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Lookup NU author(s): Professor John Common
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
© The Author(s) 2025. Metatranscriptomics methods for the skin are hampered by low microbial biomass, contamination with host cells and low RNA stability. In this study, we developed a robust, clinically tractable skin metatranscriptomics workflow that provides high technical reproducibility of profiles, uniform coverage across gene bodies and strong enrichment of microbial mRNAs. Paired application of this protocol with metagenomics to five skin sites in a cohort of 27 healthy adults identifies a notable divergence between transcriptomic and genomic abundances. Specifically, Staphylococcus species and the fungi Malassezia had an outsized contribution to metatranscriptomes at most sites, despite their modest representation in metagenomes. Species-level analysis shows signatures of microbial adaptation to their niches. Gene-level analysis identifies diverse antimicrobial genes transcribed by skin commensals in situ, including several uncharacterized bacteriocins. Correlation of microbial gene expression with organismal abundances uncovers more than 20 genes that putatively mediate interactions between microbes. This work highlights how skin metatranscriptomics identifies active species and microbial functions in situ.
Author(s): Chia M, Ng AHQ, Ravikrishnan A, Mohamed Naim AN, Wearne S, Common J, Nagarajan N
Publication type: Article
Publication status: Published
Journal: Nature Biotechnology
Year: 2025
Pages: Epub ahead of print
Online publication date: 28/08/2025
Acceptance date: 28/07/2025
Date deposited: 23/01/2026
ISSN (print): 1087-0156
ISSN (electronic): 1546-1696
Publisher: Springer Nature
URL: https://doi.org/10.1038/s41587-025-02797-4
DOI: 10.1038/s41587-025-02797-4
Data Access Statement: Shotgun metagenomic and metatranscriptomic sequencing data after human read removal are available from the European Nucleotide Archive (https://www.ebi.ac.uk/ena/browser/home) under project accession number PRJEB89273 (ref. 117). All large datasets, Foldseek webserver outputs, DALI webserver outputs, the Kraken 2 database used for taxonomic classification and other gene annotation databases are available on figshare at https://doi.org/10.6084/m9.figshare.c.7902962.v1 (ref. 91). Source data are provided with this paper.
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