Dataset Information

Unusual metabolic diversity of hyperalkaliphilic microbial communities associated with subterranean serpentinization at The Cedars.

ABSTRACT: Water from The Cedars springs that discharge from serpentinized ultramafic rocks feature highly basic (pH=~12), highly reducing (Eh<-550?mV) conditions with low ionic concentrations. These conditions make the springs exceptionally challenging for life. Here, we report the metagenomic data and recovered draft genomes from two different springs, GPS1 and BS5. GPS1, which was fed solely by a deep groundwater source within the serpentinizing system, was dominated by several bacterial taxa from the phyla OD1 ('Parcubacteria') and Chloroflexi. Members of the GPS1 community had, for the most part, the smallest genomes reported for their respective taxa, and encoded only archaeal (A-type) ATP synthases or no ATP synthases at all. Furthermore, none of the members encoded respiration-related genes and some of the members also did not encode key biosynthesis-related genes. In contrast, BS5, fed by shallow water, appears to have a community driven by hydrogen metabolism and was dominated by a diverse group of Proteobacteria similar to those seen in many terrestrial serpentinization sites. Our findings indicated that the harsh ultrabasic geological setting supported unexpectedly diverse microbial metabolic strategies and that the deep-water-fed springs supported a community that was remarkable in its unusual metagenomic and genomic constitution.

SUBMITTER: Suzuki S

PROVIDER: S-EPMC5649167 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Unusual metabolic diversity of hyperalkaliphilic microbial communities associated with subterranean serpentinization at The Cedars.

Suzuki Shino S Ishii Shun'ichi S Hoshino Tatsuhiko T Rietze Amanda A Tenney Aaron A Morrill Penny L PL Inagaki Fumio F Kuenen J Gijs JG Nealson Kenneth H KH

The ISME journal 20170721 11

Water from The Cedars springs that discharge from serpentinized ultramafic rocks feature highly basic (pH=~12), highly reducing (E<sub>h</sub><-550 mV) conditions with low ionic concentrations. These conditions make the springs exceptionally challenging for life. Here, we report the metagenomic data and recovered draft genomes from two different springs, GPS1 and BS5. GPS1, which was fed solely by a deep groundwater source within the serpentinizing system, was dominated by several bacterial taxa ...[more]

PMID: 28731475

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Project description:The profiling of 16S rRNA revolutionized the exploration of microbiomes, allowing to describe community composition by enumerating relevant taxa and their abundances. However, taxonomic profiles alone lack interpretability in terms of bacterial metabolism, and their translation into functional characteristics of microbiomes is a challenging task. This bottom-up approach minimally requires a reference collection of major metabolic traits deduced from the complete genomes of individual organisms, an accurate method of projecting these traits from a reference collection to the analyzed amplicon sequence variants (ASVs), and, ultimately, an approach to a microbiome-wide aggregation of predicted individual traits into physiologically relevant cumulative metrics to characterize and compare multiple microbiome samples. In this study, we extended a previously introduced computational approach for the functional profiling of complex microbial communities, which is based on the concept of binary metabolic phenotypes encoding the presence ("1") or absence ("0") of various measurable physiological properties in individual organisms that are termed phenotype carriers or non-carriers, respectively. Derived from complete genomes via metabolic reconstruction, binary phenotypes provide a foundation for the prediction of functional traits for each ASV identified in a microbiome sample. Here, we introduced three distinct mapping schemes for a microbiome-wide phenotype prediction and assessed their accuracy on the 16S datasets of mock bacterial communities representing human gut microbiome (HGM) as well as on two large HGM datasets, the American Gut Project and the UK twins study. The 16S sequence-based scheme yielded a more accurate phenotype predictions, while the taxonomy-based schemes demonstrated a reasonable performance to warrant their application for other types of input data (e.g., from shotgun metagenomics or qPCR). In addition to the abundance-weighted Community Phenotype Indices (CPIs) reflecting the fractional representation of various phenotype carriers in microbiome samples, we employ metrics capturing the diversity of phenotype carriers, Phenotype Alpha Diversity (PAD) and Phenotype Beta Diversity (PBD). In combination with CPI, PAD allows to classify the robustness of metabolic phenotypes by their anticipated stability in the face of potential environmental perturbations. PBD provides a promising approach for detecting the metabolic features potentially contributing to disease-associated metabolic traits as illustrated by a comparative analysis of HGM samples from healthy and Crohn's disease cohorts.

Dataset Information

Unusual metabolic diversity of hyperalkaliphilic microbial communities associated with subterranean serpentinization at The Cedars.

Publications

Unusual metabolic diversity of hyperalkaliphilic microbial communities associated with subterranean serpentinization at The Cedars.

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