GEO series

Muscarinic agonism restores degenerated salivary glands through a calcium-ATP metabolic axis [snRNA-Seq]

GSE273445 Mus musculus (mouse) Single-nucleus RNA-seq 3 samples Submitted 2025/12/01 Platform GPL24247

At a glance

Single-nucleus RNA-seq · mouse · 3 samples

What it is: Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue).
Organism: Mus musculus (mouse)
Samples: 3 samples
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)

Chronic damage to tissues and organs is deemed irreversible. This has led to a focus on the development of regenerative therapies that replace tissues. Here, we break with this dogma by demonstrating that the chronically injured degenerating salivary gland can be functionally and structurally restored through a nerve-associated mechanism.

Read the full summary ↓

Extensive disruption of the chronically injured secretory acinar-nerve niche can be reversed by muscarinic agonism, with the tissue maintaining a homeostatic-like state months after treatment ends. In addition, the proportion of de-differentiated acinar cell types that appear with chronic damage are greatly reduced by muscarinic stimulation, suggesting recovery of cells critical for function. This reversal is due, in part, to re-balancing a calcium-dependent metabolic pathway that enables cell replacement. Finally, we show that radiation damaged hair follicles also benefit from muscarinic stimulation through a similar mechanism. Thus, these data challenge the concept that chronic damage is irreversible and provide a new avenue for the development of restorative treatments, a paradigm shift that can be explored more broadly.

This dataset

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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 GSE273445_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1141941 and SRA study SRP523118. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Samples in this study

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+ 3 more — browse all 3 samples with per-sample file links →

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