Bioinformatics of the Urinary Proteome

Abstract

Proteomics-based biomarker discovery studies usually entail the isolation of peptide fragments from candidate biomarkers of interest. Detection of such peptides from biological or clinical samples and identification of the corresponding full-length protein and the gene encoding that protein provide the means to gather a wealth of information. This information, termed annotation because it is attached to the gene or protein sequence under study, describes relationships to human disease, cytogenetic map position, protein domains, protein–protein and small molecule interactions, tissues or cell types in which the gene is expressed, as well as several other aspects of gene and protein function. Bioinformatics tools are employed and genome databases are mined to retrieve this information. Coupled with extensive gene and protein annotation, detected peptides are better placed in a biological context with respect to the health status of the subject. Examples of the status include cancers (bladder, kidney), metabolic disorders (diabetes and kidney function), and the nutritional state of the subject.