Dataset Information

Improving HIV proteome annotation: new features of BioAfrica HIV Proteomics Resource.

ABSTRACT: The Human Immunodeficiency Virus (HIV) is one of the pathogens that cause the greatest global concern, with approximately 35 million people currently infected with HIV. Extensive HIV research has been performed, generating a large amount of HIV and host genomic data. However, no effective vaccine that protects the host from HIV infection is available and HIV is still spreading at an alarming rate, despite effective antiretroviral (ARV) treatment. In order to develop effective therapies, we need to expand our knowledge of the interaction between HIV and host proteins. In contrast to virus proteins, which often rapidly evolve drug resistance mutations, the host proteins are essentially invariant within all humans. Thus, if we can identify the host proteins needed for virus replication, such as those involved in transporting viral proteins to the cell surface, we have a chance of interrupting viral replication. There is no proteome resource that summarizes this interaction, making research on this subject a difficult enterprise. In order to fill this gap in knowledge, we curated a resource presents detailed annotation on the interaction between the HIV proteome and host proteins. Our resource was produced in collaboration with ViralZone and used manual curation techniques developed by UniProtKB/Swiss-Prot. Our new website also used previous annotations of the BioAfrica HIV-1 Proteome Resource, which has been accessed by approximately 10 000 unique users a year since its inception in 2005. The novel features include a dedicated new page for each HIV protein, a graphic display of its function and a section on its interaction with host proteins. Our new webpages also add information on the genomic location of each HIV protein and the position of ARV drug resistance mutations. Our improved BioAfrica HIV-1 Proteome Resource fills a gap in the current knowledge of biocuration.Database URL:http://www.bioafrica.net/proteomics/HIVproteome.html.

SUBMITTER: Druce M

PROVIDER: S-EPMC4834208 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Improving HIV proteome annotation: new features of BioAfrica HIV Proteomics Resource.

Druce Megan M Hulo Chantal C Masson Patrick P Sommer Paula P Xenarios Ioannis I Le Mercier Philippe P De Oliveira Tulio T

Database : the journal of biological databases and curation 20160417

The Human Immunodeficiency Virus (HIV) is one of the pathogens that cause the greatest global concern, with approximately 35 million people currently infected with HIV. Extensive HIV research has been performed, generating a large amount of HIV and host genomic data. However, no effective vaccine that protects the host from HIV infection is available and HIV is still spreading at an alarming rate, despite effective antiretroviral (ARV) treatment. In order to develop effective therapies, we need ...[more]

PMID: 27087306

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Project description:Most Internet online resources for investigating HIV biology contain either bioinformatics tools, protein information or sequence data. The objective of this study was to develop a comprehensive online proteomics resource that integrates bioinformatics with the latest information on HIV-1 protein structure, gene expression, post-transcriptional/post-translational modification, functional activity, and protein-macromolecule interactions. The BioAfrica HIV-1 Proteomics Resource http://bioafrica.mrc.ac.za/proteomics/index.html is a website that contains detailed information about the HIV-1 proteome and protease cleavage sites, as well as data-mining tools that can be used to manipulate and query protein sequence data, a BLAST tool for initiating structural analyses of HIV-1 proteins, and a proteomics tools directory. The Proteome section contains extensive data on each of 19 HIV-1 proteins, including their functional properties, a sample analysis of HIV-1HXB2, structural models and links to other online resources. The HIV-1 Protease Cleavage Sites section provides information on the position, subtype variation and genetic evolution of Gag, Gag-Pol and Nef cleavage sites. The HIV-1 Protein Data-mining Tool includes a set of 27 group M (subtypes A through K) reference sequences that can be used to assess the influence of genetic variation on immunological and functional domains of the protein. The BLAST Structure Tool identifies proteins with similar, experimentally determined topologies, and the Tools Directory provides a categorized list of websites and relevant software programs. This combined database and software repository is designed to facilitate the capture, retrieval and analysis of HIV-1 protein data, and to convert it into clinically useful information relating to the pathogenesis, transmission and therapeutic response of different HIV-1 variants. The HIV-1 Proteomics Resource is readily accessible through the BioAfrica website at: http://bioafrica.mrc.ac.za/proteomics/index.html.

Project description:The purpose of national HIV surveillance is to track and summarize trends in newly diagnosed cases as an indicator of HIV transmission within Canada, and supports the development and evaluation of programs and policies for prevention, testing and delivery of care. Accurately capturing and interpreting trends in HIV diagnoses within national surveillance becomes complicated when there is movement of people within a country or when individuals are diagnosed with HIV prior to migrating to a new country. This has been identified as an issue in other countries, including Australia, New Zealand and Switzerland. The Public Health Agency of Canada (PHAC) recently assessed this in Canada after noting a rise in new HIV cases in Canada between 2014 to 2017. An environmental scan was conducted to better understand how new and previously diagnosed cases of HIV were recorded by and reported to PHAC from provincial and territorial (PT) public health authorities. It was discovered there was variation with respect to the reporting of cases who had received a new diagnosis of HIV within the province or territory, but who had previously received an HIV diagnosis from another PT or another country. Five PTs included cases previously diagnosed in another Canadian PT within the HIV surveillance data reported to PHAC and nine PTs included people who were diagnosed with HIV outside of Canada. The provincial and territorial public health authorities then reviewed HIV surveillance data from 2007 to 2017 to identify cases using a common definition of "previous HIV-positive test result". This included any case who gave a history, or had laboratory evidence, of an HIV-positive result from another PT or another country before presenting for care in the province or territory where they now resided. When these cases were subtracted from the total, a revised number of new HIV diagnoses was calculated for Canada. Re-analysis of surveillance data using this common definition for 2007 to 2017 explained more than half of the increase in HIV cases that had been documented in Canada over the last four years. In the future, national surveillance data will be calculated adopting this new common definition of a previous positive test result, in order to more accurately describe the trends in HIV transmission occurring in Canada.

Project description:BACKGROUND: The comprehensive analysis of human kidney glomerulus we previously performed using highly purified glomeruli, provided a dataset of 6,686 unique proteins representing 2,966 distinct genes. This dataset, however, contained considerable redundancy resulting from identification criteria under which all the proteins matched with the same set of peptides and its subset were reported as identified proteins. In this study we reanalyzed the raw data using the Mascot search engine and highly stringent criteria in order to select proteins with the highest scores matching peptides with scores exceeding the "Identity Threshold" and one or more unique peptides. This enabled us to exclude proteins with lower scores which only matched the same set of peptides or its subset. This approach provided a high-confidence, non-redundant dataset of identified proteins for extensive profiling, annotation, and comparison with other proteome datasets that can provide biologically relevant knowledge of glomerulus proteome. RESULTS: Protein identification using the Mascot search engine under highly stringent, computational strategy generated a non-redundant dataset of 1,817 proteins representing 1,478 genes. These proteins were represented by 2-D protein array specifying observed molecular weight and isoelectric point range of identified proteins to demonstrate differences in the observed and calculated physicochemical properties. Characteristics of glomerulus proteome could be illustrated by GO analysis and protein classification. The depth of proteomic analysis was well documented via comparison of the dynamic range of identified proteins with other proteomic analyses of human glomerulus, as well as a high coverage of biologically important pathways. Comparison of glomerulus proteome with human plasma and urine proteomes, provided by comprehensive analysis, suggested the extent and characteristics of proteins contaminated from plasma and excreted into urine, respectively. Among the latter proteins, several were demonstrated to be highly or specifically localized in the glomerulus by cross-reference analysis with the Human Protein Atlas database, and could be biomarker candidates for glomerular injury. Furthermore, comparison of ortholog proteins identified in human and mouse glomeruli suggest some biologically significant differences in glomerulus proteomes between the two species. CONCLUSIONS: A high-confidence, non-redundant dataset of proteins created by comprehensive proteomic analysis could provide a more extensive understanding of human glomerulus proteome and could be useful as a resource for the discovery of biomarkers and disease-relevant proteins.

Dataset Information

Improving HIV proteome annotation: new features of BioAfrica HIV Proteomics Resource.

Publications

Improving HIV proteome annotation: new features of BioAfrica HIV Proteomics Resource.

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