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Identification of targets of miR-200b by a SILAC-based quantitative proteomic approach

miRNAs regulate gene expression by binding to cognate mRNAs causing mRNA degradation or translational repression. Mass spectrometry-based proteomic analysis is being widely used to identify miRNA targets. The miR-200b miRNA cluster is often overexpressed in multiple cancer types, but the identity of the targets remains elusive. Using SILAC-based analysis, we examined the effects of overexpression of a miR-200b mimic or a control miRNA in fibrosarcoma cells. We identified around 300 potential targets of miR-200b based on a change in the expression of protein levels. We validated a subset of potential targets at the transcript level using quantitative PCR

Proteogenomic analysis of Candida glabrata using high resolution mass spectrometry.

Item does not contain fulltextCandida glabrata is a common opportunistic human pathogen leading to significant mortality in immunosuppressed and immunodeficient individuals. We carried out proteomic analysis of C. glabrata using high resolution Fourier transform mass spectrometry with MS resolution of 60,000 and MS/MS resolution of 7500. On the basis of 32,453 unique peptides identified from 118,815 peptide-spectrum matches, we validated 4421 of the 5283 predicted protein-coding genes (83%) in the C. glabrata genome. Further, searching the tandem mass spectra against a six frame translated genome database of C. glabrata resulted in identification of 11 novel protein coding genes and correction of gene boundaries for 14 predicted gene models. A subset of novel protein-coding genes and corrected gene models were validated at the transcript level by RT-PCR and sequencing. Our study illustrates how proteogenomic analysis enabled by high resolution mass spectrometry can enrich genome annotation and should be an integral part of ongoing genome sequencing and annotation efforts

Development of Human Protein Reference Database as an Initial Platform for Approaching Systems Biology in Humans

Human Protein Reference Database (HPRD) is an object database that integrates a wealth of information relevant to the function of human proteins in health and disease. Data pertaining to thousands of protein-protein interactions, posttranslational modifications, enzyme/substrate relationships, disease associations, tissue expression, and subcellular localization were extracted from the literature for a nonredundant set of 2750 human proteins. Almost all the information was obtained manually by biologists who read and interpreted >300,000 published articles during the annotation process. This database, which has an intuitive query interface allowing easy access to all the features of proteins, was built by using open source technologies and will be freely available at http://www.hprd.org to the academic community. This unified bioinformatics platform will be useful in cataloging and mining the large number of proteomic interactions and alterations that will be discovered in the postgenomic era

Correspondence. Human Proteinpedia enables sharing of human protein data

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