Description
Despite considerable efforts to characterize the microbial ecology of the built environment, the metabolic mechanisms underpinning microbial colonization and successional dynamics remain unclear, particularly at high moisture conditions. Here, we applied bacterial/viral particle counting, qPCR, amplicon sequencing of the genes encoding 16S and ITS rRNA, and metabolomics to longitudinally characterize the ecological dynamics of four common building materials maintained at high humidity. We varied the natural inoculum provided to each material and wet half of the samples to simulate a potable water leak. Wetted materials had higher growth rates and lower alpha diversity compared to non-wetted materials, and wetting described the majority of the variance in bacterial, fungal, and metabolite structure. Inoculation location was weakly associated with bacterial and fungal beta diversity. Material type influenced bacterial and viral particle abundance and bacterial and metabolic (but not fungal) diversity. Metabolites indicative of microbial activity were identified, and they too differed by material.
[doi:10.25345/C54N4T]
[dataset license: CC0 1.0 Universal (CC0 1.0)]
Keywords: metabolomics ; built environment
Contact
Principal Investigators:
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Jack Gilbert, University of California, San Diego, USA
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kelleheroffice
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GNPS content goes here (MSV000086209 [task=998da1c18fad44629897519c7dfd9a47])
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Distinct condition labels are counted across all files submitted in the "Metadata" category
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Originally identified proteins that were automatically
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Number of distinct proteins found to be differentially abundant in at least one comparison
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Distinct protein accessions are counted across all files submitted in the "Statistical Analysis
of Quantified Analytes" category having a "Protein" column in this dataset.
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