A murine aging cell atlas reveals cell identity and tissue-specific trajectories of aging

Abstract

Background: Aging is a pleiotropic process affecting many aspects of organismal and cellular 1 physiology. Mammalian organisms are composed of a constellation of distinct cell type and state 2 identities residing within different tissue environments. Due to technological limitations, the study 3 of aging has traditionally focused on changes within individual cell types, or the aggregate changes 4 across cell types within a tissue. The influence of cell identity and tissue environment on the trajectory 5 of aging therefore remains unclear.6Results: Here, we perform single cell RNA-seq on >50,000 individual cells across three tissues in 7 young and aged mice. These molecular profiles allow for comparison of aging phenotypes across cell 8 types and tissue environments. We find transcriptional features of aging common across many cell 9 types, as well as features of aging unique to each type. Leveraging matrix factorization and optimal 10 transport methods, we compute a trajectory and magnitude of aging for each cell type. We find that 11 cell type exerts a larger influence on these measures than tissue environment. 12Conclusion: In this study, we use single cell RNA-seq to dissect the influence of cell identity and 13 tissue environment on the aging process. Single cell analysis reveals that cell identities age in unique 14 ways, with some common features of aging shared across identities. We find that both cell identities 15 and tissue environments exert influence on the trajectory and magnitude of aging, with cell identity 16 influence predominating. These results suggest that aging manifests with unique directionality and 17 magnitude across the diverse cell identities in mammals. 18 Introduction 19Aging is a gradual process of functional and homeostatic decline in living systems. This decline results in increased 20 mortality risk and disease prevalence, eventually resulting in death. Aging appears to be a conserved feature of 21 eukaryotic biology, affecting organisms as phylogenetically diverse as the single celled S. cerevisiea, the eutelic 22 nematode C. elegans, mice, and humans [45, 63, 91]. Despite the near universal nature of the aging process, the 23 underlying causes of aging are poorly understood. Aging phenotypes have been observed and hypotheses have been 24 proposed for more than a hundred years [97, 50, 37, 64], but we do not yet know the cellular and molecular players 25 that cause aging or how they differ between biological contexts. Both the fundamental nature of aging and its negative 26 effects provide motivation to enumerate these players and establish causal relationships among aging phenotypes. 27Mammalian aging phenotypes manifest at the organismal, tissue, cellular, and molecular levels [100]. Extensive 28 research has produced catalogs of aging phenotypes at the physiological level, providing functional and behavioral 29 * Equal Contribution † Current Address: DuPont Nutrition and Biosciences, 200 Powder Mill Rd, Wilmington, DE, 19803 PREPRINT hallmarks of age related decline. Likewi...

Differentiation reveals the plasticity of age-related change in murine muscle progenitors

“…1B). This suggests that age-related changes are a smaller source of variation than cell type differences, as in previous single cell genomics studies of aging [24,2,44,83]. We recovered comparatively fewer immune cells in aged animals at the freshly-isolated time point.…”

“…After normalization and dimensionality reduction, we used a deep neural network classifier and manual validation to identify cell types from each relative mRNA abundance profile [44]. We identified skeletal muscle satellite cells (MuSCs), fibro/adipose progenitors (FAPs), endothelial cells, and multiple lymphoid cell types ( Fig.…”

“…During muscle regeneration, a subset of both MuSCs and FAPs shift cell identity and commit to cell fates by differentiation [14,92]. Recent investigations of murine aging with single cell transcriptomics report that aging manifests uniquely across distinct cell identities [2,44]. The relation-ship between aging and cellular differentiation however has been less explored.…”

“…Despite the marked functional defects of aged MuSCs during regeneration, transcriptional profiling studies have reported subtle age-related changes in MuSCs [51,19,77,42]. Transcriptional age-related changes are similarly subtle in unchallenged cells from multiple tissues in recent single cell transcriptomics atlas studies [44,83]. This disparity between functional defects and transcriptional changes suggests that some latent age-related changes may only manifest when cells are functionally challenged.…”

“…By contrast, recent developments in single cell genomics allow for the simultaneous profiling of the entire transcriptome across thousands of single cells [86]. Single cell genomics studies have already revealed novel aspects of aging in multiple tissues, including changes in the heterogeneity and distribution of cellular states and gene expression levels [46,24,2,44,83]. In the context of muscle aging, single cell genomics allows us to simultaneously identify the differentiation state of a progenitor cell and measure transcriptional features that may change with age.…”