Dataset Information

Sequence quality analysis tool for HIV type 1 protease and reverse transcriptase.

ABSTRACT: Access to antiretroviral therapy is increasing globally and drug resistance evolution is anticipated. Currently, protease (PR) and reverse transcriptase (RT) sequence generation is increasing, including the use of in-house sequencing assays, and quality assessment prior to sequence analysis is essential. We created a computational HIV PR/RT Sequence Quality Analysis Tool (SQUAT) that runs in the R statistical environment. Sequence quality thresholds are calculated from a large dataset (46,802 PR and 44,432 RT sequences) from the published literature ( http://hivdb.Stanford.edu ). Nucleic acid sequences are read into SQUAT, identified, aligned, and translated. Nucleic acid sequences are flagged if with >five 1-2-base insertions; >one 3-base insertion; >one deletion; >six PR or >18 RT ambiguous bases; >three consecutive PR or >four RT nucleic acid mutations; >zero stop codons; >three PR or >six RT ambiguous amino acids; >three consecutive PR or >four RT amino acid mutations; >zero unique amino acids; or <0.5% or >15% genetic distance from another submitted sequence. Thresholds are user modifiable. SQUAT output includes a summary report with detailed comments for troubleshooting of flagged sequences, histograms of pairwise genetic distances, neighbor joining phylogenetic trees, and aligned nucleic and amino acid sequences. SQUAT is a stand-alone, free, web-independent tool to ensure use of high-quality HIV PR/RT sequences in interpretation and reporting of drug resistance, while increasing awareness and expertise and facilitating troubleshooting of potentially problematic sequences.

SUBMITTER: Delong AK

PROVIDER: S-EPMC3399557 | biostudies-literature | 2012 Aug

REPOSITORIES: biostudies-literature

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Sequence quality analysis tool for HIV type 1 protease and reverse transcriptase.

Delong Allison K AK Wu Mingham M Bennett Diane D Parkin Neil N Wu Zhijin Z Hogan Joseph W JW Kantor Rami R

AIDS research and human retroviruses 20111026 8

Access to antiretroviral therapy is increasing globally and drug resistance evolution is anticipated. Currently, protease (PR) and reverse transcriptase (RT) sequence generation is increasing, including the use of in-house sequencing assays, and quality assessment prior to sequence analysis is essential. We created a computational HIV PR/RT Sequence Quality Analysis Tool (SQUAT) that runs in the R statistical environment. Sequence quality thresholds are calculated from a large dataset (46,802 PR ...[more]

PMID: 21916749

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Project description:UnlabelledHIV-1 protease (PR), reverse transcriptase (RT), and integrase (IN) variability presents a challenge to laboratories performing genotypic resistance testing. This challenge will grow with increased sequencing of samples enriched for proviral DNA such as dried blood spots and increased use of next-generation sequencing (NGS) to detect low-abundance HIV-1 variants. We analyzed PR and RT sequences from >100,000 individuals and IN sequences from >10,000 individuals to characterize variation at each amino acid position, identify mutations indicating APOBEC-mediated G-to-A editing, and identify mutations resulting from selective drug pressure. Forty-seven percent of PR, 37% of RT, and 34% of IN positions had one or more amino acid variants with a prevalence of ?1%. Seventy percent of PR, 60% of RT, and 60% of IN positions had one or more variants with a prevalence of ?0.1%. Overall 201 PR, 636 RT, and 346 IN variants had a prevalence of ?0.1%. The median intersubtype prevalence ratios were 2.9-, 2.1-, and 1.9-fold for these PR, RT, and IN variants, respectively. Only 5.0% of PR, 3.7% of RT, and 2.0% of IN variants had a median intersubtype prevalence ratio of ?10-fold. Variants at lower prevalences were more likely to differ biochemically and to be part of an electrophoretic mixture compared to high-prevalence variants. There were 209 mutations indicative of APOBEC-mediated G-to-A editing and 326 mutations nonpolymorphic treatment selected. Identification of viruses with a high number of APOBEC-associated mutations will facilitate the quality control of dried blood spot sequencing. Identifying sequences with a high proportion of rare mutations will facilitate the quality control of NGS.ImportanceMost antiretroviral drugs target three HIV-1 proteins: PR, RT, and IN. These proteins are highly variable: many different amino acids can be present at the same position in viruses from different individuals. Some of the amino acid variants cause drug resistance and occur mainly in individuals receiving antiretroviral drugs. Some variants result from a human cellular defense mechanism called APOBEC-mediated hypermutation. Many variants result from naturally occurring mutation. Some variants may represent technical artifacts. We studied PR and RT sequences from >100,000 individuals and IN sequences from >10,000 individuals to quantify variation at each amino acid position in these three HIV-1 proteins. We performed analyses to determine which amino acid variants resulted from antiretroviral drug selection pressure, APOBEC-mediated editing, and naturally occurring variation. Our results provide information essential to clinical, research, and public health laboratories performing genotypic resistance testing by sequencing HIV-1 PR, RT, and IN.

Project description:BackgroundSuccessful management of chronic human immunodeficiency virus type 1 (HIV-1) infection with a cocktail of antiretroviral medications can be negatively affected by the presence of drug resistant mutations in the viral targets. These targets include the HIV-1 protease (PR) and reverse transcriptase (RT) proteins, for which a number of inhibitors are available on the market and routinely prescribed. Protein mutational patterns are associated with varying degrees of resistance to their respective inhibitors, with extremes that can range from continued susceptibility to cross-resistance across all drugs.ResultsHere we implement statistical learning algorithms to develop structure- and sequence-based models for systematically predicting the effects of mutations in the PR and RT proteins on resistance to each of eight and eleven inhibitors, respectively. Employing a four-body statistical potential, mutant proteins are represented as feature vectors whose components quantify relative environmental perturbations at amino acid residue positions in the respective target structures upon mutation. Two approaches are implemented in developing sequence-based models, based on use of either relative frequencies or counts of n-grams, to generate vectors for representing mutant proteins. To the best of our knowledge, this is the first reported study on structure- and sequence-based predictive models of HIV-1 PR and RT drug resistance developed by implementing a four-body statistical potential and n-grams, respectively, to generate mutant attribute vectors. Performance of the learning methods is evaluated on the basis of tenfold cross-validation, using previously assayed and publicly available in vitro data relating mutational patterns in the targets to quantified inhibitor susceptibility changes.ConclusionOverall performance results are competitive with those of a previously published study utilizing a sequence-based strategy, while our structure- and sequence-based models provide orthogonal and complementary prediction methodologies, respectively. In a novel application, we describe a technique for identifying every possible pair of RT inhibitors as either potentially effective together as part of a cocktail, or a combination that is to be avoided.

Project description:Despite the high degree of HIV-1 protease and reverse transcriptase (RT) mutation in the setting of antiretroviral therapy, the spectrum of possible virus variants appears to be limited by patterns of amino acid covariation. We analyzed patterns of amino acid covariation in protease and RT sequences from more than 7,000 persons infected with HIV-1 subtype B viruses obtained from the Stanford HIV Drug Resistance Database (http://hivdb.stanford.edu). In addition, we examined the relationship between conditional probabilities associated with a pair of mutations and the order in which those mutations developed in viruses for which longitudinal sequence data were available. Patterns of RT covariation were dominated by the distinct clustering of Type I and Type II thymidine analog mutations and the Q151M-associated mutations. Patterns of protease covariation were dominated by the clustering of nelfinavir-associated mutations (D30N and N88D), two main groups of protease inhibitor (PI)-resistance mutations associated either with V82A or L90M, and a tight cluster of mutations associated with decreased susceptibility to amprenavir and the most recently approved PI darunavir. Different patterns of covariation were frequently observed for different mutations at the same position including the RT mutations T69D versus T69N, L74V versus L74I, V75I versus V75M, T215F versus T215Y, and K219Q/E versus K219N/R, and the protease mutations M46I versus M46L, I54V versus I54M/L, and N88D versus N88S. Sequence data from persons with correlated mutations in whom earlier sequences were available confirmed that the conditional probabilities associated with correlated mutation pairs could be used to predict the order in which the mutations were likely to have developed. Whereas accessory nucleoside RT inhibitor-resistance mutations nearly always follow primary nucleoside RT inhibitor-resistance mutations, accessory PI-resistance mutations often preceded primary PI-resistance mutations.

Project description:Amino acid Lys(65) is part of the highly flexible beta3-beta4 loop in the fingers domain of the 66 kDa subunit of human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT). Recent crystal data show that the epsilon-amino group of Lys(65) interacts with the gamma-phosphate of the bound deoxynucleoside triphosphate ('dNTP') substrate [Huang, Chopra, Verdine and Harrison (1998) Science 282, 1669-1675]. In order to biochemically define the function of RT Lys(65), we have used site-specific mutagenesis to generate RT with a variety of substitutions at this position, including K65E, K65Q, K65A and K65R. Kinetic analyses demonstrate that if Lys(65) in RT is substituted with an amino acid other than arginine the enzyme exhibits dramatic decreases in the binding affinity (K(m)) for all dNTP substrates, in RT catalytic efficiency (k(cat)/K(m)) and in the mutant enzyme's ability to carry out pyrophosphorolysis, the reverse reaction of DNA synthesis. The pH optimum for the DNA polymerase activity of K65E RT was 6.5, compared to 7.5 for the wild-type enzyme, and 8.0 for the K65R, K65A and K65Q mutants. Molecular modelling studies show that mutations of Lys(65) do not affect the geometry of the loop's alpha-carbon backbone, but rather lead to changes in positioning of the side chains of residues Lys(70) and Arg(72). In particular, Glu in K65E can form a salt bridge with Arg(72), leading to the diminution of the latter residue's interaction with the alpha-phosphate of the dNTP residue. This alteration in dNTP-binding may explain the large pH-dependent changes in both dNTP-binding and catalytic efficiency noted with the enzyme. Furthermore, the K65A, K65Q and K65E mutant enzymes are 100-fold less sensitive to all dideoxynucleoside triphosphate ('ddNTP') inhibitors, whereas the K65R mutation results in a selective 10-fold decrease in binding of ddCTP and ddATP only. This implies that mutations at position 65 in HIV-1 RT influence the nucleotide-binding specificity of the enzyme.

Dataset Information

Sequence quality analysis tool for HIV type 1 protease and reverse transcriptase.

Publications

Sequence quality analysis tool for HIV type 1 protease and reverse transcriptase.

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