Mahadevan2006 - Genome-scale metabolic network of Geobacter sulfurreducens (iRM588)

Mahadevan2006 - Genome-scale metabolic
network of Geobacter sulfurreducens (iRM588)

This model is described in the article:

Characterization of
metabolism in the Fe(III)-reducing organism Geobacter
sulfurreducens by constraint-based modeling.

Mahadevan R, Bond DR, Butler JE,
Esteve-Nuñez A, Coppi MV, Palsson BO, Schilling CH, Lovley
DR.
Appl. Environ. Microbiol. 2006 Feb;
72(2): 1558-1568
Abstract:

Geobacter sulfurreducens is a well-studied representative of
the Geobacteraceae, which play a critical role in organic
matter oxidation coupled to Fe(III) reduction, bioremediation
of groundwater contaminated with organics or metals, and
electricity production from waste organic matter. In order to
investigate G. sulfurreducens central metabolism and electron
transport, a metabolic model which integrated genome-based
predictions with available genetic and physiological data was
developed via the constraint-based modeling approach.
Evaluation of the rates of proton production and consumption in
the extracellular and cytoplasmic compartments revealed that
energy conservation with extracellular electron acceptors, such
as Fe(III), was limited relative to that associated with
intracellular acceptors. This limitation was attributed to lack
of cytoplasmic proton consumption during reduction of
extracellular electron acceptors. Model-based analysis of the
metabolic cost of producing an extracellular electron shuttle
to promote electron transfer to insoluble Fe(III) oxides
demonstrated why Geobacter species, which do not produce
shuttles, have an energetic advantage over shuttle-producing
Fe(III) reducers in subsurface environments. In silico analysis
also revealed that the metabolic network of G. sulfurreducens
could synthesize amino acids more efficiently than that of
Escherichia coli due to the presence of a pyruvate-ferredoxin
oxidoreductase, which catalyzes synthesis of pyruvate from
acetate and carbon dioxide in a single step. In silico
phenotypic analysis of deletion mutants demonstrated the
capability of the model to explore the flexibility of G.
sulfurreducens central metabolism and correctly predict mutant
phenotypes. These results demonstrate that iterative modeling
coupled with experimentation can accelerate the understanding
of the physiology of poorly studied but environmentally
relevant organisms and may help optimize their practical
applications.

This model is hosted on
BioModels Database
and identified by:
MODEL1507180000.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.

To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.