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Merge Metabolic Models into Community Model
fba_tools

v.1.7.6

By: chenry

Launch

Merge two or more metabolic models into a compartmentalized community model.

The method merges two or more metabolic models of individual organisms resulting in a compartmentalized joint model of a community of multiple organisms.

Community models demonstrate how metagenomic data can be used to produce a compartmentalized model of a multi-species community. As with any FBA model, this compartmentalized model can then be optimized for generation of the community biomass. In the community model generated by this method all compounds and reactions in species 1, 2, etc. are localized into their own respective compartments labelled c1, c2, etc. Compounds transported out of any of the community members to the extracellular environment are labelled e0. Any member of the community having the transport reaction capable of importing these compounds is able to utilize these extracellular compounds.

The community model is capable of predicting the community flux profiles, trophic interactions between the community members and overall community consumption and production of nutrients.

This method primarily requires two input parameters: (i) the list of models IDs of individual organisms (ii) relative abundances (in the same order as model IDs) of each of those organisms in the community. The relative abundance values allow one to formulate the biomass composition for the entire community. Relative abundances need to be normalized to one. For example, a four species community with equal abundances of these species is represented by 0.25; 0.25; 0.25; 0.25 in the second input field.

Team members who developed & deployed algorithm in KBase: Chris Henry, Janaka Edirisinghe, Sam Seaver, and Neal Conrad. For questions, e-mail help@kbase.us


App Specification:

https://github.com/cshenry/fba_tools/tree/584206644abfeb5f3184783aaa27b3a0993ca583/ui/narrative/methods/merge_metabolic_models_into_community_model

Module Commit: 584206644abfeb5f3184783aaa27b3a0993ca583