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Microbial metabolic networks in a complex electrogenic biofilm recovered from a stimulus-induced metatranscriptomics approach.

Ishii S, Suzuki S, Tenney A, Norden-Krichmar TM, Nealson KH, Bretschger O - Sci Rep (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Microbial and Environmental Genomics, J. Craig Venter Institute, La Jolla, CA 92037, USA.

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.

No MeSH data available.


Related in: MedlinePlus

Estimated metabolic network between dominant microbes within the EET-active microbial community.Metabolic roles of eleven Bin-genomes (colored rounded rectangles) are estimated from the cell activity and metabolism-associated gene expression dynamics related to EET stimuli additions. Metabolism switches between MFC and SP conditions are described by thick arrows with blue (MFC) or red (SP) color. Intracellular and extracellular EET processes are described by orange arrows. Cytoplasmic carbon metabolic flows are described by right blue arrows.
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f5: Estimated metabolic network between dominant microbes within the EET-active microbial community.Metabolic roles of eleven Bin-genomes (colored rounded rectangles) are estimated from the cell activity and metabolism-associated gene expression dynamics related to EET stimuli additions. Metabolism switches between MFC and SP conditions are described by thick arrows with blue (MFC) or red (SP) color. Intracellular and extracellular EET processes are described by orange arrows. Cytoplasmic carbon metabolic flows are described by right blue arrows.

Mentions: From the combination of metagenomic, genome binning and stimulus-induced metatranscriptomics analyses, it is possible to hypothesize the metabolic networks that exist between the eleven dominant strains within the complex EET-active microbial community (Fig. 5). Since we added EET stimuli to the community, the suggested metabolic network and metabolism shifts between microbes were identified relative to the terminal electron accepting reaction to the anode electrode. EET-active strains DB1 and DM1 competed with each other for acetate utilization and the EET rate defined which strain prevailed, which was not expected from the previous study21. Strain DB1 was more active under the higher EET-rate condition (SP), while strain DM1 was the active acetate utilizer under the lower EET-rate condition (MFC). Strain DB1 also appeared to be correlated with sulfur metabolisms like dissimilatory sulfate reduction and sulfide oxidation, but the mechanisms that strain DB1 may use for these processes are not yet clear.


Microbial metabolic networks in a complex electrogenic biofilm recovered from a stimulus-induced metatranscriptomics approach.

Ishii S, Suzuki S, Tenney A, Norden-Krichmar TM, Nealson KH, Bretschger O - Sci Rep (2015)

Estimated metabolic network between dominant microbes within the EET-active microbial community.Metabolic roles of eleven Bin-genomes (colored rounded rectangles) are estimated from the cell activity and metabolism-associated gene expression dynamics related to EET stimuli additions. Metabolism switches between MFC and SP conditions are described by thick arrows with blue (MFC) or red (SP) color. Intracellular and extracellular EET processes are described by orange arrows. Cytoplasmic carbon metabolic flows are described by right blue arrows.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4595844&req=5

f5: Estimated metabolic network between dominant microbes within the EET-active microbial community.Metabolic roles of eleven Bin-genomes (colored rounded rectangles) are estimated from the cell activity and metabolism-associated gene expression dynamics related to EET stimuli additions. Metabolism switches between MFC and SP conditions are described by thick arrows with blue (MFC) or red (SP) color. Intracellular and extracellular EET processes are described by orange arrows. Cytoplasmic carbon metabolic flows are described by right blue arrows.
Mentions: From the combination of metagenomic, genome binning and stimulus-induced metatranscriptomics analyses, it is possible to hypothesize the metabolic networks that exist between the eleven dominant strains within the complex EET-active microbial community (Fig. 5). Since we added EET stimuli to the community, the suggested metabolic network and metabolism shifts between microbes were identified relative to the terminal electron accepting reaction to the anode electrode. EET-active strains DB1 and DM1 competed with each other for acetate utilization and the EET rate defined which strain prevailed, which was not expected from the previous study21. Strain DB1 was more active under the higher EET-rate condition (SP), while strain DM1 was the active acetate utilizer under the lower EET-rate condition (MFC). Strain DB1 also appeared to be correlated with sulfur metabolisms like dissimilatory sulfate reduction and sulfide oxidation, but the mechanisms that strain DB1 may use for these processes are not yet clear.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Microbial and Environmental Genomics, J. Craig Venter Institute, La Jolla, CA 92037, USA.

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.

No MeSH data available.


Related in: MedlinePlus