Human skin is home to a vast community of bacteria, fungi, and viruses that help shape its protective barrier, immune defenses, and overall health. These microbes constantly interact with the skin and with one another, influencing everything from inflammation to protection against harmful organisms. Credit: Stock

The most abundant microbes on your skin may not be the ones doing most of the work.

Human skin supports vast communities of bacteria, fungi, and viruses that can influence its protective barrier, immune defenses, and overall health. Yet simply cataloging these organisms cannot reveal which ones are active, how they respond to their surroundings, or what substances they produce.

Researchers at the A*STAR Genome Institute of Singapore (A*STAR GIS) and the A*STAR Skin Research Labs (A*STAR SRL) have now developed a way to analyze microbial RNA collected directly from the skin. Described in Nature Biotechnology, the method captures gene activity rather than microbial presence alone, offering a closer look at how these communities behave on the body.

Beyond a Microbial Head Count

Most skin microbiome studies examine DNA. This can identify organisms and the genes they carry, but it cannot show whether those genes are being used. DNA may also come from inactive or dead cells, meaning abundance does not necessarily reflect biological influence.

RNA provides a more immediate record of which genes microbes have switched on. Recovering it from skin is difficult, however, because microbial material is scarce compared with samples from environments such as the gut. Human genetic material can overwhelm the microbial signal, while RNA itself is fragile and can deteriorate quickly.

The researchers overcame these obstacles with a workflow designed to enrich microbial RNA and filter out misleading signals. They tested it at five skin sites in 27 healthy adults, pairing metatranscriptomics, which measures RNA activity, with metagenomics, which identifies organisms through DNA.

The Busiest Microbes Were Not Always the Most Common

The comparison exposed a striking mismatch between population size and activity. Cutibacterium acnes accounted for 46% to 90% of the microbial DNA at most sites outside the toe webs, yet contributed only 2% to 31% of the RNA. By contrast, Malassezia fungi and Staphylococcus bacteria generated an unexpectedly large share of microbial transcripts despite sometimes appearing far less prominent in the DNA data.

This means a microbe that looks minor in a conventional survey may still be performing a major role. Measuring activity could therefore help researchers distinguish organisms that merely occupy the skin from those actively shaping its chemistry and microbial community.

Microbial activity also varied sharply across different parts of the body. Microbes altered their gene activity across the scalp, cheek, forearm, inner elbow, and toe web, each of which offers a different combination of oils, moisture, nutrients, and environmental exposure.

On the scalp and cheek, for example, microbes expressed different lipid-related genes as they adapted to the distinct oils available at each site. Organisms in toe webs showed activity suited to a moist, sweat-rich environment, while microbes on exposed forearms increased genes involved in protection against oxidative stress. Such local specialization may help explain why acne, eczema, psoriasis, and other skin conditions tend to favor particular parts of the body.

A Chemical Battle on the Skin

The team also detected genes used to produce antimicrobial substances directly on human skin. Among them were previously uncharacterized bacteriocins, compounds that bacteria can deploy against microbial competitors. Some were expressed at levels comparable to known antimicrobial genes, suggesting they may be active participants in maintaining the skin’s ecological balance.

By comparing gene expression with changes in microbial abundance, the researchers identified more than 20 genes that may help mediate interactions among skin organisms. These findings offer potential starting points for discovering natural antimicrobial molecules or developing treatments that influence selected microbes without broadly disrupting the microbiome.

Dr. Chia Minghao, Senior Scientist at A*STAR GIS, said, “With this workflow, we can now see what skin microbes are actually doing on the skin. That gives us a much richer picture of how microbial communities function, adapt to different skin sites, and potentially influence health and disease.”

New Clues for Skin Disease Research

The workflow can now be combined with genomics, metabolic modeling, and culture-based experiments to investigate how microbial activity affects human skin. Researchers could use it to identify pathways associated with disease, search for useful microbial molecules, and examine whether shifts in gene activity appear before or during symptoms.

This could be especially valuable for studying acne, eczema, and psoriasis, where the behavior of familiar microbes may matter as much as their abundance. The same organism can live harmlessly on one person or body site while contributing to inflammation under different conditions, making activity a potentially important part of the explanation.

Dr. Niranjan Nagarajan, Associate Director, AI & Compute, at A*STAR GIS, said, “This approach gives researchers and clinicians a new way to profile microbial activity directly on the skin. By revealing biological pathways linked to microbial activity and skin health, it can help identify markers and mechanisms that may be relevant for prediction, diagnosis, and treatment.”

The current research involved a relatively small group of healthy adults, so it does not yet establish which patterns cause or predict skin disease. The team plans to refine the technique and apply it in clinical studies, where comparisons between healthy and affected skin could eventually support more precise and personalized approaches to diagnosis and treatment.

Reference: “Skin metatranscriptomics reveals a landscape of variation in microbial activity and gene expression across the human body” by Minghao Chia, Amanda Hui Qi Ng, Aarthi Ravikrishnan, Ahmad Nazri Mohamed Naim, Stephen Wearne, John Common and Niranjan Nagarajan, 28 August 2025, Nature Biotechnology.
DOI: 10.1038/s41587-025-02797-4

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