Paper Single-cell transcriptomic analysis uncovers diverse and dynamic senescent cell populations

Senescence is a state of enduring growth arrest triggered by sublethal cell damage. Given that senescent cells actively secrete proinflammatory and matrix-remodeling proteins, their accumulation in tissues of older persons has been linked to many diseases of aging. Despite intense interest in identifying robust markers of senescence, the highly heterogeneous and dynamic nature of the senescent phenotype has made this task difficult. Here, we set out to comprehensively analyze the senescent transcriptome of human diploid fibroblasts at the individual -cell scale by performing single-cell RNA-sequencing analysis through two approaches. First, we characterized the different cell states in cultures undergoing senescence triggered by different stresses, and found distinct cell subpopulations that expressed mRNAs encoding proteins with roles in growth arrest, survival, and the secretory phenotype. Second, we characterized the dynamic changes in the transcriptomes of cells as they developed etoposide-induced senescence; by tracking cell transitions across this process, we found two different senescence programs that developed divergently, one in which cells expressed traditional senescence markers such as p16 (CDKN2A) mRNA, and another in which cells expressed long noncoding RNAs and splicing was dysregulated. Finally, we obtained evidence that the proliferation status at the time of senescence initiation affected the path of senescence, as determined based on the expressed RNAs. We propose that a deeper understanding of the transcriptomes during the progression of different senescent cell phenotypes will help develop more effective interventions directed at this detrimental cell population.

Automated summary

Senescence is a state of enduring growth arrest triggered by sublethal cell damage, and the accumulation of senescent cells in older individuals has been linked to age-related diseases. However, identifying robust markers of senescence has been challenging due to the heterogeneous and dynamic nature of the senescent phenotype. In this study, single-cell RNA-sequencing analysis was used to comprehensively analyze the senescent transcriptome of human diploid fibroblasts, revealing distinct cell subpopulations and dynamic changes in gene expression during senescence. This research provides a deeper understanding of senescent cell phenotypes and may lead to the development of more effective interventions.