变化(天文学)
基因
表达式(计算机科学)
生物
基因表达
遗传学
进化生物学
计算机科学
物理
天体物理学
程序设计语言
作者
Minghao Chia,Amanda Hui Qi Ng,Aarthi Ravikrishnan,Ahmad Nazri Mohamed Naim,Stephen Wearne,John Common,Niranjan Nagarajan
标识
DOI:10.1101/2024.12.02.626500
摘要
The skin microbiome plays an important role in immune homeostasis and skin health, and yet our understanding of in vivo microbial gene activity is hindered by the lack of a robust, non-invasive protocol for metatranscriptomics across skin sites. Circumventing the challenges of low microbial biomass, host contamination, and RNA stability, we developed a clinically tractable skin metatranscriptomics workflow that provides high technical reproducibility of profiles (Pearson r>0.95), uniform coverage across gene bodies, and strong enrichment of microbial mRNAs (2.5-40x;). Applying this protocol to a cohort of healthy adults (n=27) across five different skin sites (n=102, paired metatranscriptomes and metagenomes), identified a striking divergence between transcriptomic and genomic abundances, with Staphylococcus species and the skin fungi Malassezia having an outsized contribution to the metatranscriptomic landscape at most sites despite their modest representation in metagenomes. Species-level analysis showed skin site-specific enrichment of gene expression (e.g. increased levels of secreted fungal phospholipase C on cheeks relative to scalp), and revealed how key pathways were transcriptionally active in vivo (e.g. propionate and 4-aminobutyrate metabolism, potentially impacting skin barrier function). Gene-level analysis identified diverse antimicrobial genes transcribed by skin commensals in situ, including several uncharacterized bacteriocins, some of which are expressed at levels comparable to known antimicrobial genes. Correlation of microbial gene expression with organismal abundances uncovered >20 genes that putatively mediate interactions between microbes (e.g. a secreted Malassezia restricta protein with strongly negative in vivo association with Cutibacterium acnes; Spearman Rho>0.7). This work showcases the potential for leveraging skin metatranscriptomics to identify microbes whose activities play an outsized role in the community, and for uncovering pivotal microbial pathways and biomarkers linked to skin health and disease.
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