13Cbased metabolic flux analysis: method development, applications, and future directions Yinjie Tan

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13C-based metabolic flux analysis method
development, applications,and future
directionsYinjie Tang Keasling GroupLawrence
Berkeley National Lab Department of Chemical
EngineeringUniversity of California at Berkeley
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What is fluxomics?
DNA
mRNA
Enzyme
Small metabolites
Metabolomics
Genomics
Transcriptomics
Proteomics
Fluxomics
Metabolic Flux the rate of turnover of
metabolites through metabolic pathways
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Importance of flux analysis

• Genome research Identify gene function
• Bioremediation study microbes physiology under
  environmental stresses or genetic perturbation
• 3. Synthetic biology identify the bottleneck
  pathways for genetic manipulation
• 4. Biomedical field reveal pathways in pathogen
  or cancer cells important for maintaining their
  growth which could be potential drug targets

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13C Metabolic Flux Analysis (MFA)

• 13C based flux balance model
• (overdetermined)
• Use 13C-label to track the carbon flow
• Calculate the actual fluxes in metabolism.

• Flux balance model
• (underdetermined)
• Based on reaction stoichiometries and energy
  balance
• Assumption of objective functions (e.g. maximum
  growth)
• Can not determine reversible pathways or circular
  reactions

E
Stephanopoulos et al. 1998. Metabolic Engineering
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Basis of 13C metabolic flux analysis
determination of intracellular fluxes
Cell
Intracellular fluxes
Carbon Source 13C1-C2-C3-C4-C5-C6 (labeled)
Glycolysis
v1
v3
v2
TCA Cycle
Measurable extracellular fluxes
Amino Acids
Measurable carbon labeling pattern of isotopomers
Tang et al., 2007. Nano Lett. 7(3)754-760.
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Determine the isotopomer distribution in key
metabolites

• Isotopic labeling of proteinogenic amino acids is
  reflective of their precursors in central
  metabolism.

Molecular structure
OAA oxaloacetate
HOOC-CH2-CO-COOH
NH2 HOOC-CH2-CH-COOH

Aspartic acid
Pingitore and Tang et al., 2007 Anal Chem.
79(6)2483-2490
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Protocols of 13C based metabolic flux analysis
Experiment
Model
Genome database
Chemostat culture
Construction of flux balance model
Measurement of isotopic labeling in the
metabolites
Search unknown fluxes
Calculate difference between experimental
predicted data
Predict isotopic labeling data
YES
Minimize difference ?
Best Solution!
NO
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Measurement of 13C isotopomers
GC/MS (Gas chromatography/ mass spectrometry)
NMR (Nuclear magnetic resonance)
Breakthroughs in Keasling lab
FT-ICR (Fourier transform ion cyclotron
resonance)
CE-MS (Capillary electrophoresis - mass
spectrometry)
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Method 1 2D-NMR method
Szyperski et al., TIBTECH, Vol 14 (1996) 453-459
Non-destructive method provide positional
info on isotopomer labeling lower sensitivity
uM mM
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Method 2 GC/MS of Protein hydrolysate
GC
MS
Serine
Higher sensitivity (nM) need to derivatize
compounds gives total mass a-carbon
labeling information
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Method 3 FT-ICR spectrum for protein hydrolysate
Pingitore and Tang et al., 2007 Anal Chem.
79(6)2483-2490
High sensitivity nM provides positional info
on isotopomer labeling the equipment is expensive
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Application of 13C based flux analysis in
Genomics GTL (DOE Project)
Hanford site, WA

• Cleanup costs for radioactive and heavy metal
  waste in US alone is 300 billion.
• Metal reducing bacteria precipitate heavy metals
  (Bio-containment).

Shewanella oneidensis MR-1 Desulfovibrio vulgaris
Geobacter metallireducens
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Shewanella versatile metabolism
Fully aerobic Micro-aerobic
Effect of different electron acceptor conditions
on metabolic fluxes?
TMAO
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Shewanella fluxomes under various oxygen
conditions
X
lt0.1 lt0.1 lt0.1
G6P 6PG
1.1 0.9 0.7
Top value fully aerobic Middle value
shaking flask Bottom value micro-aerobic
0 19.4 35
56.2 46.0 45.5
Tang and Hwang et al, 2007, Appl Environ
Microbiol. 73(3)718-29
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Shewanella hypothesized anaerobic pathways
A C1 metabolic pathway was proposed based on
enzyme activities, genome annotation and
microarray data Scott and Nealson, 1994, J. Bact.
176(11)3408
C-C-COOH
C
C-C-COOH
Is this pathway correct?
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Shewanella mapping uncharted pathways via 13C
labeling
1 2 3
Condition 1 Fumarate reduction
Condition 2 TMAO reduction
Tang et al, 2007, J. Bact. 189(3)894
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Shewanella effect of transposon mutations on
metabolism

• Central metabolism is robust against to random
  genetic changes.
• Glycine degradation is a key route for C1 pool in
  wide type.

The outliers are from a mutant which lacks the
glycine cleavage system glycine X
C1
Tang et al, 2007, unpublished data
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Geobacter metallireducens pathway analysis
TCA cycle
www.microbesonline.org
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Geobacter metallireducens confirming TCA cycle
under anaerobic condition (Fe3 reduction)
0
A complete TCA cycle in the anaerobic condition!
X
X
X
Tang and Chakraborty et al. 2007, Flux analysis
of Geobacter Applied Environmental Microbiology
73(2)
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Geobacter metallireducens finding an unusual
isoleucine pathway via citramalate as an
intermediate
usual pathway
Acetate
Proposed unusual pathway
Citramalate synthase activity is verified by
Derek Lovley group (personal communication)!
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Desulfovibrio vulgaris confirming genome
annotation
TCA cycle
?
?
www.microbesonline.org
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Desulfovibrio vulgaris confirming genome
annotation
v
X
X
X
X
Tang, Pingitore and Mukhopadhyay et al., J. Bact.
189(3)940-9
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Desulfovibrio vulgaris finding an atypical
citrate synthase
Pingitore and Tang et al. 2007, Anal Chem 79(6),
2483-90
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Ongoing research
Tracking evolutionary metabolic changes in
Shewanella strains
Phylogenetic relatedness of sequenced Shewanella
genomes.
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Ongoing research Improving artemisinin
production in Saccharomyces cerevisiae
G6P
FDP
deoxyxylulose 5-phosphate
DHAP
G3P
PEP
Yeast
Glycolysis
PYR
AcCoA
IPP
DMAPP
GPP
Monoterpenes
OAA
CIT
TCA Cycle
FPP
Sesquiterpenes
MAL
GGPP
Amorphadiene
Artemisinin
Artemisinic acid
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Ongoing research Producing fuels from biomass
Biomass
Enzymes
Geobacillus thermoglucosidasius
Cellulose
Microbes
Sugar
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Flux analysis of Geobacillus thermoglucosidasius
under micro-aerobic conditions
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Journal publications on 13C flux analysis
13C metabolic flux analysis
metabolic flux analysis
Key words Total
Papers Review Earliest
publication 13C Metabolic flux analysis 164
14 1983
Metabolic flux analysis 1664
155 1960s
DNA microarray 23474
2718 1995
All papers were searched via Pubmed Data base
(May 10, 2007)
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What are the challenges in 13C based flux
analysis research?
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Challenge 1 Achieving steady state
Continuous fermentation best for flux analysis,
but very expensive. Shaking flask approximate
approach growth condition is not stable.
Isotopomer distribution curves in amino acids
(shaking flask culture) Shewanella ( gly ?
Ser ? Ala) E.coli growth (? gly ? Ser ?
Ala)
Mini-bioreactor high throughput low cost for
labeled medium (10mL) controlled growth
conditions.
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Challenge 2 Minimal medium limits the 13C flux
analysis
Addition of nutrients (amino acids) complicates
the isotopomer analysis!!!
Only Ala, Asp, and Glu (?) Labeling was not
affected by addition of amino acids

This makes flux analysis for mammalian cells
difficult !
Effect of addition of 17 non-labeled amino acid
mix (25 µM each) on labeling pattern in
Shewanella proteinogenic amino acids
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Challenge 3 measurement of metabolites
Measure isotopomer distribution
Measure metabolites Concentrations

• NMR
• Lower sensitivity mM mM

• GC/MS
• Need to derivatize compounds
• Provide total mass and a-carbon
• labeling information

CE-MS(MS) /LC-MS(MS)
CE-FT-ICR
Carbon balance for yeast metabolism
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Challenge 4 13C labeling alone cannot always
solve some pathways
Shewanella (MR-1) acetate metabolism proposed
pathway.
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Challenge 4 13C labeling alone cannot always
identify unique pathways
Shewanella (MR-1) acetate metabolism proposed
pathway

• Solutions
• Genome annotation
• Micro-array
• Mutants (knockout)
• Enzyme assay

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Challenge 5 Global minimum is difficult to
determine (Simulate annealing Monte Carlo
Levenberg-Marquardt Genetic algorithm
Nelder-Mead simplex, etc)
Case 2 multiple global minimums
Case 1 single global minimum
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Future 13C based flux analysis research
13C metabolic Flux analysis
Reviewer comments Tang et al. determine the
intracellular flux distribution of an important
environmental organism using 13C labeling
followed by GC-MS and NMR analysis. This is a
well established experimental/computational
technique, but is usually applied to model or
industrial microbes. Therefore, it is exciting to
see application of this powerful technique
broadened to new organisms.
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Future 13C based flux analysis research

• Flux analysis for new biological systems (Plant
  cell, mammalian cell, pathogen, microbial
  communities).
• Combine the genomics, transcriptomics,
  proteomics, metabolomics tools with fluxomics
  studies.
• Develop new isotopomer measurement methods such
  as LC-MS/MS, CE-TOF and FT-ICR.
• Develop new flux models and computational
  algorithms improve searching algorithms
  integrate genome scale flux balance analysis with
  isotopomer models.

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Acknowledgement
Aindrila Mukhopadhyay Edward Baidoo Jim
Kirby Francesco Pingitore Eric Paradise
Farnaz Nowroozi Rob Dahl
Sandra Villa Wenqing
Shui Michelle Chang Sarah
Rodriguez Jeannie Chu James Carothers
Ding Chen Mario
Ouellet Christopher Petzold Peter Benke
Afshan Shaikh Alyssa Redding
Swapnil Chhabra
Ongoing collaborations
Arkin Hazen Stahl
Bertozzi
Thank you very much!