Constraint-Based Model of Shewanella oneidensis MR-1 Metabolism: a Tool for Data Analysis and Hypothesis Generation
Shewanellae are gram-negative facultatively anaerobic metal-reducing bacteria commonly found in chemically (i.e., redox) stratified environments. Occupying such niches requires the ability to rapidly acclimate to changes in electron donor/acceptor type and availability; hence, the ability to compete and thrive in such environments must ultimately be reflected in the organization and flexibility of the electron transfer networks as well as central and peripheral carbon metabolism pathways. To understand the factors contributing to the ecophysiological success of Shewanellae, the metabolic network of S. oneidensis MR-1 was reconstructed. The resulting network consists of 774 reactions, 783 genes, and 634 unique metabolites and contains biosynthesis pathways for all cell constituents. Using constraint-based modeling, we investigated aerobic growth of S. oneidensis MR-1 on numerous carbon sources. To achieve this, we (i) used experimental data to formulate a biomass equation and estimate cellular ATP requirements, (ii) developed an approach to identify futile cycles, (iii) classified how reaction usage affects cellular growth, (iv) predicted cellular biomass yields on different carbon sources and compared model predictions to experimental measurements, and (v) used experimental results to refine metabolic fluxes for growth on lactate. The results revealed that aerobic lactate-grown cells of S. oneidensis MR-1 used less efficient enzymes to couple electron transport to proton motive force generation, and possibly operated at least one futile cycle involving malic enzymes. Several examples are provided whereby model predictions were validated by experimental data, in particular the role of serine hydroxymethyltransferase and glycine cleavage system in the metabolism of one-carbon units, and growth on different sources of carbon and energy. This work illustrates how integration of computational and experimental efforts facilitates the understanding of microbial metabolism at a systems level and the discovery of new physiological properties.
- Research Organization:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-76RL01830
- OSTI ID:
- 984222
- Report Number(s):
- PNNL-SA-68769; KP1501021; TRN: US201015%%878
- Journal Information:
- PLoS Computational Biology, 6(6):Art. No. e1000822, Vol. 6, Issue 6
- Country of Publication:
- United States
- Language:
- English
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