A. 2001. Varied Diazotrophies, Morphologies, and

Toxicities of Genetically Similar Isolates of Cylindrospermopsis raciborskii

(Nostocales, Cyanophyceae) from Northern Australia. Applied and

Environmental Microbiology, 67, 1839-1845.

SALMON, T. P., ROSE, A. L., NEILAN, B. A. & WAITE, T. D. 2006. The FeL model

of iron acquisition: Nondissociative reduction of ferric complexes in the marine

environment. Limnology and Oceanography, 51, 1744-1754.

References

180

SANUDO-WILHELMY, S. A., KUSTKA, A. B., GOBLER, C. J., HUTCHINS, D. A.,

YANG, M., LWIZA, K., BURNS, J., CAPONE, D. G., RAVEN, J. A. &

CARPENTER, E. J. 2001. Phosphorus limitation of nitrogen fixation by

Trichodesmium in the central Atlantic Ocean. Nature, 411, 66-69.

SAUER, J., SCHREIBER, U., SCHMID, R., VÖLKER, U. & FORCHHAMMER, K.

2001. Nitrogen Starvation-Induced Chlorosis in Synechococcus PCC 7942.

Low-Level Photosynthesis As a Mechanism of Long-Term Survival. Plant

Physiology, 126, 233-243.

SCA 2010. Cyanobacteria Risk Profile. In: AUTHORITY, S. C. (ed.).

SCHATZ, D., KEREN, Y., HADAS, O., CARMELI, S., SUKENIK, A. & KAPLAN,

A. 2005. Ecological implications of the emergence of non-toxic subcultures

from toxic Microcystis strains. Environmental Microbiology, 7, 798-805.

SCHATZ, D., KEREN, Y., VARDI, A., SUKENIK, A., CARMELI, S., BORNER, T.,

DITTMANN, E. & KAPLAN, A. 2007. Towards clarification of the biological

role of microcystins, a family of cyanobacterial toxins. Environ Microbiol, 9,

965-70.

SEENAYYA, G. & RAJU, N. S. On the ecology and systematic position of the alga

known as Anabaenopsis raciborskii (Wolosz.) Elenk. and a critical evaluation of

the forms described under the genus Anabaenopis. International Symposium on

Taxonomy and Biology of Bluegreen Algae, 1st, Madras, 1970. Papers, 1972.

SEVILLA, E., MARTIN-LUNA, B., VELA, L., BES, M. T., FILLAT, M. F. &

PELEATO, M. L. 2008. Iron availability affects mcyD expression and

microcystin-LR synthesis in Microcystis aeruginosa PCC7806. Environmental


SEVILLA, E., MARTIN-LUNA, B., VELA, L., TERESA BES, M., LUISA PELEATO,

M. & FILLAT, M. 2010. Microcystin-LR synthesis as response to nitrogen:

transcriptional analysis of the mcyD gene in Microcystis aeruginosa PCC7806.

Ecotoxicology, 19, 1167-1173.

SHAKED, Y., KUSTKA, A. B. & MOREL, F. M. M. 2005. A general kinetic model for

iron acquisition by eukaryotic phytoplankton. Limnology and Oceanography,

50, 872-882.

SHAKED, Y., KUSTKA, A. B., MOREL, F. M. M. & EREL, Y. 2004. Simultaneous

determination of iron reduction and uptake by phytoplankton. Limnology and

Oceanography - Methods, 2, 137-145.

SHI, L., CARMICHAEL, W. W. & MILLER, I. 1995. Immuno-gold localization of

hepatotoxins in cyanobacterial cells. Arch Microbiol, 163, 7-15.

SHILLER, A. M., DUAN, S. W., VAN ERP, P. & BIANCHI, T. S. 2006. Photo-

oxidation of dissolved organic matter in river water and its effect on trace

element speciation. Limnology and Oceanography, 51, 1716-1728.

SHIRAI, M., OHTAKE, A., SANO, T., MATSUMOTO, S., SAKAMOTO, T., SATO,

A., AIDA, T., HARADA, K., SHIMADA, T., SUZUKI, M. & ET AL. 1991.

Toxicity and toxins of natural blooms and isolated strains of Microcystis spp.

(Cyanobacteria) and improved procedure for purification of cultures. Appl

Environ Microbiol, 57, 1241-5.

SIMPSON, F. B. & NEILANDS, J. B. 1976. Siderochromes in cyanophyceae: Isolation

and characterization of schizokinen from Anabaena sp. Journal of Phycology,

12, 44-48.

References

181

SINGH, D. P., TYAGI, M. B., KUMAR, A., THAKUR, J. K. & KUMAR, A. 2001.

Antialgal activity of a hepatotoxin-producing cyanobacterium, Microcystis

aeruginosa. World Journal of Microbiology and Biotechnology, 17, 15-22.

SINHA, R., PEARSON, L., DAVIS, T., MUENCHHOFF, J., PRATAMA, R., JEX, A.,

BURFORD, M. & NEILAN, B. 2014. Comparative genomics of

Cylindrospermopsis raciborskii strains with differential toxicities. BMC

Genomics, 15, 83.

SINHA, R., PEARSON, L. A., DAVIS, T. W., BURFORD, M. A., ORR, P. T. &

NEILAN, B. A. 2012. Increased incidence of Cylindrospermopsis raciborskii in

temperate zones – Is climate change responsible? Water Research, 46, 1408-

1419.

SIVONEN, K. 1990. Effects of light, temperature, nitrate, orthophosphate, and bacteria

on growth of and hepatotoxin production by Oscillatoria agardhii strains. Appl.

Environ. Microbiol., 56, 2658-2666.

SIVONEN, K. 2009. Cyanobacterial toxins. In: MOSELIO, S. (ed.) Encyclopedia of

Microbiology. Oxford: Academic Press.

SOARES, R. M., YUAN, M., SERVAITES, J. C., DELGADO, A., MAGALHÃES, V.

F., HILBORN, E. D., CARMICHAEL, W. W. & AZEVEDO, S. M. F. O. 2006.

Sublethal exposure from microcystins to renal insufficiency patients in Rio de

Janeiro, Brazil. Environmental Toxicology, 21, 95-103.

SPRŐBER, P., SHAFIK, H. M., PRÉSING, M., KOVÁCS, A. W. & HERODEK, S.

2003. Nitrogen uptake and fixation in the cyanobacterium Cylindrospermopsis

raciborskii under different nitrogen conditions. Hydrobiologia, 506, 169-174.

STAL, L. J. 2001. Nitrogen fixation in cyanobacteria. eLS. John Wiley & Sons, Ltd.

STEVANOVIC, M., HAHN, A., NICOLAISEN, K., MIRUS, O. & SCHLEIFF, E.

2012. The components of the putative iron transport system in the

cyanobacterium Anabaena sp PCC 7120. Environmental Microbiology, 14,

1655-1670.

STOOKEY, L. L. 1970. Ferrozine - a new spectrophotometric reagent for iron.

Analytical Chemistry, 42, 779-781.

SUNDA, W. & HUNTSMAN, S. 2003. Effect of pH, light, and temperature on Fe-

EDTA chelation and Fe hydrolysis in seawater. Marine Chemistry, 84, 35-47.

SUNDA, W. G. (ed.) 2001. Bioavailability and bioaccumulation of iron in the sea,

Chichester ; New York: J. Wiley.

SUNDA, W. G. 2012. Feedback interactions between trace metal nutrients and

phytoplankton in the ocean. Frontiers in Microbiology, 3, 1-22.

SUNDA, W. G. & HUNTSMAN, S. A. 1996. Antagonisms between cadmium and zinc

toxicity and manganese limitation in a coastal diatom. Limnology and


SUNDA, W. G. & HUNTSMAN, S. A. 1998. Interactions among Cu2+, Zn2+, and

Mn2+ in controlling cellular Mn, Zn, and growth rate in the coastal alga

Chlamydomonas. Limnology and Oceanography, 43, 1055-1064.

SUNDA, W. G. & HUNTSMAN, S. A. 2000. Effect of Zn, Mn, and Fe on Cd

accumulation in phytoplankton: Implications for oceanic Cd cycling. Limnology

and Oceanography, 45, 1501-1516.

TAKAYAMA, K. & KJELLEBERG, S. 2000. The role of RNA stability during

bacterial stress responses and starvation. Environmental Microbiology, 2, 355-

365.

References

182

TANG, D. G. & MOREL, F. M. M. 2006. Distinguishing between cellular and Fe-

oxide-associated trace elements in phytoplankton. Marine Chemistry, 98, 18-30.

THOMPSEN, J. C. & MOTTOLA, H. A. 1984. Kinetics of the complexation of iron(II)

with ferrozine. Analytical Chemistry, 56, 755-757.

TILLETT, D., DITTMANN, E., ERHARD, M., VON DÖHREN, H., BÖRNER, T. &

NEILAN, B. A. 2000. Structural organization of microcystin biosynthesis in

Microcystis aeruginosa PCC7806: an integrated peptide-polyketide synthetase

system. Chemistry & Biology, 7, 753-764.

TIPPING, E. 2002. Cation binding by humic substances, Cambridge University Press,

UK.

TONIETTO, A., PETRIZ, B. A., ARAUJO, W. C., MEHTA, A., MAGALHAES, B. S.

& FRANCO, O. L. 2012. Comparative proteomics between natural Microcystis

isolates with a focus on microcystin synthesis. Proteome Science, 10.

TONK, L., VISSER, P. M., CHRISTIANSEN, G., DITTMANN, E., SNELDER, E. O.

F. M., WIEDNER, C., MUR, L. R. & HUISMAN, J. 2005. The microcystin

composition of the cyanobacterium Planktothrix agardhii changes toward a

more toxic variant with increasing light intensity. Applied and Environmental


TOOMING-KLUNDERUD, A., MIKALSEN, B., KRISTENSEN, T. & JAKOBSEN,

K. S. 2008. The mosaic structure of the mcyABC operon in Microcystis.


TUIT, C., WATERBURY, J. & RAVIZZA, G. 2004. Diel variation of molybdenum and

iron in marine diazotrophic cyanobacteria. Limnology and Oceanography, 49,

978-990.

UENO, Y., NAGATA, S., TSUTSUMI, T., HASEGAWA, A., WATANABE, M. F.,

PARK, H.-D., CHEN, G.-C., CHEN, G. & YU, S.-Z. 1996. Detection of

microcystins, a blue-green algal hepatotoxin, in drinking water sampled in

Haimen and Fusui, endemic areas of primary liver cancer in China, by highly

sensitive immunoassay. Carcinogenesis, 17, 1317-1321.

UTKILEN, H. & GJOLME, N. 1995. Iron-stimulated toxin production in Microcystis

aeruginosa. Appl Environ Microbiol, 61, 797-800.

VAN SCHAIK, J. W. J., PERSSON, I., KLEJA, D. B. & GUSTAFSSON, J. P. 2008.

EXAFS study on the reactions between iron and fulvic acid in acid aqueous

solutions. Environmental Science & Technology, 42, 2367-2373.

VELAYUDHAN, J., HUGHES, N. J., MCCOLM, A. A., BAGSHAW, J., CLAYTON,

C. L., ANDREWS, S. C. & KELLY, D. J. 2000. Iron acquisition and virulence

in Helicobacter pylori: a major role for FeoB, a high-affinity ferrous iron

transporter. Molecular Microbiology, 37, 274-286.

VERSPAGEN, J. M. H., SNELDER, E. O. F. M., VISSER, P. M., HUISMAN, J.,

MUR, L. R. & IBELINGS, B. W. 2004. Recruitment of benthic Microcystis

(Cyanophyceae) to the water column: Internal buoyancy changes or

resuspension? Journal of Phycology, 40, 260-270.

VÉZIE, C., RAPALA, J., VAITOMAA, J., SEITSONEN, J. & SIVONEN, K. 2002.

Effect of nitrogen and phosphorus on growth of toxic and nontoxic Microcystis

strains and on intracellular microcystin concentrations. Microbial Ecology, 43,

443-454.

References

183

VILHENA, L. C., HILLMER, I. & IMBERGER, J. R. 2010. The role of climate change

in the occurrence of algal blooms: Lake Burragorang, Australia. Limnology and


VIZCAINO, J., DEUTSCH, E., WANG, R., CSORDAS, A., REISINGER, F., RIOS,

D., DIANES, J., SUN, Z., FARRAH, T., BANDEIRA, N., BINZ, P.,

XENARIOS, I., ELSENACHER, M., MAYER, G., GATTO, L., CAMPOS, A.,

CHALKLEY, R., KRAUS, H., ALBAR, J., MARTINEZ-BARTOLOME, S.,

APWEILER, R., OMENN, G. S., MARTENS, L., JONES, A. & HERMJAKOB,

H. 2014. ProteomeXchange provides globally co-ordinated proteomics data

submission and dissemination. Nature Biotechnol, 30, 223-226.

WANG, C., KONG, H. N., WANG, X. Z., WU, H. D., LIN, Y. & HE, S. B. 2010a.

Effects of iron on growth and intracellular chemical contents of Microcystis

aeruginosa. Biomed Environ Sci, 23, 48-52.

WANG, Z., LI, D., LI, G. & LIU, Y. 2010b. Mechanism of photosynthetic response in

Microcystis aeruginosa PCC7806 to low inorganic phosphorus. Harmful Algae,

9, 613-619.

WEGENER, K. M., SINGH, A. K., JACOBS, J. M., ELVITIGALA, T., WELSH, E. A.,

KEREN, N., GRITSENKO, M. A., GHOSH, B. K., CAMP, D. G., 2ND,

SMITH, R. D. & PAKRASI, H. B. 2010. Global proteomics reveal an atypical

strategy for carbon/nitrogen assimilation by a cyanobacterium under diverse

environmental perturbations. Mol Cell Proteomics, 9, 2678-89.

WHITTAKER, S., BIDLE, K. D., KUSTKA, A. B. & FALKOWSKI, P. G. 2011.

Quantification of nitrogenase in Trichodesmium IMS 101: implications for iron

limitation of nitrogen fixation in the ocean. Environmental Microbiology

Reports, 3, 54-58.

WIEDNER, C., VISSER, P. M., FASTNER, J., METCALF, J. S., CODD, G. A. &

MUR, L. R. 2003. Effects of light on the microcystin content of Microcystis

strain PCC 7806. Appl Environ Microbiol, 69, 1475-81.

WIESE, S., REIDEGELD, K. A., MEYER, H. E. & WARSCHEID, B. 2007. Protein

labeling by iTRAQ: A new tool for quantitative mass spectrometry in proteome

research. PROTEOMICS, 7, 340-350.

WILLIAMS, T. J., BURG, D. W., ERTAN, H., RAFTERY, M. J., POLJAK, A.,

GUILHAUS, M. & CAVICCHIOLI, R. 2010. Global proteomic analysis of the

insoluble, soluble, and supernatant fractions of the psychrophilic archaeon

Methanococcoides burtonii. Part II: the effect of different methylated growth

substrates. J Proteome Res, 9, 653-63.

WILLIS, A., CHUANG, A. W. & BURFORD, M. A. 2016. Nitrogen fixation by the

reluctant diazotroph Cylindrospermopsis raciborskii (Cyanophyceae). Journal of

Phycology, n/a-n/a.

WIRTZ, N. L., TREBLE, R. G. & WEGER, H. G. 2010. Siderophore-independent iron

uptake by iron-limited cells of the cyanobacterium Anabaena flos-aquae.

Journal of Phycology, 46, 947-957.

WOJCIECHOWSKI, J., FERNANDES, L. F. & FONSECA, F. V. B. 2016. Morpho-

physiological responses of a subtropical strain of Cylindrospermopsis

raciborskii (Cyanobacteria) to different light intensities. Acta Botanica

Brasilica, 30.

References

184

XING, W., HUANG, W. M., LI, D. H. & LIU, Y. D. 2007. Effects of iron on growth,

pigment content, photosystem II efficiency, and siderophores production of

Microcystis aeruginosa and Microcystis wesenbergii. Curr Microbiol, 55, 94-8.

XING, W., HUANG, W. M., LIU, G. H. & LIU, Y. D. 2008. Effects of iron on

physiological and biochemical charcterisitics of Microcystis wesenbergii (Kom.)

Kom. (Cyanobacterium). Fresenius Environmental Bulletin, 17, 2034-2042.

YEUNG, A. C., D'AGOSTINO, P. M., POLJAK, A., MCDONALD, J., BLIGH, M. W.,

WAITE, T. D. & NEILAN, B. A. 2016. Physiological and Proteomic Responses

of Continuous Cultures of Microcystis aeruginosa PCC 7806 to Changes in Iron

Bioavailability and Growth Rate. Appl Environ Microbiol, 82, 5918-29.

YUE, D., PENG, Y., YIN, Q. & XIAO, L. 2014. Proteomic analysis of Microcystis

aeruginosa in response to nitrogen and phosphorus starvation. Journal of

Applied Phycology, 1-10.

ZILLIGES, Y., KEHR, J. C., MEISSNER, S., ISHIDA, K., MIKKAT, S.,

HAGEMANN, M., KAPLAN, A., BORNER, T. & DITTMANN, E. 2011. The

cyanobacterial hepatotoxin microcystin binds to proteins and increases the

fitness of Microcystis under oxidative stress conditions. PLoS One, 6, e17615.

ZOHARY, T. & BREEN, C. M. 1989. Environmental factors favouring the formation

of Microcystis aeruginosa hyperscums in a hypertrophic lake. Hydrobiologia,

178, 179-192.

ZUO, Y. G. & HOIGNE, J. 1992. Formation of hydrogen peroxide and depletion of

oxalic acid in atmospheric water by photolysis of Iron(III) oxalato complexes.

Environmental Science & Technology, 26, 1014-1022.

Appendix A

185

Appendix A

This appendix contains additional information about the different culturing media

used throughout this thesis.

Appendix A

186

BG11

Prepare stock solutions in MQ water and sterilise through 0.22 µm syringe driven filter.

Stock 1 - in 1 L of MQ, add:

EDTA Na 0.90 g

(NH4) Fe(III) citrate 0.60 g

Citric acid 0.60 g

CaCl·2H2O 3.60 g

Stock 2 - in 1 L of MQ, add:

MgSO4 7.50 g

Stock 3 – in 400 mL of MQ, add:

K2HPO4 3.05 g

Stock 5 – in 1 L of MQ, add

H3O3 2.86 g

MnCl2·4H2O 1.81 g

ZnSO4·7H2O 0.22 g

Na2MoO4·2H2O 0.39 g

CuSO4·5H2O 0.08 g

Co(NO3)2·6H2O 0.05 g

Add 0.02 g of Na2CO3 and 1.5 g of NaNO3 to 800 mL of MQ water and autoclave, after

cooling to room temperature add 10 mL of filter sterilised stock solutions 1, 2 and 3 and

1 mL of filter sterilised stock solution 5, add sterile MQ to make up to 1L of BG11.

Appendix A

187

Jaworski Medium (JM)

Stock solutions are prepared in 200 mL MQ water and sterilised through 0.22 µm

syringe driven filters.

Stock solutions

1 Ca(NO3)2·4H2O 4.0 g

2 KH2PO4 2.48 g

3 MgSO4·7H2O 10.0 g

4 NaHCO3 3.18 g

5 EDTA FeNa 0.45 g

EDTA Na2·2H2O 0.50 g

6 H3BO3 0.496 g

MnCl2·4H2O 0.278 g

(NH4)6MoO24·4H2O 0.20 g

7a Cyanocobalomin (Vitamin B12) 0.008 g

7b Thiamine HCl (Vitamin B1) 0.008 g

Biotin 0.008 g

8 NaNO3 16.0 g

9 Na2HPO4·12H2O 7.2 g

Add 1mL of each stock solution to 800 mL of sterilised MQ water except Stock 7. Add

100 µL of 7a and 110 µL of 7b. Top up with sterilised MQ water to make up 1 L of JM.

Appendix A

188

Modified Jaworski Medium (JM*)

JM* differs from conventional JM in that combined nitrogen sources have been

replaced and iron is supplied as FeCl3 and mixed with the EDTA ligand in

concentrations required by each experiment. Stock solutions are prepared in 200 mL

MQ water and sterilised through 0.22µm syringe driven filters.

Stock solutions

1 CaCl2·2H2O 2.49 g

2 KH2PO4 2.48 g

3 MgSO4·7H2O 10.0 g

4 NaHCO3 3.18 g

5 FeCl3 6H2O 0.331 g

EDTA Na2·2H2O 0.50 g

6 H3BO3 0.496 g

MnCl2·4H2O 0.278 g

Na2 MoO4·2H2O 0.073 g

7a Cyanocobalomin (Vitamin B12) 0.008 g

7b Thiamine HCl (Vitamin B1) 0.008 g

Biotin 0.008 g

8 NaCl 11.0 g

9 Na2HPO4·12H2O 7.2 g

Add 1 mL of each stock solution to 1L of sterilised MQ water except Stocks 5 and 7.

For Stock 5, mix FeCl3 with EDTA at concentrations as required by experiment prior to

addition into JM* to avoid precipitation. Add 100 µL of 7a and 110 µL of 7b.

Appendix A

189

Fraquil* and Fraquil*BG11

Salt stocks Fraquil* (in 100 mL MQ)

Fraquil*BG11 (in 100mL MQ)

Add to 1L MQ

CaCl2·2H2O 1 3.8225 3.8225 1 mL

MgSO4·7H2O 2 3.746 7.4927 1 mL

NaHCO3 3 0.850 4.2005 1 mL

K2HPO4 4 0.174 16.9980 1 mL

HEPES 5 3.0482 3.0482 1 mL

Trace metal stocks a

CuSO4·5H2O 6 0.0394 0.0789 100 µL

CoCl2·6H2O 7 0.0119 0.0404 100 µL

MnCl2·4H2O 8 0.1191 1.8109 100 µL

ZnSO4·7H2O 9 0.3450 0.3450 100 µL

Na2SeO3 10 0.0017 0.0017 100 µL

Na2MoO4·2H2O 11 0.0024 0.0484 100 µL

Fe-ligand stocks

Na2EDTA·2H2O 12 0.9672 0.9672 1ml

FeCl3·6H2O a 13 0.0270 0.0270 1ml

Vitamin stocks

Thiamine HCl 14 0.010 g

Biotin 15 0.0501 0.0501

Cyanocobalamin 16 0.0550 0.0550

a Dissolve in 0.01 M HCl to prevent precipitation

Stock solutions are prepared separately in a clean room in MQ water then

sterilised through 0.22 µm filters. Fe-ligand stocks were mixed together at desired

concentrations (EDTA final concentration 2.6 µM, FeCl3 at final concentrations 100 nM

or 1000 nM) and equilibrated for 5 min prior to addition to avoid precipitation in the

medium. The pH of the medium was adjusted to pH 8.0 with NaOH then sterilised in a

1000V microwave at 3:2:2 min intervals. Filter sterilised vitamin stocks were added

once medium has cooled to room temperature.

Appendix B

191

Appendix B

This appendix contains development of the optimized protein extraction method

used in Chapters 2 and 5 by examining the effectiveness of different protein extraction

buffers and cell lysis methods on cyanobacteria.

1 Introduction

The protein extraction process is important; particularly for global proteomic

studies to ensure certain functional categories are not over represented or biased by the

extraction method. Therefore, the lack of standardised protocols amongst proteomic

studies provides the opportunity to optimise a protein extraction method for gel-free

applications. One of the challenges with cyanobacterial proteomics is to recover

substantial amount of protein from cultures, secondly buffers of the extracted proteins

should not contain thiols or primary amines as these can interfere with the cysteine

blocking and react with the isobaric tags.

This study compares the protein extraction efficiency of three previously

published buffers (Battchikova et al., 2010, Herbert et al., 2006, Pandhal et al., 2007), a

general lysis buffer (Buffer G) adapted from European Molecular Biology Laboratory

(EMBL) as well as the method of cell lysis to optimise the protein extraction from

unicellular (Microcystis aeruginosa) and filamentous (Cylindrospermopsis raciborskii)

cyanobacteria. Bicinchoninic Acid (BCA) protein assay was used to quantify the

extracted protein for comparisons between each extraction method. The optimized

protocol was then applied to batch cultures of C. raciborskii and M. aeruginosa.

Appendix B

192

2 Materials and methods

Cyanobacterial culture conditions

Cultures of Microcystis aeruginosa PCC7806 and Cylindrospermopsis raciborskii

CS-509 were grown to late exponential phase (OD750 ~ 0.80) using a modified Fraquil*

(Dang et al., 2012a) and JM* medium respectively. Cultures were incubated at 25 oC

under ambient fluorescent light. Cells were collected by filtering 500 mL of cells

through 3 μm filters (Millipore). Filters were washed with fresh media to remove

contaminating heterotrophic bacteria and resuspended in 20 mL of media. Cell pellets

were collected by centrifuging at 5000g for 20 minutes.

Buffer compositions

All extraction buffers tested in this study were from published literature for

cyanobacterial protein extraction (Herbert et al., 2006, Pandhal et al., 2007, Battchikova

et al., 2010). For simplicity the buffers are named A, B and C (Table B1). Cell pellets

were resuspended in 500 μL of protein extraction buffer A, B or C or G in triplicates for

each test condition. Partial cell lysis was achieved by three freeze/thaw cycles in liquid

nitrogen and 37 °C water bath. To protect from protein degradation, 10 μL of PMSF (10

μM final concentration) was added to the samples. Samples were then either subjected

to further lysis by bead beating or sonication.

Appendix B

193

Table B1 Composition of buffers used in this optimization study.

Buffer Composition Reference

A 7M Urea, 2M Thiourea, 2% CHAPS, 2% Sulfobetaine 3-10, 80 mM Citric acid, pH 4

Herbert et al (2006)

B 50 mM HEPES-KOH, 0.1% SDS, 0.1% Triton X-100

Battchikova et al (2010)

C 9M Urea, 4% (w/v) CHAPS, 1% (w/v) DTT, 0.8% (w/v) Ampholine, 10 mM PVPP

Pandhal et al (2007)

G (General lysis

buffer)

Tris-HCl 100 mM, KCl 200 mM, DTT 5 mM, PMSF 1 mM

Modified from EMBL protocols

Bead beating procedure

To one set of samples (A1, B1, C1, G1), an equal volume of silica beads was

added. Samples were disrupted using a Fastprep FP120 Cell Disrupter (Thermo Savant,

Carlsbad, USA) for 1 min intervals at top speed, with breaks on ice in between, with the

process repeated three times. The crude extract was centrifuged at 1000 x g for 5 min to

remove unbroken cells and beads. The supernatant was transferred to a new tube and

incubated for 30 min with 2% (v/v) SDS to facilitate extraction of membrane proteins

while the unbroken cells and beads were re-extracted as above. Samples were then

centrifuged and the pellets discarded. Supernatant fractions were combined and 9

volumes of ice-cold acetone was added, samples were left to precipitate overnight at -20

oC. Samples were resuspended in 500 μL of dissolving buffer (500 mM NaHCO3, 2%

SDS) for quantification and gel electrophoresis.

Sonication procedure

Partially lysed cell samples in respective testing buffers (A2, B2, C2 and G2)

were sonicated on ice using a Digital sonifier S-450 (Branson) for 3 cycles of 30 s at

30% amplitude and placed on ice for 2 minutes. The extracts were centrifuged and the

pellet was extracted once more with additional 500 μL of buffer A, B, C. or G The two

Appendix B

194

fractions were combined and precipitated with 9 volumes of ice-cold acetone and

allowed to precipitate overnight at -20oC. The cell pellet was resuspended in 500 μl of

dissolving buffer (500 mM NaHCO3, 2% SDS) for quantification and gel

electrophoresis.

Quantification of protein extracts

Protein extracts were quantified using the PierceTM

BCA protein assay kit

(Thermo Scientific) as per the manufacturer instructions for 96 well microplate assay.

Serial dilutions of bovine serum albumin (BSA) standards (2 mg/mL) were made to the

working range of 20-2000 μg/mL for the standard curve. Absorbance readings were

measured at 562 nm on a VersaMax molecular devices microplate reader. Initially the

extracts were quantified by BCA without precipitation; however the high urea

concentration in buffers A and C reacted with the assay kit reagents, resulting in over

estimation of the amount of protein in the samples. Hence acetone precipitation was

performed overnight prior to quantification.

SDS-PAGE gel electrophoresis

4x Loading buffer (200 mM Tris-HCl, pH 6.8, 400 mM DTT, 8% (w/v) SDS,

0.4% bromophenol blue, 40% glycerol) was mixed with 50 μg of protein sample then

heated for 5 minutes at 90 °C. Samples were allowed to cool then loaded on to a 15%

polyacrylamide gel and run at 100V for 10 min until dye front reached resolving layer,

then voltage was increased to 180V and run for 40 minutes. Gels were stained for 1h in

Coomassie (0.1% Coomassie Brilliant Blue R-250, 10% (v/v) glacial acetic acid, 40%

(v/v) methanol) and fixed with a fixing solution (Acetic acid, Methanol). Protein gels

were destained overnight with MQ. The gel was visualised on flatbed scanner.

Appendix B

195

3 Results and discussion

This study reports the optimised protein extraction protocol for cyanobacterial

shotgun proteomic studies using iTRAQ labels. Most of the cyanobacterial proteomic

studies to date have been performed on traditional methods requiring gel excision, while

a few recent studies have used label methods (D’Agostino et al., 2014, Battchikova et

al., 2010) even fewer studies have focused on the method of extraction (Plominsky et

al., 2009). There is a lack of standardisation between methods used in protein extraction

from proteomic studies hence here we propose an optimised protein extraction protocol

for Cyanobacteria for use with iTRAQ labels.

Sonication versus bead beating

The two methods tested for cell lysis were bead beating and sonication. Both

methods were effective in the lysis of Microcystis and Cylindrospermopsis cells when

examined under the microscope (Figure B 1).

Figure B 1 Microscopic observations of membrane disruption before and after lysis

treatment. Successful membrane disruption is observed in the post-lysis photograph.

Appendix B

196

Figure B 2 Comparison of lysis efficiency. Efficiency of extractions is calculated as the amount (μg) of protein recovered per mg of cell mass. Protein amount was determined by BCA assay and visualisation by PAGE.

However, the BCA assay of protein extracts from M. aeruginosa found that

sonication recovered a greater protein yield when compared to bead beating (Figure B

2), similar results were observed for C. raciborskii (data not shown). For the sonication

method, Buffer B had the highest yield followed by Buffer C then Buffer G (357, 338

and 304 µg respectively) while Buffer A recovered the least amount of protein (225 µg).

The same order for buffer performance was observed for bead beat samples (240 µg;

202 µg; 160 µg and 125 µg respectively).

Comparison of the buffer compositions

Consistent with the measurements from the BCA protein assay, the 1D SDS-

PAGE gel showed Buffer A had the faintest banding when compared to Buffers B, C, or

G, despite the same amount of protein being loaded across all lanes (Figure B 3). All

protein bands on the gel were clear and not diffused suggesting that protein degradation

was not the cause of the difference between buffers used. By comparison, extracts from

Appendix B

197

bead beating were faint on the 1D gel (Figure B 3), and there were marginally fewer

visible bands at the top of the gel when compared to sonicated samples suggesting that

perhaps bead beating was less effective in recovering larger proteins.

Figure B 3 SDS gel for buffer comparison in M. aeruginosa. Acetone precipitated samples were resuspended in dissolving buffer and 50 μg of sample was boiled with loading buffer and visualised on 15% polyacrylamide gel. The first letter, S or B, denotes the lysis methods sonication and bead beating respectively. The second letter: A, B, C or G, denotes the respective extraction buffers used. Protein marker (M), Broad Range 2-212 kDa (New England Biolabs)

Buffer B in conjunction with sonication was most effective in protein extraction

and yield the most amount of protein. Incubation with low concentration of SDS did not

yield any more membrane bound proteins than without SDS incubation, thus this step

was omitted for future extractions. The optimised protocol for the extraction of proteins

from unicellular and filamentous cyanobacteria for gel-free proteomic analysis is

presented in Table 2. Buffer B adapted from Battchikova et al (2010) was a suitable

buffer for iTRAQ proteomics as it does not contain secondary amines whereas Buffers

A and C would require buffer exchanges before samples could be used for iTRAQ

Appendix B

198

labelling and a greater risk of sample loss during the process.

4 Conclusions

From this comparison study for optimal protein recovery, it was evident that both

extraction buffer composition and lysis method affected the overall effectiveness in the

extraction of protein from the cyanobacteria used in this study. It was found that Buffer

B yield the best results in comparison with the buffers tested. Cell lysis by sonication

was more efficient than bead beating. Buffer exchange is not required for this method.

The optimized protocol was applied to the filamentous cyanobacteria, C. raciborskii

CS-509 and showed that protein categories were not biased as demonstrated by the

shotgun proteomics results. Furthermore the proteomic results effectively showed

differences in the proteome between levels of iron limitation. Based on this study the

following protocol can be applied for future cyanobacterial gel-free proteomic

experiments.

Appendix C

199

Appendix C

This appendix contains additional information and Figures to Chapter 4 and is published as the

supplementary information for:

Competitive Effects of Calcium and Magnesium Ions on the Photochemical Transformation and

Associated Cellular Uptake of Iron by the Freshwater Cyanobacterial Phytoplankton Microcystis

aeruginosa. Manabu Fujii, Anna C. Y. Yeung, and T. David Waite. Environmental Science &

Technology 2015 49 (15), 9133-9142. doi: 10.1021/acs.est.5b01583

1 Details of Experimental Procedures

In this study, cell culturing, photochemical experiment and Fe uptake assay were performed by

employing the methods previously described elsewhere (Fujii et al., 2011a, Fujii et al., 2014b) but

with some modifications. Following sections provides full descriptions of experimental procedures

including preparation of chemical stocks, culturing medium, cell culturing and procedures of

photochemical and biological Fe uptake experiments.

Reagents

All chemicals were used as received and stored according to package instruction. Unless

otherwise stated, ultrapure water (Milli-Q water, Millipore, 18.2 MΩ・cm resistivity at 25oC) was

Appendix C

200

used for the preparation of reagents and stock solutions. The stock solutions were made in a trace

metal clean room supplied with HEPA-filtered air and stored in the dark at 4oC when not in use.

Stock solutions of 10-100 mM ethylenediaminetetraacetic acid (EDTA) and 100 g.L-1

Suwannee River fulvic acid (SRFA) were prepared by dissolving Na2EDTA (Sigma) and SRFA

(International Humic Substance Society) in Milli-Q, respectively. Stock solutions of 0.1 M ferrozine

(FZ; 3-(2-pyridyl)-5,6-diphenyl-1,2,4-triazine-4’,4’’-disulfonic acid sodium salt, Sigma) and

ascorbate (sodium L-ascorbate, Sigma) were prepared in Milli-Q. All ligand and ascorbate stocks

were adjusted to pH 8.0 to avoid a significant pH change when added to the culture medium. A stock

solution of non-radiolabeled Fe(III) (FeIII

Cl3, Ajax Finechem, Australia) was made in 0.01 M HCl at

concentrations of 1-10 mM. For the Fe uptake experiment, a 23 mM stock of radiolabeled ferric

chloride (55

FeIII

Cl3 in 0.5 M HCl, 185 MBq, Perkin-Elmer, Australia) was diluted with the 1 mM

non-radiolabeled FeCl3 to yield a final Fe concentration of 1.9 mM. A 2 mM bicarbonate buffered

solution at pH 8 was made by dissolving sodium hydrogen carbonate (NaHCO3, Sigma) in Milli-Q.

Solutions of organically complexed Fe(III) (FeIII

EDTA or FeIII

SRFA) were then made by placing the

either non-radiolabelled or radiolabeled Fe(III) solution in the bottom of a 1.5 mL polypropylene

container followed by addition of an appropriate volume of EDTA or SRFA stock solution. Before

use, the solution was stored for 24 hr under dark conditions at 25oC in order to reach equilibrium. A

stock solution of Fe(II) was prepared by dissolving ammonium ferrous sulfate in 1 mM HCl at a final

concentration of 4 mM. To remove metals non-specifically adsorbed onto cell surfaces (including Fe

Appendix C

201

oxyhydroxides) via the ligand-exchange process, cells were washed by using a chelate solution (pH

7) containing 50 mM Na2EDTA (Sigma) and 100 mM Na2oxalate (Sigma) (hereafter referred to as

“EDTA/oxalate”) (Tang and Morel, 2006).

To avoid metal contamination, only plastic ware was used for the solution preparation, storage

and sample incubation. Plastic ware was washed in detergent, soaked in a 0.1 M HCl bath for at least

24 hr, rinsed with MQ and dried prior to use. Solution pH used in this study was determined by using

a pH meter (pH/ION 340i, WTW, Germany), which was calibrated with phthalate and phosphate

standard pH buffers (pH 4.01 and 6.86 at 25oC, respectively). Adjustment of pH was performed by

dropwise addition of concentrated HCl or NaOH solutions (e.g., concentration of 1-5 M). The HCl or

NaOH solutions were prepared from highly purified 30% w/v HCl (Fluka) or NaOH (Riedel-deHaën,

Germany), respectively. All pH values in this study appear on the hydrogen ion activity scale.

The photochemical experiment, Fe uptake assay and cell culturing were conducted in a light-

and temperature-controlled incubator at 27oC (Thermoline Scientific). The Fe(II)-ligand

complexation experiment was performed in the temperature controlled room at 25oC and dark

condition. If necessary, the water temperature of chemical solutions was adjusted to 25oC by using a

water bath prior to the experiments.

Appendix C

202

Culturing medium

A modified Fraquil medium (Fraquil*) was used as a medium for cell culturing and other

experiments since speciation and transformation kinetics of iron in this medium have been well

studied.(Fujii et al., 2014b, Fujii et al., 2011a) For the long-term cell culturing, the Fraquil* medium

was prepared as previously described.(Fujii et al., 2014b, Fujii et al., 2011a, Andersen, 2005) The

medium was prepared the trace metal clean room by using at least reagent grade salts. Major salts

and trace metals stocks for Fraquil* were developed in Milli-Q water individually rather than as a

mixture. All solutions were stored in the dark at 4oC. The stock solutions were mixed in ~1L Milli-Q

water except for Fe(III) and ligand stocks. The 1 mM FeIII

Cl3 and 13 mM EDTA solutions were

separately mixed followed by addition to the 1 L nutrient solution. This procedure is necessary to

prevent significant precipitation of Fe(III) in the medium. The medium was then sterilized by heating

in a 700 W microwave oven for totally 10 minutes with 3, 2, 3 and 2 minutes interval. After cooling

to the room temperature, the medium pH was adjusted to 8.0 followed by the addition of filter-

sterilized vitamin solutions. Final concentrations of chemical compounds were as follows: 2.6 × 10-4

M for CaCl2, 1.5 × 10-4

M for MgSO4, 1.0 × 10-3

M for NaNO3, 1.0 × 10-5

M for K2HPO4, 5.0 × 10-4

M for NaHCO3, 1.0 × 10-3

M for HEPES, 1.6 × 10-7

M for CuSO4, 5.0 × 10-8

M for CoCl2, 6.0 × 10-7

M for MnCl2, 1.2 × 10-6

M for ZnSO4, 1.0 × 10-8

M for Na2SeO3, 1.0 × 10-8

M for Na2MoO24, 1 × 10-

7 M for Fe and 2.6 × 10

-5 M, EDTA, 3.0 × 10

-7 M for thiamine HCl (Vitamin B1), 2.1 × 10

-9 M for

biotin (Vitamin H) and 3.6 × 10-10

M for cyanocobalamin (Vitamin B12).

Appendix C

203

For the photochemical experiment and Fe uptake assay, Fe-, ligand- and Me-free Fraquil* was

prepared by using the identical procedure to that described in the long-term incubation medium,

except that addition of FeCl3, EDTA, CaCl2, and MgSO4 stocks were omitted: thus concentrations of

all nutrients other than these compounds were unchanged. Prior to the commencement of the

experiments, the solutions of Fe-ligand complex and Me were added to the Fe-, ligand- and Me-free

Fraquil* at concentrations required in each experimental conditions. The level of Fe contamination in

the Fe-free Fraquil* (except for the Fraquil* containing SRFA) was determined to below ~1

nM(Fujii et al., 2010a), which was much less than the lowest concentration used in this study (i.e.,

100 nM) based on (i) calculation of Fe concentrations in the salt reagents using the manufactures’

specifications and (ii) determination of Fe concentration in the Fe-free Fraquil* using the FZ

colorimetric method with a 1 m Ocean Optics long pathlength spectrophotometry system (detection

limit of measurement was ~ 1 nM). Thus, additional cleaning procedure was not undertaken (e.g.,

Chelex treatment) (Andersen, 2005). However, in case of SRFA, it is recognized that SRFA

inherently contains trace metals including Fe to some extent. Furthermore, while HEPES has been

reported to be a strong copper agent (Mash et al., 2003), this pH buffer is unlikely to affect Fe

complexation by EDTA or SRFA under the condition examined in this work, as discussed in Section

2 of this appendix.

Appendix C

204

Long-term cell culturing

In the long-term incubation, a batch culture of Microcystis aeruginosa PCC7806 was incubated

in pH 8 Fraquil* medium (containing 26 μM EDTA and 100 nM Fe) under sterile conditions. The

culture was incubated in the light- and temperature-controlled incubator (Thermoline Scientific) at a

temperature of 27oC and 14h:10 h light dark cycle. Cells were regularly subcultured into the fresh

medium when the culture reached to stationary growth phase. Under this incubational condition, the

specific growth rate was determined to be ~0.6 d-1

. Given that the specific growth rate in the Fe

sufficient Fraquil* medium is ~1.0 d-1

(Fujii et al., 2010a), the growth of M. aeruginosa is

moderately limited due to the lower availability of Fe, If the incubation started at cell density of 10-4

cell.mL-1

, the culture reaches to the stationary growth phase approximately after a 2 weeks period.

Cell density was determined under an optical microscope (Nikon, Japan) using a Neubauer

hemocytometer (0.1 mm depth).

Light condition

In the incubator, light was horizontally supplied with three cool-white fluorescent tubes (36 W,

28 diameter, 1.2 m length, Philips). Cell cultures and all samples in the photochemical and Fe uptake

experiments were placed at 10 cm distance from the fluorescent light tubes. At this distance, total

radiation intensity was determined to be 157 μmol.m-2

.s-1

. By using an Ocean Optics USB 4000

spectrophotometer equipped with an optical fiber and cosine converter that was calibrated against a

Appendix C

205

DH-2000 VIS light source. The cell culture and other abiotic samples were incubated in either 100

mL polycarbonate vessel (Nalgene, mainly for the long-term cell culturing) or 1 cm pathlength

polystyrene spectrophotometer cuvette (Starna Pty Ltd, Australia, mainly for the photochemical

experiment and Fe uptake assay) to minimize interfere with light transmission (Fujii et al., 2011a).

During the dark incubations, samples were covered with aluminum foil to prevent light penetration

into sample.

Photochemical experiment

The photochemical experiments were conducted by using the ferrozine (FZ) competitive

assay(Fujii et al., 2011a). In this assay, the rate of Fe(II)' formation due to the photolysis of

organically complexed Fe(III) was determined by spectrophotometrically measuring the time course

of ferrous-ferrozine (FeIIFZ3) complex concentration after mixing the equilibrated Fe

IIIL solution and

FZ stock in Fraquil containing various concentrations of Me.

Prior to the experiment, the Fe- and ligand-free Fraquil* media with various Me concentrations

were prepared by pipetting appropriate volumes of CaCl2 and MgSO4 solutions to the Fe-, ligand-

and Me-free Fraquil*. Then, the equilibrated FeIII

EDTA or FeIII

SRFA solution was added into the

Fe- and ligand-free Fraquil*. The photochemical experiment was initiated by adding appropriate

amount of the FZ stock to the Fraquil* medium containing equilibrated Fe-ligand and Me. Final

Appendix C

206

concentrations of chemicals in the samples were adjusted to 20 μM for Fe, 40 μM for EDTA, 2 μM -

20 mM for Me and 1 mM for FZ in the EDTA system and 5 μM for Fe, 50 mg.L-1

for SRFA, 20 mM

for Me and 1 mM for FZ in the SRFA system. After the addition of FZ stock, the absorbance of

solution was monitored at a wavelength of 562 nm, where FeIIFZ3 complex absorbs most strongly

(Stookey, 1970), by using a Varian Cary 50 UV-vis spectrophotometer with 1 cm pathlength quartz

cuvette. The sample incubation was conducted under light or dark condition and the absorbance

measurement was performed every 2 hours for up to 8 hours. The measured absorbance was

converted to FeIIFZ3 concentration by using the molar absorptivity of 27,000 M

-1.cm

-1. The

photochemical experiments were conducted in the light- and temperature-controlled incubator, as

noted above.

The effect of Fe contamination in the reagents on the FeIIFZ3 formation rate was determined to

be negligible by repeating the photochemical experiment with the identical methods except that

addition of Fe to the sample solution was omitted. While fulvic acids typically absorb light in visible

region, light absorbance of SRFA at 562 nm is small. Thus, effect of SRFA (at 10 mg.L-1

concentration) on the determination of FeIIFZ3 formation rate was determined to be negligible.

Although it is well known that Fe(III) is reduced to Fe(II) in the presence of fulvic acid (Pullin and

Cabaniss, 2003, Pham et al., 2012), concentration of Fe(II) initially present in the FeIII

SRFA stock

(i.e., initial concentration of Fe(II) in the photochemical experiment) was estimated to be negligibly

small.

Appendix C

207

Fe uptake experiment

Prior to the Fe uptake assay, cells were harvested by filtration of the long-term culture with a

0.65 μm PVDF membrane filter (25 mm diameter, Millipore) during the daytime of late exponential

growth phase (at cell density of ~106 cell.mL

-1). The cells on the filter were then gently washed with

10 mL of the EDTA/oxalate chelate solution and subsequently rinsed with 10 mL of 2 mM

bicarbonate solution (total washing time was ~15 minutes). The test culture was prepared by

resuspending the washed cells to Fe- and ligand-free Fraquil* which was previously amended with

different Me concentrations ranging from 2 μM - 20 mM. The short-term incubational assays were

initiated by spiking the pre-equilibrated radiolabeled 55

Fe-ligand stock solution to the cell culture.

The 55

Fe-ligand stock was added at final concentrations of 0.05-1 μM for Fe and 20 μM for EDTA in

the assay using EDTA and 0.5 μM for Fe and 10 mg.L-1

for SRFA in the case of SRFA system. The

final cellular concentration was adjusted to ~2 × 106 cell.mL

-1. Cells were incubated for 2 h (where

55Fe accumulation is linear with respect to time) under the incubator fluorescent lighting condition.

In some cases, cells were also incubated in the additional presence of 1 mM FZ.

After the short term incubation, cells were vacuum-filtered onto 0.65 μm PVDF membrane

filter. Then, filtered cells were rinsed three times with 1 mL of EDTA/oxalate and three times with 1

mL of 2 mM NaHCO3 (total rinsing time is ~10 minutes). The filtered cells were then placed in glass

scintillation vials with 5 mL of scintillation cocktail (Beckman ReadyScint). The cellular

radioactivity was then measured by a Packard TriCarb Liquid Scintillation Counter (PerkinElmer).

Appendix C

208

For the calibration purpose, 1-5 μM 55

Fe-ligand stocks were also prepared in 5 mL scintillation

cocktail and the scintillation counts of these stocks were measured concurrently with sample

measurement. The scintillation counts of sample (disintegrations per minute) were then converted to

moles of Fe by using the scintillation counts of 55

Fe-ligand stocks. Process blanks were determined

by repeating the identical experiment except that addition of cells was omitted. Issues of fulvic acid

adsorption to the cell surface and availability of photolyzed Fe-ligand complex are also discussed in

below.

2 Analytical concerns

Concentration and reactivity of Fe that originally present in SRFA

Suwannee River Fulvic Acid (SRFA, 1S101F) is one of the most common standard humic

substance material provided by the International Humic Substance Society (IHSS). Since the

isolation and purification procedure of IHSS standard samples (IHSS) include acidification by HCl,

XAD-8 resin adsorption, elution by NaOH, most of labile metals present in the collected natural

waters are likely removed. However, it is recognized that the materials still inherently contain trace

metals to some extent (Fujii et al., 2014b). The measurement using an inductively coupled plasma

mass spectrometry (ICP-MS, Agilent Technologies 7700x) indicated that trace metal concentrations

in the SRFA stock solution are 1.5 nmol.mg-1

for Fe, 0.04 nmol.mg-1

for Cu, 0.72 nmol.mg-1

for Zn

Appendix C

209

and 0.01 nmol.mg-1

for Mn. Therefore, among the trace metals measured, the contamination of Fe is

relatively high.

In the photochemical experiment, final concentrations of externally added Fe(III) and SRFA

were adjusted to 5 μM and 50 mg.L-1

, respectively. In the 55

Fe uptake assay, 0.5 μM for externally

added Fe(III) and 10 mg.L-1

for SRFA were employed. These experimental conditions with Fe

contamination in SRFA (1.5 nmol.mg-1

) indicate that concentrations of Fe inherently present in

SRFA correspond to 75 nM and 15 nM in the photochemical and Fe uptake experiments,

respectively. These Fe concentrations account for 1.5% and 3% relative to externally added Fe(III) in

the photochemical and Fe uptake experiments, respectively. Thus, Fe inherently present in SRFA

may be relatively small compared to externally added Fe in the most photochemical and uptake

assays. Given that bioavailability of Fe by phytoplankton is typically associated with chemical

reactivity of Fe, the important issue is whether most of Fe originally present in SRFA solution is

chemically reactive or biologically available thus influencing the determination of cellular Fe uptake

rate. As noted below, however, the additional measurement of Fe(II) formation in a reducing

environment indicated that most of the Fe originally present in SRFA solution is far less chemically

reactive that the externally added Fe.

The reactivity of Fe inherently present in SRFA was previously examined in comparison with

externally added Fe, as follows (Fujii et al., 2014b). In this test, we monitored Fe(II) formation in the

100 mg.L-1

SRFA solution (pH 8) containing 1 mM FZ and 1 mM ascorbate (reducing reagent).

Appendix C

210

Under this condition, concentration of Fe inherently present in SRFA was calculated to be 150 nM

and any reactive forms of Fe are expected to be rapidly reduced to Fe(II) by ascorbate and

subsequently complexed by FZ forming FeIIFZ complex. The sample incubation and absorbance

measurement at 562 nm were undertaken in the dark and 25oC. Upon addition of FZ and ascorbate

stocks to the SRFA solution, FeIIFZ concentration increases with time and the Fe

IIFZ formation

reached to a steady-state within a few hours. The steady-state FeIIFZ concentration was determined

to be 4-6 nM, corresponding to 3-4% of total Fe in SRFA. Thus, the result indicated that reactive

pool of Fe present in SRFA solution is very small both in the photochemical experiment (0.05-

0.06%) and Fe uptake assays (0.09-0.12%). For comparison, the Fe(II) formation experiment in the

same reducing environment was also repeated by using the identical method except that Fe(III) was

externally added to the SRFA solution at concentrations of 1.0-2.5μM. In this case, therefore, the

FeIIFZ measurement was initiated by addition of FZ and ascorbate stocks into the equilibrated

FeIII

SRFA solution. As a result, the FeIIFZ measurement indicated that ~60% of externally added Fe

was converted to FeIIFZ within 2 hours. Therefore, externally added Fe was found to be far more

chemically reactive than inherently present Fe in SRFA.

The distinct difference in Fe(II) formation between original and added Fe suggest that

externally added Fe is far more chemically reactive and biologically important Fe source for uptake

by phytoplankton. Therefore, chemically reactivity and bioavailability of Fe originally present in

SRFA was considered to be negligibly small in this work. The chemically-less reactive forms of Fe

Appendix C

211

in the SRFA solution may include Fe oxides and strongly complexed Fe, which still remains after the

treatment with standard IHSS isolation procedure including acidification process by strong acid.

Effect of HEPES on the Fe complexation

Since HEPES is a popular zwitterionic buffer, this pH buffer is used in Fraquil* medium at

concentration of 1 mM. The previous study indicated that HEPES binds to copper relatively strongly

(log Kc value ranging from 7.04-7.68) (Mash et al., 2003). However, our previous study (Fujii et al.,

2014c) indicated that HEPES at concentration level of 20 mM does not significantly interfere with

the Fe complexation by 5-sulfosalicylic acid (SSA) at 8 mM for SSA (pH 8). Given that stability

constant for ferric SSA complex is cond

FeSSA,Fe(III)'K = 1.6 × 108 M

-1 at pH 8 (Fujii et al., 2014c), the

product of stability constant and SSA concentration (α coefficient) is calculated to be 1.3 × 106 in the

same condition, corresponding to the α coefficient of 6.5 × 104 at the HEPES concentration

employed in this study (i.e., 1 mM). The α coefficients for Fe-binding ligands used in this work

were calculated to be 4.0 × 105

– 6.4 × 106 for EDTA (

cond

Fe(III)L,Fe'K = 0.2-3.2 × 1011

M-1

at pH 8

depending on Me concentration) and 6.5 × 104

– 3.3 × 105 for SRFA (

cond

Fe(III)L,Fe'K = 2.5 × 1010

M-1

at

pH 8) in the photochemical and Fe uptake experiments where 20 μM EDTA and 10-50 mg.L-1

SRFA were employed. Since the α coefficients for EDTA and SRFA were calculated to be

comparable to or greater than 6.5 × 104, we considered that association of HEPES and Fe negligibly

influences to the Fe complexation by EDTA and SRFA at least under the conditions examined in this

Appendix C

212

work.

Effect of thermal redox reactions on the Fe(II) formation

In this study, the FeIIFZ3 formation experiment was also conducted in the absence of light. The

representative kinetic data are shown in Figure C5 In the dark SRFA system, concentration of

FeIIFZ3 complex increased with time, although the Fe

IIFZ3 formation rate was smaller than that

observed in the light condition by ~3-fold (e.g., 9.2 × 10-6

s-1

and 3.1 × 10-5

s-1

in the dark and light

conditions, respectively). In contrast, the dark FeIIFZ3 formation was very small (by 40-300-fold)

when EDTA was used as Fe-binding ligand (e.g., 2.0 × 10-8

s-1

in dark and 6.0 × 10-6

s-1

in light in

case of excess Mg and 1.4 × 10-7

s-1

in dark and 6.0 × 10-6

s-1

in light in case of excess Ca). The

FeIIFZ3 formation in the dark SRFA system suggest that Fe(III) bound to SRFA is continuously

reduced even in dark most likely due to the presence of redox-active moieties in fulvic acids (e.g.,

hydroquinones) as reported previously (Pullin and Cabaniss, 2003, Pham et al., 2012).

The presence of FZ may promote Fe(III) reduction rate under some conditions due to the direct

association of Fe(III)’ with FZ (Shaked et al., 2004). However, given the dark FeIIFZ3 formation is

indiscernible in the EDTA case (pFe’ = 12.0), FZ-promoted Fe(III) reduction is unlikely in our

system. Our previous study also indicated that dark FeIIFZ3 formation is negligibly slow when citrate

(a weaker model Fe-binding ligand, pFe’ = 10.1) is used for the same experiment. The absence of

dark FeIIFZ3 formation in the model ligand systems indicates that Fe(III) reduction due to the light

leakage into the sample or any constituents of the test solution (e.g., Fraquil*) are unlikely.

Appendix C

213

As noted in text (eqs. 2 and 3), the generated Fe(II)′ may subsequently form complexes with

the ligand (L) and FZ. In air-saturated and circumneutral pH waters, Fe(II)' appears to be oxidized at

appreciable rates primarily by dissolved oxygen (O2) (Sunda and Huntsman, 2003, Pham and Waite,

2008). The oxidation process potentially significantly affects the steady-state concentration of

unchelated Fe in some conditions. For example, previous study by Sunda and Huntsman (2003)

demonstrated that photo-reduction of FeIII

EDTA complex in the seawater medium causes a

substantial increase in steady-state Fe(III)' concentration due to the higher rate of Fe(III)' formation

(via FeIII

EDTA photo-reduction followed by oxidation of Fe(II)') than the thermal FeIII

EDTA

dissociation rate. In contrast, our previous studies (Fujii et al., 2011a, Fujii et al., 2014b) indicated

that, when other reactions including complexation of Fe(II)' by organic ligands outcompetes Fe(II)'

oxygenation, the effect of oxidation on the Fe(III)' concentration is expected to be minimal.

Under our experimental conditions using freshwater medium, the rates of complexation of

Fe(II)' by EDTA and FZ were calculated to be at least > ~103 folds greater than the Fe(II)'

oxygenation rate, consistent with previous studies (Fujii et al., 2011a, Fujii et al., 2014b). More

specifically, at the FZ concentration employed in this work (1 mM), the complexation reaction of

Fe(II)' by FZ occurs at a rate of kf-FZ[FZ]3 = 310 s

-1. In the photochemical experiment, free EDTA

concentrations of 20 μM were used, yielding Fe(II)' complexation rates by EDTA of kf-EDTA[EDTA]

= 142 s-1

in the absence of Me and kf-EDTA[EDTA] = 5.4-19.2 s-1

in the presence of excess Me. Thus,

the oxidation of Fe(II)' by dissolved oxygen [kox[O2] = 0.002 s-1

at pH 8.0] is slower than Fe(II)-

Appendix C

214

ligand complexation reactions at least by 2,700 fold in air-saturated solution ([O2] = ~0.24 mM at

25oC). Thus, oxidation of Fe(II)' was considered to be negligible in all cases of photochemical

experiment. In addition, sensitivity analysis below in section 5 consistently suggested that the Fe(II)'

oxidation reaction is a relatively unimportant contributor to the steady-state Fe(III)' concentration

under the conditions used in our study. The magnitude of the effect of Fe(II)' oxidation on Fe(III)'

formation may vary depending on ligand types and solution conditions.

The comparison between FeIIFZ3 and Fe

IIEDTA complexation rates suggests that Fe(II)' and

EDTA complexation occur at comparable rates to Fe(II)' and FZ complexation in the absence of Me,

while FZ complexation is likely the dominant reaction in the Fe(II)' complexation in the presence of

excess Me.

Fe(II) concentration in the equilibrated FeSRFA solution

Thermal reduction of Fe(III) occurs in the presence of SRFA. Thus, it is likely that Fe(II) is

formed to some extent in the equilibrated FeIII

SRFA even though the solution was incubated in the

dark condition, where Fe(II) concentration is maintained by the balance among thermal reduction

and oxidation. Our previous study (Fujii et al., 2014c) investigated the extent of Fe(II) formation in

the equilibrated FeSRFA solution in dark at pH 8 by examining the FeIIFZ3 formed shortly (~20

seconds) after the addition of 1 mM FZ to the equilibrated FeIII

SRFA. The final concentrations were

Appendix C

215

5 μM for Fe and 200 mg.L-1

SRFA, corresponding to an Fe:HS concentration ratio of 25 nmol.mg-1

,

which is comparable to or a little lower than the values used for this study (e.g., 50 mol.mg-1

for Fe

uptake assay and 100 mol.mg-1

for photochemical experiment). The result that FeIIFZ3 formation was

very small (accounting for 0.1% relative to total Fe) indicate that Fe(III) is the dominant oxidation

state of Fe in the equilibrated FeSRFA solution. Thus, we considered that initial Fe(II) concentration

in the photochemical and uptake experiments using FeSRFA solution (incubated for 24 h prior to the

experiments) was also negligibly small. The lower ratio of Fe(II) in the fulvic acid solution is also

consistent with previous studies by van Schaik et al. (2008) and Karlsson and Persson (2010) where

major oxidation state of Fe at circumneutral and acidic pH (3-8) was determined to be Fe(III) by the

X-ray absorption fine structure spectroscopy.

Fulvic acid adsorption to cell surface and availability of photolyzed Fe-ligand

complex in the Fe uptake experiment

Adsorption of SRFA to the cell surface may occur to some extent in the Fe uptake experiment.

Previous study (Fujii et al., 2014b) indicated that SRFA is adsorbed to Microcystis aeruginosa

PCC7806 at the rate of 1.2-4.7 × 10-11

mg.cell-1

in the Fraquil* medium containing 0.1-100 mg.L-1

SRFA and ~6 × 106 cell.mL

-1 cells. The results generally suggest that only small portion of SRFA

(0.1-1.4% of total SRFA) is adsorbed to cells in the range of SRFA concentrations comparable to this

study (e.g., 10-100 mg.L-1

SRFA). Therefore, the cellular adsorption of SRFA is unlikely to affect

Appendix C

216

SRFA concentration in the bulk medium to significant extent. Although effects of SRFA adsorption

on the cellular metabolism (thus Fe uptake, if any) remain unclear, our kinetic modeling approaches

(as presented in the previous (Fujii et al., 2014b)) are reasonably capable of accounting for a range of

Fe uptake data obtained in the SRFA system, suggesting that the SRFA adsorption may not

substantially influence on the Fe uptake.

Previous study by Barbeau et al. (2001) has indicated that the availability of photolyzed 59

Fe-

aquachelin (a suite of siderophores produced by marine bacterium Halomonas aquamarina strain

DS40M3) complex for uptake by natural phytoplankton assemblage is significantly higher than that

for the intact complex (i.e., non-photolyzed 59

Fe-acquachelin). The facilitated uptake may be due to

the formation of relatively weaker Fe complex via oxidative cleavage of the ligand at the site of β-

hydroxyasparate residue. Thus, the availability of photolyzed 55

FeEDTA complex had been

examined in our previous study (Fujii et al., 2011a) by (i) exposing the pre-equilibrated 55

FeEDTA to

the fluorescent light for upto 48 h, (ii) adding (within 5min after the pre-exposure) the photolyzed

55FeEDTA solution to the Fraquil* Microcystis cell culture at final concentrations of 200 nM for Fe

and 26 uM for EDTA and (iii) incubating the culture for 2 h in the dark. As a result, no significant

differences were observed between 55

Fe uptake rates in the assays with and without pre-exposure

treatment. In addition, 55

Fe uptake rates were substantially lower than uptake in the light by a factor

of ~100. These results suggest that (i) pre-photolyzed FeEDTA has a low availability in the dark, (ii)

Fe species only generated during the light exposure (most likely unchelated Fe(II)) is highly

Appendix C

217

available and (iii) once light is turned off, however, uptake rate decreases due to the rapid

complexation and oxidation of photo-produced Fe(II)’.

3 Formation rate of FeIIEDTA complex in the absence and presence of Me

In this study, the rate of Fe(II) complexation by EDTA was determined using the FZ

competition method (Fujii et al., 2011a) with some modifications. In this method, the concentration

of FeIIFZ3 complex was spectrophotometrically determined at a wavelength of 562 nm shortly after

addition of inorganic Fe(II) solution into Fraquil* containing EDTA, FZ and Me at various

concentrations. Ascorbate was also added as a reducing reagent. At particular concentrations of

EDTA and FZ, Fe(II) complexation by EDTA or EDTA-Me complex effectively competes with that

for FZ. Under such condition, the concentration of the FeIIFZ3 complex formed is a function of the

rate constants for the competing reactions of Fe(II) complexation, as noted below.

Methods

Test solutions were prepared by pipetting appropriate volumes of EDTA, FZ, ascorbate and Me

stocks into the Fe-, ligand- and Me-free Fraquil* to create ~2 mL of solution. While final

concentrations of FZ and ascorbate were fixed at 1 mM, final concentrations of Me and EDTA were

varied from 0 to 20 mM for Me (Ca or Mg) and from 50 to 5,000 μM for EDTA (Table S1). The test

Appendix C

218

solution was transferred to a 1 cm polystyrene cuvette and placed in the sample holder of a Cary 1E

UV–Visible spectrophotometer. The absorbance of the solution was initially zeroed. The solution in

the cuvette was then spiked with the Fe(II) stock to a final concentration of 5 μM and mixed by

manual shaking. Immediately, the concentration of FeIIFZ3 complex formed was

spectrophotometrically monitored. The time lag between the addition of Fe(II) stock (t = 0) and the

measurement of initial data was approximately 3-5 s. The pH change of the solution after addition of

the chemicals was preliminarily determined to be less than 0.1 pH units. Calibration was performed

by addition of Fe(II) stock to Fraquil* containing 1 mM FZ and ascorbate (in the absence of EDTA),

yielding a molar absorptivity of ε562 = ~27,000 M-1

cm-1

. Measurements were conducted at 25oC in

dark.

Results and Discussion

Upon addition of the inorganic Fe(II) stock into a solution containing the strong complexing

ligand FZ, Fe(II) rapidly reacts with FZ to form a purple color FeIIFZ3 complex. If the solution

additionally contains EDTA, this Fe-binding ligand effectively competes with FZ for Fe(II)

complexation. In addition, oxidation of Fe(II) is negligible in the presence of high concentration of

ascorbate. Under such condition, the system can be simply described by two competing reactions:

3

II FZFe 3FZ Fe(II)' FZf k (S1)

Fe(II)' EDTA k

fEDTA FeIIEDTA (S2)

Appendix C

219

where Fe(II)' represents dissolved inorganic Fe(II) species and kf-EDTA and kf-FZ are rate constants for

Fe(II)' complexation by EDTA and FZ, respectively.

In the previous studies, values of kf-FZ have been determined to be 3.1 × 1011

M-3

s-1

in 0.1 M

NaClO4 (Thompsen and Mottola, 1984) and 2.0 × 1011

M-3

s-1

in seawater (Lin and Kester, 1992).

The effect of solution pH on kf-FZ is insignificant in the range of pH 3 to 8. Since the ionic strength

was close, the value of 3.1 × 1011

M-3

s-1

was used in this study. Calculation of FeIIFZ3 complexation

rate using eq. S1 indicates that 99.9% of Fe(II) binds with FZ in < 0.03 s under the conditions

examined, such that the competitive complexation reactions by FZ and EDTA can be completed at

least within a few seconds after the addition of Fe(II) stock. Given that the FeIIFZ3 and Fe

IIEDTA

complexes dissociate relatively slowly with a first-order rate constants of 4.3 × 10-5

s-1

(half-life of

270 min) (Thompsen and Mottola, 1984) and 1.2 × 10-3

s-1

(half-life of 10 min) (Fujii et al., 2011a),

the dissociation of Fe(II)-ligand complexes is negligible in this timescale.

We assume a situation that the two competing Fe(II) complexation reactions are complete

while extent of dissociation of Fe(II)-ligand complexes are negligible (e.g., a time scale of 0.03s < t

< a several seconds). Under the experimental conditions examined, concentrations of Fe species are

smaller compared to ligand concentrations (e.g., by at least 10-1,200 fold), as such we can make

approximations as follows: [FZ] = [FZ]T - [FeIIFZ3] ≈ [FZ]T, [EDTA] = [EDTA]T - [Fe

IIEDTA] ≈

[EDTA]T (where subscript T indicates the total concentration). In addition, the approximation of

[Fe(II)]T ≈ [FeIIFZ3] + [Fe

IIEDTA] is also reasonable, as the total concentration of dissolved Fe(II)

Appendix C

220

inorganic species were determined to be substantially lower than that of the Fe(II)-ligand complexes

after the completion of formation reactions (based on the experimental observation). Under this

condition, a simple first order differential equation derived from eqs. S1 and S2 can be solved using

an identical procedure to that employed by Fujii et al. (Fujii et al., 2011a, Fujii et al., 2008). This

analysis generates the following relationship between kf-EDTA and the concentration of the FeIIFZ3

complex detected (see Electronic Annex in ref (Fujii et al., 2008) for a complete derivation):

kf-EDTA

k

f-FZ[FZ]

T

3

[EDTA]T

[Fe(II)]T

[FeIIFZ3]1

(S3)

The rate constants kf-EDTA were calculated by substituting the total concentrations of Fe(II), FZ

and EDTA, the value of kf-FZ, and the spectrophotometrically determined [FeIIFZ3] into eq. S3. As

can be seen in Table S1, kf-EDTA were determined to be 7.1 (± 1.0) × 106 M

-1.s

-1 for the no Me

condition, 2.7 (± 0.59) × 105 M

-1.s

-1 for the excess Ca condition (20 mM) and 4.8 (± 0.44) × 10

5 M

-

1.s

-1 for the excess Mg condition (20 mM), indicating the substantial decreases in Fe(II)-EDTA

complexation rate in the presence of excess Me (by 17-30 folds). The averaged value and standard

deviation were determined from the rate constants measured in the various EDTA concentrations

(e.g., 10-5,000 μM).

Appendix C

221

4 Detailed procedure of parameter determination

Photochemical Fe(II) generation

Time course data for [FeIIFZ3] was experimentally determined in the photochemical

experiments over a range of Me concentrations, as shown in Figure C1A, C and E. After the

conversion of [FeIIFZ3] data to ln([Fe]T/([Fe]T-[Fe

IIFZ3])), linear regression analysis was performed

for the plot of time versus ln([Fe]T/([Fe]T-[FeIIFZ3])) (Figure C1B, D and F), yielding the k

*hv values

over the range of Me concentrations used. According to the equations 9 and 10 in the text, k*hv is

described as follows:

hv Me hv,Me Me* 3

hv f-FZ 3

f-L f f-MeL f-FZ

k (1-α )+k αk k [FZ]


. (S4)

The photochemical experiments were performed in the absence of Me (i.e., αMe = 0) and in the

presence of excess Me (i.e., αMe = 1). In these two extreme cases, k*hv is written as follows:

* 3 hvhv f-FZ 3

f-L f f-FZ

kk k [FZ]

k [L ] k [FZ]

(in the absence of Me) (S5)

hv,Me* 3

hv f-FZ 3

f-MeL f-FZ

kk k [FZ]

k [MeL] k [FZ]

(in the presence of excess Me) (S6)

Since rate constants for the Fe(II)-ligand and Fe(II)-FZ formation reactions and ligand

concentrations are known, khv and khv,Me was determined by substitutions of k*hv values in the

absence of Me and in the presence of excess Me, respectively (Table 4.1).

The k*hv values for EDTA in a range of Me are shown in Figure C2A. The saturated behavior

Appendix C

222

of FeIIFZ3 formation rate constant (k

*hv) in the higher Me (e.g., log [Me] > -4) is consistent with the

assumption that Fe(III)-EDTA complex is saturated with the ternary complex (FeIII

EDTA-Me) in the

presence of excess Me (αMe =1). Under the saturated condition, the Fe(III) ternary complex is

considered to be a primary precursor of photochemically-generated Fe(II)'.

As noted in the text, the fraction of the ternary complex (FeIII

L-Me) relative to total Fe(III)

bound to ligand (αMe) may be written as follows:

FeL-MeMe

FeL-Me

K [Me]α =

1+K [Me]. (S7)

Substitution of αMe to eq. S4 yields the following relationship:

FeL-Me FeL-Mehv hv,Me

* 3 FeL-Me FeL-Mehv f-FZ 3

f-L f f-MeL f-FZ

K [Me] K [Me]k (1- )+k

1+K [Me] 1+K [Me]k k [FZ]


. (S8)

Concentrations of MeL, Lf and Me were independently determined by using eqs 6-8 with

assumption of the pseudo-equilibrium (side) reaction between L and Me. Therefore, KFeL-Me was

determined by fitting the equation to all k*hv values determined in the range of Me concentrations

shown in Figure C2A.

Cellular uptake

Five parameters (KS,X, KS,MeX, max

S,Xρ , max

S,MeXρ and KMeX) were considered to be fitting parameters.

Appendix C

223

The first two parameters (i.e., KS,X and KS,MeX) were experimentally determined from a non-linear fit

of the Michaelis-Menten equation to the 55

Fe uptake data measured over a range of Fe(II)′

concentrations (Figure C3A). In the non-linear fit, the steady-state concentration of Fe(II)′ was

calculated by eq. 9 but without the FZ complexation term (because FZ addition was omitted in the

55Fe uptake experiments), as follows:

hv Me hv,Me Me

SS T

f-L f f-MeL

k (1-α )+k α[Fe(II)'] = [Fe]

k [L ] k [MeL]. (S9)

Note that detail analysis of unchelated Fe concentration was provided in Section 5. By fitting

eq. 14 to the 55

Fe uptake in the absence of Me (βMe = 0), the half-saturation constant (KS,X) was

determined to be 1.0 × 10-14

M. Fitting to the data in the presence of excess Ca ([Ca]=200 μM, βMe =

1) yielded a higher half-saturation constant (KS,MeX) of 4.1 × 10-13

M. The maximum Fe uptake rates

(max

S,Xρ and max

S,MeXρ in eq. 15) were also determined from the 55

Fe uptake data in the SRFA system

where Fe uptake rate is saturated. The 55

Fe uptake rates in the absence of Me (βMe=0) and presence

of excess Me (20 mM, βMe=1) were assumed to be equal to max

S,Xρ and max

S,MeXρ , respectively (Figure

4.3B).

The affinity of the membrane-located transporter to Me (KMeX) was determined by fitting eq.

15 to the 55

Fe uptake data (in the SRFA system) for all Me concentrations in Figure 4.3B. To this

end, the βMe value was calculated by using the equation βMe = KMeX[Me]/(1+ KMeX[Me])). The Me

concentration was calculated from the pseudo-equilibrium between L and Me using eqs 6-8.

Appendix C

224

Model fitting

The best fit of the model to the experimentally determined data was performed by a least-

squares method using Microsoft excel. In the method, the mean square error between the modelled

value and average of experimental data was minimized. Some Fe uptake parameters were determined

from best-fit of model to the 55

Fe uptake data (e.g., Figure 4.3A) via non-linear regression using

software R.

5 Fe concentrations in the 55Fe uptake assay

Selection of important reactions via sensitivity analysis

The compete version of kinetic models that include all possible reactions associated with Fe

transformation in the EDTA and SRFA systems were shown in Table C2and Table C3, respectively.

In this model, for example, Fe(II) oxidants other than dissolved oxygen including reactive oxygen

species were considered. In addition, this full model considers not only Fe(II) transformation

kinetics, but also reduction of Fe(III) and complexation and dissociation of Fe(III) and Fe-binding

ligand complex (with assumption of the single ligand class for the binding site). The photo-oxidation

may convert dissolved organic matters into lower molecular weight compounds with different Fe

complexation capacities, as such the photo-oxidation of organic ligand may be an important

Appendix C

225

determinant in photochemical transformation of Fe under some conditions (Shiller et al., 2006).

However, transformation of Fe (e.g., dissociation of unchelated Fe) by the organic ligand photo-

oxidation was not considered in this model as reactions involved in the organic ligand photolysis

system under the conditions examined in this work are not well defined. At least for the EDTA case,

photo-oxidation of EDTA and its complex with Fe(III) is unlikely to facilitate the cellular Fe uptake

due to the lower availability of photolyzed FeEDTA complex (as discussed in section 2). The

formation of organic and inorganic radicals associated with the photo-oxidation of Fe-binding

ligands was also not considered.

Although reactions associated with photo-oxidation of Fe-binding ligands were not considered

here, the complete model still consists of a number of reactions. Therefore, the particular reactions

that significantly influence the concentrations of substrates available for uptake (i.e., unchelated Fe

concentration) were identified by the sensitivity analysis using the method identical to that employed

in the previous work.(Fujii et al., 2014b) Briefly, normalized sensitivity coefficients (NSCs) were

used to examine the important reactions in the comprehensive reaction model presented in Table C2

for EDTA and Table C3 for SRFA. NSCs are defined by following equation:

[ ]

ln[ ][ ]

ln k

k

Species

SpeciesSpeciesNSC

k k

k

. (S10)

where [Species] indicates concentration of chemical species and k is an associated reaction

constant. By Kintecus simulation software V4.55 (Ianni, 2002), NSC matrices (S1, S2, S3, …., Sn)

Appendix C

226

were calculated at various evenly spaced simulation times under the conditions used in 55

Fe uptake

assays (e.g., concentrations of 20 μM for EDTA, 10 mg.L-1

for SRFA and 500 nM for initial FeIII

L

under light conditions). The time-averaged NSC matrix for 2 hr, which corresponds to the incubation

period of assays, was then calculated. The models for this analysis using Kintecus were presented in

Table C4 (EDTA system) and Table C5 (SRFA system).

The results from sensitivity analysis are shown in Table C6 (EDTA system) and Table C7

(SRFA system). In the EDTA system, reaction 1 (i.e., photochemical Fe(II)' formation from

FeIII

EDTA complex) and reaction 8 (Fe(II)' complexation by EDTA) were determined to

substantially influence Fe(II)' concentration in the both absence and presence of excess Me. The

logarithmic values of squared NSC for these reactions were highest and ranged from -0.029 to 0.002

(Table C6). Although the squared NSC values for some other competing reactions (e.g., reactions 3,

5, 9 and 14) were also relatively high, the values were generally at least a few orders of magnitude

smaller than those for reactions 1 and 8. Therefore, it is reasonable to consider only reactions 1 and 8

in the calculation of Fe(II)' concentration in the EDTA system.

In the SRFA system, similarly, reactions 1 (photochemical reduction of FeIII

SRFA forming

Fe(II)') and 8 (Fe(II)' complexation by SRFA) were found to be two important reactions in the

determination of Fe(II)' concentration. The squared NSC values for these reactions were more than a

few orders of magnitude greater than those for other reactions in both the light and dark conditions

(values ranged from -0.13 to -0.0022, Table C7). Therefore, Reaction 1 and 8 were selected to be the

Appendix C

227

important reactions for the calculation of steady-state Fe(II)' concentrations in the SRFA system.

Calculation of unchelated Fe concentrations

The sensitivity analysis indicated that steady-state Fe(II)' concentrations ([Fe(II)']SS) in the Fe

uptake experiment (for EDTA and SRFA systems and the presence and absence of Me) can be

determined approximately by the balance of light mediated-reduction of FeIII

L (including thermal

reduction in case of SRFA) and complexation of photo-generated Fe(II)' by L, as described in eq. S

9. In this study, therefore, the steady-state concentration of Fe(II)' was determined by using eq. S9 in

the range of conditions employed in the Fe uptake assay. Again, the sensitivity analysis indicated

that the effect of Fe(II)' oxidation on unchelated Fe(III)' concentrations is unimportant in our system.

Our previous study (Fujii et al., 2014b) consistently indicated that Fe(II)' oxidation (followed by

reductive dissociation of FeIII

SRFA) becomes important reaction in the Fe(III)' formation only when

lower concentration of SRFA is used (e.g., 1 mg.L-1

) where complexation of Fe(II)' by SRFA is

relatively slow.

Appendix C

228

Table C1 Determination of Fe(II)-EDTA formation rate constant in the absence and presence of excess Me.

sample [Ca]T [Mg]T [EDTA]T [Fe(II)]T [FZ]T abs@ [FeIIFZ3] kf-EDTA log kf-EDTA kf-EDTA kf-EDTA

# mM mM μM μM mM 562 μM M-1

.s-1

M-1

.s-1

average SD

1 0 0 0 5 1 0.137

2 0 0 0 5 1 0.140

3 0 0 50 5 1 0.061 2.18 8.0.E+06 6.90 7.1.E+06 9.9.E+05

4 0 0 50 5 1 0.061 2.18 8.0.E+06 6.90

5 0 0 100 5 1 0.042 1.51 7.2.E+06 6.86

6 0 0 200 5 1 0.025 0.91 6.9.E+06 6.84

7 0 0 200 5 1 0.030 1.09 5.6.E+06 6.75

8 20 0 100 5 1 0.132 4.77 1.5.E+05 5.17 2.7.E+05 5.9.E+04

9 20 0 100 5 1 0.126 4.56 3.0.E+05 5.48

10 20 0 500 5 1 0.103 3.70 2.2.E+05 5.34

11 20 0 500 5 1 0.104 3.75 2.1.E+05 5.32

12 20 0 1000 5 1 0.073 2.62 2.8.E+05 5.45

13 20 0 1000 5 1 0.068 2.46 3.2.E+05 5.51

14 20 0 2500 5 1 0.042 1.52 2.8.E+05 5.45

15 20 0 2500 5 1 0.038 1.36 3.3.E+05 5.52

16 20 0 5000 5 1 0.024 0.87 2.9.E+05 5.47

17 0 20 5000 5 1 0.023 0.83 3.1.E+05 5.50

18 0 20 100 5 1 0.120 4.33 4.8.E+05 5.68 4.8.E+05 4.4.E+04

19 0 20 250 5 1 0.103 3.71 4.3.E+05 5.63

20 0 20 250 5 1 0.098 3.53 5.2.E+05 5.71

Appendix C

229

Table C2 Kinetic model and rate constants in EDTA systema.

No Reaction Rate constant Reference

no Me excess Me

Rate constants for organically complexed Fe

1 FeIIIL + hv

→ Fe(II)' + L

1.6 × 10

-7 b 5.9 × 10

-6 b s

-1 This study

2 FeIIIL + O2

•- →Fe

IIL + O2

1.3 × 10

5 M

-1 s

-1

(Rose and Waite, 2005)

3 FeIIL + O2 →Fe

IIIL + O2

•-

31

c M

-1 s

-1

(Fujii et al., 2010a)

4 FeIIL + O2

•- →Fe

IIIL + H2O2 1.2 × 10

6 d M

-1 s

-1

(Fujii et al., 2010b)

5 FeIIL + H2O2 →Fe

IIIL + OH

- 3.2 × 10

5 d M

-1 s

-1

(Miller et al., 2009)

6 Fe(III)' + L →FeIIIL

3.2 × 10

6 e 1.7 × 10

5 e M

-1 s

-1

(Fujii et al., 2008)

7 FeIIIL→ Fe(III)' + L

1.0 × 10

-5 s

-1


8 Fe(II)' + L →FeIIL 7.1 × 10

6 e 2.7 × 10

5 e M

-1 s

-1 This study

9 FeIIL→ Fe(II)' + L 2 × 10

-4 s

-1

(Garg et al., 2007)

Rate constants for unchelated Fe

10 Fe(III)' + O2•-

→Fe(II)' + O2 1.5 × 108 M

-1 s

-1

(Rush and Bielski, 1985)

11 Fe(II)' + O2 →Fe(III)' + O2•- 8.8

c M

-1 s

-1

(Pham and Waite, 2008)

12 Fe(II)' + O2•- →Fe(III)' + H2O2 1.0 × 10

7 M

-1 s

-1


13 Fe(II)' + H2O2 →Fe(III)' + OH• 5.0 × 10

4 M

-1 s

-1

(Millero and Sotolongo, 1989)

14 Fe(II)' + OH• → Fe(III)' + OH

- 5.0 × 10

8 M

-1 s

-1

(Zuo and Hoigne, 1992)

Rate constants for superoxide

15 O2•-

+ O2

•-→ H2O2 + O2 5.0 × 10

4 M

-1 s

-1

(Bielski et al., 1985)

16 Microcystis cells → O2•-

1.2 × 10-18

mol cell-1

h-1


Appendix C

230

a Boldface reactions represent important reactions that directly affect calculation of steady-state substrate

concentrations, as determined by sensitivity analysis.

b Photoreduction rate constant determined in the absence and presence of Me.

c Dissolved oxygen concentration in air-saturated water at 27oC (~0.24 mM) was used in model calculations.

d The rate constants for SRFA were used as those for EDTA are unknown.

e Complexation reactions for FeIIIEDTA and FeIIEDTA complexes were considered to be influenced by Me.

Appendix C

231

Table C3 Kinetic model and rate constants in SRFA systema

No Reaction Rate constant Reference

Rate constants for organically complexed Fe

1 FeIIIL + hv

→ Fe(II)' + L

9.2 × 10-6 b

3.1 × 10-5 b

s-1

This study

2 FeIIIL + O2

•- →Fe

IIL + O2

2.8 × 10

5 M

-1 s

-1


3 FeIIL + O2 →Fe

IIIL + O2

•-

1.5 × 10

2 d M

-1 s

-1


4 FeIIL + O2

•- →Fe

IIIL + H2O2 1.2 × 10

6 M

-1 s

-1

(Fujii et al., 2010b)

5 FeIIL + H2O2 →Fe

IIIL + OH

- 3.2 × 10

5 M

-1 s

-1


6 Fe(III)' + L →FeIIIL

7.9 × 10

6 M

-1 s

-1

(Bligh and Waite, 2010)

7 FeIIIL→ Fe(III)' + L

3.2 × 10

-4 s

-1


8 Fe(II)' + L →FeIIL 4.5 × 10

4 M

-1 s

-1


9 FeIIL→ Fe(II)' + L 7.9 × 10

-4 s

-1


Rate constants for unchelated Fe

10 Fe(III)' + O2•-

→Fe(II)' + O2 1.5 × 108 M

-1 s

-1


11 Fe(II)' + O2 →Fe(III)' + O2•- 8.8

c M

-1 s

-1

(Pham and Waite, 2008)

12 Fe(II)' + O2•- →Fe(III)' + H2O2 1.0 × 10

7 M

-1 s

-1


13 Fe(II)' + H2O2 →Fe(III)' + OH• 5.0 × 10

4 M

-1 s

-1

(Millero and Sotolongo, 1989)

14 Fe(II)' + OH• → Fe(III)' + OH

- 5.0 × 10

8 M

-1 s

-1

(Zuo and Hoigne, 1992)

Rate constants for superoxide

15 O2•-

+ O2

•-→ H2O2 + O2 5.0 × 10

4 M

-1 s

-1

(Bielski et al., 1985)

16 Microcystis cells → O2•-

1.2 × 10-18

mol cell-1

h-1


17 O2•-

+ B →O2 + B

- (3.3 × 10

-2) /[BT]

d M

-1 s

-1

(Garg et al., 2011)

Appendix C

232

a Boldface reactions represent important reactions that directly affect calculation of steady-state substrate

concentrations, as determined by sensitivity analysis. Fe binding capacity (CFe) of 260 μmol.g-1 (Rose and

Waite, 2003) was used for SRFA in the calculation of steady-state unchelated Fe concentration.

b Thermal and photo-reduction rate constants determined in the absence and presence of fluorescent light,

respectively.

c Dissolved oxygen concentration in air-saturated water at 27oC (~0.24 mM) was used in model calculations.

d B is a redox-active organic moiety which results in oxidation of superoxide. Total concentration for B ([BT])

was assumed to be 20 nmol.(mg-SRFA)-1.(Garg et al., 2011)

Appendix C

233

Table C4 Comprehensive set of chemical reactions and rate constants (EDTA system) used for

sensitivity analysis by Kintecus.a

Reaction number

Chemical equations for Kintecus Rate constants b

no Me excess Me

Reaction 1 Fe(III)L +hv ==> Fe(II) + L (fluorescent light) 1.6.E-07 5.9.E-06

Reaction 2 Fe(III)L + O2- ==> Fe(II)L + O2 1.3.E+05

Reaction 3 Fe(II)L + O2 ==> Fe(III)L + O2- 3.1.E+01

Reaction 4 Fe(II)L + O2- ==> Fe(III)L + H2O2 1.2.E+06

Reaction 5 Fe(II)L + H2O2 ==> Fe(III)L + OH 3.2.E+05

Reaction 6 Fe(III) + L ==> Fe(III)L 3.2.E+06 1.7.E+05

Reaction 7 Fe(III)L ==> Fe(III) + L 1.0.E-05

Reaction 8 Fe(II) + L ==> Fe(II)L 7.1.E+06 2.7.E+05

Reaction 9 Fe(II)L ==> Fe(II) + L 1.5.E+08

Reaction 10 Fe(III) + O2- ==> Fe(II) + O2 8.8.E+00

Reaction 11 Fe(II) + O2 ==> Fe(III) + O2- 1.0.E+07

Reaction 12 Fe(II) + O2- ==> Fe(III) + H2O2 5.0.E+04

Reaction 13 Fe(II) + H2O2 ==> Fe(III) + OH 5.0.E+08

Reaction 14 Fe(II) + OH ==> Fe(III) 5.0.E+04

Reaction 15 O2- + O2

- ==> H2O2 + O2 1.0.E-12

Reaction 16 Cell ==> O2- 1.7.E+06

a In reaction 16, superoxide production by cell was assumed to be invariant during the period of simulation.

b Apparent rate constants include zero-, first- and second-order constants depending on the reactions.

Appendix C

234

Table C5 Comprehensive set of chemical reactions and rate constants (SRFA system) used for

sensitivity analysis by Kintecus.a

Reaction number

Chemical equations for Kintecus Rate constants b

Reaction 1

Fe(III)L ==> Fe(II) + L (dark)

Fe(III)L + hv ==> Fe(II) + L (fluorescent light)

9.2.E-06

3.1.E-05

Reaction 2 Fe(III)L + O2- ==> Fe(II)L + O2 2.8.E+05

Reaction 3 Fe(II)L + O2 ==> Fe(III)L + O2- 1.5.E+02

Reaction 4 Fe(II)L + O2- ==> Fe(III)L + H2O2 1.2.E+06

Reaction 5 Fe(II)L + H2O2 ==> Fe(III)L + OH 3.2.E+05

Reaction 6 Fe(III) + L ==> Fe(III)L 7.9.E+06

Reaction 7 Fe(III)L ==> Fe(III) + L 3.2.E-04

Reaction 8 Fe(II) + L ==> Fe(II)L 4.5.E+04

Reaction 9 Fe(II)L ==> Fe(II) + L 7.9.E-04

Reaction 10 Fe(III) + O2- ==> Fe(II) + O2 1.5.E+08

Reaction 11 Fe(II) + O2 ==> Fe(III) + O2- 8.8.E+00

Reaction 12 Fe(II) + O2- ==> Fe(III) + H2O2 1.0.E+07

Reaction 13 Fe(II) + H2O2 ==> Fe(III) + OH 5.0.E+04

Reaction 14 Fe(II) + OH ==> Fe(III) 5.0.E+08

Reaction 15 O2- + O2

- ==> H2O2 + O2 5.0.E+04

Reaction 16 Cell ==> O2- 1.0.E-12

Reaction 17 O2- + B ==> O2 1.7.E+06

a In reactions 16 and 17, reactants other than iron and superoxide (i.e., cell and B) were assumed to be

invariant during the period of simulation.

b Apparent rate constants include zero-, first- and second-order constants depending on the reactions.

Appendix C

235

Table C6 Logarithm of squared NSC for Fe(II) and Fe(III) species under the condition of Fe uptake

assay using EDTA ([EDTA] = 20 μM and [FeIIIL] = 500 nM).

a,b

Fluorescent light condition

Reaction [EDTA] = 20 μM (no Me)

[EDTA] = 20 μM (excess Me)

number Fe(III)' Fe(II)' Fe(III)' Fe(II)'

Reaction1 -9.5 -0.0002 -2.8 -0.029

Reaction2 -13.7 -7.5 -10.3 -9.9

Reaction3 -9.5 -3.3 -4.0 -3.7

Reaction4 -21.1 -15.0 -13.4 -12.7

Reaction5 -13.1 -7.3 -3.9 -3.4

Reaction6 0.0022 -11.8 -0.0076 -12.2

Reaction7 0.000 -11.8 -0.010 -12.1

Reaction8 -12.7 0.0021 -4.0 -0.011

Reaction9 -16.0 -3.3 -7.4 -3.3

Reaction10 -15.3 -11.7 -11.8 -11.3

Reaction11 -13.2 -9.6 -7.2 -6.8

Reaction12 -21.9 -18.3 -14.9 -14.4

Reaction13 -17.7 -14.1 -9.8 -9.3

Reaction14 -14.0 -10.4 -4.1 -3.5

Reaction15 -13.9 -10.3 -8.0 -7.5

Reaction16 -26.9 -26.5 -24.0 -23.5

a Reaction numbers correspond to those listed in Table S4. The sensitivity analysis was performed for the

absence and presence of 20 mM Me under following concentrations: 500 nM for initial FeIIIL, 20 μM for

EDTA, 0.24 mM for dissolved oxygen, 2 × 109 cell.L-1 for cellular density. Initial concentrations for chemical

species other than those described here were assumed to be zero.

b Reactions with bold-faced numbers were considered in the calculation of steady-state concentration of

unchelated Fe.

Appendix C

236

Table C7 Logarithm of squared NSC for Fe(II) and Fe(III) species under the condition of Fe uptake

assay using SRFA ([SRFA] = 10 mg.L-1

and [FeIIIL] = 500 nM).

a,b

Fluorescent light

Reaction [SRFA] = 10 mg/L (dark)

[SRFA] = 10 mg/L (light)

number Fe(III)' Fe(II)' Fe(III)' Fe(II)'

Reaction1 -4.9 -0.022 -3.4 -0.061

Reaction2 -12.5 -9.5 -11.0 -8.9

Reaction3 -6.8 -3.9 -5.0 -2.9

Reaction4 -17.7 -14.3 -16.0 -13.7

Reaction5 -6.6 -3.4 -4.9 -2.7

Reaction6 0.0022 -10.2 0.0022 -10.0

Reaction7 -0.003 -10.2 -0.013 -10.0

Reaction8 -5.3 -0.13 -4.3 -0.13

Reaction9 -8.7 -3.6 -7.8 -3.6

Reaction10 -13.2 -10.0 -12.5 -10.3

Reaction11 -6.7 -3.6 -5.8 -3.6

Reaction12 -14.2 -11.0 -12.4 -10.3

Reaction13 -8.4 -5.2 -6.4 -4.2

Reaction14 -10.0 -6.8 -9.2 -7.0

Reaction15 -5.5 -2.3 -4.6 -2.4

Reaction16 -26.7 -23.5 -23.3 -20.5

Reaction17 -7.4 -4.2 -6.5 -4.3

a Reaction numbers correspond to those listed in Table S5. The sensitivity analysis for the dark condition (in

the absence of Me) was performed under following concentrations: 500 nM for initial FeIIIL, 10 mg.L-1 for

SRFA, 0.24 mM for dissolved oxygen, 2 × 109 cell.L-1 for cellular density, 20 nmol.(mg-SRFA)-1 for B. Initial

concentrations for chemical species other than those described here were assumed to be zero.

b Reactions with bold-faced numbers were considered in the calculation of steady-state concentration of

unchelated Fe.

Appendix C

237

Table C8 Definitions of parameters used in this study.

Symbol Description

Symbols and abbreviations of chemical species

L Metal-binding ligands (EDTA and SRFA)

Lf Free ligand that is not bound to Fe, Me and other trace metals present in Fraquil*

medium

L* Sum of free ligand (Lf) and ligand bound to Me (MeL) (or ligand that is not bound to Fe

and other trace metals present in Fraquil*)

Lox Photochemically oxidized ligand

FZ Ferrozine

FeIIIL Organically complexed Fe(III)

FeIIL Organically complexed Fe(II)

Fe(III)' Dissolved inorganic Fe(III) species (e.g., Fe(OH)2+, Fe(OH)3

0, and Fe(OH)4

−)

Fe(II)' Dissolved inorganic Fe(II) species (e.g., Fe(OH)+, Fe

2+)

FeIIFZ3 Ferrous iron and ferrozine complex

Me Free form of divalent cations (e.f., Ca2+

and Mg2+

)

MeL Ligand and Me complex

MeLox Me complex with photochemically oxidized L that can be produced via FeIIIL-Me photo-

reduction

FeIIIL-Me Ternary complex between Fe

IIIL and Me that is formed by the adjunctive association of

Me to FeIIIL

FeIIIL

* Sum of Fe

IIIL and Fe

IIIL-Me

[Fe(II)']SS Steady-state concentration of Fe(II)'

[Fe]T Total concentration of Fe in the system (e.g., [Fe]T = [FeIIIL] + [Fe

IIFZ3] + [Fe

IIL] +

[Fe(II)'] + [Fe(III)'] ≈ [FeIIIL] + [Fe

IIFZ3]). Concentrations for organically complex Fe(II),

Fe(II)' and Fe(III)' were considered to be negligibly small due to the rapid complexation by ligands and oxidation by oxygen for these Fe(II) species as well as lower solubility of Fe(III)'

[FZ]T Total concentration of FZ in the system

Kinetic and thermodynamic constants

kf-L Rate constant for Fe(II)' complexation by L (M-1

.s-1

)

kf-FZ Rate constant for Fe(II)' complexation by FZ (M-1

.s-1

)

kf-MeL Rate constant for compelxation between MeL and Fe(II)'

khv Rate constant for photo-reductive dissociation of FeIIIL generating Fe(II)' (s

-1). The

reaction is assumed to be pseudo-first-order under constant illumination.

khv,Me Rate constant for photo-reductive dissociation of FeIIIL-Me generating Fe(II)' (s

-1).

k*hv Pseudo-first order rate constant for Fe

IIFZ3 formation (s

-1)

KMeL Conditional stability constant for Me and L complexation (M-1

)

KFeL-Me Conditional stability constant for the ternary complex formation between FeIIIL and Me

(M-1

)

αMe Parameter as a function of [Me]

Appendix C

238

Parameters for cellular Fe uptake

S Biologically available portion of Fe in the extracellular environment ([Fe(II)'] in our system)

X Plasma-membrane Fe transporters

MeX Fe transporter and Me complex

KS Half saturation constant under the conditions examined

KS,X Half-saturation constants for X (i.e., in the absence of Me)

KS,MeX Half-saturation constants for MeX (i.e., in the presence of excess Me)

max

Sρ Maximum uptake rate under the conditions examined (max

Sρ is equal to kup[X]T)

max

S,Xρ Rates of maximum Fe uptake in the absence of Me (max

S,Xρ =kup,X[X])

max

S,MeXρ Rates of maximum Fe uptake in the presence of excess Me (max

S,MeXρ = kup,MeX[MeX])

kup First-order rate constant for Fe transport

kup,X First-order rate constants for Fe uptake in the absence of Me,

kup,MeX First-order rate constants for Fe uptake in the presence of excess Me

[X]T Total concentration of transporter which is a sum of X and MeX concentrations (i.e., [X]T = [X] + [MeX])

KMeX Conditional stability constant for complexation between X and Me

βMe Fraction of MeX relative to total transporter (βMe = KMeX[Me]/(1+ KMeX[Me]), Me0 β 1 )

Appendix C

239

Figure C1 Representative time course data of FeIIFZ3 formation in the photochemical experiment in the presence and absence of Me.

Primary kinetic data for FeIIFZ3 formation measured in (A) EDTA+Ca, (C) EDTA+Mg and (E) SRFA+Ca or SRFA+Mg systems. All the data were

collected in the presence of light treatment. Final concentrations in the EDTA system were 20 μM for Fe, 40 μM for EDTA and 1 mM for FZ. In the

SRFA system, concentrations were adjusted to 5 μM for Fe, 10 mg.L-1

for SRFA and 1 mM for FZ. Time course values of ln([Fe]T/([Fe]T-[FeIIFZ3])) for

(B) EDTA+Ca, (D) EDTA+Mg and (F) SRFA+Ca or SRFA+Mg systems were also shown.

R² = 0.9992

R² = 0.9037

0

5

10

15

20

25

0 2 4 6 8 10

B.

ln (

[Fe

] T/(

[Fe

] T-[

FeIIFZ

3])

-0.5

0

0.5

1

1.5

2

2.5

3

3.5

4

0 2 4 6 8 10

[Ca] = 200 μM

[Ca] = 10 μM

[Ca] = 0 μM

A.

-0.5

0

0.5

1

1.5

2

2.5

3

3.5

4

0 2 4 6 8 10

[Mg] = 200 μM

[Mg] = 10 μM

[Mg] = 0 μM

C.

R² = 0.9913

0

5

10

15

20

25

0 2 4 6 8 10

D.

-0.5

0

0.5

1

1.5

2

2.5

3

3.5

4

0 1 2 3 4 5

no Me

20 mM Ca

20 mM Mg

E.

R² = 0.8592

R² = 0.9195

R² = 0.8997

0

20

40

60

80

100

120

0 1 2 3 4 5

F.

Fe(I

I)-F

Z co

mp

lex

con

cen

trat

ion

(μM

)

Time (hr)

Appendix C

240

Figure C2 Equilibrium calculation of ligand and Me species in the systems of (A) EDTA/Ca, (B) EDTA/Mg, (C) Fe-EDTA/Ca (ternary complex),

(D) Fe-EDTA/Mg (ternary complex), (E) SRFA/Ca and (F) SRFA/Mg.

-12

-11

-10

-9

-8

-7

-6

-5

-4

-3

-2

-7 -6 -5 -4 -3 -2 -1

Loga

rith

m o

f co

nce

ntr

atio

n (

M)

Logarithm of total Ca concentration (M)

CaL

L'

Free Ca

(E) SRFA/Ca

-0.6

-9

-8

-7

-6

-5

-4

-3

-2

-7 -6 -5 -4 -3 -2 -1

Loga

rith

m o

f co

nce

ntr

atio

n (

M)

Logarithm of total Mg concentration (M)

MgL

L'

Free Mg

(F) SRFA/Mg

-1.2

-12

-11

-10

-9

-8

-7

-6

-5

-4

-3

-2

-7 -6 -5 -4 -3 -2

Loga

rith

m o

f co

nce

ntr

atio

n (

M)


CaL

L'

Free Ca

-5.0

(A) EDTA/Ca

-9

-8

-7

-6

-5

-4

-3

-2

-7 -6 -5 -4 -3 -2

Loga

rith

m o

f co

nce

ntr

atio

n (

M)


MgL

L'

Free Mg

-5.0

(B) EDTA/Mg

-12

-11

-10

-9

-8

-7

-6

-5

-4

-3

-2

-7 -6 -5 -4 -3 -2

Loga

rith

m o

f co

nce

ntr

atio

n (

M)


FeL-Ca

FeL

Free Ca

-4.5

(C) Fe-EDTA/Ca

-9

-8

-7

-6

-5

-4

-3

-2

-7 -6 -5 -4 -3 -2

Loga

rith

m o

f co

nce

ntr

atio

n (

M)


FeL-Mg

FeL

Free Mg-4.3

(D) Fe-EDTA/Mg

Appendix C

241

Figure C3 Effect of Me on the (A) Fe(II)-EDTA formation rate constant (kf-L and kf-MeL in eqs. 2 and

4) and (B) photochemical Fe(II)' formation rate in the EDTA system (khv and khv,Me in eqs. 1 and 5).

Symbols and error bars represent average value and standard deviation from triplicate experiments.

However, error range shown in the panel B was not provided as the values were calculated from the

products of averaged data (eq. 9).

5.0

5.5

6.0

6.5

7.0

7.5

8.0


Lo

gari

thm

of

Fe(I

I)-E

DT

A

form

ati

on

ra

te c

on

sta

nt

(M-1

.s-1

)

A

-7.5

-7

-6.5

-6

-5.5

-5

-4.5


Lo

gari

thm

of

ph

oto

ch

em

ical

red

uc

tio

n r

ate

co

nsta

nt

(s-1

)

B

Appendix C

242

Figure C4 55

Fe uptake rate in a range of Me concentration. 55

Fe uptake rates were measured in

SRFA-buffered Fraquil* in the absence and presence of Me (Ca: black-colored bars, Mg: grey-colored

bars). Total concentrations were adjusted to 0.5 μM for 55

Fe, 10 mg.L-1

for SRFA, 0-20 mM for Me and

~2 × 106 cell.mL

-1 for Microcystis cells. Averaged data with standard deviation from triplicate runs were

shown.

0

100

200

300

400

500

600

700

800

900

1000

No Me 0.02 mM 0.2 mM 20 mM

55Fe

up

take

rat

e (

zmo

l/ce

ll/h

)

Me concentration

+Ca

+Mg

B

0

20

40

60

80

100

120

140

160

180

No Me 0.02 mM 0.2mM 2mM 20mM

55Fe

up

take

rat

e (

zmo

l/ce

ll/h

)

Me concentration

+Ca

+MgA

Appendix C

243

Figure C5 Representative time course data of FeIIFZ3 formation in the photochemical experiment in the presence (triangle) and absence

(cross) of light treatment. Primary kinetic data for FeIIFZ3 formation measured in (A) EDTA+Ca, (C) EDTA+Mg and (E) SRFA+Ca or SRFA+Mg

systems. Final concentrations in the EDTA system were 20 μM for Fe, 40 μM for EDTA, 200 μM for Me and 1 mM for FZ. In the SRFA system,

concentrations were adjusted to 5 μM for Fe, 10 mg.L-1

for SRFA and 1 mM for FZ. Time course values of ln([Fe]T/([Fe]T-[FeIIFZ3])) for (B) EDTA+Ca,

(D) EDTA+Mg and (F) SRFA+Ca or SRFA+Mg systems were also shown.

R² = 0.9992

0

5

10

15

20

25

0 2 4 6 8 10

B.

ln (

[Fe

] T/(

[Fe

] T-[

FeIIFZ

3])

-0.5

0

0.5

1

1.5

2

2.5

3

3.5

4

0 2 4 6 8 10

[Ca] = 200 μM (light)

[Ca] = 200 μM (dark)

A.

-0.5

0

0.5

1

1.5

2

2.5

3

3.5

4

0 2 4 6 8 10

[Mg] = 200 μM (light)

[Mg] = 200 μM (dark)

C.

R² = 0.9913

0

5

10

15

20

25

0 2 4 6 8 10

D.

-0.5

0

0.5

1

1.5

2

2.5

3

3.5

4

0 1 2 3 4 5

no Me (light)

no Me (dark)

E.

R² = 0.8592

R² = 0.9068

0

20

40

60

80

100

120

0 1 2 3 4 5

no Me (light)

no Me (dark)F.

Fe(I

I)-F

Z co

mp

lex

con

cen

trat

ion

(μM

)

Time (hr)

Appendix C

244

Effecs of iron on nitrogen-fixing and non-fixing cyanobacteria

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