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Title: Constraint-Based Model of Shewanella oneidensis MR-1 Metabolism: a Tool for Data Analysis and Hypothesis Generation

Abstract

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 tomore » 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.« less

Authors:
; ; ; ; ; ; ; ; ; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
984222
Report Number(s):
PNNL-SA-68769
KP1501021; TRN: US201015%%878
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Journal Name:
PLoS Computational Biology, 6(6):Art. No. e1000822
Additional Journal Information:
Journal Volume: 6; Journal Issue: 6
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; BACTERIA; BIOMASS; BIOSYNTHESIS; CARBON; CARBON SOURCES; CELL CONSTITUENTS; CLEAVAGE; DATA ANALYSIS; ELECTRON TRANSFER; ELECTRONS; ENZYMES; FLEXIBILITY; GENES; GLYCINE; HYPOTHESIS; METABOLISM; METABOLITES; PROTONS; SERINE; TRANSPORT

Citation Formats

Pinchuk, Grigoriy E, Hill, Eric A, Geydebrekht, Oleg V, De Ingeniis, Jessica, Zhang, Xiaolin, Osterman, Andrei, Scott, James H, Reed, Samantha B, Romine, Margaret F, Konopka, Allan, Beliaev, Alex S, Fredrickson, Jim K, and Reed, Jennifer L. Constraint-Based Model of Shewanella oneidensis MR-1 Metabolism: a Tool for Data Analysis and Hypothesis Generation. United States: N. p., 2010. Web. doi:10.1371/journal.pcbi.1000822.
Pinchuk, Grigoriy E, Hill, Eric A, Geydebrekht, Oleg V, De Ingeniis, Jessica, Zhang, Xiaolin, Osterman, Andrei, Scott, James H, Reed, Samantha B, Romine, Margaret F, Konopka, Allan, Beliaev, Alex S, Fredrickson, Jim K, & Reed, Jennifer L. Constraint-Based Model of Shewanella oneidensis MR-1 Metabolism: a Tool for Data Analysis and Hypothesis Generation. United States. https://doi.org/10.1371/journal.pcbi.1000822
Pinchuk, Grigoriy E, Hill, Eric A, Geydebrekht, Oleg V, De Ingeniis, Jessica, Zhang, Xiaolin, Osterman, Andrei, Scott, James H, Reed, Samantha B, Romine, Margaret F, Konopka, Allan, Beliaev, Alex S, Fredrickson, Jim K, and Reed, Jennifer L. 2010. "Constraint-Based Model of Shewanella oneidensis MR-1 Metabolism: a Tool for Data Analysis and Hypothesis Generation". United States. https://doi.org/10.1371/journal.pcbi.1000822.
@article{osti_984222,
title = {Constraint-Based Model of Shewanella oneidensis MR-1 Metabolism: a Tool for Data Analysis and Hypothesis Generation},
author = {Pinchuk, Grigoriy E and Hill, Eric A and Geydebrekht, Oleg V and De Ingeniis, Jessica and Zhang, Xiaolin and Osterman, Andrei and Scott, James H and Reed, Samantha B and Romine, Margaret F and Konopka, Allan and Beliaev, Alex S and Fredrickson, Jim K and Reed, Jennifer L},
abstractNote = {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.},
doi = {10.1371/journal.pcbi.1000822},
url = {https://www.osti.gov/biblio/984222}, journal = {PLoS Computational Biology, 6(6):Art. No. e1000822},
number = 6,
volume = 6,
place = {United States},
year = {Thu Jun 24 00:00:00 EDT 2010},
month = {Thu Jun 24 00:00:00 EDT 2010}
}