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  • P-III-0813

Liver proteome analysis in 111 knock-out mouse models provides crucial references for the function of genes influencing metabolic processes

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Data Integration: With Bioinformatics to Biological Knowledge

Poster

Liver proteome analysis in 111 knock-out mouse models provides crucial references for the function of genes influencing metabolic processes

Thema

  • Data Integration: With Bioinformatics to Biological Knowledge

Mitwirkende

Areum Nam (Seoul / KR), Heeyoun Hwang (Cheongju / KR), Sanghyuk Yoon (Seoul / KR), Hoonyoung Yoon (Seoul / KR), Haeju Lee (Seoul / KR), Yeo-Jin Im (Seoul / KR), Je-Yoel Cho (Seoul / KR)

Abstract

The liver serves as a metabolic orchestra, playing a pivotal role in fundamental homeostasis, including lipid, carbohydrate, and protein metabolism. Understanding how the liver copes with overloaded metabolic processes is challenging due to the numerous factors involved in the metabolic pathway. We conducted a large-scale isobaric labeling proteomics analysis using TMT on liver tissues from 111 knock-out mouse models. From this liver proteomics profiling, we discerned the informative relationships between each of the 111 genes (randomly selected by KMPC) and metabolism. Using differentially expressed proteins, we established liver-specific gene scores, named the 'Liver Impact Factor'. This factor indicates the degree of a gene's relevance to the liver. To verify the specific metabolic phenotype present in the knock-out mouse model, we turned to clinical blood chemistry analysis data. Both the proteomics data and the clinical blood chemistry data suggested a focus on cholesterol and lipid metabolism in the knock-out mouse models. We identified differentially expressed proteins (DEPs) associated with cholesterol metabolism. We performed a correlation analysis between protein expression and serum cholesterol levels to further pinpoint candidate target proteins related to cholesterol metabolism. The resulting data offers a reference for normal and abnormal mouse model liver proteomes. This correlation between liver-associated metabolic values and protein expression provides insights into potential candidate proteins related to these metabolic processes.

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