Only a small fraction of skin microorganisms can be cultured using standard techniques. This is why culture-independent molecular methods have become the essential foundation of skin microbiome analysis. From 16S rRNA sequencing to metabolomics, each technique answers a different question, with its own resolution level and cost. Here is how to choose the right method for your claim, and how to turn raw data into usable scientific evidence.
Overview of high-throughput sequencing techniques
Culture-independent methods have become indispensable for comprehensive microbiome analysis, since they remove the constraint of in vitro culture, which excludes most skin species. Each technique covers a distinct level of information:
- 16S rRNA sequencing identifies the bacterial taxa present in a sample;
- ITS sequencing characterizes fungal communities;
- shotgun metagenomics enables evaluation of all microbial genes present in a sample, with finer taxonomic resolution than 16S;
- metatranscriptomics assesses active gene expression, meaning which genes are actually being expressed at a given time, not merely present;
- metabolomics and proteomics reveal the functional consequences of microbial activity, precisely documenting a product’s impact at both the community and molecular levels.
A useful cost benchmark for scoping a study budget: the cost of 16S rRNA sequencing dropped more than tenfold between 2015 and 2024, making much larger clinical datasets accessible than before.
A sensitivity issue: detection threshold changes how results should be read
Not all sequencing methods share the same sensitivity, and this parameter has direct consequences for how a claim result should be interpreted:
- 16S sequencing detects species present from an abundance threshold of around 0.1%;
- shotgun metagenomics can detect taxa down to an abundance threshold of around 0.01%, ten times more sensitive.
In practice, a minority species that may still be functionally significant can be invisible in 16S data yet detected via shotgun. This methodological choice should therefore be settled upstream of the protocol, based on the nature of the claim (overall composition versus detection of specific low-abundance species).
The table below summarizes the main molecular methods available.
| Method | What it measures | Threshold / resolution | Typical use |
|---|---|---|---|
| 16S rRNA sequencing | Bacterial taxa present | Abundance ≥ 0.1% | Composition mapping, routine studies |
| ITS sequencing | Fungal communities | Taxonomic equivalent for fungi | Claims targeting the fungal microbiome (dandruff, etc.) |
| Shotgun metagenomics | All microbial genes in the sample | Abundance ≥ 0.01% | Fine detection, deeper taxonomic resolution |
| Metatranscriptomics | Active gene expression | Genes actually expressed, not just present | Real-time functional evidence |
| Metabolomics / proteomics | Metabolites and proteins produced | Functional consequences of microbial activity | Product impact at the molecular level |
From raw data to a validated claim
The volume of data generated by these techniques only has value if it is properly processed. Robust microbiome analysis requires advanced bioinformatics and statistical pipelines: sequencing outputs are processed to quantify relative abundance, diversity indices, and functional gene expression. Integrated platforms such as HolXplore or Byome Labs enable multi-layered interpretation combining metagenomics, proteomics, and metabolomics within a single dataset.
Bioinformatics also makes it possible to identify cause-effect relationships, functional correlations with host physiology, and to build predictive models of microbial response to a cosmetic ingredient. This level of analysis is what allows a simple observation to become validated mechanistic proof. A concrete example from the literature: moving from “the product changes the quantity of bacteria” to “the product increases the relative abundance of the S. epidermidis taxon by 15%, and our metagenomic data show this increase is associated with a rise in the expression of anti-inflammatory genes.” This level of detail is what makes it possible to validate complex claims such as “maintains microbial balance” or “protects the skin’s natural defenses.”
To identify laboratories equipped with these sequencing technologies and the associated bioinformatics pipelines, the Skinobs platform references providers specialized in molecular microbiome analysis.
Discover skin microbiome testing solutions on Skinobs → https://www.skinobs.com/
