Sturmlechner, I. | bioRxiv Science

bioRxiv2022

HD-PTP/PTPN23 hypomorphic mice display lipodystrophy

Endosomal Sorting Complexes Required for Transport (ESCRTs) drive reverse topology membrane remodeling events including the formation of intralumenal vesicles within multivesicular bodies, the budding of retroviruses from the plasma membrane, and the scission of the cytokinetic bridge. It has been difficult to study the physiological relevance of this machinery in mammals because many contributing components are essential for viability. To bypass this problem we used combinations of knockout (-), hypomorphic (H) and wildtype (+) alleles to generate a series of mice with a gradual reduction of HD-PTP (product of PTPN23), an ESCRT-associated protein known to cause embryonic lethality when fully depleted. Whereas PTPN23-/H mice died shortly after birth, PTPN23H/H mice developed into adulthood but had reduced size, lipodystrophy, and shortened lifespan. Analysis of 14-day inguinal adipose tissue indicated reduced expression of adipogenesis markers, and PTPN23 knockout preadipocytes similarly display reduced adipogenesis in vitro. Defects in insulin-stimulated signaling were apparent in differentiated PTPN23 knockout adipocytes and PTPN23H/H inguinal adipose tissue in vitro, correlating with reduced levels of insulin signaling hallmarks observed in adult PTPN23H/H inguinal adipose tissue in vivo. Whereas the ESCRT machinery have been suggested to downregulate signaling, these results indicate that HD-PTP promotes insulin-induced signaling in, as well as differentiation of, inguinal adipose tissue. These results revealed unexpected roles for HD-PTP in promoting fat accumulation in mammalian cells through supporting insulin signaling, adipogenesis, and lipid droplet formation.

cell biology↗

bioRxiv2022

Transfer learning of an in vivo-derived senescence signature identifies conserved and tissue-specific senescence across species and diverse pathologies

Senescent cells (SnCs) contribute to normal tissue development and repair but accumulate with aging where they are implicated in a number of pathologies and diseases. Despite their pathological role and therapeutic interest, SnC phenotype and function in vivo remains unclear due to the challenges in identifying and isolating these rare cells. Here, we developed an in vivo-derived senescence gene expression signature using a model of the foreign body response (FBR) fibrosis in a p16Ink4a-reporter mouse, a cell cycle inhibitor commonly used to identify SnCs. We identified stromal cells (CD45-CD31- CD29+) as the primary p16Ink4a expressing cell type in the FBR and collected the cells to produce a SnC transcriptomic signature with bulk RNA sequencing. To computationally identify SnCs in bulk and single-cell data sets across species and tissues, we used this signature with transfer learning to generate a SnC signature score (SenSig). We found senescent pericyte and cartilage-like fibroblasts in newly collected single cell RNAseq (scRNASeq) data sets of murine and human FBR suggesting populations associated with angiogenesis and secretion of fibrotic extracellular matrix, respectively. Application of the senescence signature to human scRNAseq data sets from idiopathic pulmonary fibrosis (IPF) and the basal cell carcinoma microenvironment identified both conserved and tissue-specific SnC phenotypes, including epithelial-derived basaloid and endothelial cells. In a wound healing model, ligand-receptor signaling prediction identified putative interactions between SnC SASP and myeloid cells that were validated by immunofluorescent staining and in vitro coculture of SnCs and macrophages. Collectively, we have found that our SenSig transfer learning strategy from an in vivo signature outperforms in vitro-derived signatures and identifies conserved and tissue-specific SnCs and their SASP, independent of p16Ink4a expression, and may be broadly applied to elucidate SnC identity and function in vivo.

bioengineering↗