HIVToolbox, an integrated web application for investigating HIV

GigaAssay - An adaptable high-throughput saturation mutagenesis assay platform

High-throughput assay systems have had a large impact on understanding the mechanisms of basic cell functions. However, high-throughput assays that directly assess molecular functions are limited. Herein, we describe the "GigaAssay", a modular high-throughput one-pot assay system for measuring molecular functions of thousands of genetic variants at once. In this system, each cell was infected with one virus from a library encoding thousands of Tat mutant proteins, with each viral particle encoding a random unique molecular identifier (UMI). We demonstrate proof of concept by measuring transcription of a GFP reporter in an engineered reporter cell line driven by binding of the HIV Tat transcription factor to the HIV long terminal repeat. Infected cells were flow-sorted into 3 bins based on their GFP fluorescence readout. The transcriptional activity of each Tat mutant was calculated from the ratio of signals from each bin. The use of UMIs in the GigaAssay produced a high average accuracy (95%) and positive predictive value (98%) determined by comparison to literature benchmark data, known C-terminal truncations, and blinded independent mutant tests. Including the substitution tolerance with structure/function analysis shows restricted substitution types spatially concentrated in the Cys-rich region. Tat has abundant intragenic epistasis (10%) when single and double mutants are compared.

HIV-1, human interaction database: current status and new features

The 'Human Immunodeficiency Virus Type 1 (HIV-1), Human Interaction Database', available through the National Library of Medicine at http://www.ncbi.nlm.nih.gov/genome/viruses/retroviruses/hiv-1/interactions, serves the scientific community exploring the discovery of novel HIV vaccine candidates and therapeutic targets. Each HIV-1 human protein interaction can be retrieved without restriction by web-based downloads and ftp protocols and includes: Reference Sequence (RefSeq) protein accession numbers, National Center for Biotechnology Information Gene identification numbers, brief descriptions of the interactions, searchable keywords for interactions and PubMed identification numbers (PMIDs) of journal articles describing the interactions. In addition to specific HIV-1 protein-human protein interactions, included are interaction effects upon HIV-1 replication resulting when individual human gene expression is blocked using siRNA. A total of 3142 human genes are described participating in 12,786 protein-protein interactions, along with 1316 replication interactions described for each of 1250 human genes identified using small interfering RNA (siRNA). Together the data identifies 4006 human genes involved in 14,102 interactions. With the inclusion of siRNA interactions we introduce a redesigned web interface to enhance viewing, filtering and downloading of the combined data set.

The HIVToolbox 2 web system integrates sequence, structure, function and mutation analysis

There is enormous interest in studying HIV pathogenesis for improving the treatment of patients with HIV infection. HIV infection has become one of the best-studied systems for understanding how a virus can hijack a cell. To help facilitate discovery, we previously built HIVToolbox, a web system for visual data mining. The original HIVToolbox integrated information for HIV protein sequence, structure, functional sites, and sequence conservation. This web system has been used for almost 40,000 searches. We report improvements to HIVToolbox including new functions and workflows, data updates, and updates for ease of use. HIVToolbox2, is an improvement over HIVToolbox with new functions. HIVToolbox2 has new functionalities focused on HIV pathogenesis including drug-binding sites, drug-resistance mutations, and immune epitopes. The integrated, interactive view enables visual mining to generate hypotheses that are not readily revealed by other approaches. Most HIV proteins form multimers, and there are posttranslational modification and protein-protein interaction sites at many of these multimerization interfaces. Analysis of protease drug binding sites reveals an anatomy of drug resistance with different types of drug-resistance mutations regionally localized on the surface of protease. Some of these drug-resistance mutations have a high prevalence in specific HIV-1 M subtypes. Finally, consolidation of Tat functional sites reveals a hotspot region where there appear to be 30 interactions or posttranslational modifications. A cursory analysis with HIVToolbox2 has helped to identify several global patterns for HIV proteins. An initial analysis with this tool identifies homomultimerization of almost all HIV proteins, functional sites that overlap with multimerization sites, a global drug resistance anatomy for HIV protease, and specific distributions of some DRMs in specific HIV M subtypes. HIVToolbox2 is an open-access web application available at [http://hivtoolbox2.bio-toolkit.com].

The Geogenomic Mutational Atlas of Pathogens (GoMAP) web system

We present a new approach for pathogen surveillance we call Geogenomics. Geogenomics examines the geographic distribution of the genomes of pathogens, with a particular emphasis on those mutations that give rise to drug resistance. We engineered a new web system called Geogenomic Mutational Atlas of Pathogens (GoMAP) that enables investigation of the global distribution of individual drug resistance mutations. As a test case we examined mutations associated with HIV resistance to FDA-approved antiretroviral drugs. GoMAP-HIV makes use of existing public drug resistance and HIV protein sequence data to examine the distribution of 872 drug resistance mutations in ∼ 502,000 sequences for many countries in the world. We also implemented a broadened classification scheme for HIV drug resistance mutations. Several patterns for geographic distributions of resistance mutations were identified by visual mining using this web tool. GoMAP-HIV is an open access web application available at http://www.bio-toolkit.com/GoMap/project/

Minimotif Miner 3.0: database expansion and significantly improved reduction of false-positive predictions from consensus sequences

Minimotif Miner (MnM available at http://minimotifminer.org or http://mnm.engr.uconn.edu) is an online database for identifying new minimotifs in protein queries. Minimotifs are short contiguous peptide sequences that have a known function in at least one protein. Here we report the third release of the MnM database which has now grown 60-fold to approximately 300,000 minimotifs. Since short minimotifs are by their nature not very complex we also summarize a new set of false-positive filters and linear regression scoring that vastly enhance minimotif prediction accuracy on a test data set. This online database can be used to predict new functions in proteins and causes of disease.