Copy-number variants in patients with a strong family history of pancreatic cancer.

Copy-number variants such as germ-line deletions and amplifications are associated with inherited genetic disorders including familial cancer. The gene or genes responsible for the majority of familial clustering of pancreatic cancer have not been identified. We used representational oligonucleotide microarray analysis (ROMA) to characterize germ-line copy number variants in 60 cancer patients from 57 familial pancreatic cancer kindreds. Fifty-seven of the 60 patients had pancreatic cancer and three had nonpancreatic cancers (breast, ovary, ovary). A familial pancreatic cancer kindred was defined as a kindred in which at least two first-degree relatives have been diagnosed with pancreatic cancer. Copy-number variants identified in 607 individuals without pancreatic cancer were excluded from further analysis. A total of 56 unique genomic regions with copy-number variants not present in controls were identified, including 31 amplifications and 25 deletions. Two deleted regions were observed in two different patients, and one in three patients. The germ-line amplifications had a mean size of 662 Kb, a median size of 379 Kb (range 8.2 Kb to 2.5 Mb) and included 425 known genes. Examples of genes included in the germ-line amplifications include the MAFK, JunD and BIRC6 genes. The germ-line deletions had a mean size of 375Kb, a median size 151 Kb (range 0.4 Kb to 2.3 Mb) and included 81 known genes. In multivariate analysis controlling for region size, deletions were 90% less likely to involve a gene than were duplications (p < 0.01). Examples of genes included in the germ-line deletions include the FHIT, PDZRN3 and ANKRD3 genes. Selected deletions and amplifications were confirmed using real-time PCR, including a germ-line amplification on chromosome 19. These genetic copy-number variants define potential candidate loci for the familial pancreatic cancer gene.

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.

An evaluation of human protein-protein interaction data in the public domain.

BACKGROUND: Protein-protein interaction (PPI) databases have become a major resource for investigating biological networks and pathways in cells. A number of publicly available repositories for human PPIs are currently available. Each of these databases has their own unique features with a large variation in the type and depth of their annotations. RESULTS: We analyzed the major publicly available primary databases that contain literature curated PPI information for human proteins. This included BIND, DIP, HPRD, IntAct, MINT, MIPS, PDZBase and Reactome databases. The number of binary non-redundant human PPIs ranged from 101 in PDZBase and 346 in MIPS to 11,367 in MINT and 36,617 in HPRD. The number of genes annotated with at least one interactor was 9,427 in HPRD, 4,975 in MINT, 4,614 in IntAct, 3,887 in BIND and <1,000 in the remaining databases. The number of literature citations for the PPIs included in the databases was 43,634 in HPRD, 11,480 in MINT, 10,331 in IntAct, 8,020 in BIND and <2,100 in the remaining databases. CONCLUSION: Given the importance of PPIs, we suggest that submission of PPIs to repositories be made mandatory by scientific journals at the time of manuscript submission as this will minimize annotation errors, promote standardization and help keep the information up to date. We hope that our analysis will help guide biomedical scientists in selecting the most appropriate database for their needs especially in light of the dramatic differences in their content.

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.

A functional annotation of subproteomes in human plasma.

The data collected by Human Proteome Organization's Plasma Proteome Pilot project phase was analyzed by members of our working group. Accordingly, a functional annotation of the human plasma proteome was carried out. Here, we report the findings of our analyses. First, bioinformatic analyses were undertaken to determine the likely sources of plasma proteins and to develop a protein interaction network of proteins identified in this project. Second, annotation of these proteins was performed in the context of functional subproteomes involved in the coagulation pathway, the mononuclear phagocytic system, the inflammation pathway, the cardiovascular system, and the liver; as well as the subset of proteins associated with DNA binding activities. Our analyses contributed to the Plasma Proteome Database (http://www.plasmaproteomedatabase.org), an annotated database of plasma proteins identified by HPPP as well as from other published studies. In addition, we address several methodological considerations including the selective enrichment of post-translationally modified proteins by the use of multi-lectin chromatography as well as the use of peptidomic techniques to characterize the low molecular weight proteins in plasma. Furthermore, we have performed additional analyses of peptide identification data to annotate cleavage of signal peptides, sites of intra-membrane proteolysis and post-translational modifications. The HPPP-organized, multi-laboratory effort, as described herein, resulted in much synergy and was essential to the success of this project.

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.

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.

Immunoassay and antibody microarray analysis of the HUPO Plasma Proteome Project reference specimens: systematic variation between sample types and calibration of mass spectrometry data.

Four different immunoassay and antibody microarray methods performed at four different sites were used to measure the levels of a broad range of proteins (N = 323 assays; 39, 88, 168, and 28 assays at the respective sites; 237 unique analytes) in the human serum and plasma reference specimens distributed by the Plasma Proteome Project (PPP) of the HUPO. The methods provided a means to (1) assess the level of systematic variation in protein abundances associated with blood preparation methods (serum, citrate-anticoagulated-plasma, EDTA-anticoagulated-plasma, or heparin-anticoagulated-plasma) and (2) evaluate the dependence on concentration of MS-based protein identifications from data sets using the HUPO specimens. Some proteins, particularly cytokines, had highly variable concentrations between the different sample preparations, suggesting specific effects of certain anticoagulants on the stability or availability of these proteins. The linkage of antibody-based measurements from 66 different analytes with the combined MS/MS data from 18 different laboratories showed that protein detection and the quality of MS data increased with analyte concentration. The conclusions from these initial analyses are that the optimal blood preparation method is variable between analytes and that the discovery of blood proteins by MS can be extended to concentrations below the ng/mL range under certain circumstances. Continued developments in antibody-based methods will further advance the scientific goals of the PPP.

Human protein reference database as a discovery resource for proteomics.

The rapid pace at which genomic and proteomic data is being generated necessitates the development of tools and resources for managing data that allow integration of information from disparate sources. The Human Protein Reference Database (http://www.hprd.org) is a web-based resource based on open source technologies for protein information about several aspects of human proteins including protein-protein interactions, post-translational modifications, enzyme-substrate relationships and disease associations. This information was derived manually by a critical reading of the published literature by expert biologists and through bioinformatics analyses of the protein sequence. This database will assist in biomedical discoveries by serving as a resource of genomic and proteomic information and providing an integrated view of sequence, structure, function and protein networks in health and disease.

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.