A Single Cell Time Course of Senescence Uncovers Discrete Cell Trajectories and Transcriptional Heterogeneity

Abstract

Senescent cells (SnCs) are typically studied as endpoints of a complex transformational process, owing to their frequent maladaptive effects on surrounding tissue and cells. SnCs accumulate with age, and while they ultimately comprise a small percentage of cells in tissues, they have important roles in age associated pathologies. Several obstacles remain in understanding the heterogeneous nature of senescence, and formulating potent beneficial intervention strategies. One approach targets senescent cells and kills them ("senolytic" approach), and is often driven by a low resolution understanding of SnC identity, which risks both incomplete clearance and off-target effects. Cellular senescence is not a singular binary response, but a suite of response trajectories that vary by multiple parameters including inducer and initial cell state. In order to elucidate the developmental trajectories of SnCs, we performed single-cell RNA sequencing on IMR90 lung fibroblasts senescencing across a 12 day time period. Our analysis reveals substantial heterogeneity in gene expression within timepoints and across the full time-course. We uncovered unique markers and differentially regulated pathways in cell populations within each timepoint. Supervised trajectory inference of the time-course data uncovered the root-origin and fates of distinct SnC lineages over 3 stages of senescence induction. Altogether our data provide a novel approach to stud SnC development, identifying cell states of interest, and differentiating between SnCs and quiescent cells. This will aid in identifying key targets for therapeutic intervention in senescence.