Abstract
Lithified layers of complex microbial mats known as microbialites are ubiquitous in the fossil record, and modern forms are increasingly identified globally. A key challenge to developing an understanding of microbialite formation and environmental role is how to investigate complex and diverse communities in situ. We selected living, layered microbialites (stromatolites) in a peritidal environment near Schoenmakerskop, Eastern Cape, South Africa to conduct a spatial survey mapping the composition and small molecule production of the microbial communities from environmental samples. Substrate core samples were collected from nine sampling stations ranging from the upper point of the freshwater inflow to the lower marine interface where tidal overtopping takes place. Substrate cores provided material for parallel analyses of microbial community diversity by 16S rRNA gene amplicon sequencing and metabolomics using LC–MS2. Species and metabolite diversities were correlated, and prominent specialized metabolites were targeted for preliminary characterization. A new series of cyclic hexadepsipeptides, named ibhayipeptolides, was most abundant in substrate cores of submerged microbialites. These results demonstrate the detection and identification of metabolites from mass-limited environmental samples and contribute knowledge about microbialite chemistry and biology, which facilitates future targeted studies of specialized metabolite function and biosynthesis.
Supplementary materials
Title
Supporting Information: Environmental metabolomics characterization of modern stromatolites and annotation of ibhayipeptolides
Description
GIS image of the stromatolite pool; photographs of flagged collection stations in the stromatolite pool; 16S rRNA phylogenetic analyses; Canopus sunburst plots; MS/MS spectra and SIRIUS5 fragmentation trees for ibhayipeptolides A-D; NMR data for ibhayipeptolides A-D; parameters for MZMine2 and SIRIUS4 MS processing
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Supplementary weblinks
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Zenodo data repository
Description
Minimal underlying data sets and code for for microbial 16S rRNA and LCMS data analyses.
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