Metagenomics reveals niche partitioning within the phototrophic zone of a microbial mat
Abstract
Hypersaline photosynthetic microbial mats are stratified microbial communities known for their taxonomic and metabolic diversity and strong light-driven day-night environmental gradients. In this study of the upper photosynthetic zone of hypersaline microbial mats of Elkhorn Slough, California (USA), we show how metagenome sequencing can be used to meaningfully assess microbial ecology and genetic partitioning in these complex microbial systems. Mapping of metagenome reads to the dominant Cyanobacteria observed in the system, Coleofasciculus (Microcoleus) chthonoplastes, was used to examine strain variants within these metagenomes. Highly conserved gene subsystems indicated a core genome for the species, and a number of variant genes and subsystems suggested strain level differentiation, especially for nutrient utilization and stress response. Metagenome sequence coverage binning was used to assess ecosystem partitioning of remaining microbes to both reconstruct the model organisms in silico and identify their ecosystem functions as well as to identify novel clades and propose their role in the biogeochemical cycling of mats. Functional gene annotation of these bins (primarily of Proteobacteria, Bacteroidetes, and Cyanobacteria) recapitulated the known biogeochemical functions in microbial mats using a genetic basis, and revealed significant diversity in the Bacteroidetes, presumably in heterotrophic cycling. This analysis also revealed evidence of putative phototrophs withinmore »
- Authors:
-
- NASA Ames Research Center (ARC), Moffett Field, Mountain View, CA (United States). Exobiology Branch; Bay Area Environmental Research Institute, Petaluma, CA (United States)
- NASA Ames Research Center (ARC), Moffett Field, Mountain View, CA (United States). Exobiology Branch
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Earth and Environmental Sciences
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Physical and Life Sciences Directorate
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC); USDOE National Nuclear Security Administration (NNSA)
- OSTI Identifier:
- 1477376
- Alternate Identifier(s):
- OSTI ID: 1513102
- Report Number(s):
- LLNL-JRNL-731625
Journal ID: ISSN 1932-6203; ark:/13030/qt87s3w18d
- Grant/Contract Number:
- AC02-05CH11231; AC52-07NA27344
- Resource Type:
- Journal Article: Accepted Manuscript
- Journal Name:
- PLoS ONE
- Additional Journal Information:
- Journal Volume: 13; Journal Issue: 9; Journal ID: ISSN 1932-6203
- Publisher:
- Public Library of Science
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; 59 BASIC BIOLOGICAL SCIENCES
Citation Formats
Lee, Jackson Z., Everroad, R. Craig, Karaoz, Ulas, Detweiler, Angela M., Pett-Ridge, Jennifer, Weber, Peter K., Prufert-Bebout, Leslie, and Bebout, Brad M. Metagenomics reveals niche partitioning within the phototrophic zone of a microbial mat. United States: N. p., 2018.
Web. doi:10.1371/journal.pone.0202792.
Lee, Jackson Z., Everroad, R. Craig, Karaoz, Ulas, Detweiler, Angela M., Pett-Ridge, Jennifer, Weber, Peter K., Prufert-Bebout, Leslie, & Bebout, Brad M. Metagenomics reveals niche partitioning within the phototrophic zone of a microbial mat. United States. https://doi.org/10.1371/journal.pone.0202792
Lee, Jackson Z., Everroad, R. Craig, Karaoz, Ulas, Detweiler, Angela M., Pett-Ridge, Jennifer, Weber, Peter K., Prufert-Bebout, Leslie, and Bebout, Brad M. Tue .
"Metagenomics reveals niche partitioning within the phototrophic zone of a microbial mat". United States. https://doi.org/10.1371/journal.pone.0202792. https://www.osti.gov/servlets/purl/1477376.
@article{osti_1477376,
title = {Metagenomics reveals niche partitioning within the phototrophic zone of a microbial mat},
author = {Lee, Jackson Z. and Everroad, R. Craig and Karaoz, Ulas and Detweiler, Angela M. and Pett-Ridge, Jennifer and Weber, Peter K. and Prufert-Bebout, Leslie and Bebout, Brad M.},
abstractNote = {Hypersaline photosynthetic microbial mats are stratified microbial communities known for their taxonomic and metabolic diversity and strong light-driven day-night environmental gradients. In this study of the upper photosynthetic zone of hypersaline microbial mats of Elkhorn Slough, California (USA), we show how metagenome sequencing can be used to meaningfully assess microbial ecology and genetic partitioning in these complex microbial systems. Mapping of metagenome reads to the dominant Cyanobacteria observed in the system, Coleofasciculus (Microcoleus) chthonoplastes, was used to examine strain variants within these metagenomes. Highly conserved gene subsystems indicated a core genome for the species, and a number of variant genes and subsystems suggested strain level differentiation, especially for nutrient utilization and stress response. Metagenome sequence coverage binning was used to assess ecosystem partitioning of remaining microbes to both reconstruct the model organisms in silico and identify their ecosystem functions as well as to identify novel clades and propose their role in the biogeochemical cycling of mats. Functional gene annotation of these bins (primarily of Proteobacteria, Bacteroidetes, and Cyanobacteria) recapitulated the known biogeochemical functions in microbial mats using a genetic basis, and revealed significant diversity in the Bacteroidetes, presumably in heterotrophic cycling. This analysis also revealed evidence of putative phototrophs within the Gemmatimonadetes and Gammaproteobacteria residing in microbial mats. This study shows that metagenomic analysis can produce insights into the systems biology of microbial ecosystems from a genetic perspective and to suggest further studies of novel microbes.},
doi = {10.1371/journal.pone.0202792},
url = {https://www.osti.gov/biblio/1477376},
journal = {PLoS ONE},
issn = {1932-6203},
number = 9,
volume = 13,
place = {United States},
year = {2018},
month = {9}
}
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