Skip to content

amsegura/Khawaja_et_al_2024

Repository files navigation

Sex- and cell type-specific loss of chaperone-mediated autophagy across tissues with aging

Abstract

Aging is associated with a progressive decline in organ and tissue integrity that eventually leads to functional impairment. Loss of proteostasis and autophagy malfunctioning are major hallmarks of aging and contribute to accelerated progression of multiple age-related diseases. The activity of chaperone-mediated autophagy (CMA), a selective type of lysosomal degradation, has been reported to decline with age in several organs and cells from rodents and humans. Organ-specific blockage of CMA recapitulates common features of aging. Conversely, preserving or activating CMA has proven protective against age-related pathologies such as Alzheimer’s diseases, retinal degeneration, and atherosclerosis in mice. Despite this tight connection between CMA activity and aging, sex and cell-type specific differences in the impact of aging on CMA remain unexplored. Here, using CMA reporter transgenic mice and single-cell transcriptomic data, we report cell type- and sex-specific differences in basal CMA activity and in the changes in this autophagic pathway during aging. Most cell-types show an age-dependent decline in CMA, albeit of different magnitude among cell type and sex. Overall, males exhibit lower CMA activity and a greater decline with aging. Mechanistically, reduced CMA is more often associated with a decrease in lysosomes competent for CMA rather than in the overall lysosomal content. Transcriptional downregulation of CMA regulatory genes may also contribute to some of the observed changes in CMA. The uncovered differential impact of aging on CMA may underlie differential vulnerability of organs to age-related degeneration.

About

This project represent the first characterization of CMA activity along aging in different tissues, accounting for cell type variability and specificity. The CMA aging atlas is comprised by scRNA and inmunofluorescence data. The scRNA data was obtained upon analysis of the well documented repository on aging at the sigle cell level known as Tabula Muris Senis.

CMA Atlas GitHub pages