jacob feala 1,2 laurence coquin, phd 2 andrew mcculloch, phd 1 giovanni paternostro, phd 1,2

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Flexibility in energy Flexibility in energy metabolism supports hypoxia metabolism supports hypoxia tolerance in Drosophila tolerance in Drosophila flight muscle: metabolomic flight muscle: metabolomic and computational systems and computational systems analysis analysis Jacob Feala Jacob Feala 1,2 1,2 Laurence Coquin, PhD Laurence Coquin, PhD 2 Andrew McCulloch, PhD Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD Giovanni Paternostro, PhD 1,2 1,2 1) UCSD Bioengineering 1) UCSD Bioengineering 2) Burnham Institute for Medical Research 2) Burnham Institute for Medical Research

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Flexibility in energy metabolism supports hypoxia tolerance in Drosophila flight muscle: metabolomic and computational systems analysis. Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2 1) UCSD Bioengineering - PowerPoint PPT Presentation

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Page 1: Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2

Flexibility in energy Flexibility in energy metabolism supports metabolism supports hypoxia tolerance in hypoxia tolerance in

Drosophila flight muscle: Drosophila flight muscle: metabolomic and metabolomic and

computational systems computational systems analysisanalysis

Jacob FealaJacob Feala1,21,2

Laurence Coquin, PhDLaurence Coquin, PhD22

Andrew McCulloch, PhDAndrew McCulloch, PhD11

Giovanni Paternostro, PhDGiovanni Paternostro, PhD1,21,2

1) UCSD Bioengineering 1) UCSD Bioengineering 2) Burnham Institute for Medical Research2) Burnham Institute for Medical Research

Page 2: Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2

Cellular hypoxia responseCellular hypoxia response Hypoxia is the cause of cell death in many Hypoxia is the cause of cell death in many

pathologies, mechanism not knownpathologies, mechanism not known All cells have intrinsic defenses All cells have intrinsic defenses Hypoxia tolerant organisms have highly orHypoxia tolerant organisms have highly or

chestrated chestrated metabolicmetabolic regulationregulation

Page 3: Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2

Drosophila as a model for Drosophila as a model for hypoxia researchhypoxia research

Flies are hypoxia tolerantFlies are hypoxia tolerant Simple system, genetic tools and librariesSimple system, genetic tools and libraries Genetic screen found gene required for tolerance Genetic screen found gene required for tolerance

11

Hypoxia tolerance gene was successfully Hypoxia tolerance gene was successfully transferred to mammalian cells transferred to mammalian cells 22

humanfly

Phylogenetic tree

1Haddad GG et. al., Proc Natl Acad Sci U S A. 1997 Sep 30;94(20):10809-12. 2Chen Q et. al., J Biol Chem. 2003 Dec 5;278(49):49113-8. Epub 2003 Sep 16.

Page 4: Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2

Systems analysis of hypoxia Systems analysis of hypoxia responseresponse

Complex balances must be maiComplex balances must be maintained to tolerate hypoxiantained to tolerate hypoxia ATP supply and demandATP supply and demand Redox potentialRedox potential Metabolic intermediatesMetabolic intermediates pHpH

Systems biology to understand Systems biology to understand and model the complex control and model the complex control systemssystems

Hochachka, P. W. J Exp Biol 2003; 206:2001-2009

Page 5: Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2

General hypothesis for hypoxia tolerGeneral hypothesis for hypoxia toleranceance

Flexible metabolic regulation is the major soFlexible metabolic regulation is the major source of hypoxia toleranceurce of hypoxia tolerance Immediate (minutes)Immediate (minutes) Global (ATP production, biosynthesis, protein trGlobal (ATP production, biosynthesis, protein tr

anslation)anslation)

Page 6: Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2

Our systems approach to modeling Our systems approach to modeling ATP-generating metabolism:ATP-generating metabolism:

Metabolomics to find all anaerobic Metabolomics to find all anaerobic pathwayspathways

Flux-balance analysis to simulate Flux-balance analysis to simulate pathways under varying oxygenpathways under varying oxygen

Generate novel, specific, testable Generate novel, specific, testable hypotheses for hypoxia tolerancehypotheses for hypoxia tolerance

Page 7: Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2

11H NMR H NMR spectroscospectrosco

py of py of hypoxic fly hypoxic fly

musclemuscle• 0.5% O2

• 240 minutes• supervised by Laurence Coquin

MAMMALIAN TISSUE:

Troy H et. al. Metabolomics 2005; 1: 293-303

Page 8: Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2

• Concentrations measured by targeted profiling (Chenomx): peak identification, alignment, subtraction• Lower confidence group due to spectra overlap

Global metabolic profileGlobal metabolic profile

Page 9: Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2

11H NMR spectroscopy of flight H NMR spectroscopy of flight muscle at t=0,1,10,60,240 muscle at t=0,1,10,60,240 minutesminutes

Significant Significant metabolitesmetabolites

Page 10: Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2

Reconstructing the Reconstructing the Drosophila Drosophila metabolic metabolic

networknetwork Database integrationDatabase integration

KEGG: metabolic genes, enzymes, reactions, KEGG: metabolic genes, enzymes, reactions, EC numbers, pathwaysEC numbers, pathways

Flybase: complete genome, proteins, function, Flybase: complete genome, proteins, function, compartment, mutant stocks, referencescompartment, mutant stocks, references

Filtered gene indexFiltered gene indexPathwaysPathways 109109EC numbersEC numbers 437437GenesGenes 13221322Genes Genes (mitochondrial)(mitochondrial)

125125

Genes (stocks Genes (stocks available)available)

507507

Page 11: Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2

Network model of central Network model of central metabolismmetabolism 162 genes, 143 proteins and 158 reactions162 genes, 143 proteins and 158 reactions Includes glycolysis, TCA cycle, oxidative Includes glycolysis, TCA cycle, oxidative

phosphorylation, phosphorylation, β-oxidation, amino acids-oxidation, amino acids Elementally- and charge-Elementally- and charge-

balancedbalanced

Reconstructing the network Reconstructing the network

Gene-protein-reactionassociations

Literature and Databases

Annotated Genome

Stoichiometric matrix

Metabolic network reconstruction

Drosophila central metabolism

Reed JL et. al., Nat Rev Genet. 2006 Feb;7(2):130-41.

Page 12: Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2

AlanineAcetyl-CoA

α-Oxoglutarate Glutamate

Cytosol

Mitochondria

Acetate

Acyl-carnitine shuttle

Glucose

Pyruvate Lactate

Main energetic pathways in model

ATP

Oxaloacetate

NADH

Acetyl-CoA

Citrate

ATP

Pyruvate

ATP

NADH

NADH

NADH/FADH2

NADH

NADH/FADH2

O2 H2OTCA cycle

Oxidative phosphorylation

Glycolysis

NADH

FADH

α-GPDH shuttle

Products seen in NMR

Hypothesized pathways

Known Drosophila pathwaysATP

CO2

CO2

NH4

Page 13: Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2

Flux-balance analysisFlux-balance analysis Steady state assumption, flux Steady state assumption, flux

constraintsconstraints Optimize for objective functionOptimize for objective function Mass and charge balance inherentMass and charge balance inherent

ATP supply and demandATP supply and demand Redox potentialRedox potential pHpH

Particular solution (optimal)

Null Space of S

Solution space

Metabolic network reconstruction

S matrix

Page 14: Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2

Simulation conditions- Glucose (and equivalents) only carbon

substrate- Lactate, alanine, acetate constrained to

NMR fluxes- Varied O2 uptake constraint- Objective: maximize ATP production

Flux-balance analysis of Flux-balance analysis of hypoxiahypoxia

lac

ala

ac

glc

Page 15: Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2

Hypoxia simulation: key fluxesHypoxia simulation: key fluxes

Abbreviations: • atp: ATP production• co2: CO2 production• glc: glucose uptake• h: proton production

• ac: acetate accumulation• lac: lactate accumulation• ala: alanine accumulation

Drosophila (Pseudo-) Mammalian

Reduced glucose uptake

Stable pH

Equivalent ATP

Page 16: Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2

ConclusionsConclusions ‘‘Exotic’ anaerobic pyruvate Exotic’ anaerobic pyruvate

pathways in fly maypathways in fly may contribute to contribute to hypoxia tolerancehypoxia tolerance

New hypotheses to test: alanine New hypotheses to test: alanine and acetate production and acetate production essential under hypoxiaessential under hypoxia

Systems modeling revealed Systems modeling revealed emergent behavioremergent behavior

Page 17: Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2

Candidate genes

Genetic perturbation

ModelExperiment

NMR metabolomics

Validate

Perturbation Analysis of Perturbation Analysis of Energy Metabolism in Energy Metabolism in

HypoxiaHypoxia

Refine

Page 18: Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2

AcknowledgementsAcknowledgements Polly HuangPolly Huang Palsson lab, UCSD BioengineeringPalsson lab, UCSD Bioengineering

Adam FeistAdam Feist Thuy VoThuy Vo

Khoi PhamKhoi Pham

QuestionsQuestions

Page 19: Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2
Page 20: Jacob Feala 1,2 Laurence Coquin, PhD 2 Andrew McCulloch, PhD 1 Giovanni Paternostro, PhD 1,2

Flux variabilityFlux variability