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Pasteurized Akkermansia muciniphila ameliorates preeclampsia via inhibiting mitochondrial dysfunction-mediated placental apoptosis in vivo and in vitro

GSE287713 Homo sapiens (human) RNA-seq (gene expression) 9 samples Submitted 2026/06/30 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 9 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
9 samples: 9 samples, each with a distinct title — no replicated groupsGroups 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.
Summary (written by the submitters)
Preeclampsia (PE) is a severe metabolic disorder that occurs during pregnancy and is linked to dysbiosis of the gut microbiota, characterised by a decrease in Akkermansia muciniphila (AKK). Emerging evidence suggests that pasteurised Akkermansia muciniphila (pAKK) is a promising candidate for preventing or treating obesity-related metabolic disorders.
Read the full summary ↓
Nonetheless, the modulatory function and underlying mechanisms of pAKK as a supplement for PE have yet to be investigated. In this study, we examined the impact of pAKK oral administration on PE and its underlying mechanisms. Our findings demonstrate that pAKK significantly improved PE-like symptoms in mice induced by nitro-L-arginine methylester (L-NAME) in a dose-dependent manner. Importantly, pAKK inhibited L-NAME-induced placental apoptosis, countered apoptosis-related biochemical alterations like the increase in the Bax/Bcl-2 ratio, and the activation of cleaved-Caspase-3, alongside mitigating L-NAME-induced placental mitochondrial dysfunction. Hypoxia-reoxygenation (H/R)-induced HTR8/SVneo cells have been established as an in vitro model to mimic the condition of PE. Interestingly, similar results were also obtained in vitro; mitochondrial dysfunction-mediated apoptosis induced by H/R in HTR-8/SVneo cells was prevented by pAKK. Furthermore, the PI3K inhibitor (LY294002) significantly negated the protective effects of pAKK on mitochondrial dysfunction and apoptosis. Our findings indicate that pAKK improved PE-like symptoms both in vivo and in vitro by activating the PI3K/Akt signalling pathway, highlighting the potential for developing a probiotic therapeutic agent based on AKK for PE.
This dataset
Open GSE287713 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 GSE287713_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 PRJNA1214288 and SRA study SRP559155. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
9 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 9 sample titles: 9 distinct titles with little repetition. 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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