Literature DB >> 20668487

Genome-scale dynamic modeling of the competition between Rhodoferax and Geobacter in anoxic subsurface environments.

Kai Zhuang1, Mounir Izallalen, Paula Mouser, Hanno Richter, Carla Risso, Radhakrishnan Mahadevan, Derek R Lovley.   

Abstract

The advent of rapid complete genome sequencing, and the potential to capture this information in genome-scale metabolic models, provide the possibility of comprehensively modeling microbial community interactions. For example, Rhodoferax and Geobacter species are acetate-oxidizing Fe(III)-reducers that compete in anoxic subsurface environments and this competition may have an influence on the in situ bioremediation of uranium-contaminated groundwater. Therefore, genome-scale models of Geobacter sulfurreducens and Rhodoferax ferrireducens were used to evaluate how Geobacter and Rhodoferax species might compete under diverse conditions found in a uranium-contaminated aquifer in Rifle, CO. The model predicted that at the low rates of acetate flux expected under natural conditions at the site, Rhodoferax will outcompete Geobacter as long as sufficient ammonium is available. The model also predicted that when high concentrations of acetate are added during in situ bioremediation, Geobacter species would predominate, consistent with field-scale observations. This can be attributed to the higher expected growth yields of Rhodoferax and the ability of Geobacter to fix nitrogen. The modeling predicted relative proportions of Geobacter and Rhodoferax in geochemically distinct zones of the Rifle site that were comparable to those that were previously documented with molecular techniques. The model also predicted that under nitrogen fixation, higher carbon and electron fluxes would be diverted toward respiration rather than biomass formation in Geobacter, providing a potential explanation for enhanced in situ U(VI) reduction in low-ammonium zones. These results show that genome-scale modeling can be a useful tool for predicting microbial interactions in subsurface environments and shows promise for designing bioremediation strategies.

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Year:  2010        PMID: 20668487      PMCID: PMC3105697          DOI: 10.1038/ismej.2010.117

Source DB:  PubMed          Journal:  ISME J        ISSN: 1751-7362            Impact factor:   10.302


  52 in total

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3.  A discrete model of bacterial metabolism.

Authors:  M R Watson
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4.  Enumeration and characterization of iron(III)-reducing microbial communities from acidic subsurface sediments contaminated with uranium(VI).

Authors:  Lainie Petrie; Nadia N North; Sherry L Dollhopf; David L Balkwill; Joel E Kostka
Journal:  Appl Environ Microbiol       Date:  2003-12       Impact factor: 4.792

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

Authors:  R Mahadevan; D R Bond; J E Butler; A Esteve-Nuñez; M V Coppi; B O Palsson; C H Schilling; D R Lovley
Journal:  Appl Environ Microbiol       Date:  2006-02       Impact factor: 4.792

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8.  Subsurface clade of Geobacteraceae that predominates in a diversity of Fe(III)-reducing subsurface environments.

Authors:  Dawn E Holmes; Regina A O'Neil; Helen A Vrionis; Lucie A N'guessan; Irene Ortiz-Bernad; Maria J Larrahondo; Lorrie A Adams; Joy A Ward; Julie S Nicoll; Kelly P Nevin; Milind A Chavan; Jessica P Johnson; Philip E Long; Derek R Lovley
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Review 9.  Applications of genome-scale metabolic reconstructions.

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Journal:  Genome Biol       Date:  2003-08-28       Impact factor: 13.583

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  100 in total

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Journal:  ISME J       Date:  2011-11-24       Impact factor: 10.302

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Review 3.  In situ to in silico and back: elucidating the physiology and ecology of Geobacter spp. using genome-scale modelling.

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Review 4.  Engineering ecosystems and synthetic ecologies.

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5.  Molecular analysis of the metabolic rates of discrete subsurface populations of sulfate reducers.

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Review 6.  Unraveling interactions in microbial communities - from co-cultures to microbiomes.

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Journal:  Proc Natl Acad Sci U S A       Date:  2015-05-04       Impact factor: 11.205

Review 8.  Using Genome-scale Models to Predict Biological Capabilities.

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9.  Anoxic Conditions Promote Species-Specific Mutualism between Gut Microbes In Silico.

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Journal:  Appl Environ Microbiol       Date:  2015-04-03       Impact factor: 4.792

Review 10.  Understanding and Engineering Distributed Biochemical Pathways in Microbial Communities.

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Journal:  Biochemistry       Date:  2018-11-20       Impact factor: 3.162

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