Implications of time‐series gene expression profiles of replicative senescence

• Published in: Aging cell Vol. 12; no. 4; pp. 622 - 634
• Main Authors: Kim, You‐Mi, Byun, Hae‐Ok, Jee, Byul A., Cho, Hyunwoo, Seo, Yong‐Hak, Kim, You‐Sun, Park, Min Hi, Chung, Hae‐Young, Woo, Hyun Goo, Yoon, Gyesoon
• Format: Journal Article
• Language: English
• Published: England John Wiley & Sons, Inc 01.08.2013
• Subjects: Aging; Animals; Association analysis; beta-Galactosidase - genetics; beta-Galactosidase - metabolism; Cell adhesion & migration; Cell Cycle; Cell Death; Cell growth; Cell Size; Cellular Senescence; Cytokines; Developmental stages; Diploids; Diploidy; Enzyme Activation; Fibroblasts; Fibroblasts - cytology; Fibroblasts - enzymology; Fibroblasts - metabolism; Gene expression; Gene Expression Regulation; Genomes; human diploid fibroblasts; Humans; Interleukins; Interleukins - genetics; Interleukins - metabolism; Isoforms; Matrix metalloproteinase; Matrix Metalloproteinase 12 - genetics; Matrix Metalloproteinase 12 - metabolism; Morphology; Phenotype; Phenotypes; Population; Rats; Rats, Sprague-Dawley; Reactive oxygen species; Reactive Oxygen Species - metabolism; replicative senescence; Senescence; senescence‐associated secretory phenotype; Skin diseases; Time Factors; Transcriptome; β-Galactosidase; human diploid fibroblasts; replicative senescence; senescence-associated secretory phenotype; gene expression
• ISSN: 1474-9718; 1474-9726
• DOI: 10.1111/acel.12087

Summary Although senescence has long been implicated in aging‐associated pathologies, it is not clearly understood how senescent cells are linked to these diseases. To address this knowledge gap, we profiled cellular senescence phenotypes and mRNA expression patterns during replicative senescence in human diploid fibroblasts. We identified a sequential order of gain‐of‐senescence phenotypes: low levels of reactive oxygen species, cell mass/size increases with delayed cell growth, high levels of reactive oxygen species with increases in senescence‐associated β‐galactosidase activity (SA‐β‐gal), and high levels of SA‐β‐gal activity. Gene expression profiling revealed four distinct modules in which genes were prominently expressed at certain stages of senescence, allowing us to divide the process into four stages: early, middle, advanced, and very advanced. Interestingly, the gene expression modules governing each stage supported the development of the associated senescence phenotypes. Senescence‐associated secretory phenotype–related genes also displayed a stage‐specific expression pattern with three unique features during senescence: differential expression of interleukin isoforms, differential expression of interleukins and their receptors, and differential expression of matrix metalloproteinases and their inhibitory proteins. We validated these phenomena at the protein level using human diploid fibroblasts and aging Sprague‐Dawley rat skin tissues. Finally, disease‐association analysis of the modular genes also revealed stage‐specific patterns. Taken together, our results reflect a detailed process of cellular senescence and provide diverse genome‐wide information of cellular backgrounds for senescence.