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StoneMod: a database for kidney stone modulatory proteins with experimental evidence.

ABSTRACT: Better understanding of molecular mechanisms for kidney stone formation is required to improve management of kidney stone disease with better therapeutic outcome. Recent kidney stone research has indicated critical roles of a group of proteins, namely 'stone modulators', in promotion or inhibition of the stone formation. Nevertheless, such information is currently dispersed and difficult to obtain. Herein, we present the kidney stone modulator database (StoneMod), which is a curated resource by obtaining necessary information of such stone modulatory proteins, which can act as stone promoters or inhibitors, with experimental evidence from previously published studies. Currently, the StoneMod database contains 10, 16, 13, 8 modulatory proteins that affect calcium oxalate crystallization, crystal growth, crystal aggregation, and crystal adhesion on renal tubular cells, respectively. Informative details of each modulatory protein and PubMed links to the published articles are provided. Additionally, hyperlinks to other protein/gene databases (e.g., UniProtKB, Swiss-Prot, Human Protein Atlas, PeptideAtlas, and Ensembl) are made available for the users to obtain additional in-depth information of each protein. Moreover, this database provides a user-friendly web interface, in which the users can freely access to the information and/or submit their data to deposit or update. Database URL: https://www.stonemod.org .

SUBMITTER: Sassanarakkit S

PROVIDER: S-EPMC7493926 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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StoneMod: a database for kidney stone modulatory proteins with experimental evidence.

Sassanarakkit Supatcha S Peerapen Paleerath P Thongboonkerd Visith V

Scientific reports 20200915 1

Better understanding of molecular mechanisms for kidney stone formation is required to improve management of kidney stone disease with better therapeutic outcome. Recent kidney stone research has indicated critical roles of a group of proteins, namely 'stone modulators', in promotion or inhibition of the stone formation. Nevertheless, such information is currently dispersed and difficult to obtain. Herein, we present the kidney stone modulator database (StoneMod), which is a curated resource by ...[more]

PMID: 32934277

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Project description:BackgroundProteins are the most abundant component of kidney stone matrices and their presence may reflect the process of the stone's formation. Many studies have explored the proteomics of urinary stones and crystals. We sought to comprehensively identify the proteins found in kidney stones and to identify new, reliable biomolecules for use in nephrolithiasis research.MethodsWe conducted bioinformatics research in November 2020 on the proteomics of urinary stones and crystals. We used the ClusterProfiler R package to transform proteins into their corresponding genes and Ensembl IDs. In each study we located where proteomic results intersected to determine the 20 most frequently identified stone matrix proteins. We used the Human Protein Atlas to obtain the biological information of the 20 proteins and conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) analysis to explore their biological functions. We also performed immunohistochemistry to detect the expression of the top five stone matrix proteins in renal tissue.ResultsWe included 19 relevant studies for analysis. We then identified 1,409 proteins in the stone matrix after the duplicates were removed. The 20 most-commonly identified stone matrix proteins were: S100A8, S100A9, uromodulin, albumin, osteopontin, lactotransferrin, vitamin K-dependent protein Z, prothrombin, hemoglobin subunit beta, myeloperoxidase, mannan-binding lectin serine protease 2, lysozyme C, complement C3, serum amyloid P-component, cathepsin G, vitronectin, apolipoprotein A-1, eosinophil cationic protein, fibrinogen alpha chain, and apolipoprotein D. GO and KEGG analysis revealed that these proteins were typically engaged in inflammation and immune response.Immunohistochemistry of the top five stone matrix proteins in renal tissue showed that the expression of S100A8, S100A9, and osteopontin increased, while uromodulin decreased in kidney stone patients. Albumin was rarely expressed in the kidney with no significant difference between healthy controls and kidney stone patients.ConclusionProteomic analysis revealed some common inflammation-related proteins in the kidney stone matrix. The role of these proteins in stone formation should be explored for their potential use as diagnostic biomarkers and therapeutic targets for urolithiasis.

Dataset Information

StoneMod: a database for kidney stone modulatory proteins with experimental evidence.

Publications

StoneMod: a database for kidney stone modulatory proteins with experimental evidence.

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