Poster Presentation 27th Annual Lorne Proteomics Symposium 2022

Proteomic analysis of muscle cell organoid identifies proteins and pathways associated with aging (#134)

Jiwon Kim 1 , Min-Sik Kim 2 , Minseok S. Kim 2 , Jason K. Sa* 3
  1. Korea University, Seongbuk-gu, SEOUL, South Korea
  2. Department of New Biology, Daegu Gyeongbuk Institute of Science & Technology, Dalseong-gun, Daegu, South Korea
  3. Department of Biomedical Sciences, Korea University College of Medicine, Seongbuk-gu, Seoul, South Korea

Purpose: Aging is an imperative process which often leads to declining of bodily functions and development of chronic diseases. Identification of underlying molecular mechanism could facilitate adaptation of alternative treatment opportunities within clinical practice. Proteomics reveal information about end-product of molecular processes, furthermore it provides insight into the changing of intercellular function by aging. In order to identify potential biomarkers for maintaining healthy life, our study aims to distinguish proteins or pathways that are specifically enriched in young versus old individuals via proteomic analysis.

 

Method: We utilized mass spectrometry to quantify protein expression in muscle cell-derived organoid models from three young and old individuals. The quantified protein expression was analyzed through differentially expressed protein (DEP) analysis. Proteins that are specifically expressed in muscle tissues from The Human Protein Atlas were compared between young and old organoid models. In addition, through Gene Set Enrichment Analysis (GSEA) analysis, significantly up-regulated pathways were identified between young and old groups, and pathway clusters related to aging were discovered through pathway annotation.

 

Results: A total of 5,727 proteins were identified via mass spectrometry. 75 proteins significantly enriched in young organoid models and 86 proteins were highly up-regulated in old group through DEP analysis. Based on The Human Protein atlas, 5 proteins were identified as potential biomarkers that could distinguish young individuals from old. Moreover, 202 pathways that were associated with translation regulation, cholesterol biosynthesis and cell cycle were considerably more enriched in the young group, whereas 127 pathways that were associated with cell growth factor, hepatocytes differentiation were significantly elevated in the old group through GSEA (p-value <0.05).

 

Conclusion: Collectively, our study presents a comprehensive overview on biological differences between young and old individual at both protein and pathway levels. Compared to the old group, highly expressed proteins in the young group could be employed as potential antiaging biomarkers for design of exercise simulation system as well as diagnostic kits.