Risso2009 - Genome-scale metabolic network of Rhodoferax ferrireducens (iCR744)

Risso2009 - Genome-scale metabolic network of
Rhodoferax ferrireducens (iCR744)

This model is described in the article:

Genome-scale comparison and
constraint-based metabolic reconstruction of the facultative
anaerobic Fe(III)-reducer Rhodoferax ferrireducens.

Risso C, Sun J, Zhuang K, Mahadevan
R, DeBoy R, Ismail W, Shrivastava S, Huot H, Kothari S, Daugherty
S, Bui O, Schilling CH, Lovley DR, Methé BA.
BMC Genomics 2009; 10: 447
Abstract:

BACKGROUND: Rhodoferax ferrireducens is a metabolically
versatile, Fe(III)-reducing, subsurface microorganism that is
likely to play an important role in the carbon and metal cycles
in the subsurface. It also has the unique ability to convert
sugars to electricity, oxidizing the sugars to carbon dioxide
with quantitative electron transfer to graphite electrodes in
microbial fuel cells. In order to expand our limited knowledge
about R. ferrireducens, the complete genome sequence of this
organism was further annotated and then the physiology of R.
ferrireducens was investigated with a constraint-based,
genome-scale in silico metabolic model and laboratory studies.
RESULTS: The iterative modeling and experimental approach
unveiled exciting, previously unknown physiological features,
including an expanded range of substrates that support growth,
such as cellobiose and citrate, and provided additional
insights into important features such as the stoichiometry of
the electron transport chain and the ability to grow via
fumarate dismutation. Further analysis explained why R.
ferrireducens is unable to grow via photosynthesis or
fermentation of sugars like other members of this genus and
uncovered novel genes for benzoate metabolism. The genome also
revealed that R. ferrireducens is well-adapted for growth in
the subsurface because it appears to be capable of dealing with
a number of environmental insults, including heavy metals,
aromatic compounds, nutrient limitation and oxidative stress.
CONCLUSION: This study demonstrates that combining genome-scale
modeling with the annotation of a new genome sequence can guide
experimental studies and accelerate the understanding of the
physiology of under-studied yet environmentally relevant
microorganisms.

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