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首页> 外文期刊>The ISME journal emultidisciplinary journal of microbial ecology >Genome-scale dynamic modeling of the competition between Rhodoferax and Geobacter in anoxic subsurface environments
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Genome-scale dynamic modeling of the competition between Rhodoferax and Geobacter in anoxic subsurface environments

机译:缺氧地下环境中杜鹃与地细菌竞争的基因组规模动态建模

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摘要

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.
机译:快速完整的基因组测序的出现以及在基因组规模的代谢模型中捕获此信息的潜力,为全面模拟微生物群落相互作用提供了可能性。例如,Rhodoferax和Geobacter菌种是在缺氧的地下环境中竞争的乙酸盐氧化Fe(III)还原剂,这种竞争可能会对铀污染的地下水的原位生物修复产生影响。因此,使用了减少细菌的土壤细菌基因组规模模型和铁还原性的杜鹃铁血球菌基因组规模模型,以评估在科罗拉多州来福市受铀污染的含水层中发现的细菌和细菌在不同条件下如何竞争。该模型预测,在预期的乙酸盐通量较低的情况下在现场自然条件下,只要有足够的铵盐,杜鹃花将比Geobacter竞争。该模型还预测,在原位生物修复过程中添加高浓度的乙酸盐时,与现场规模的观察结果一致,土杆菌将占主导地位。这可以归因于红景天的更高的预期生长产量以及土杆菌固定氮的能力。该模型预测了Rifle站点地球化学不同区域中的Geobacter和Rhodoferax的相对比例,该比例与之前用分子技术记录的相对比。该模型还预测,在固氮作用下,较高的碳通量和电子通量将转移到呼吸作用,而不是在土壤细菌中形成生物量,这为增强低铵区原位U(VI)还原提供了可能的解释。这些结果表明,基因组规模的建模可以成为预测地下环境中微生物相互作用的有用工具,并显示出设计生物修复策略的希望。

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