Title: MicrobesFlux: a web platform for drafting metabolic models from the KEGG database

Abstract

Concurrent with the efforts currently underway in mapping microbial genomes using high-throughput sequencing methods, systems biologists are building metabolic models to characterize and predict cell metabolisms. One of the key steps in building a metabolic model is using multiple databases to collect and assemble essential information about genome-annotations and the architecture of the metabolic network for a specific organism. To speed up metabolic model development for a large number of microorganisms, we need a user-friendly platform to construct metabolic networks and to perform constraint-based flux balance analysis based on genome databases and experimental results. We have developed a semi-automatic, web-based platform (MicrobesFlux) for generating and reconstructing metabolic models for annotated microorganisms. MicrobesFlux is able to automatically download the metabolic network (including enzymatic reactions and metabolites) of ~1,200 species from the KEGG database (Kyoto Encyclopedia of Genes and Genomes) and then convert it to a metabolic model draft. The platform also provides diverse customized tools, such as gene knockouts and the introduction of heterologous pathways, for users to reconstruct the model network. The reconstructed metabolic network can be formulated to a constraint-based flux model to predict and analyze the carbon fluxes in microbial metabolisms. The simulation results can be exported inmore » the SBML format (The Systems Biology Markup Language). Furthermore, we also demonstrated the platform functionalities by developing an FBA model (including 229 reactions) for a recent annotated bioethanol producer, Thermoanaerobacter sp. strain X514, to predict its biomass growth and ethanol production. MicrobesFlux is an installation-free and open-source platform that enables biologists without prior programming knowledge to develop metabolic models for annotated microorganisms in the KEGG database. Our system facilitates users to reconstruct metabolic networks of organisms based on experimental information. Through human-computer interaction, MicrobesFlux provides users with reasonable predictions of microbial metabolism via flux balance analysis. This prototype platform can be a springboard for advanced and broad-scope modeling of complex biological systems by integrating other “omics” data or ¹³C- metabolic flux analysis results.« less

Authors:

Feng, Xueyang ^[1]; Xu, You ^[2]; Chen, Yixin ^[2]; Tang, Yinjie J. ^[2]

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+ Show Author Affiliations

1. Washington University, St. Louis, MO (United States); University of Illinois at Urbana-Champaign, IL (United States)
2. Washington University, St. Louis, MO (United States)

Publication Date:

Thu Aug 02 00:00:00 EDT 2012

Research Org.:

Washington Univ., St. Louis, MO (United States)

Sponsoring Org.:

USDOE Office of Science (SC); National Science Foundation (NSF)

OSTI Identifier:

1904607

Grant/Contract Number:  

FG02-08ER64694; MCB0954016

Resource Type:

Accepted Manuscript

Journal Name:

BMC Systems Biology

Additional Journal Information:

Journal Volume: 6; Journal Issue: 1; Journal ID: ISSN 1752-0509

Publisher:

BioMed Central

Country of Publication:

United States

Language:

English

Subject:

97 MATHEMATICS AND COMPUTING; metabolic network; metabolic model; flux balance analysis; metabolic flux analysis; KEGG database