Literature DB >> 32963032

Global Proteome and Phosphoproteome Characterization of Sepsis-induced Kidney Injury.

Yi-Han Lin1, Maryann P Platt1, Haiyan Fu2, Yuan Gui3, Yanlin Wang3, Norberto Gonzalez-Juarbe4, Dong Zhou5, Yanbao Yu6.   

Abstract

Sepsis-induced acute kidney injury (S-AKI) is the most common complication in hospitalized and critically ill patients, highlighted by a rapid decline of kidney function occurring a few hours or days after sepsis onset. Systemic inflammation elicited by microbial infections is believed to lead to kidney damage under immunocompromised conditions. However, although AKI has been recognized as a disease with long-term sequelae, partly because of the associated higher risk of chronic kidney disease (CKD), the understanding of kidney pathophysiology at the molecular level and the global view of dynamic regulations in situ after S-AKI, including the transition to CKD, remains limited. Existing studies of S-AKI mainly focus on deriving sepsis biomarkers from body fluids. In the present study, we constructed a mid-severity septic murine model using cecal ligation and puncture (CLP), and examined the temporal changes to the kidney proteome and phosphoproteome at day 2 and day 7 after CLP surgery, corresponding to S-AKI and the transition to CKD, respectively, by employing an ultrafast and economical filter-based sample processing method combined with the label-free quantitation approach. Collectively, we identified 2,119 proteins and 2950 phosphosites through multi-proteomics analyses. Among them, we identified an array of highly promising candidate marker proteins indicative of disease onset and progression accompanied by immunoblot validations, and further denoted the pathways that are specifically responsive to S-AKI and its transition to CKD, which include regulation of cell metabolism regulation, oxidative stress, and energy consumption in the diseased kidneys. Our data can serve as an enriched resource for the identification of mechanisms and biomarkers for sepsis-induced kidney diseases.
© 2020 Lin et al.

Entities:  

Keywords:  Quantification; acute kidney infection; biomarker: diagnostic; chronic kidney disease; infectious disease; kidney disease; label-free quantitation; mass spectrometry; omics; phosphoproteome; systems biology

Mesh:

Substances:

Year:  2020        PMID: 32963032      PMCID: PMC7710145          DOI: 10.1074/mcp.RA120.002235

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   7.381


  102 in total

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