Building Metabolic Models © 2013 SRI International

Metabolic Model Building Wonderful puzzles! Convert molecules in the environment into the molecules needed to sustain life

Flux-Balance Analysis Nutrients Metabolic Reaction List Secretions A A B C D D Biomass Metabolites X

What Could Possibly Go Wrong? Incomplete knowledge Missing reactions Genome annotation is incomplete Genome annotation is incorrect MetaCyc reactions sometimes in incorrect directions Failures in reaction instantiation Model uses the wrong reactions Utilization of reactions that are inactivated Nutrients, secretions, BMs uncertain

Reactions in the Metabolic Model Reactions in the metabolic model are obtained from the PGDB Metabolic pathways in PGDB not relevant to metabolic model Note also that .fba file can modify reactions present in model Reactions exist in PGDB because Presence inferred by PathoLogic from enzymes in annotated genome Metabolic pathway inference imports reactions in MetaCyc that may lack enzymes in the PGDB Reactions added or deleted manually by the user

PathoLogic Reactome Inference For each protein in the organism Infer reaction(s) it catalyzes Import reaction(s) from MetaCyc into current PGDB Match protein functions to MetaCyc reactions Enzyme names (uncontrolled vocabulary) EC numbers Gene Ontology terms Genome annotation subject to false positives and false negatives Reactome inference subject to false positives and false negatives

PathoLogic Enzyme Name Matcher Name matcher generates alternative variants of each name and matches each to MetaCyc Strips extraneous information found in enzyme names Putative carbamate kinase, alpha subunit Flavin subunit of carbamate kinase Cytoplasmic carbamate kinase Carbamate kinase (abcD) Carbamate kinase (3.2.1.4)

Read the Literature for Your Organism Chemical composition of growth medium Energy source, elemental sources Quantitative data Cellular doubling time P/O ratio if cell respires Anaerobic respiration electron acceptors? Cellular chemical composition – BMs and their coefficients % fraction of dry cell weight for protein, RNA, etc Membrane composition Length of quinol chains Known pathways, enzymes, transporters On/off under different growth conditions Cellular architecture

The Metabolic Maze Seven major and intertwined themes: Atomic assimilation of carbon, nitrogen, sulfur, phosphorus Electron transfer Nucleotide phosphorylation Production of ion gradients

Starting Point Place nutrients into the cytoplasm Set an upper bound of 10 on one nutrient Leave other nutrients unbounded Define as unbounded nutrients and secretions: CO2, WATER, PROTON

Prop Compounds Add this set of temporary prop compounds as both nutrients and secretions ATP[CCO-CYTOSOL] ADP[CCO-CYTOSOL] Pi[CCO-CYTOSOL] NAD[CCO-CYTOSOL] NADH[CCO-CYTOSOL] NADP[CCO-CYTOSOL] NADPH[CCO-CYTOSOL] WATER[CCO-CYTOSOL] Reduced-ferredoxins[CCO-CYTOSOL] Oxidized-ferredoxins[CCO-CYTOSOL] Reduced-flavodoxins[CCO-CYTOSOL] Oxidized-flavodoxins[CCO-CYTOSOL] CO-A[CCO-CYTOSOL] ACP[CCO-CYTOSOL] HYDROGEN-MOLECULE[CCO-CYTOSOL] PROTON[CCO-CYTOSOL] THF[CCO-CYTOSOL] 5-METHYL-THF[CCO-CYTOSOL] METHYLENE-THF[CCO-CYTOSOL] 10-FORMYL-THF[CCO-CYTOSOL]

Achieve Production of all Biomass Metabolites

Finally Remove prop compounds Implement transport so nutrients are no longer placed in the cytoplasm Some compounds change form during transport

Bottom-Up vs Top-Down Model Building Proceed incrementally from nutrients to selected intermediates and BMs Slow, methodical, carefully ordered Controls complexity by incrementally expanding the needed network Ensure the correct reactions are used to produce each BM Expand explicit reaction list along the way Top down: Throw all nutrients, reactions, BMs into a pot and stir Let gap filler figure out what is missing Faster, but less controlled Gap filler is powerful, but minimal-cost solution is not always correct BMs may be produced by the wrong reactions Both approaches can be accelerated by gap filler and blocked-reaction tools

Bottom-Up Model Building Reach all biomass metabolites, remove all prop compounds Work forward toward one biomass metabolite at a time See bottom-up-methodology.docx

Validating Your Model Small-scale validation Large-scale validation All BMs can be made from expected nutrient set Relative nutrient uptake rates and associated cellular growth rate Reaction usage, reaction fluxes Large-scale validation Gene knock-outs Different nutrient conditions