Reconstruction and analysis of human kidney-specific metabolic network based on omics data.
With the advent of the high-throughput data production, recent studies of tissue-specific metabolic networks have largely advanced our understanding of the metabolic basis of various physiological and pathological processes. However, for kidney, which plays an essential role in the body, the available kidney-specific model remains incomplete. This paper reports the reconstruction and characterization of the human kidney metabolic network based on transcriptome and proteome data. In silico simulations revealed that house-keeping genes were more essential than kidney-specific genes in maintaining kidney metabolism. Importantly, a total of 267 potential metabolic biomarkers for kidney-related diseases were successfully explored using this model. Furthermore, we found that the discrepancies in metabolic processes of different tissues are directly corresponding to tissue's functions. Finally, the phenotypes of the differentially expressed genes in diabetic kidney disease were characterized, suggesting that these genes may affect disease development through altering kidney metabolism. Thus, the human kidney-specific model constructed in this study may provide valuable information for the metabolism of kidney and offer excellent insights into complex kidney diseases.
State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China ; Graduate School of the Chinese Academy of Sciences, Kunming 650223, China.
Ai-Di
AD
Zhang
Shao-Xing
SX
Dai
Jing-Fei
JF
Huang
D015415:Biomarkers / Q000378:metabolism*; D003198:Computer Simulation; D005786:Gene Expression Regulation; D006801:Humans; D007668:Kidney / Q000378:metabolism*; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D009928:Organ Specificity / Q000235:genetics; D020543:Proteome; D059467:Transcriptome
D015415:Biomarkers; D020543:Proteome