Microbial Communities Can Be Described by Metabolic Structure: A General Framework and Application to a Seasonally Variable, Depth-Stratified Microbial Community from the Coastal West Antarctic Peninsula

PLOS ONE, Dec 2019

Taxonomic marker gene studies, such as the 16S rRNA gene, have been used to successfully explore microbial diversity in a variety of marine, terrestrial, and host environments. For some of these environments long term sampling programs are beginning to build a historical record of microbial community structure. Although these 16S rRNA gene datasets do not intrinsically provide information on microbial metabolism or ecosystem function, this information can be developed by identifying metabolisms associated with related, phenotyped strains. Here we introduce the concept of metabolic inference; the systematic prediction of metabolism from phylogeny, and describe a complete pipeline for predicting the metabolic pathways likely to be found in a collection of 16S rRNA gene phylotypes. This framework includes a mechanism for assigning confidence to each metabolic inference that is based on a novel method for evaluating genomic plasticity. We applied this framework to 16S rRNA gene libraries from the West Antarctic Peninsula marine environment, including surface and deep summer samples and surface winter samples. Using statistical methods commonly applied to community ecology data we found that metabolic structure differed between summer surface and winter and deep samples, comparable to an analysis of community structure by 16S rRNA gene phylotypes. While taxonomic variance between samples was primarily driven by low abundance taxa, metabolic variance was attributable to both high and low abundance pathways. This suggests that clades with a high degree of functional redundancy can occupy distinct adjacent niches. Overall our findings demonstrate that inferred metabolism can be used in place of taxonomy to describe the structure of microbial communities. Coupling metabolic inference with targeted metagenomics and an improved collection of completed genomes could be a powerful way to analyze microbial communities in a high-throughput manner that provides direct access to metabolic and ecosystem function.

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Microbial Communities Can Be Described by Metabolic Structure: A General Framework and Application to a Seasonally Variable, Depth-Stratified Microbial Community from the Coastal West Antarctic Peninsula

August Microbial Communities Can Be Described by Metabolic Structure: A General Framework and Application to a Seasonally Variable, Depth-Stratified Microbial Community from the Coastal West Antarctic Peninsula Jeff S. Bowman 0 1 Hugh W. Ducklow 0 1 0 1 Lamont-Doherty Earth Observatory, Columbia University , Palisades , New York, United States of America, 2 Blue Marble Space Institute of Science , Seattle, Washington , United States of America 1 Editor: Christine Moissl-Eichinger, Medical University Graz , AUSTRIA Taxonomic marker gene studies, such as the 16S rRNA gene, have been used to successfully explore microbial diversity in a variety of marine, terrestrial, and host environments. For some of these environments long term sampling programs are beginning to build a historical record of microbial community structure. Although these 16S rRNA gene datasets do not intrinsically provide information on microbial metabolism or ecosystem function, this information can be developed by identifying metabolisms associated with related, phenotyped strains. Here we introduce the concept of metabolic inference; the systematic prediction of metabolism from phylogeny, and describe a complete pipeline for predicting the metabolic pathways likely to be found in a collection of 16S rRNA gene phylotypes. This framework includes a mechanism for assigning confidence to each metabolic inference that is based on a novel method for evaluating genomic plasticity. We applied this framework to 16S rRNA gene libraries from the West Antarctic Peninsula marine environment, including surface and deep summer samples and surface winter samples. Using statistical methods commonly applied to community ecology data we found that metabolic structure differed between summer surface and winter and deep samples, comparable to an analysis of community structure by 16S rRNA gene phylotypes. While taxonomic variance between samples was primarily driven by low abundance taxa, metabolic variance was attributable to both high and low abundance pathways. This suggests that clades with a high degree of functional redundancy can occupy distinct adjacent niches. Overall our findings demonstrate that inferred metabolism can be used in place of taxonomy to describe the structure of microbial communities. Coupling metabolic inference with targeted metagenomics and an improved collection of completed genomes could be a powerful way to analyze microbial communities in a high-throughput manner that provides direct access to metabolic and ecosystem function. - Funding: Funding provided by National Science Foundation Division of Polar Programs, http://www. nsf.gov/div/index.jsp?div=PLR, grant number 1440435 to HWD and National Science Foundation Division of Polar Programs, http://www.nsf.gov/div/ index.jsp?div=PLR, grant number 1340886 to HWD. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. Biological communities are structured by a variety of physical, chemical, and ecological environmental factors. For the marine microbial community, these include the availability of dissolved organic carbon (DOC), the distribution of bioavailable nitrogen and phosphorous, light, and temperature, among numerous other biological, chemical, and physical factors. Although microbial community structure is often described in terms of taxonomy, with clear correlations between the taxonomic composition of various microbial communities and different environmental settings [1,2], these environmental conditions are more directly linked to metabolic structure. The cyanobacterial genus Trichodesmium, for example, is associated with the low concentration of bioavailable nitrogen in the tropical and subtropical oceans. It is the metabolic properties (e.g. diazotrophy) of the genus and not its taxonomy, however, that afford a direct link with environmental conditions. To understand the role of microbial communities in biogeochemical processes it is preferable to consider the metabolic structure of a community over its taxonomic structure. The correlation between taxonomy and metabolic function [3,4] is the basis for the considerable body of work focused on the identification of community structure and composition through taxonomic marker gene analysis, namely the 16S rRNA gene. Although sometimes criticized as “stamp collecting” [5], these marker gene studies have enabled microbial ecologists to identify complex patterns of microbial diversity in a large number of geographic locations, and under widely varying environmental conditions. In contrast to the ease with which large 16S rRNA gene libraries can be generated however, it is not practical for a team of investigators to manually and exhaustively explore the metabolisms known to associate with all the observed operational taxonomic units (OTUs). More recently metagenomics (...truncated)


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Jeff S. Bowman, Hugh W. Ducklow. Microbial Communities Can Be Described by Metabolic Structure: A General Framework and Application to a Seasonally Variable, Depth-Stratified Microbial Community from the Coastal West Antarctic Peninsula, PLOS ONE, 2015, 8, DOI: 10.1371/journal.pone.0135868