The KUPKB: a novel Web application to access multiomics data on kidney disease

Abstract

The information gathered from the large number of omics experiments in renal biology is underexplored, as it is scattered over many publications or held in supplemental data. To address this, we have developed an open-source Kidney and Urinary Pathway Knowledge Base (KUPKB) that facilitates simple exploration of these omics data. The KUPKB currently comprises 220 data sets (miRNA, mRNA, proteins, and metabolites) extracted from existing publications or databases. Researchers can explore the integrated data using the iKUP browser, and a simple template is provided to submit new omics data sets to the knowledge base. As an example of iKUP's use, we show how we identified, in silico, calreticulin as a protein induced in human interstitial fibrosis and tubular atrophy (IFTA) in chronic kidney transplant rejection; a link that would have been difficult to establish using existing Web-based tools. Using immunohistochemistry, we validated in vivo this in silico result in human and rat biopsies of IFTA, thus identifying calreticulin as a potential new player in chronic kidney transplant rejection. The KUPKB provides a simple tool that enables users to quickly survey a wide range of omics data sets and has been shown to facilitate rapid hypothesis generation in the context of renal pathophysiology.

Establishment of a integrative multi-omics expression database CKDdb in the context of chronic kidney disease (CKD)

“…The majority of these databases are only focused in one or maximum two ‘omic platforms, lacking a multi-omics database that unifies the bulk of the scattered single ‘omics repositories. The Kidney and Urinary Pathway Knowledge Base (KUPKB) gave the first step to fill this gap, mining and collecting information of about 220 data sets across miRNA, mRNA, protein and metabolites in urine and kidney tissues33. Nevertheless, KUPKB only provides the molecular expression as nominal tags like ‘medium’, ‘strong’, ‘up’, ‘down’, ‘absent’, and ‘present’ which raises additionally difficulties in a forward systems level analysis that requires numerical data.…”

Applying proteomics to detect early signs of chronic kidney disease: where has the magic gone?

“…Inclusion criteria were peptidomics or proteomics case-control studies relative to CKD and only studies that examined human specimens. In addition to the literature search, the authors queried several databases including the 'Chronic Kidney Disease database' [7], 'The Kidney and Urinary Pathway Knowledge Base' [8], and the 'Human Urinary Proteome Fingerprint Database' to identify proteomic data that might produce CKD biomarker candidates [9][10][11]. The authors identified 114 manuscripts in their literature mining that fit inclusion criteria.…”

The KUPNetViz: a biological network viewer for multiple -omics datasets in kidney diseases

“…Although considerable effort has been devoted in aggregating data from several resources [5-7], the resulting databases fail to meet the multi-omics attribute and remain dispersed across the web. To address this problem, we developed the Kidney and Urinary Pathway Knowledge Base (KUPKB) [8], a publicly available repository which organizes an important amount of existing knowledge regarding renal tissue, cell and disease categorization, using Semantic Web technologies [9]. The KUPKB can be queried through the user-friendly iKUP browser, [8], accessible at http://www.kupkb.org.…”