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Unleashing the potential of mRNA-seq to uncover the microbiome structure and their crosstalk with host cells: the vulvar case

GSE314734 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2026/04/30 Platform GPL30882
At a glance

RNA-seq (gene expression) · human · 36 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
36 samples: 36 × Vulvar SwabGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Unleashing the potential of mRNA-seq to uncover the microbiome structure and their crosstalk with host cells: the vulvar ecosystemMicrobiome · 2026
Summary (written by the submitters)
To comprehensively describe both host gene expression and microbiome composition in a single sample, parallel experimental and computational workflows -mRNA sequencing and either 16S or metagenomics- have been traditionally applied.
Read the full summary ↓
Here, following in vitro validation of the reliability of Poly(A)-enriched mRNA sequencing in reconstructing the microbiota composition on a defined microbial mock community, we process a cohort of 30 vulvar mRNA-seq samples to fully analyze not only the transcriptome of the vulvar cells, but also the composition of microbial communities and their parallel changes. This three-level analysis on the very same specimens further enables a gene-level exploration of the reciprocal molecular crosstalk between host and microbes. The vulvar milieu represents an area of emerging research for its role in health and disease. Being at the anatomical intersection between the vaginal milieu and the perineal area, the vulvar microbiome displays an intermediate signature, with contamination from both ecosystems. Using this unified framework, we reveal marked heterogeneity and high inter-individual variability in the vulvar microbiota of healthy individuals, identifying community state types that mirror those described in the vaginal ecosystem. Importantly, we show that distinct microbial configurations are associated with specific host transcriptional programs: Lactobacillus crispatus dominated communities correlate with epithelial differentiation and barrier integrity, whereas communities enriched in taxa associated with dysbiosis exhibit transcriptional signatures linked to inflammation. Beyond providing new biological insights into an understudied anatomical niche, our study introduces a broadly applicable strategy with substantial impact for the field. With tens of thousands of human RNA-seq datasets already available in public repositories, our approach enables retrospective extraction of microbiome information and host-microbe interaction signals from existing transcriptomic data, without the need for additional sequencing or specialized microbiome protocols. This unlocks a powerful and cost-effective opportunity to revisit archived RNA-seq studies across tissues, diseases, and low-biomass environments, revealing previously inaccessible layers of host-microbiome crosstalk and maximizing the scientific value of data that already exist.
Published in
Unleashing the potential of mRNA-seq to uncover the microbiome structure and their crosstalk with host cells: the vulvar ecosystem
Monteleone E, Cianci MA, Albano A et al. · Microbiome 2026 · PMID 42098796 · doi:10.1186/s40168-026-02420-x
This dataset
Open GSE314734 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE314734_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1392516 and SRA study SRP657333. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42098796) ↗
Study design
36 × Vulvar Swab

Supports a between-group comparison across 36 samples.

How we read this: 1 replicated groups read from 36 sample titles; they account for 36 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
Datasets on a similar topic

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