Quantitative Proteomic Analysis of Serum Reveals MST1 as a Potential Candidate Biomarker in Spontaneously Diabetic Cynomolgus Monkeys

血清定量蛋白质组学分析显示 MST1 是自发性糖尿病食蟹猴的潜在候选生物标志物

阅读:5
作者:Chaoyang Tian, Mingyin Qiu, Haizhou Lv, Feng Yue, Feifan Zhou

Abstract

The prevalence of type 2 diabetes (T2DM) is increasing globally, creating essential demands for T2DM animal models for the study of disease pathogenesis, prevention, and therapy. A non-human primate model such as cynomolgus monkeys can develop T2DM spontaneously in an age-dependent way similar to humans. In this study, a data-independent acquisition-based quantitative proteomics strategy was employed to investigate the serum proteomic profiles of spontaneously diabetic cynomolgus monkeys compared with healthy controls. The results revealed significant differences in protein abundances. A total of 95 differentially expressed proteins (DEPs) were quantitatively identified in the current study, among which 31 and 64 proteins were significantly upregulated and downregulated, respectively. Bioinformatic analysis revealed that carbohydrate digestion and absorption was the top enriched pathway by the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Protein-protein interaction network analysis demonstrated that MST1 was identified as the most connected protein in the network and could be considered as the hub protein. MST1 was significantly and inversely associated with FSG and HbA1c. Furthermore, recent lines of evidence also indicate that MST1 acts as a crucial regulator in regulating hepatic gluconeogenesis to maintain metabolic homeostasis while simultaneously suppressing the inflammatory processes. In conclusion, our study provides novel insights into serum proteome changes in spontaneously diabetic cynomolgus monkeys and points out that the dysregulation of several DEPs may play an important role in the pathogenesis of T2DM.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。