Abstract
Microorganisms almost always exist as mixed communities in nature. While the significance of microbial community activities is well appreciated, a thorough understanding about how microbial communities respond to environmental perturbations has not yet been achieved. Here we have used a combination of metagenomic, genome binning, and stimulus-induced metatranscriptomic approaches to estimate the metabolic network and stimuli-induced metabolic switches existing in a complex microbial biofilm that was producing electrical current via extracellular electron transfer (EET) to a solid electrode surface. Two stimuli were employed: to increase EET and to stop EET. An analysis of cell activity marker genes after stimuli exposure revealed that only two strains within eleven binned genomes had strong transcriptional responses to increased EET rates, with one responding positively and the other responding negatively. Potential metabolic switches between eleven dominant members were mainly observed for acetate, hydrogen, and ethanol metabolisms. These results have enabled the estimation of a multi-species metabolic network and the associated short-term responses to EET stimuli that induce changes to metabolic flow and cooperative or competitive microbial interactions. This systematic meta-omics approach represents a next step towards understanding complex microbial roles within a community and how community members respond to specific environmental stimuli.
Highlights
Cooperative, competitive, or neutral interactions that may occur between microbes[8,9]
Electron donors for the electron transfer (EET)-active microbes were supplied via the decomposition of complex organic matter in wastewater, which is usually performed by other microbes[24]; thereby, establishing successful microbial metabolic networks is necessary for maintaining a functional EET-active community
An EET-active electrogenic biofilm was established in a microbial fuel cell (MFC) bio-reactor repeatedly fed with wastewater for over 2 years[23,25]
Summary
Cooperative, competitive, or neutral interactions that may occur between microbes[8,9]. Metatranscriptomic mRNA-based analyses are used to quantify transcripts within complex microbial communities in many different environments[16,17,18], enabling the characterization of gene activity within entire communities directly through measuring levels of gene expression Many of these studies faced challenges relative to correlating gene activities with specific environmental variables because multiple variables (e.g., temperature, light, and redox) often change simultaneously. The genetic background can shift temporally[19] and/or spatially[20] along with community composition changes, adding yet another challenge to the interpretation of metatranscriptomic data While these data sets have contributed significant new knowledge relative to describing whole community activities, they cannot address each member’s functional role, metabolic interactions, or adaptability to environmental perturbations. Electron donors for the EET-active microbes were supplied via the decomposition of complex organic matter in wastewater, which is usually performed by other microbes[24]; thereby, establishing successful microbial metabolic networks is necessary for maintaining a functional EET-active community
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