Metabolomics, spring 06

Hans BohnertERML 196

bohnerth@life.uiuc.edu

265-5475333-5574

http://www.life.uiuc.edu/bohnert/

Second discussion topic:

Fan TWM, Bandura LL, Higashi RM, Lane AN (2005) Metabolomics-edited transcriptomics of Se anticancer action in human lung cancer cells. Metabolomics 1, 325.

class April 13

Arabidopsis ecotypes in high CO2 in FACE--

Attempts at correlating

gene expression,

metabolite concentrations

and changes

Metabolomics Essentiality

I am expanding the “FACE” discussion based on two papers on

stochastic events in gene expression and single cell protein synthesis

Blake WJ, Kaern M, Cantor ER, Collins JJ (2003) Noise in eukaryotic gene expression. Nature 422, 633.

Cai L, Friedman N, Xie XS (2006) Stochastic protein expression in individual cells at the single molecule level. Nature 440, 358.

Stochastic events in gene expression

How to measure protein synthesisin single cells

Single reporter molecule sensitivity on a microfluidic

device

Quantitative real-time measurements of individual protein expression

events in E. coli

Steady-state protein copy numberdistributions in a population of cells

Two regimes of stochasticity in protein expression

temperature difference between ambient and high CO2

in SoyFACE.

http://www.soyface.uiuc.edu

ArabidopsisArabidopsis in the field? in the field?

• AmbientAmbient• high COhigh CO22

• high Ohigh O33

• [CO2 + O3]

‘You are mad!’

SoyFACE

Starting earlyto midJune

No further comment!

High ozone ring #7 -ecotype: Cape Verde;

least affected by ozone or CO2

all experimentsused

collections of more then

10 plants(entire above-

ground material)for each

hybridizationsample!

Microarray materials:

Ozone ring, R7- WS;growing next to ecotype CapeVerde;

shot taken the same day;most affected by elevated CO2/O3

PhenotypicallyWS

turned out the most

‘sensitive’ecotypeunder

all conditions!

typical examplemature rosette Col,

control ring

3.01 0

1 11758 3 9

Col 21 Cvi 21 Cvi 27 Col 27

Supplemental Figure 1(SF1).

Cluster 1

Cluster 2

Cluster 3

Cluster 4

Cluster 5

Cluster 6

Col 21 Col 27 Cvi 21 Cvi27

90

54

171

4

29

133

Figure 4.

Microarrays3 rings ambient and 3 rings high CO2hybridizations (3/sample, dye-swap)normalizationstatistical analysis - R, SASfuzzy k-means clustering cluster centroids metabolites from same material – rosette leaves

Ecotypes

Col - ColumbiaCvi - Cape Verde Island

Supplemental Figure 2 (SF2). HSPs/GSTs

HSPs

GSTs

Col 21 Cvi 21 Col27 Cvi 27

Figure 5A.

Light reactions

Photorespiration

Calvin cycle

-0.6 0 0.6

(log 2 fold change)

Col 21 Cvi 21 Col27 Cvi 27

Photosynthesis functions down-regulated

Cvi recovers over time

Figure 5B.

Cell wall precursor synthesis

Cellulose synthesis

Hemicellulose synthesis

Cell wall Proteins AGPs

Cell wall proteinsLRR

Cell wall, HRGP

Cell wall, RGPCol 21 Cvi 21 Col27 Cvi 27

Col grows faster in CO2

Ct & Mt ribosomal proteins

40S ribosomal proteins

60S ribosomal proteins

putative ribosomal proteins

Col 21 Cvi 21 Col27 Cvi 27

Figure 5C.

Transient down-regulation

of translation functions

Supplemental Figure 3C.

RNA metabolism/

protein synthesis

Col Jun 21

Cvi Jun 21

Col Jun 27

Cvi Jun 27

Metabolites Col 21 CO2/ P-ambient valuefold change

glutamic acid 0.39 0.00threonine 0.61 0.11Total 0.56 0.02

citric acid 0.73 0.05malic acid 0.77 0.10p-hydroxybenzoic

acid 0.55 0.09Total 0.86 0.07

maltose 1.55 0.09trehalose 0.80 0.31Total 1.08 0.53

mannitol 1.33 0.11glycerol 0.87 0.23inositol 0.96 0.84Total 0.97 0.74

glucose-6-P 0.55 0.10

phosphate 0.71 0.24

Alc

oh

ols

Su

gar

sO

rgan

ic

acid

sA

min

o

acid

s

Absolute change and Confidence

In total ~60 metabolitescould be scored

Cvi June 21 A

Cvi June 27 C

Cvi June 27 A

Cvi June 21 C

Col June 21 A

Col June 27 ACol June 21 C

Col June 27 C

-60

-40

-20

0

20

40

60

-60 -40 -20 0 20 40 60

F1 77.71 %

F2

16.9

2 %

Supplemental Figure 5.

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

-1.5 -1 -0.5 0 0.5 1 1.5

Jun

e 21

June 27

SugarsOrganic acid

Amino acid Polyols

6 carbon sugars

12 carbon sugars

18 carbon sugars

Col-0

Cvi-0

Figure 6.

Metabolite changes(major categories)over time points

Raffinose

SucroseStarch

Galactose

Glucose Fructose Melibiose

3-Phosphoglycerate

Pyruvate

Acetyl-CoA

Citrate

Isocitrate

alpha-Ketoglutarate

Succinate

Fumarate

Malate

Oxaloacetate

Chorismate

Serine

Cysteine

Tyrosine

Phenylalanine

Prephenate

PEP

Tryptophan

Glycine

Leucine

Valine

Aspartate

Asparagine

Aspartate-4-semialdehyde

Lysine

Homoserine-4-phosphate

Threonine

Isoleucine

Methionine

Glutamate

Glutamine

Proline

2.3.3.1

4.2.1.3

1.1.1.42

6.2.1.41.3.5.1

4.2.1.2

1.1.99.16

5.4.2.1

4.2.1.11

2.7.1.40

1.1.1.952.6.1.523.1.3.32.1.2.1

2.3.1.30

4.2.99.8

3.2.1.26Neutral

Invertase

Invertase, cell wall

Invertase, vacuole

5.3.1.9

2.7.1.1

1.2.1.12

2.7.2.3

Maltose

Oxaloacetate

4.1.1.49

4.1.1.31

4. 1.3.8

2.2.1.61.1.1.862.6.1.42

4.1.3.124.2.1.331.1.1.852.6.1.42

2.6.1.1

6.3.5.4

2.7.2.4

1.2.1.11

4.2.1.52

1.3.1.26

2.6.1.17

3.5.1.18

5.1.1.7

1.1.1.3

2.7.1.39

4.2.3.1

2.2.1.6

1.1.1.86

2.6.1.42

4.2.99

4.4.1.8

2.1.1.142.1.1.10

1.4.7.1

6.3.1.2

4.1.3.27

4.2.1.10

2.7.1.71

2.5.1.194.2.3.5

2.4.2.18

5.3.1.24

4.1.1.48

5.4.99.5

1.3.1.12

4.2.1.51

2.6.1.5

4.2.3.4

3.2.1.1

3.2.1.22.4.1.25MEX1

DEP2

Galactinol2.4.1.123

2.4.1.82

AT5G65750

At4g02610At4g27070

At5g14800At5g62530

Figure 7.

Co

l 21

Transcripts

Metabolites

-0.6 0 0.6

(log2 - fold change)C

ol

27

Cvi

21

Cvi

27

isoforms

-C

-N

-P

Col June 21 Col June 27

-C

-N

-P

Cvi June 21 Cvi June 27

Figure 8.

DoArabidopsisin high CO2

experiencenitrogendeficit?

Ecotype-specificreactions

AdaptationAcclimation

Evolutionary background?

Col Jun 21 Cell wall Col Jun 27 Cell wall

Supplemental Figure 3B.

Cvi Jun 21 Cell wall Cvi Jun 27 Cell wall

• Absorption by nuclei [not electrons] of electromagnetic radiation (up to ~900 MHz)• Certain nuclei with spin and magnetic moment split energy levels in a field• The split is characteristic of the nucleus and the bonds in which it is involved• Continuous wave (CW) and pulsed (Fourier-transformed, FT) spectrometers• http://en.wikipedia.org/wiki/Nuclear_magnetic_resonance

What NMR signals mean

Chemical shift is usually expressed in parts per million (ppm) by frequency, because it is calculated from:

                                                                         

Since the numerator is usually in hertz, and the denominator in megahertz, delta is expressed in ppm.

The detected frequencies (in Hz) for 1H, 13C, and 29Si nuclei are usually referenced against TMS (tetramethylsilane), which is assigned the chemical shift of zero.

Other standard materials are used for setting the chemical shift for other nuclei.The operating frequency of a magnet is calculate from the Larmor equation:

Flarmor = γ * B0, where B0 is the actual strength of the magnet

in units like teslas or gauss, and

γ is the gyromagnetic ratio of the nucleus being tested.

Isotope Occurrence

in nature(%)

spin number l

Magnetic moment

μ(A·m²)

Electric quadrupole

moment(e×10-24 cm2)

Frequency at 7 T

(MHz)

Relative sensitivit

y

1H 99.984 1/2 2.79628 300.13 1

2H 0.016 1 0.85739 2.8 x 10-3 46.07 0.0964

10B 18.8 3 1.8005 7.4 x 10-2 32.25 0.0199

11B 81.2 3/2 2.6880 2.6 x 10-2 96.29 0.165

12C 98.9 0

13C 1.1 1/2 0.70220 75.47 0.0159

14N 99.64 1 0.40358 7.1 x 10-2 21.68 0.00101

15N 0.37 1/2 −0.28304 30.41 0.00104

16O 99.76 0

17O 0.0317 5/2 −1.8930 −4.0 x 10-3 40.69 0.0291

Not only 13C or 1H – other atoms as well can be seen

What NMR signals mean

Metabolomics-edited transcriptomics analysis ofMetabolomics-edited transcriptomics analysis ofSe anticancer action in human lung cancer cellsSe anticancer action in human lung cancer cells

Fan, Bandura, Higashi & Lane (2005) Metabolomics 1, 325-339

(META)

Transcriptomic analysis is an essential tool for systems biology but it has been stymied by a lack of global understanding of genomic functions, resulting in the inability to link functionally disparate gene expression events. Using the anticancer agent selenite and human lung cancer A549 cells as a model system, we demonstrate that these difficulties can be overcome by a progressive approach which harnesses the emerging power of metabolomics for transcriptomic analysis. We have named the approach Metabolomics-edited transcriptomicanalysis (META). The main analytical engine was 13C isotopomer profiling using a combination of multi-nuclear 2-D NMR and GC-MS techniques. Using 13C-glucose as a tracer, multiple disruptions to the central metabolic network in A549 cells induced by selenite were defined. META was then achieved by coupling the metabolic dysfunctionsto altered gene expression profiles to: (1) provide new insights into the regulatory network underlying the metabolic dysfunctions; (2) enable the assembly of disparate gene expression events into functional pathways that was not feasible by transcriptomic analysis alone. This was illustrated in particular by the connection of mitochondrial dysfunctions to perturbed lipid metabolism via the AMP-AMPK pathway. Thus, META generated both extensive and highly specific working hypotheses for further validation, thereby accelerating the resolution of complex biological problems such as the anticancer mechanism of selenite.

Key words (3-6) two-dimensional NMR; GC-tandem MS; 13C isotopomer profiling; selenite; lung adenocarcinoma A549 cells.

Abbreviations 1H–13C HMBC: 1H–13C heteronuclear multiple bond correlation spectroscopy; 1H–13C HSQC: 1H–13C heteronuclear single quantum coherence spectroscopy; 2-D 1H TOCSY: two dimensional 1H total correlation spectroscopy; [U)13C]-glucose: uniformly 13C-labeled glucose; MSn: mass spectrometry to the nth dimension; MTBSTFA: N-methyl-N-[tert-butyldimethylsilyl]trifluoroacetamide; P-choline or PC: phosphorylcholine; PDA: photodiode array; TCA: trichloroacetic acid.

Knowledge: Se is an essential atom, high amounts affect (cancer) growth, Se inproteins is related to ROS homeostasis (somehow)

Experiment: The addition of Se to lung cells affects growth – what is the basis?Use genomics platforms (transcript analysis), GC-MS & esp. NMR

Hypothesis: gene expression is altered, and metabolite analysis can be correlated with transcript changes – can it, is the question!

Approaches Microscopy, NMR, GC-MS, transcripts

Se interferes with the cytoskeleton and mitochondrial activity

Selenite effects proliferating cells;

Selenite-rich diets may have anti-cancerapplications.

Se leads to degradation of DNA

TUNEL assay?

High resolution 2D NMR spectra of control and Se-treated cellsHigh resolution 2D NMR spectra of control and Se-treated cells

*

*

Metabolites with chemical shift indicative of changes Metabolites with chemical shift indicative of changes 1212C/C/1313C and C and 11H connectivityH connectivity