Biomedical subjects

Raghunath Reddy

Publications and source records attributed to Raghunath Reddy.

6 recordsLinked to original sources

PubMed2006

Human protein reference database--2006 update.

Human Protein Reference Database (HPRD) (http://www.hprd.org) was developed to serve as a comprehensive collection of protein features, post-translational modifications (PTMs) and protein-protein interactions. Since the original report, this database has increased to >20 000 proteins entries and has become the largest database for literature-derived protein-protein interactions (>30 000) and PTMs (>8000) for human proteins. We have also introduced several new features in HPRD including: (i) protein isoforms, (ii) enhanced search options, (iii) linking of pathway annotations and (iv) integration of a novel browser, GenProt Viewer (http://www.genprot.org), developed by us that allows integration of genomic and proteomic information. With the continued support and active participation by the biomedical community, we expect HPRD to become a unique source of curated information for the human proteome and spur biomedical discoveries based on integration of genomic, transcriptomic and proteomic data.

Databases, Protein↗

PubMed2005

Biomarker discovery from pancreatic cancer secretome using a differential proteomic approach.

Quantitative proteomics can be used as a screening tool for identification of differentially expressed proteins as potential biomarkers for cancers. Candidate biomarkers from such studies can subsequently be tested using other techniques for use in early detection of cancers. Here we demonstrate the use of stable isotope labeling with amino acids in cell culture (SILAC) method to compare the secreted proteins (secretome) from pancreatic cancer-derived cells with that from non-neoplastic pancreatic ductal cells. We identified 145 differentially secreted proteins (>1.5-fold change), several of which were previously reported as either up-regulated (e.g. cathepsin D, macrophage colony stimulation factor, and fibronectin receptor) or down-regulated (e.g. profilin 1 and IGFBP-7) proteins in pancreatic cancer, confirming the validity of our approach. In addition, we identified several proteins that have not been correlated previously with pancreatic cancer including perlecan (HSPG2), CD9 antigen, fibronectin receptor (integrin beta1), and a novel cytokine designated as predicted osteoblast protein (FAM3C). The differential expression of a subset of these novel proteins was validated by Western blot analysis. In addition, overexpression of several proteins not described previously to be elevated in human pancreatic cancer (CD9, perlecan, SDF4, apoE, and fibronectin receptor) was confirmed by immunohistochemical labeling using pancreatic cancer tissue microarrays suggesting that these could be further pursued as potential biomarkers. Lastly the protein expression data from SILAC were compared with mRNA expression data obtained using gene expression microarrays for the two cell lines (Panc1 and human pancreatic duct epithelial), and a correlation coefficient (r) of 0.28 was obtained, confirming previously reported poor associations between RNA and protein expression studies.

Biomarkers, Tumor↗

PubMed2005

Proteomic resources: integrating biomedical information in humans.

Recent improvements in high-throughput proteomic technologies have unleashed the potential for generating vast amounts of data. Managing and sharing proteomic data is not an easy task. In this article, we will discuss some of the high-throughput proteomic techniques that are commonly used today. We will also review the major issues in sharing and dissemination of proteomic data and the recent community initiatives to standardize data formats and ontologies. An overview of the web-based resources and databases for analysis of proteomic data is also provided. Integration of disparate proteomic data sources with genomic and transcriptomic data should make systems biology type of approaches feasible in the near future.

Amino Acid Sequence↗

PubMed2005

Genome annotation of Anopheles gambiae using mass spectrometry-derived data.

BACKGROUND: A large number of animal and plant genomes have been completely sequenced over the last decade and are now publicly available. Although genomes can be rapidly sequenced, identifying protein-coding genes still remains a problematic task. Availability of protein sequence data allows direct confirmation of protein-coding genes. Mass spectrometry has recently emerged as a powerful tool for proteomic studies. Protein identification using mass spectrometry is usually carried out by searching against databases of known proteins or transcripts. This approach generally does not allow identification of proteins that have not yet been predicted or whose transcripts have not been identified. RESULTS: We searched 3,967 mass spectra from 16 LC-MS/MS runs of Anopheles gambiae salivary gland homogenates against the Anopheles gambiae genome database. This allowed us to validate 23 known transcripts and 50 novel transcripts. In addition, a novel gene was identified on the basis of peptides that matched a genomic region where no gene was known and no transcript had been predicted. The amino termini of proteins encoded by two predicted transcripts were confirmed based on N-terminally acetylated peptides sequenced by tandem mass spectrometry. Finally, six sequence polymorphisms could be annotated based on experimentally obtained peptide sequences. CONCLUSION: The peptide sequences from this study were mapped onto the genomic sequence using the distributed annotation system available at Ensembl and can be visualized in the context of all other existing annotations. The strategy described in this paper can be used to correct and confirm genome annotations and permit discovery of novel proteins in a high-throughput manner by mass spectrometry.

Animals↗

PubMed2005

A proteomic analysis of salivary glands of female Anopheles gambiae mosquito.

Understanding the development of the malaria parasite within the mosquito vector at the molecular level should provide novel targets for interrupting parasitic life cycle and subsequent transmission. Availability of the complete genomic sequence of the major African malaria vector, Anopheles gambiae, allows discovery of such targets through experimental as well as computational methods. In the female mosquito, the salivary gland tissue plays an important role in the maturation of the infective form of the malaria parasite. Therefore, we carried out a proteomic analysis of salivary glands from female An. gambiae mosquitoes. Salivary gland extracts were digested with trypsin using two complementary approaches and analyzed by LC-MS/MS. This led to identification of 69 unique proteins, 57 of which were novel. We carried out a functional annotation of all proteins identified in this study through a detailed bioinformatics analysis. Even though a number of cDNA and Edman degradation-based approaches to catalog transcripts and proteins from salivary glands of mosquitoes have been published previously, this is the first report describing the application of MS for characterization of the salivary gland proteome. Our approach should prove valuable for characterizing proteomes of parasites and vectors with sequenced genomes as well as those whose genomes are yet to be fully sequenced.

Animals↗

PubMed2005

Plasma Proteome Database as a resource for proteomics research.

Plasma is one of the best studied compartments in the human body and serves as an ideal body fluid for the diagnosis of diseases. This report provides a detailed functional annotation of all the plasma proteins identified to date. In all, gene products encoded by 3778 distinct genes were annotated based on proteins previously published in the literature as plasma proteins and the identification of multiple peptides from proteins under HUPO's Plasma Proteome Project. Our analysis revealed that 51% of these genes encoded more than one protein isoform. All single nucleotide polymorphisms involving protein-coding regions were mapped onto the protein sequences. We found a number of examples of isoform-specific subcellular localization as well as tissue expression. This database is an attempt at comprehensive annotation of a complex subproteome and is available on the web at http://www.plasmaproteomedatabase.org.

Amino Acid Motifs↗