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Modulating Immune-Stem Cell Crosstalk Enables Robust Bone Regeneration via Tuning Compositions of Macroporous Scaffolds

GSE296431 Mus musculus (mouse) Single-cell RNA-seq 2 samples Submitted 2025/07/09 Platform GPL24247

At a glance

Single-cell RNA-seq · mouse · 2 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Mus musculus (mouse)
Samples: 2 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.
Paper: Modulating immune-stem cell crosstalk enables robust bone regeneration via tuning compositions of macroporous scaffoldsNPJ Regenerative medicine · 2025

Summary (written by the submitters)

Cellular crosstalk is critical for tissue healing. Following bone injury, macrophages (Mφ) initiate the immune response by secreting signals that recruit mesenchymal stem cells (MSC) and other niche cells to shape healing. Despite its importance, most studies focus on designing biomaterials that modulate individual cell type, leaving the potential of enhancing bone regeneration by modulating immune-stem cell crosstalk largely unexplored.

Read the full summary ↓

Here, we report a macroporous microribbon (µRB) scaffold with tunable ratios of gelatin (Gel) and chondroitin sulfate (CS), achieving rapid endogenous bone regeneration in a critical-sized defect model without exogenous growth factors or cells. The 3D MSC/Mφ co-culture model, but not the mono-culture model, effectively identified Gel50_CS50 as the leading ratio for accelerating bone regeneration in vivo. Single-cell sequencing (scRNAseq) of cells infiltrated at day 7 showed Gel50_CS50 led to distinct cellular compositions changes compared to Gel100, and identified a unique M2-like 2 Mφ subpopulation associated with robust bone regeneration. CellChat analysis revealed that Gel50_CS50 significantly enhanced the frequency and intensity of cellular crosstalk among Mφ and other bone niche cell types, with signaling pathways linked to immunomodulation, angiogenesis, and osteogenesis. This study demonstrates Gel50_CS50 µRB as a promising biomaterials-based therapy for treating critical-sized bone defects by modulating cellular crosstalk.

Published in

Modulating immune-stem cell crosstalk enables robust bone regeneration via tuning compositions of macroporous scaffolds

Su N, Saqib H, Villicana C et al. · NPJ Regenerative medicine 2025 · PMID 40595820 · doi:10.1038/s41536-025-00421-2

This dataset

Open GSE296431 in finder → Find more mouse 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 GSE296431_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 PRJNA1259375 and SRA study SRP583348. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40595820) ↗

Samples in this study

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+ 2 more — browse all 2 samples with per-sample file links →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.