Similar prevalence of low-abundance drug-resistant variants in treatment-naive patients with genotype 1a and 1b hepatitis C virus infections as determined by ultradeep pyrosequencing.

BACKGROUND AND OBJECTIVES: Hepatitis C virus (HCV) variants that confer resistance to direct-acting-antiviral agents (DAA) have been detected by standard sequencing technology in genotype (G) 1 viruses from DAA-naive patients. It has recently been shown that virological response rates are higher and breakthrough rates are lower in G1b infected patients than in G1a infected patients treated with certain classes of HCV DAAs. It is not known whether this corresponds to a difference in the composition of G1a and G1b HCV quasispecies in regards to the proportion of naturally occurring DAA-resistant variants before treatment. METHODS: We used ultradeep pyrosequencing to determine the prevalence of low-abundance (<25% of the sequence reads) DAA-resistant variants in 191 NS3 and 116 NS5B isolates from 208 DAA-naive G1-infected patients. RESULTS: A total of 3.5 million high-quality reads of ≥ 200 nucleotides were generated. The median coverage depth was 4150x and 4470x per NS3 and NS5B amplicon, respectively. Both G1a and G1b populations showed Shannon entropy distributions, with no difference between G1a and G1b in NS3 or NS5B region at the nucleotide level. A higher number of substitutions that confer resistance to protease inhibitors were observed in G1a isolates (mainly at amino acid 80 of the NS3 region). The prevalence of amino acid substitutions that confer resistance to NS5B non-nucleoside inhibitors was similar in G1a and G1b isolates. The NS5B S282T variant, which confers resistance to the polymerase inhibitors mericitabine and sofosbuvir, was not detected in any sample. CONCLUSION: The quasispecies genetic diversity and prevalence of DAA-resistant variants was similar in G1a and G1b isolates and in both NS3 and NS5B regions, suggesting that this is not a determinant for the higher level of DAA resistance observed across G1a HCV infected patients upon treatment.

Non-nucleoside reverse transcriptase inhibitor (NNRTI) cross-resistance: implications for preclinical evaluation of novel NNRTIs and clinical genotypic resistance testing.

OBJECTIVES: The introduction of two new non-nucleoside reverse transcriptase inhibitors (NNRTIs) in the past 5 years and the identification of novel NNRTI-associated mutations have made it necessary to reassess the extent of phenotypic NNRTI cross-resistance. METHODS: We analysed a dataset containing 1975, 1967, 519 and 187 genotype-phenotype correlations for nevirapine, efavirenz, etravirine and rilpivirine, respectively. We used linear regression to estimate the effects of RT mutations on susceptibility to each of these NNRTIs. RESULTS: Sixteen mutations at 10 positions were significantly associated with the greatest contribution to reduced phenotypic susceptibility (≥10-fold) to one or more NNRTIs, including: 14 mutations at six positions for nevirapine (K101P, K103N/S, V106A/M, Y181C/I/V, Y188C/L and G190A/E/Q/S); 10 mutations at six positions for efavirenz (L100I, K101P, K103N, V106M, Y188C/L and G190A/E/Q/S); 5 mutations at four positions for etravirine (K101P, Y181I/V, G190E and F227C); and 6 mutations at five positions for rilpivirine (L100I, K101P, Y181I/V, G190E and F227C). G190E, a mutation that causes high-level nevirapine and efavirenz resistance, also markedly reduced susceptibility to etravirine and rilpivirine. K101H, E138G, V179F and M230L mutations, associated with reduced susceptibility to etravirine and rilpivirine, were also associated with reduced susceptibility to nevirapine and/or efavirenz. CONCLUSIONS: The identification of novel cross-resistance patterns among approved NNRTIs illustrates the need for a systematic approach for testing novel NNRTIs against clinical virus isolates with major NNRTI-resistance mutations and for testing older NNRTIs against virus isolates with mutations identified during the evaluation of a novel NNRTI.

Trends in Genotypic HIV-1 Antiretroviral Resistance between 2006 and 2012 in South African Patients Receiving First- and Second-Line Antiretroviral Treatment Regimens.

OBJECTIVES: South Africa's national antiretroviral (ARV) treatment program expanded in 2010 to include the nucleoside reverse transcriptase (RT) inhibitors (NRTI) tenofovir (TDF) for adults and abacavir (ABC) for children. We investigated the associated changes in genotypic drug resistance patterns in patients with first-line ARV treatment failure since the introduction of these drugs, and protease inhibitor (PI) resistance patterns in patients who received ritonavir-boosted lopinavir (LPV/r)-containing therapy. METHODS: We analysed ARV treatment histories and HIV-1 RT and protease mutations in plasma samples submitted to the Tygerberg Academic Hospital National Health Service Laboratory. RESULTS: Between 2006 and 2012, 1,667 plasma samples from 1,416 ARV-treated patients, including 588 children and infants, were submitted for genotypic resistance testing. Compared with 720 recipients of a d4T or AZT-containing first-line regimen, the 153 recipients of a TDF-containing first-line regimen were more likely to have the RT mutations K65R (46% vs 4.0%; p<0.001), Y115F (10% vs. 0.6%; p<0.001), L74VI (8.5% vs. 1.8%; p<0.001), and K70EGQ (7.8% vs. 0.4%) and recipients of an ABC-containing first-line regimen were more likely to have K65R (17% vs 4.0%; p<0.001), Y115F (30% vs 0.6%; p<0.001), and L74VI (56% vs 1.8%; p<0.001). Among the 490 LPV/r recipients, 55 (11%) had ≥1 LPV-resistance mutations including 45 (9.6%) with intermediate or high-level LPV resistance. Low (20 patients) and intermediate (3 patients) darunavir (DRV) cross resistance was present in 23 (4.6%) patients. CONCLUSIONS: Among patients experiencing virological failure on a first-line regimen containing two NRTI plus one NNRTI, the use of TDF in adults and ABC in children was associated with an increase in four major non- thymidine analogue mutations. In a minority of patients, LPV/r-use was associated with intermediate or high-level LPV resistance with predominantly low-level DRV cross-resistance.

Prototypical Recombinant Multi-Protease-Inhibitor-Resistant Infectious Molecular Clones of Human Immunodeficiency Virus Type 1.

The many genetic manifestations of HIV-1 protease inhibitor (PI) resistance present challenges to research into the mechanisms of PI resistance and the assessment of new PIs. To address these challenges, we created a panel of recombinant multi-PI-resistant infectious molecular clones designed to represent the spectrum of clinically relevant multi-PI-resistant viruses. To assess the representativeness of this panel, we examined the sequences of the panel's viruses in the context of a correlation network of PI resistance amino acid substitutions in sequences from more than 10,000 patients. The panel of recombinant infectious molecular clones comprised 29 of 41 study-defined PI resistance amino acid substitutions and 23 of the 27 tightest amino acid substitution clusters. Based on their phenotypic properties, the clones were classified into four groups with increasing cross-resistance to the PIs most commonly used for salvage therapy: lopinavir (LPV), tipranavir (TPV), and darunavir (DRV). The panel of recombinant infectious molecular clones has been made available without restriction through the NIH AIDS Research and Reference Reagent Program. The public availability of the panel makes it possible to compare the inhibitory activities of different PIs with one another. The diversity of the panel and the high-level PI resistance of its clones suggest that investigational PIs active against the clones in this panel will retain antiviral activity against most if not all clinically relevant PI-resistant viruses.

Low-level persistence of drug resistance mutations in hepatitis B virus-infected subjects with a past history of Lamivudine treatment.

We sought to determine the prevalence of hepatitis B virus (HBV) lamivudine (LAM)-resistant minority variants in subjects who once received LAM but had discontinued it prior to virus sampling. We performed direct PCR Sanger sequencing and ultradeep pyrosequencing (UDPS) of HBV reverse transcriptase (RT) of plasma viruses from 45 LAM-naive subjects and 46 LAM-experienced subjects who had discontinued LAM a median of 24 months earlier. UDPS was performed to a depth of ∼3,000 reads per nucleotide. Minority variants were defined as differences from the Sanger sequence present in ≥0.5% of UDPS reads in a sample. Sanger sequencing identified ≥1 LAM resistance mutations (rtL80I/V, rtM204I, and rtA181T) in samples from 5 (11%) of 46 LAM-experienced and none of 45 LAM-naive subjects (0%; P = 0.06). UDPS detected ≥1 LAM resistance mutations (rtL80I/V, rtV173L, rtL180M, rtA181T, and rtM204I/V) in 10 (22%) of the 46 LAM-experienced subjects, including 5 in whom LAM resistance mutations were not identified by Sanger sequencing. Overall, LAM resistance mutations were more likely to be present in LAM-experienced (10/46, 22%) than LAM-naive subjects (0/45, 0%; P = 0.001). The median time since LAM discontinuation was 12.8 months in the 10 subjects with a LAM resistance mutation compared to 30.5 months in the 36 LAM-experienced subjects without a LAM resistance mutation (P < 0.001). The likelihood of detecting a LAM resistance mutation was significantly increased using UDPS compared to Sanger sequencing and was inversely associated with the time since LAM discontinuation.

Collinearity of protease mutations in HIV-1 samples with high-level protease inhibitor class resistance.

OBJECTIVES: To determine whether pan-protease inhibitor (PI)-resistant virus populations are composed predominantly of viruses with resistance to all PIs or of diverse virus populations with resistance to different subsets of PIs. METHODS: We performed deep sequencing of plasma virus samples from nine patients with high-level genotypic and/or phenotypic resistance to all licensed PIs. The nine virus samples had a median of 12 PI resistance mutations by direct PCR Sanger sequencing. RESULTS: For each of the nine virus samples, deep sequencing showed that each of the individual viruses within a sample contained nearly all of the mutations detected by Sanger sequencing. Indeed, a median of 94.9% of deep sequence reads had each of the PI resistance mutations present as a single chromatographic peak in the Sanger sequence. A median of 5.0% of reads had all but one of the Sanger mutations that were not part of an electrophoretic mixture. CONCLUSIONS: The collinearity of PI resistance mutations in the nine virus samples demonstrated that pan-PI-resistant viruses are able to replicate in vivo despite their highly mutated protease enzymes. We hypothesize that the marked collinearity of PI resistance mutations in pan-PI-resistant virus populations results from the unique requirements for multi-PI resistance and the extensive cross-resistance conferred by many of the accessory PI resistance mutations.

Standardized representation, visualization and searchable repository of antiretroviral treatment-change episodes.

BACKGROUND: To identify the determinants of successful antiretroviral (ARV) therapy, researchers study the virological responses to treatment-change episodes (TCEs) accompanied by baseline plasma HIV-1 RNA levels, CD4+ T lymphocyte counts, and genotypic resistance data. Such studies, however, often differ in their inclusion and virological response criteria making direct comparisons of study results problematic. Moreover, the absence of a standard method for representing the data comprising a TCE makes it difficult to apply uniform criteria in the analysis of published studies of TCEs. RESULTS: To facilitate data sharing for TCE analyses, we developed an XML (Extensible Markup Language) Schema that represents the temporal relationship between plasma HIV-1 RNA levels, CD4 counts and genotypic drug resistance data surrounding an ARV treatment change. To demonstrate the adaptability of the TCE XML Schema to different clinical environments, we collaborate with four clinics to create a public repository of about 1,500 TCEs. Despite the nascent state of this TCE XML Repository, we were able to perform an analysis that generated a novel hypothesis pertaining to the optimal use of second-line therapies in resource-limited settings. We also developed an online program (TCE Finder) for searching the TCE XML Repository and another program (TCE Viewer) for generating a graphical depiction of a TCE from a TCE XML Schema document. CONCLUSIONS: The TCE Suite of applications - the XML Schema, Viewer, Finder, and Repository - addresses several major needs in the analysis of the predictors of virological response to ARV therapy. The TCE XML Schema and Viewer facilitate sharing data comprising a TCE. The TCE Repository, the only publicly available collection of TCEs, and the TCE Finder can be used for testing the predictive value of genotypic resistance interpretation systems and potentially for generating and testing novel hypotheses pertaining to the optimal use of salvage ARV therapy.

Automating HIV drug resistance genotyping with RECall, a freely accessible sequence analysis tool.

Genotypic HIV drug resistance testing is routinely used to guide clinical decisions. While genotyping methods can be standardized, a slow, labor-intensive, and subjective manual sequence interpretation step is required. We therefore performed external validation of our custom software RECall, a fully automated sequence analysis pipeline. HIV-1 drug resistance genotyping was performed on 981 clinical samples at the Stanford Diagnostic Virology Laboratory. Sequencing trace files were first interpreted manually by a laboratory technician and subsequently reanalyzed by RECall, without intervention. The relative performances of the two methods were assessed by determination of the concordance of nucleotide base calls, identification of key resistance-associated substitutions, and HIV drug resistance susceptibility scoring by the Stanford Sierra algorithm. RECall is freely available at http://pssm.cfenet.ubc.ca. In total, 875 of 981 sequences were analyzed by both human and RECall interpretation. RECall analysis required minimal hands-on time and resulted in a 25-fold improvement in processing speed (∼150 technician-hours versus ∼6 computation-hours). Excellent concordance was obtained between human and automated RECall interpretation (99.7% agreement for >1,000,000 bases compared). Nearly all discordances (99.4%) were due to nucleotide mixtures being called by one method but not the other. Similarly, 98.6% of key antiretroviral resistance-associated mutations observed were identified by both methods, resulting in 98.5% concordance of resistance susceptibility interpretations. This automated sequence analysis tool provides both standardization of analysis and a significant improvement in data workflow. The time-consuming, error-prone, and dreadfully boring manual sequence analysis step is replaced with a fully automated system without compromising the accuracy of reported HIV drug resistance data.

The HIVdb system for HIV-1 genotypic resistance interpretation.

The Stanford HIV Drug Resistance Database hosts a freely available online genotypic resistance interpretation system called HIVdb to help clinicians and laboratories interpret HIV-1 genotypic resistance tests. These tests are designed to assess susceptibility to nucleoside and nonnucleoside reverse transcriptase inhibitors (NRTI and NNRTI), protease inhibitors and integrase inhibitors. The HIVdb genotypic resistance interpretation system output consists of (1) a list of penalty scores for each antiretroviral (ARV) resistance mutation in a submitted sequence, (2) estimates of decreased NRTI, NNRTI, protease and integrase inhibitor susceptibility, and (3) comments about each ARV resistance mutation in the submitted sequence. The application's strengths are its convenience for submitting sequences, its quality control analysis, its transparency and its extensive comments. The Sierra Web service is an extension that enables laboratories analyzing many sequences to individualize the format of their results. The algorithm specification interface compiler makes it possible for HIVdb to provide results using a variety of different HIV-1 genotypic resistance interpretation algorithms.

HIV-1 integrase sequence variability in antiretroviral naïve patients and in triple-class experienced patients subsequently treated with raltegravir.

Viruses were sequenced from 75 antiretroviral therapy (ARV)-naïve and from 75 ARV-treated patients who subsequently received a raltegravir-containing regimen. No major integrase inhibitor (INI)-resistance mutations were present in the 150 integrase (IN) sequences. Four ARV-naïve (5.3%) and two ARV-treated patients (2.7%) had one of the following minor INI-resistance mutations: L74M, E157Q, G163R, and R263K but there was no association between baseline raltegravir genotype and subsequent response to raltegravir treatment. We also combined our sequences with 4170 previously published group M IN sequences from INI-naïve patients to assess IN sequence variability and compared our findings with those of a study we performed in 2008 using data from 1563 patients. The number of polymorphic IN positions increased from 40% to 41% between the two studies. However, none of the major INI-resistance mutations was found to be polymorphic in either study and there were no significant changes in the prevalence of any of the minor INI-resistance mutations.

Hepatitis B virus reverse transcriptase sequence variant database for sequence analysis and mutation discovery.

Drug resistance resulting from reverse transcriptase (RT) mutations is one of the main obstacles to successful hepatitis B virus (HBV) therapy. Indeed, HBV treatment guidelines recommend HBV genotypic resistance testing for patients receiving nucleos(t)ide RT inhibitors (N(t)RTIs) who develop virological failure. N(t)RTI-resistance mutations at 10 RT positions have been well characterized in phenotypic studies, however, data are lacking on the relative frequency of these mutations in N(t)RTI-treated and untreated individuals. There are also few published data on the extent of amino acid variation at most of the 344 positions of HBV RT and the extent to which this variation is influenced by N(t)RTI treatment. We retrieved 23,871 HBV RT sequences from GenBank and reviewed the published reports of these sequences to ascertain the number of individuals from whom the sequences were obtained, the N(t)RTI treatments of these individuals, and the year and region of virus sampling. We then used these data to populate a relational database we named HBVrtDB. As of July 2010, HBVrtDB contained 6811 sequences from 3869 individuals reported in 281 references. Among these 3869 individuals, 73% were N(t)RTI-naïve and 27% received one or more N(t)RTIs. Among the 10 well-characterized N(t)RTI-resistance mutations, L80I/V, V173L, L180M, A181T, T184S, S202G and M204I/V were significantly associated with treatment with lamivudine, an l-nucleoside analog, and A181S/T/V and N236T were significantly associated with treatment with adefovir, an acyclic nucleoside phosphonate. A similar analysis of ten additional less well-characterized resistance mutations demonstrated a significant association with N(t)RTI treatment for four of the mutations: L82M, S85A, A200V, and Q215S. We also created an interactive program, HBVseq, to enable users to identify mutations in submitted sequences and retrieve the prevalence of these mutations in HBVrtDB according to genotype and N(t)RTI treatment. HBVrtDB and HBVseq are available at http://hivdb.stanford.edu/HBV/releaseNotes/.

Nonpolymorphic human immunodeficiency virus type 1 protease and reverse transcriptase treatment-selected mutations.

The spectrum of human immunodeficiency virus type 1 (HIV-1) protease and reverse transcriptase (RT) mutations selected by antiretroviral (ARV) drugs requires ongoing reassessment as ARV treatment patterns evolve and increasing numbers of protease and RT sequences of different viral subtypes are published. Accordingly, we compared the prevalences of protease and RT mutations in HIV-1 group M sequences from individuals with and without a history of previous treatment with protease inhibitors (PIs) or RT inhibitors (RTIs). Mutations in protease sequences from 26,888 individuals and in RT sequences from 25,695 individuals were classified according to whether they were nonpolymorphic in untreated individuals and whether their prevalence increased fivefold with ARV therapy. This analysis showed that 88 PI-selected and 122 RTI-selected nonpolymorphic mutations had a prevalence that was fivefold higher in individuals receiving ARVs than in ARV-naïve individuals. This was an increase of 47% and 77%, respectively, compared with the 60 PI- and 69 RTI-selected mutations identified in a similar analysis that we published in 2005 using subtype B sequences obtained from one-fourth as many individuals. In conclusion, many nonpolymorphic mutations in protease and RT are under ARV selection pressure. The spectrum of treatment-selected mutations is changing as data for more individuals are collected, treatment exposures change, and the number of available sequences from non-subtype B viruses increases.

Predictive value of HIV-1 genotypic resistance test interpretation algorithms.

BACKGROUND: Interpreting human immunodeficiency virus type 1 (HIV-1) genotypic drug-resistance test results is challenging for clinicians treating HIV-1-infected patients. Multiple drug-resistance interpretation algorithms have been developed, but their predictive value has rarely been evaluated using contemporary clinical data sets. METHODS: We examined the predictive value of 4 algorithms at predicting virologic response (VR) during 734 treatment-change episodes (TCEs). VR was defined as attaining plasma HIV-1 RNA levels below the limit of quantification. Drug-specific genotypic susceptibility scores (GSSs) were calculated by applying each algorithm to the baseline genotype. Weighted GSSs were calculated by multiplying drug-specific GSSs by antiretroviral (ARV) potency factors. Regimen-specific GSSs (rGSSs) were calculated by adding unweighted or weighted drug-specific GSSs for each salvage therapy ARV. The predictive value of rGSSs were estimated by use of multivariate logistic regression. RESULTS: Of 734 TCEs, 475 (65%) were associated with VR. The rGSSs for the 4 algorithms were the variables most strongly predictive of VR. The adjusted rGSS odds ratios ranged from 1.6 to 2.2 (P < .001). Using 10-fold cross-validation, the averaged area under the receiver operating characteristic curve for all algorithms increased from 0.76 with unweighted rGSSs to 0.80 with weighted rGSSs. CONCLUSIONS: Unweighted and weighted rGSSs of 4 genotypic resistance algorithms were the strongest independent predictors of VR. Optimizing ARV weighting may further improve VR predictions.

Drug resistance mutations for surveillance of transmitted HIV-1 drug-resistance: 2009 update.

Programs that monitor local, national, and regional levels of transmitted HIV-1 drug resistance inform treatment guidelines and provide feedback on the success of HIV-1 treatment and prevention programs. To accurately compare transmitted drug resistance rates across geographic regions and times, the World Health Organization has recommended the adoption of a consensus genotypic definition of transmitted HIV-1 drug resistance. In January 2007, we outlined criteria for developing a list of mutations for drug-resistance surveillance and compiled a list of 80 RT and protease mutations meeting these criteria (surveillance drug resistance mutations; SDRMs). Since January 2007, several new drugs have been approved and several new drug-resistance mutations have been identified. In this paper, we follow the same procedures described previously to develop an updated list of SDRMs that are likely to be useful for ongoing and future studies of transmitted drug resistance. The updated SDRM list has 93 mutations including 34 NRTI-resistance mutations at 15 RT positions, 19 NNRTI-resistance mutations at 10 RT positions, and 40 PI-resistance mutations at 18 protease positions.

The calibrated population resistance tool: standardized genotypic estimation of transmitted HIV-1 drug resistance.

UNLABELLED: The calibrated population resistance (CPR) tool is a web-accessible program for performing standardized genotypic estimation of transmitted HIV-1 drug resistance. The program is linked to the Stanford HIV drug resistance database and can additionally perform viral genotyping and algorithmic estimation of resistance to specific antiretroviral drugs. AVAILABILITY: http://cpr.stanford.edu/cpr/index.html.

Natural variation of HIV-1 group M integrase: implications for a new class of antiretroviral inhibitors.

HIV-1 integrase is the third enzymatic target of antiretroviral (ARV) therapy. However, few data have been published on the distribution of naturally occurring amino acid variation in this enzyme. We therefore characterized the distribution of integrase variants among more than 1,800 published group M HIV-1 isolates from more than 1,500 integrase inhibitor (INI)-naïve individuals. Polymorphism rates equal or above 0.5% were found for 34% of the central core domain positions, 42% of the C-terminal domain positions, and 50% of the N-terminal domain positions. Among 727 ARV-naïve individuals in whom the complete pol gene was sequenced, integrase displayed significantly decreased inter- and intra-subtype diversity and a lower Shannon's entropy than protease or RT. All primary INI-resistance mutations with the exception of E157Q--which was present in 1.1% of sequences--were nonpolymorphic. Several accessory INI-resistance mutations including L74M, T97A, V151I, G163R, and S230N were also polymorphic with polymorphism rates ranging between 0.5% to 2.0%.

Minority human immunodeficiency virus type 1 variants in antiretroviral-naive persons with reverse transcriptase codon 215 revertant mutations.

T215 revertant mutations such as T215C/D/E/S that evolve from the nucleoside reverse transcriptase (RT) inhibitor mutations T215Y/F have been found in about 3% of human immunodeficiency virus type 1 (HIV-1) isolates from newly diagnosed HIV-1-infected persons. We used a newly developed sequencing method-ultradeep pyrosequencing (UDPS; 454 Life Sciences)--to determine the frequency with which T215Y/F or other RT inhibitor resistance mutations could be detected as minority variants in samples from untreated persons that contain T215 revertants ("revertant" samples) compared with samples from untreated persons that lack such revertants ("control" samples). Among the 22 revertant and 29 control samples, UDPS detected a mean of 3.8 and 4.8 additional RT amino acid mutations, respectively. In 6 of 22 (27%) revertant samples and in 4 of 29 control samples (14%; P = 0.4), UDPS detected one or more RT inhibitor resistance mutations. T215Y or T215F was not detected in any of the revertant or control samples; however, 4 of 22 revertant samples had one or more T215 revertants that were detected by UDPS but not by direct PCR sequencing. The failure to detect viruses with T215Y/F in the 22 revertant samples in this study may result from the overwhelming replacement of transmitted T215Y variants by the more fit T215 revertants or from the primary transmission of a T215 revertant in a subset of persons with T215 revertants.

Sequence editing by Apolipoprotein B RNA-editing catalytic component [corrected] and epidemiological surveillance of transmitted HIV-1 drug resistance.

DESIGN: Promiscuous guanine (G) to adenine (A) substitutions catalysed by apolipoprotein B RNA-editing catalytic component (APOBEC) enzymes are observed in a proportion of HIV-1 sequences in vivo and can introduce artifacts into some genetic analyses. The potential impact of undetected lethal editing on genotypic estimation of transmitted drug resistance was assessed. METHODS: Classifiers of lethal, APOBEC-mediated editing were developed by analysis of lentiviral pol gene sequence variation and evaluated using control sets of HIV-1 sequences. The potential impact of sequence editing on genotypic estimation of drug resistance was assessed in sets of sequences obtained from 77 studies of 25 or more therapy-naive individuals, using mixture modelling approaches to determine the maximum likelihood classification of sequences as lethally edited as opposed to viable. RESULTS: Analysis of 6437 protease and reverse transcriptase sequences from therapy-naive individuals using a novel classifier of lethal, APOBEC3G-mediated sequence editing, the polypeptide-like 3G (APOBEC3G)-mediated defectives (A3GD) index', detected lethal editing in association with spurious 'transmitted drug resistance' in nearly 3% of proviral sequences obtained from whole blood and 0.2% of samples obtained from plasma. CONCLUSION: Screening for lethally edited sequences in datasets containing a proportion of proviral DNA, such as those likely to be obtained for epidemiological surveillance of transmitted drug resistance in the developing world, can eliminate rare but potentially significant errors in genotypic estimation of transmitted drug resistance.

Prevalence of darunavir resistance-associated mutations: patterns of occurrence and association with past treatment.

Eleven protease mutations have been associated with reduced susceptibility to darunavir (DRV). We examined the prevalence and covariates of these mutations in 2 populations. Thirty percent of 1175 Northern California patients and 24% of 2744 non-California patients in the Stanford HIV Drug Resistance Database had viruses with 1 or more mutations associated with resistance to DRV. In multivariate analyses, the number of DRV resistance-associated mutations depended on the number of previous protease inhibitors (PIs) administered and on amprenavir/fosamprenavir treatment. Most PI-treated patients should respond favorably to DRV-based salvage therapy.

HIV-1 subtype B protease and reverse transcriptase amino acid covariation.

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.