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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‘I hereby grant the University of New South Wales or its agents the right to archive and to make available my thesis or dissertation in whole or part in the University libraries in all forms of media, now or here after known, subject to the provisions of the Copyright Act 1968. I retain all proprietary rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertation. I also authorise University Microfilms to use the 350 word abstract of my thesis in Dissertation Abstract International (this is applicable to doctoral theses only). I have either used no substantial portions of copyright material in my thesis or I have obtained permission to use copyright material; where permission has not been granted I have applied/will apply for a partial restriction of the digital copy of my thesis or dissertation.'
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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
Abbreviations and symbols
[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
Abbreviations and symbols
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
Chapter 1: Introduction
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
Chapter 1: Introduction
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
Chapter 1: Introduction
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,
Chapter 1: Introduction
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
Chapter 1: Introduction
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
Chapter 1: Introduction
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
Chapter 1: Introduction
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-
Chapter 1: Introduction
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
Chapter 1: Introduction
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,
Chapter 1: Introduction
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).
Chapter 1: Introduction
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).
Chapter 1: Introduction
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
Chapter 1: Introduction
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
Chapter 1: Introduction
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
Chapter 1: Introduction
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
Chapter 1: Introduction
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
Chapter 1: Introduction
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
Chapter 1: Introduction
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
Chapter 1: Introduction
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
Chapter 1: Introduction
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
Chapter 1: Introduction
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).
Chapter 1: Introduction
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.
Chapter 1: Introduction
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
Chapter 1: Introduction
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
Chapter 1: Introduction
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),
Chapter 1: Introduction
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.,
Chapter 1: Introduction
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
Chapter 1: Introduction
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
Chapter 1: Introduction
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
Chapter 1: Introduction
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
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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.
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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.
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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.
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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.
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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.
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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.
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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.
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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.
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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
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
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
F lu o re s c e n c e in te n s ity
% 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
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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
F lu o re s c e n c e in te n s ity
% 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
F lu o re s c e n c e in te n s ity
% 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
F lu o re s c e n c e in te n s ity
% 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
F lu o re s c e n c e in te n s ity
% 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
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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.
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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.
Chapter 2: Physiological responses of Microcystis aeruginosa PCC 7806 in continuous cultures
of different iron bioavailability and growth rates
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
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron
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
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron
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
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron
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
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron
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
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron
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.
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron
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
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron
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.
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron
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.
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron
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.
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron
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.
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron
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.
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron
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
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron
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.
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron
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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,
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron
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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
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron
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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).
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron
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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.
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron
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
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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
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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
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron concentration
76
Amino acid metabolism
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
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron concentration
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
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron concentration
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
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron concentration
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_57595 30S ribosomal protein S16 0.236 0.0126 -2.086
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_57420 50S ribosomal protein L4 0.203 0.0224 -2.299
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
MAE_57320 50S ribosomal protein L24 0.067 0.0323 -3.893
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
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron concentration
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
Hypothetical proteins
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
MAE_61990 Hypothetical protein 7.798 0.0015 2.963
MAE_15680 Hypothetical protein 0.247 0.0024 -2.020
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron concentration
81
MAE_46700 Hypothetical protein 6.792 0.0023 2.764
MAE_07350 Hypothetical protein 4.875 0.0202 2.286 5.012 0.0037 2.325
MAE_11840 Hypothetical protein 0.281 0.0412 -1.834
MAE_07360 Hypothetical protein 7.871 0.0093 2.976 5.808 0.0293 2.538
MAE_36690 Hypothetical protein 4.699 0.0250 2.232
MAE_02150 Hypothetical protein 5.861 0.0408 2.551 4.613 0.0444 2.206
MAE_44430 Hypothetical protein 5.395 0.0255 2.432
MAE_41180 Hypothetical protein 9.818 0.0204 3.295 5.346 0.1626 2.418
MAE_35080 Hypothetical protein 0.686 0.0428 -0.545 16.904 0.0084 4.079 3.631 0.0367 1.860
MAE_19620 Hypothetical protein 5.395 0.0425 2.432
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron concentration
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.
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
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
MAE_44930 30S ribosomal protein S2 0.809 0.0306 -0.306
Transport and binding proteins
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
Chapter 3: Proteomic responses of Microcystis aeruginosa PCC 7806 in differing iron concentration
83
Table 3.3 cont.
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
Other categories
MAE_37620 Gas vesicle structural protein, GvpC 3.436 0.0049 1.781
Hypothetical proteins
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
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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.
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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.
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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.
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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.,
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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.
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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:
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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 ]
k [L ] k [MeL] k [FZ]
, (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
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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-
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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:
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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).
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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)
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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.
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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.
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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).
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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).
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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.
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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
Chapter 4: Effect of divalent metal ions on iron transformation and uptake by M. aeruginosa
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).
Chapter 5: The physiological responses of two closely related strains of Cylindrospermopsis
raciborskii to differing iron availability under nitrogen-fixing conditions
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
Chapter 5: The physiological responses of two closely related strains of Cylindrospermopsis
raciborskii to differing iron availability under nitrogen-fixing conditions
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);
Chapter 5: The physiological responses of two closely related strains of Cylindrospermopsis
raciborskii to differing iron availability under nitrogen-fixing conditions
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.
Chapter 5: The physiological responses of two closely related strains of Cylindrospermopsis
raciborskii to differing iron availability under nitrogen-fixing conditions
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).
Chapter 5: The physiological responses of two closely related strains of Cylindrospermopsis
raciborskii to differing iron availability under nitrogen-fixing conditions
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).
Chapter 5: The physiological responses of two closely related strains of Cylindrospermopsis
raciborskii to differing iron availability under nitrogen-fixing conditions
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
Chapter 5: The physiological responses of two closely related strains of Cylindrospermopsis
raciborskii to differing iron availability under nitrogen-fixing 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 (
Chapter 5: The physiological responses of two closely related strains of Cylindrospermopsis
raciborskii to differing iron availability under nitrogen-fixing conditions
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-
Chapter 5: The physiological responses of two closely related strains of Cylindrospermopsis
raciborskii to differing iron availability under nitrogen-fixing conditions
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).
Chapter 5: The physiological responses of two closely related strains of Cylindrospermopsis
raciborskii to differing iron availability under nitrogen-fixing conditions
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
Chapter 5: The physiological responses of two closely related strains of Cylindrospermopsis
raciborskii to differing iron availability under nitrogen-fixing conditions
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.
Chapter 5: The physiological responses of two closely related strains of Cylindrospermopsis
raciborskii to differing iron availability under nitrogen-fixing conditions
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
Chapter 5: The physiological responses of two closely related strains of Cylindrospermopsis
raciborskii to differing iron availability under nitrogen-fixing conditions
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
Chapter 5: The physiological responses of two closely related strains of Cylindrospermopsis
raciborskii to differing iron availability under nitrogen-fixing conditions
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).
Chapter 5: The physiological responses of two closely related strains of Cylindrospermopsis
raciborskii to differing iron availability under nitrogen-fixing conditions
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
Chapter 5: The physiological responses of two closely related strains of Cylindrospermopsis
raciborskii to differing iron availability under nitrogen-fixing conditions
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
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in
response to iron under N2-fixing conditions
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.
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in
response to iron under N2-fixing conditions
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.
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in
response to iron under N2-fixing conditions
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.
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in
response to iron under N2-fixing conditions
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.
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in
response to iron under N2-fixing conditions
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.
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in
response to iron under N2-fixing conditions
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.
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in
response to iron under N2-fixing conditions
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
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in
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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
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in
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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
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in
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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
Amino acid metabolism
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
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in response to iron under N2-fixing conditions
147
Table 6.1 cont.
Accession Protein ID 50 vs 1000
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
Transport and binding proteins
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
Hypothetical proteins
D4TL32_9NOST Hypothetical protein 0.655 0.049 -0.611
533241.6.peg.1265 Hypothetical protein 1.057 0.008 0.080
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in response to iron under N2-fixing conditions
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
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in response to iron under N2-fixing conditions
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Table 6.2 cont.
Accession Protein ID 50 Fe vs 1000
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
Genetic information (Transcription and translation proteins)
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
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in response to iron under N2-fixing conditions
150
Table 6.2 cont.
Accession Protein ID 50 Fe vs 1000
Pval Log2 Fold
200 Fe vs 1000
Pval Log2 Fold
Transport and binding proteins
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
533241.6.peg.1529 Hypothetical protein 0.545 0.012 -0.877
533241.6.peg.160 Hypothetical protein 0.474 0.002 -1.076 0.592 0.003 -0.757
533241.6.peg.1265 Hypothetical protein 0.413 0.004 -1.276
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in response to iron under N2-fixing conditions
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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.
Accession Protein ID 50 vs 1000
Pval Log 2 Fold
200 vs 1000
Pval Log 2 Fold
Amino acid metabolism
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
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in response to iron under N2-fixing conditions
152
Table 6.3 cont.
Accession Protein ID 50 vs 1000
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
Transport and binding proteins
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
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in response to iron under N2-fixing conditions
153
Table 6.3 cont.
Accession Protein ID 50 vs 1000
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
533244.4.peg.2588 Hypothetical protein 0.134 0.043 -2.897
533244.4.peg.219 Hypothetical protein 0.052 0.004 -4.279
533244.4.peg.799 Hypothetical protein 0.122 0.004 -3.030 0.501 0.025 -0.997
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in response to iron under N2-fixing conditions
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.
Accession Protein ID 50 vs 1000
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
Genetic information (Transcription and translation proteins)
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
Transport and binding proteins
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
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in
response to iron under N2-fixing conditions
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.
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in
response to iron under N2-fixing conditions
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.
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in
response to iron under N2-fixing conditions
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
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in
response to iron under N2-fixing conditions
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.
Chapter 6: Comparative proteomics of C. raciborskii strains with different toxigenicity in
response to iron under N2-fixing conditions
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
Chapter 7: Summary and future work
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
Chapter 6: Summary and future work
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
Chapter 7: Summary and future work
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
Chapter 6: Summary and future work
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
Chapter 7: Summary and future work
165
membranes which allow for the exchange of nutrients and other small molecules, while
still keeping testing strains separate.
References
167
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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.
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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]
k [L ] k [MeL] 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]
k [L ] k [MeL] 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
(Fujii et al., 2010a)
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
(Rush and Bielski, 1985)
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
(Fujii et al., 2010a)
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
(Rose and Waite, 2005)
3 FeIIL + O2 →Fe
IIIL + O2
•-
1.5 × 10
2 d M
-1 s
-1
(Miller et al., 2009)
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
(Miller et al., 2009)
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
(Rose and Waite, 2003)
8 Fe(II)' + L →FeIIL 4.5 × 10
4 M
-1 s
-1
(Bligh and Waite, 2010)
9 FeIIL→ Fe(II)' + L 7.9 × 10
-4 s
-1
(Bligh and Waite, 2010)
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
(Rush and Bielski, 1985)
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
(Fujii et al., 2010a)
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)
Logarithm of total Ca concentration (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)
Logarithm of total Mg concentration (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)
Logarithm of total Ca concentration (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)
Logarithm of total Mg concentration (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
no Me 20 mM Ca 20 mM Mg
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
no Me 20 mM Ca 20 mM Mg
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
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