A knowledge base of vasopressin actions in the kidney

Abstract

Biological information is growing at a rapid pace, making it difficult for individual investigators to be familiar with all information that is relevant to their own research. Computers are beginning to be used to extract and curate biological information; however, the complexity of human language used in research papers continues to be a critical barrier to full automation of knowledge extraction. Here, we report a manually curated knowledge base of vasopressin actions in renal epithelial cells that is designed to be readable either by humans or by computer programs using natural language processing algorithms. The knowledge base consists of three related databases accessible at https://helixweb.nih.gov/ESBL/TinyUrls/Vaso_portal.html. One of the component databases reports vasopressin actions on individual proteins expressed in renal epithelia, including effects on phosphorylation, protein abundances, protein translocation from one subcellular compartment to another, protein-protein binding interactions, etc. The second database reports vasopressin actions on physiological measures in renal epithelia, and the third reports specific mRNA species whose abundances change in response to vasopressin. We illustrate the application of the knowledge base by using it to generate a protein kinase network that connects vasopressin binding in collecting duct cells to physiological effects to regulate the water channel protein aquaporin-2.

Database of osmoregulated proteins in mammalian cells

“…Next we used the spreadsheet to generate a Hyper Text Markup Language (HTML) file, as previously described in the Appendix of Sanghi et al. (). This was placed on a publicly accessible web server at https://helixweb.nih.gov/ESBL/Database/Osmo/.…”

“…We constructed each database entry to conform to English grammar syntax and to read from left to right as <subject> <verb phrase><object><prepositional phrase><parenthetical information>. Next we used the spreadsheet to generate a Hyper Text Markup Language (HTML) file, as previously described in the Appendix of Sanghi et al (2014). This was placed on a publicly accessible web server at https://helixweb.nih.gov/ESBL/Database/ Osmo/.…”

“…An example of a similar database on a different topic, namely vasopressin actions in the kidney, is offered by Sanghi et al. ().…”

“…The latter is necessary to facilitate computational network building. An example of a similar database on a different topic, namely vasopressin actions in the kidney, is offered by Sanghi et al (2014).…”

Inhibition of ENaC by Endothelin-1

“…Hormones are key regulators of sodium transport in the kidney and in ASDN specifically. In addition to the RAAS, it was shown that arginine vasopressin (AVP) (Ecelbarger et al, 2000; Mironova et al, 2012; Stockand, 2012; Bankir, Bouby, & Ritz, 2013; Bankir et al, 2013; Sanghi et al, 2014), atrial natriuretic peptide (ANP) (Kudo & Baird, 1984; Wang et al, 2006; Guo, Alli, Eaton, & Bao, 2013) and insulin (alongside with Insulin-like growth factor 1, IGF-1) (Blazer-Yost, Liu, & Helman, 1998; Li et al, 2013; Ilatovskaya, Pavlov, Levchenko, & Staruschenko, 2013; Pavlov et al, 2013a) are critical modulators of ENaC activity. The kallikrein-kinin systems through its peptide bradykinin also play a specific role in blunting ENaC activity, particularly under conditions of elevated sodium intake (Zaika, Mamenko, O'Neil, & Pochynyuk, 2011; Mamenko, Zaika, Doris, & Pochynyuk, 2012; Mamenko, Zaika, & Pochynyuk, 2014).…”