General Information
Overview
Data ID:
SAID008
GSE:
GSE270324
GSM:
GSM3516775
Species:
Mus musculus
Disease:
Tissue:
Characteristics
Sex: pooled male and female
age: P19
strain: CD1
genotype: transgenic for Krt14-H2B-GFP
tissue: back skin
tissue location: posterior
cell type: hair follicle stem cells
sorting markers: EGFP (high), CD45 (neg) CD31 (neg) CD140a (neg), DAPI (ned), Sca-1 (neg), Alfa 6 integrin (pos) CD34 (pos)
Experiment Information
Title:
The integrated stress response fine-tunes stem cell fate decisions in response to serine deprivation and tissue injury [RNA-seq]
Summary:
Epidermal stem cells constantly rejuvenate the skin’s barrier, which excludes harmful microbes and prevents dehydration. In routine wounds, underlying hair follicle stem cells (HFSCs), normally dedicated to hair regeneration, must also reconstruct and thereafter maintain the overlying epidermis. How these fate choices are balanced to restore physiologic function to damaged tissue remains poorly understood. Here, we uncover the non-essential amino acid serine as a surprising rheostat in this process. Utilizing diet and HFSC-specific loss-of-function studies, we show that under serine-depleted conditions, HFSCs delay hair growth, and upon injury skew their fate towards epidermal re-epithelialization while concomitantly limiting hair growth. Combining temporal single-cell RNA sequencing, genetics and pharmacological intervention, we show that serine deficiency augments an injury-activated integrated stress response (ISR), boosting re-epithelization and rapidly restoring the skin’s barrier at the wound edge. Our findings integrate injury, the ISR, metabolism, tissue fate-selection and repair, offering potential for dietary and pharmacologic intervention to accelerate wound healing.
Overall Design:
Mouse hair follicle stem cells from HFSCs in telogen and anagen from K15-CrePGR; Shh+/- were isolated and transcriptomically analyzed.Reanalyzed samples were submitted to GEO previously in GSE67404 (third-party reanalysis) and in GSE123913 (self-reanalysis).
Cell Clustering
DEG Results



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