Proteomic quantification of native and ECM-enriched mouse ovaries reveals an age-dependent fibro-inflammatory signature

对天然和富含 ECM 的小鼠卵巢进行蛋白质组学定量分析,揭示出年龄依赖性的纤维炎症特征

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作者:Shweta S Dipali, Christina D King, Jacob P Rose, Joanna E Burdette, Judith Campisi, Birgit Schilling, Francesca E Duncan

Abstract

The ovarian microenvironment becomes fibrotic and stiff with age, in part due to increased collagen and decreased hyaluronan. However, the extracellular matrix (ECM) is a complex network of hundreds of proteins, glycoproteins, and glycans which are highly tissue specific and undergo pronounced changes with age. To obtain an unbiased and comprehensive profile of age-associated alterations to the murine ovarian proteome and ECM, we used a label-free quantitative proteomic methodology. We validated conditions to enrich for the ECM prior to proteomic analysis. Following analysis by data-independent acquisition (DIA) and quantitative data processing, we observed that both native and ECM-enriched ovaries clustered separately based on age, indicating distinct age-dependent proteomic signatures. We identified a total of 4,721 proteins from both native and ECM-enriched ovaries, of which 383 proteins were significantly altered with advanced age, including 58 ECM proteins. Several ECM proteins upregulated with age have been associated with fibrosis in other organs, but to date their roles in ovarian fibrosis are unknown. Pathways regulating DNA metabolism and translation were downregulated with age, whereas pathways involved in ECM remodeling and immune response were upregulated. Interestingly, immune-related pathways were upregulated with age even in ECM-enriched ovaries, suggesting a novel interplay between the ECM and the immune system. Moreover, we identified putative markers of unique immune cell populations present in the ovary with age. These findings provide evidence from a proteomic perspective that the aging ovary provides a fibroinflammatory milieu, and our study suggests target proteins which may drive these age-associated phenotypes for future investigation.

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