1. The Pathway Tools FBA Module
Overview of MetaFlux –
The Pathway Tools FBA Module
© 2013 SRI International

2. Metabolic Modeling Steady-state modeling Dynamic modeling
Biological system is at equilibrium
Flux-balance analysis (FBA)
Dynamic modeling
Biological system changes over time
Kinetic modeling
Dynamic FBA
FBA has gained great popularity in the past decade
Much more feasible on genome scale
Does not require the huge number of parameters needed by kinetic modeling
Kinetic modeling requires
Concentrations for all substrates and enzymes
Kinetic parameters for all enzymes

3. Flux-Balance Analysis
Information required for FBA
E. coli model derived from EcoCyc (BMC Sys Biol :79):
16 nutrients
108 biomass metabolites
2286 reactions
Nutrients
Metabolic Reaction List
Secretions A A B C D D X
Biomass

4. Metabolic Modeling Applications
Identify gaps in genome annotation
Predict steady-state reaction fluxes for the metabolic network
Predict growth rates, nutrient uptake rates
Remove genes/reactions from model to predict knock-out phenotypes
Supply alternative nutrient sets to predict growth rates
Metabolic engineering

5. Metabolic Model Generation in Pathway Tools
PathoLogic: Qualitative metabolic model reconstruction
Inference of the reactome from the annotated genome
Inference of metabolic pathways by selecting from MetaCyc pathways
Karp et al, Stand Genomic Sci, :424
MetaFlux: Quantitative model reconstruction
Infer biomass reaction
Can biomass metabolites be synthesized? Are fluxes accurate?
Gap fill
Edit reaction complement
Iterate
Karp et al, Briefings in Bioinformatics 2015, in press

6. Pathway Tools Software: MetaFlux
Steady-state quantitative flux-models generated directly from PGDBs
Multiple gap filler accelerates model development by suggesting model completions:
Reactions to add from MetaCyc
Additional nutrients and secreted compounds
Model communities of interacting organisms
Pathway visualization of fluxes
Plotting of organism biomass and metabolite concentrations

7. Other Aspects of MetaFlux
Store and update metabolic model within PGDB
Curate metabolic model and organism database simultaneously
Enriching information increases understandability of model
Genome, chemical structures, atom mappings, regulation
Pathway definitions
Unique identifiers for each component of the model are used consistently across multiple PGDBs/models
All query and visualization tools applicable to FBA model
Graphical exploration of model results
Visualize computed reaction fluxes via cellular overview
Plot organism composition, metabolite concentrations
Programmatic execution of models from Lisp and PythonCyc APIs
MetaFlux: Latendresse et al, Bioinformatics :388-96

8. E. coli Metabolic Model
Generated from EcoCyc, updated on each EcoCyc release
Predicts phenotypes of E. coli knock-outs
95.2% accuracy for 1445 genes
Predicts growth/no-growth of E. coli on different nutrients
80.7% accuracy for 431 chemically defined growth media
BMC Syst Biol Jun 30;8:79

9. Cost for High Quality Models of 300 Microbiome Organisms
Multiple body sites of human, mouse, farm animals…
500 species in human pan metagenome (Nielsen)
321 organisms for human alone (Magnusdottir)
300 models x 2 months/model x $100K/yr = $5M
Assumes cost of combining models is zero
If every model is duplicated 5 times: $25M

10. Microbiome Modeling in Pathway Tools
Key ideas:
Let's divide and conquer the problem of microbiome modeling
Plug-and-play metabolic models