HIV-1 Protease and reverse-transcriptase mutations: correlations with antiretroviral therapy in subtype B isolates and implications for drug-resistance surveillance

Mechanistic basis of zidovudine hypersusceptibility and lamivudine resistance conferred by the deletion of codon 69 in the HIV-1 reverse transcriptase coding region

Deletions in the beta 3-beta 4 hairpin loop of human immunodeficiency virus type 1 reverse transcriptase (RT) are associated with the emergence of multidrug resistance. Common mutational patterns involve the deletion of Asp67 (Delta 67) and mutations such as K70R and T215F or T215Y, or the deletion of Thr69 (Delta 69) and mutations of the Q151M complex. Human immunodeficiency virus type 1 clones containing Delta 69 in a multidrug-resistant sequence background, including the Q151M complex and substitutions K103N, Y181C, M184V, and G190A, showed high-level resistance to all tested nucleoside RT inhibitors. In a multidrug-resistant sequence context, the deletion increases viral replication capacity. By itself, Delta 69 conferred increased susceptibility to beta-d-(+)-3'-azido-3'-deoxythymidine (AZT) and beta-l-(-)-2',3'-dideoxy-3'-thiacytidine resistance. Here, we use transient kinetics to show that, in a wild-type sequence background, Delta 69 does not affect the discrimination between AZT triphosphate and 2'-deoxythymidine 5'-triphosphate, but decreases the catalytic efficiency of the incorporation of beta-l-(-)-2',3'-dideoxy-3'-thiacytidine triphosphate relative to 2'-deoxycytidine 5'-triphosphate. In comparison with the wild-type RT, the Delta 69 mutant showed decreased ability to excise primers terminated with AZT monophosphate in the presence of ATP or pyrophosphate (PPi). These data support the role of the excision mechanism in mediating AZT hypersusceptibility. In addition, we demonstrate that the deletion has no effect on resistance to foscarnet (a PPi analogue) on phenotypic and nucleotide incorporation assays carried out with viral clones and recombinant enzymes, respectively. The results of molecular modeling studies suggest that the side chains of Lys65, Asp67, and Lys219 could play an important role in AZT hypersusceptibility mediated by Delta 69, whereas in the absence of Thr69, local structural rearrangements affecting the beta 3-beta 4 and beta 11a-beta 12 loops of the 66-kDa subunit of the RT could reduce the accessibility of the PPi donor to the terminating nucleotide at the 3' end of the primer.

Impact on replicative fitness of the G48E substitution in the protease of HIV-1: an in vitro and in silico evaluation

We observed an unusual glycine-to-glutamate substitution at protease (PR) residue position 48 (G48E) in an African patient infected with a subtype A1 HIV-1 strain failing a saquinavir-containing regimen. Phenotypic analysis of protease inhibitor (PI) susceptibility showed that the G48E site-directed mutant, when introduced into an NL4-3 HIV-1 PR backbone, was slightly resistant to SQV (2-fold when compared with the wild-type virus). In addition, the G48E and G48E/V82A site-directed mutants were associated with a decrease in fitness, whereas a reversion to the wild type at position 48 was observed in vitro. Growth competition experiments using a novel growth competition assay based on enhanced green fluorescent protein- or Discosoma spp. red fluorescent protein-expressing viruses showed that the replicative fitness of the G48E virus was reduced to 55% compared with the parental NL4-3 virus. Synthesizing all possible site-directed mutants found in the patient strain is too time-consuming; therefore, a molecular dynamics (MD) simulation approach was used to understand why this mutation survived despite its fitness cost. These simulations documented that the G48E mutant interacted with PI resistance mutations (M46I, I54V, Q58E, and L63P) and with natural polymorphisms specific to subtype A1 (E35D, M36I, and R57K) that were present in the patient's virus. We hypothesize that the polymorphisms contained in the PR flap regions of the patient's virus may compensate for the presence of G48E, possibly by restoring the flexibility of the PR flaps. In summary, our results demonstrate that the G48E substitution, when introduced in the context of an HIV-1 subtype B strain, is highly unstable and gives rise to viruses with a poor replicative fitness in vitro. We also showed that when confronted with too many mutations to evaluate in vitro, MD simulations are helpful to draft hypotheses on how polymorphisms can interact with resistance mutations to stabilize their potential fitness cost.

Resilience to resistance of HIV-1 protease inhibitors: profile of darunavir

The current effectiveness of HAART in the management of HIV infection is compromised by the emergence of extensively cross-resistant strains of HIV-1, requiring a significant need for new therapeutic agents. Due to its crucial role in viral maturation and therefore HIV-1 replication and infectivity, the HIV-1 protease continues to be a major development target for antiretroviral therapy. However, new protease inhibitors must have higher thresholds to the development of resistance and cross-resistance. Research has demonstrated that the binding characteristics between a protease inhibitor and the active site of the HIV-1 protease are key factors in the development of resistance. More specifically, the way in which a protease inhibitor fits within the substrate consensus volume, or "substrate envelope", appears to be critical. The currently available inhibitors are not only smaller than the native substrates, but also have a different shape. This difference in shape underlies observed patterns of resistance because primary drug-resistant mutations often arise at positions in the protease where the inhibitors protrude beyond the substrate envelope but are still in contact with the enzyme. Since all currently available protease inhibitors occupy a similar space (in spite of their structural differences) in the active site of the enzyme, the specific positions where the inhibitors protrude and contact the enzyme correspond to the locations where most mutations occur that give rise to multidrug-resistant HIV-1 strains. Detailed investigation of the structure, thermodynamics, and dynamics of the active site of the protease enzyme is enabling the identification of new protease inhibitors that more closely fit within the substrate envelope and therefore decrease the risk of drug resistance developing. The features of darunavir, the latest FDA-approved protease inhibitor, include its high binding affinity (Kd = 4.5 x 10-12 M) for the protease active site, the presence of hydrogen bonds with the backbone, and its ability to fit closely within the substrate envelope (or consensus volume). Darunavir is potent against both wild-type and protease inhibitor-resistant viruses in vitro, including a broad range of over 4,000 clinical isolates. Additionally, in vitro selection studies with wild-type HIV-1 strains have shown that resistance to darunavir develops much more slowly and is more difficult to generate than for existing protease inhibitors. Clinical studies have shown that darunavir administered with low-dose ritonavir (darunavir/ritonavir) provides highly potent viral suppression (including significant decreases in HIV viral load in patients with documented protease inhibitor resistance) together with favorable tolerability. In conclusion, as a result of its high binding affinity for and overall fit within the active site of HIV-1 protease, darunavir has a higher genetic barrier to the development of resistance and better clinical efficacy against multidrug-resistant HIV relative to current protease inhibitors. The observed efficacy, safety and tolerability of darunavir in highly treatment-experienced patients makes darunavir an important new therapeutic option for HIV-infected patients.

An HIV-1 215V mutant shows increased phenotypic resistance to d4T

Human immunodeficiency virus type 1 (HIV-1) viruses with C/S/D/E at 215 codon of the reverse transcriptase (RT) have been associated with the T215Y/F HIV-1 resistant viruses transmission to naïve patients. The uncommon T215V mutation was detected in DNA proviral samples of a treatment-naïve patient. Virus T215V was obtained after cloning the patient-RT into a molecular clone. Wild-type (T215) and resistant (T215F) clones, were obtained in T215V clone by "in vitro" site-directed mutagenesis. Phenotypic resistance against AZT, ddI and d4T, replication kinetics and the selection of resistance mutations were estimated "in vitro". The T215V virus replicated as efficiently as the wild-type (T215) without antivirals and in the presence of AZT or ddI. The T215V virus showed higher replicative capacity than the wild-type and a 4.3-fold increase in the IC(50) values in cultures with d4T. Selection of resistance mutations was not observed in viral quasispecies of the T215V virus after serial passages in culture in presence of increasing concentrations of AZT, ddI or d4T. This work demonstrates that the T215V mutation decreases the susceptibility of HIV-1 to d4T, and consequently, it could compromise the response to regimens containing this antiviral.

Proteochemometric modeling of HIV protease susceptibility

BACKGROUND

A major obstacle in treatment of HIV is the ability of the virus to mutate rapidly into drug-resistant variants. A method for predicting the susceptibility of mutated HIV strains to antiviral agents would provide substantial clinical benefit as well as facilitate the development of new candidate drugs. Therefore, we used proteochemometrics to model the susceptibility of HIV to protease inhibitors in current use, utilizing descriptions of the physico-chemical properties of mutated HIV proteases and 3D structural property descriptions for the protease inhibitors. The descriptions were correlated to the susceptibility data of 828 unique HIV protease variants for seven protease inhibitors in current use; the data set comprised 4792 protease-inhibitor combinations.

RESULTS

The model provided excellent predictability (R2 = 0.92, Q2 = 0.87) and identified general and specific features of drug resistance. The model's predictive ability was verified by external prediction in which the susceptibilities to each one of the seven inhibitors were omitted from the data set, one inhibitor at a time, and the data for the six remaining compounds were used to create new models. This analysis showed that the over all predictive ability for the omitted inhibitors was Q2 inhibitors = 0.72.

CONCLUSION

Our results show that a proteochemometric approach can provide generalized susceptibility predictions for new inhibitors. Our proteochemometric model can directly analyze inhibitor-protease interactions and facilitate treatment selection based on viral genotype. The model is available for public use, and is located at HIV Drug Research Centre.

Ninety-nine is not enough: molecular characterization of inhibitor-resistant human immunodeficiency virus type 1 protease mutants with insertions in the flap region

While the selection of amino acid insertions in human immunodeficiency virus (HIV) reverse transcriptase (RT) is a known mechanism of resistance against RT inhibitors, very few reports on the selection of insertions in the protease (PR) coding region have been published. It is still unclear whether these insertions impact protease inhibitor (PI) resistance and/or viral replication capacity. We show that the prevalence of insertions, especially between amino acids 30 to 41 of HIV type 1 (HIV-1) PR, has increased in recent years. We identified amino acid insertions at positions 33 and 35 of the PR of HIV-1-infected patients who had undergone prolonged treatment with PIs, and we characterized the contribution of these insertions to viral resistance. We prepared the corresponding mutated, recombinant PR variants with or without insertions at positions 33 and 35 and characterized them in terms of enzyme kinetics and crystal structures. We also engineered the corresponding recombinant viruses and analyzed the PR susceptibility and replication capacity by recombinant virus assay. Both in vitro methods confirmed that the amino acid insertions at positions 33 and 35 contribute to the viral resistance to most of the tested PIs. The structural analysis revealed local structural rearrangements in the flap region and in the substrate binding pockets. The enlargement of the PR substrate binding site together with impaired flap dynamics could account for the weaker inhibitor binding by the insertion mutants. Amino acid insertions in the vicinity of the binding cleft therefore represent a novel mechanism of HIV resistance development.

HIV-1 drug resistance mutations: an updated framework for the second decade of HAART

More than 200 mutations are associated with antiretroviral resistance to drugs belonging to six licensed antiretroviral classes. More than 50 reverse transcriptase mutations are associated with nucleoside reverse transcriptase inhibitor resistance including M184V, thymidine analog mutations, mutations associated with non-thymidine analog containing regimens, multi-nucleoside resistance mutations, and several recently identified accessory mutations. More than 40 reverse transcriptase mutations are associated with nonnucleoside reverse transcriptase inhibitor resistance including major primary and secondary mutations, non-polymorphic minor mutations, and polymorphic accessory mutations. More than 60 mutations are associated with protease inhibitor resistance including major protease, accessory protease, and protease cleavage site mutations. More than 30 integrase mutations are associated with the licensed integrase inhibitor raltegravir and the investigational inhibitor elvitegravir. More than 15 gp41 mutations are associated with the fusion inhibitor enfuvirtide. CCR5 inhibitor resistance results from mutations that promote gp120 binding to an inhibitor-bound CCR5 receptor or CXCR4 tropism; however, the genotypic correlates of these processes are not yet well characterized.

Protease inhibitor resistance update: where are we now?

The introduction of protease inhibitors (PIs) and highly active antiretroviral therapy in the mid-1990s dramatically altered the treatment of HIV infection, enabling suppression of viral replication to undetectable levels and preventing disease progression. Most PIs present a strong barrier against viral resistance; the accumulation of multiple mutations is often required to produce resistance. However, there is variability of resistance within the PI class, as demonstrated by the fact that some PIs require fewer mutations to confer resistance compared with others. Resistance to individual PIs as well as the development of broad cross-resistance to multiple agents in this class remain major challenges in clinical practice. Resistance to PIs may involve primary or secondary mutations in the protease gene in addition to mutations outside of protease in the gag cleavage and noncleavage sites. Primary mutations may be sufficient to confer resistance to select PIs. Secondary mutations may be required to produce resistance with some PIs, whereas other mutations may be compensatory, restoring activity of the viral protease or increasing the replicative capacity of the virus. Specific resistance patterns associated with individual PIs have been identified. Strategies to prevent PI cross-resistance and to manage its occurrence involve rational sequencing of PIs, ritonavir boosting to maintain a strong barrier against viral resistance, the use of newer PIs with activity against resistant viruses or unique resistance profiles, avoidance of PI combinations with overlapping resistance patterns, and application of knowledge of mutations associated with hypersusceptibility to other agents in this class.

Conservation patterns of HIV-1 RT connection and RNase H domains: identification of new mutations in NRTI-treated patients

Background

Although extensive HIV drug resistance information is available for the first 400 amino acids of its reverse transcriptase, the impact of antiretroviral treatment in C-terminal domains of Pol (thumb, connection and RNase H) is poorly understood.

Methods and Findings

We wanted to characterize conserved regions in RT C-terminal domains among HIV-1 group M subtypes and CRF. Additionally, we wished to identify NRTI-related mutations in HIV-1 RT C-terminal domains. We sequenced 118 RNase H domains from clinical viral isolates in Brazil, and analyzed 510 thumb and connection domain and 450 RNase H domain sequences collected from public HIV sequence databases, together with their treatment status and histories. Drug-naïve and NRTI-treated datasets were compared for intra- and inter-group conservation, and differences were determined using Fisher's exact tests. One third of RT C-terminal residues were found to be conserved among group M variants. Three mutations were found exclusively in NRTI-treated isolates. Nine mutations in the connection and 6 mutations in the RNase H were associated with NRTI treatment in subtype B. Some of them lay in or close to amino acid residues which contact nucleic acid or near the RNase H active site. Several of the residues pointed out herein have been recently associated to NRTI exposure or increase drug resistance to NRTI.

Conclusions

This is the first comprehensive genotypic analysis of a large sequence dataset that describes NRTI-related mutations in HIV-1 RT C-terminal domains in vivo. The findings into the conservation of RT C-terminal domains may pave the way to more rational drug design initiatives targeting those regions.

Identification of a novel resistance (E40F) and compensatory (K43E) substitution in HIV-1 reverse transcriptase

Background

HIV-1 nucleoside reverse transcriptase inhibitors (NRTIs) have been used in the clinic for over twenty years. Interestingly, the complete resistance pattern to this class has not been fully elucidated. Novel mutations in RT appearing during treatment failure are still being identified. To unravel the role of two of these newly identified changes, E40F and K43E, we investigated their effect on viral drug susceptibility and replicative capacity.

Results

A large database (Quest Diagnostics database) was analysed to determine the associations of the E40F and K43E changes with known resistance mutations. Both amino acid changes are strongly associated with the well known NRTI-resistance mutations M41L, L210W and T215Y. In addition, a strong positive association between these changes themselves was observed. A panel of recombinant viruses was generated by site-directed mutagenesis and phenotypically analysed. To determine the effect on replication capacity, competition and in vitro evolution experiments were performed. Introduction of E40F results in an increase in Zidovudine resistance ranging from nine to fourteen fold depending on the RT background and at the same time confers a decrease in viral replication capacity. The K43E change does not decrease the susceptibility to Zidovudine but increases viral replication capacity, when combined with E40F, demonstrating a compensatory role for this codon change.

Conclusion

In conclusion, we have identified a novel resistance (E40F) and compensatory (K43E) change in HIV-1 RT. Further research is indicated to analyse the clinical importance of these changes.

Consensus Drug Resistance Mutations for Epidemiological Surveillance: Basic Principles and Potential Controversies

Programmes 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 programmes. The World Health Organization (WHO) has established a global programme for genotypic surveillance of HIV-1 drug resistance and has recommended the adoption of a consensus definition of genotypic drug resistance. Such a definition is necessary to accurately compare transmitted drug resistance rates across geographical regions and time periods. HIV-1 diversity and the large number of mutations associated with antiretroviral drug resistance complicate the development of a consensus definition for genotypic drug resistance. This paper reviews the data that must be considered to determine which of the many HIV-1 drug resistance mutations are likely to be both sensitive and specific indicators of transmitted drug resistance. The process used to create a previously published list of drug resistance mutations for HIV-1 surveillance is reviewed and alternative approaches to this process are discussed.

Amino acid mutation N348I in the connection subdomain of human immunodeficiency virus type 1 reverse transcriptase confers multiclass resistance to nucleoside and nonnucleoside reverse transcriptase inhibitors

We identified clinical isolates with phenotypic resistance to nevirapine (NVP) in the absence of known nonnucleoside reverse transcriptase inhibitor (NNRTI) mutations. This resistance is caused by N348I, a mutation at the connection subdomain of human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT). Virologic analysis showed that N348I conferred multiclass resistance to NNRTIs (NVP and delavirdine) and to nucleoside reverse transcriptase inhibitors (zidovudine [AZT] and didanosine [ddI]). N348I impaired HIV-1 replication in a cell-type-dependent manner. Acquisition of N348I was frequently observed in AZT- and/or ddI-containing therapy (12.5%; n = 48; P < 0.0001) and was accompanied with thymidine analogue-associated mutations, e.g., T215Y (n = 5/6) and the lamivudine resistance mutation M184V (n = 1/6) in a Japanese cohort. Molecular modeling analysis shows that residue 348 is proximal to the NNRTI-binding pocket and to a flexible hinge region at the base of the p66 thumb that may be affected by the N348I mutation. Our results further highlight the role of connection subdomain residues in drug resistance.

Consensus drug resistance mutations for epidemiological surveillance: basic principles and potential controversies

Programmes 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 programmes. The World Health Organization (WHO) has established a global programme for genotypic surveillance of HIV-1 drug resistance and has recommended the adoption of a consensus definition of genotypic drug resistance. Such a definition is necessary to accurately compare transmitted drug resistance rates across geographical regions and time periods. HIV-1 diversity and the large number of mutations associated with antiretroviral drug resistance complicate the development of a consensus definition for genotypic drug resistance. This paper reviews the data that must be considered to determine which of the many HIV-1 drug resistance mutations are likely to be both sensitive and specific indicators of transmitted drug resistance. The process used to create a previously published list of drug resistance mutations for HIV-1 surveillance is reviewed and alternative approaches to this process are discussed.

Factors associated with the selection of mutations conferring resistance to protease inhibitors (PIs) in PI-experienced patients displaying treatment failure on darunavir

The objective of this study was to characterize the mutations selected by darunavir (DRV) use in protease inhibitor (PI)-experienced patients and the associated factors. We analyzed treatment failure in 54 PI-experienced human immunodeficiency virus (HIV)-infected patients on a DRV- and ritonavir-containing regimen. Viral genotyping was carried out at the baseline, at between 1 and 3 months of treatment, and at between 3 and 6 months of treatment to search for the selection of mutations conferring resistance to PIs. The median baseline HIV RNA level was 4.9 log(10) copies/ml, and the median CD4 count was 87 cells/mm(3). At the baseline, the median numbers of resistance mutations were as follows: 3 DRV resistance mutations, 4 major PI resistance mutations, and 10 minor PI resistance mutations. The most common mutations that emerged at rebound included V32I (44%), I54M/L (24%), L33F (25%), I84V (21%), and L89V (12%). Multivariate analysis showed that higher baseline HIV RNA levels and smaller numbers of nucleoside reverse transcriptase inhibitor simultaneously used with DRV were associated with a higher risk of DRV resistance mutation selection. By contrast, L76V, a known DRV resistance mutation, was found to decrease the risk of selection of another DRV resistance mutation. The occurrence of virological failure while a patient was on DRV was associated with the selection of mutations that increased the level of DRV resistance without affecting susceptibility to tipranavir (TPV). In these PI-treated patients who displayed treatment failure while they were on a DRV-containing regimen, we confirmed the set of emerging mutations associated with DRV failure and identified the factors associated with the selection of these mutations. TPV susceptibility does not seem to be affected by the selection of a DRV resistance mutation.

An ontology-driven method for hierarchical mining of temporal patterns: application to HIV drug resistance research

Many biomedical research databases contain time-oriented data resulting from longitudinal, time-series and time-dependent study designs, knowledge of which is not handled explicitly by most data-analytic methods. To make use of such knowledge about research data, we have developed an ontology-driven temporal mining method, called ChronoMiner. Most mining algorithms require data be inputted in a single table. ChronoMiner, in contrast, can search for interesting temporal patterns among multiple input tables and at different levels of hierarchical representation. In this paper, we present the application of our method to the discovery of temporal associations between newly arising mutations in the HIV genome and past drug regimens. We discuss the various components of ChronoMiner, including its user interface, and provide results of a study indicating the efficiency and potential value of ChronoMiner on an existing HIV drug resistance data repository.

Characterization and structural analysis of novel mutations in human immunodeficiency virus type 1 reverse transcriptase involved in the regulation of resistance to nonnucleoside inhibitors

Resistance to antivirals is a complex and dynamic phenomenon that involves more mutations than are currently known. Here, we characterize 10 additional mutations (L74V, K101Q, I135M/T, V179I, H221Y, K223E/Q, and L228H/R) in human immunodeficiency virus type 1 (HIV-1) reverse transcriptase which are involved in the regulation of resistance to nonnucleoside reverse transcriptase inhibitors (NNRTIs). These mutations are strongly associated with NNRTI failure and strongly correlate with the classical NNRTI resistance mutations in a data set of 1,904 HIV-1 B-subtype pol sequences from 758 drug-naïve patients, 592 nucleoside reverse transcriptase inhibitor (NRTI)-treated but NNRTI-naïve patients, and 554 patients treated with both NRTIs and NNRTIs. In particular, L74V and H221Y, positively correlated with Y181C, were associated with an increase in Y181C-mediated resistance to nevirapine, while I135M/T mutations, positively correlated with K103N, were associated with an increase in K103N-mediated resistance to efavirenz. In addition, the presence of the I135T polymorphism in NNRTI-naïve patients significantly correlated with the appearance of K103N in cases of NNRTI failure, suggesting that I135T may represent a crucial determinant of NNRTI resistance evolution. Molecular dynamics simulations show that I135T can contribute to the stabilization of the K103N-induced closure of the NNRTI binding pocket by reducing the distance and increasing the number of hydrogen bonds between 103N and 188Y. H221Y also showed negative correlations with type 2 thymidine analogue mutations (TAM2s); its copresence with the TAM2s was associated with a higher level of zidovudine susceptibility. Our study reinforces the complexity of NNRTI resistance and the significant interplay between NRTI- and NNRTI-selected mutations. Mutations beyond those currently known to confer resistance should be considered for a better prediction of clinical response to reverse transcriptase inhibitors and for the development of more efficient new-generation NNRTIs.

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.

Hydrophobic sliding: a possible mechanism for drug resistance in human immunodeficiency virus type 1 protease

Hydrophobic residues outside the active site of HIV-1 protease frequently mutate in patients undergoing protease inhibitor therapy; however, the mechanism by which these mutations confer drug resistance is not understood. From analysis of molecular dynamics simulations, 19 core hydrophobic residues appear to facilitate the conformational changes that occur in HIV-1 protease. The hydrophobic core residues slide by each other, exchanging one hydrophobic van der Waal contact for another, with little energy penalty, while maintaining many structurally important hydrogen bonds. Such hydrophobic sliding may represent a general mechanism by which proteins undergo conformational changes. Mutation of these residues in HIV-1 protease would alter the packing of the hydrophobic core, affecting the conformational flexibility of the protease. Therefore these residues impact the dynamic balance between processing substrates and binding inhibitors, and thus contribute to drug resistance.

Sequential emergence and clinical implications of viral mutants with K70E and K65R mutation in reverse transcriptase during prolonged tenofovir monotherapy in rhesus macaques with chronic RT-SHIV infection

BACKGROUND

We reported previously on the emergence and clinical implications of simian immunodeficiency virus (SIVmac251) mutants with a K65R mutation in reverse transcriptase (RT), and the role of CD8+ cell-mediated immune responses in suppressing viremia during tenofovir therapy. Because of significant sequence differences between SIV and HIV-1 RT that affect drug susceptibilities and mutational patterns, it is unclear to what extent findings with SIV can be extrapolated to HIV-1 RT. Accordingly, to model HIV-1 RT responses, 12 macaques were inoculated with RT-SHIV, a chimeric SIV containing HIV-1 RT, and started on prolonged tenofovir therapy 5 months later.

RESULTS

The early virologic response to tenofovir correlated with baseline viral RNA levels and expression of the MHC class I allele Mamu-A*01. For all animals, sensitive real-time PCR assays detected the transient emergence of K70E RT mutants within 4 weeks of therapy, which were then replaced by K65R mutants within 12 weeks of therapy. For most animals, the occurrence of these mutations preceded a partial rebound of plasma viremia to levels that remained on average 10-fold below baseline values. One animal eventually suppressed K65R viremia to undetectable levels for more than 4 years; sequential experiments using CD8+ cell depletion and tenofovir interruption demonstrated that both CD8+ cells and continued tenofovir therapy were required for sustained suppression of viremia.

CONCLUSION

This is the first evidence that tenofovir therapy can select directly for K70E viral mutants in vivo. The observations on the clinical implications of the K65R RT-SHIV mutants were consistent with those of SIVmac251, and suggest that for persons infected with K65R HIV-1 both immune-mediated and drug-dependent antiviral activities play a role in controlling viremia. These findings suggest also that even in the presence of K65R virus, continuation of tenofovir treatment as part of HAART may be beneficial, particularly when assisted by antiviral immune responses.

Stratified medicine: strategic and economic implications of combining drugs and clinical biomarkers

The potential to use biomarkers for identifying patients that are more likely to benefit or experience an adverse reaction in response to a given therapy, and thereby better match patients with therapies, is anticipated to have a major effect on both clinical practice and the development of new drugs and diagnostics. In this article, we consider current and emerging examples in which therapies are matched with specific patient population characteristics using clinical biomarkers - which we call stratified medicine - and discuss the implications of this approach to future product development strategies and market structures.

Long-Term Foscarnet Therapy Remodels Thymidine Analogue Mutations and Alters Resistance to Zidovudine and Lamivudine in HIV-1

Objective

To study the evolution of multi-drug-resistant HIV-1 in treatment-experienced patients receiving foscarnet (PFA) as part of salvage therapy and to investigate the virological consequences of emerging mutations.

Methods

Genotypic and phenotypic resistance tests were performed on plasma viruses from seven patients at baseline and during treatment with PFA. The phenotypic effects of mutations suspected to be associated with PFA resistance were evaluated by site-directed mutagenesis of wild-type or thymidine analogue mutations (TAM)-carrying pNL4–3. Reversion of single mutations was performed in a patient-derived recombinant clone.

Results

Baseline multi-drug-resistant isolates exhibited hypersusceptibility to PFA. In two patients who received >12 months of PFA treatment, a novel mutation pattern including K70G, V75T, K219R and L228R emerged. These viruses had 3–6-fold resistance to PFA, a 2–20-fold decrease in resistance to zidovudine compared to baseline, and 14–39-fold resistance to lamivudine, in the absence of M184V. In wild-type clones mutations K70G and V75T induced moderate PFA resistance. In the case of TAMs, combinations of ≥3 mutations (K70G+K219R+L228R±V75T) induced PFA resistance and decreased zidovudine resistance 3–13-fold. These mutants exhibited high-level lamivudine resistance (>20-fold) without mutation M184V. Reversion of K70G→R and K219R→E in a patient-derived clone confirmed the contribution of individual mutations and the negative association between PFA resistance and zidovudine resistance.

Conclusions

In the context of multiple TAMs, hypersusceptibility to PFA was observed and a novel pattern of resistance, including alternative amino acid substitutions at TAM loci, emerged. This mutational pattern was associated with decreases in zidovudine resistance and surprisingly high-level lamivudine resistance.

Super learning: an application to the prediction of HIV-1 drug resistance

Many alternative data-adaptive algorithms can be used to learn a predictor based on observed data. Examples of such learners include decision trees, neural networks, support vector regression, least angle regression, logic regression, and the Deletion/Substitution/Addition algorithm. The optimal learner for prediction will vary depending on the underlying data-generating distribution. In this article we introduce the "super learner", a prediction algorithm that applies any set of candidate learners and uses cross-validation to select between them. Theory shows that asymptotically the super learner performs essentially as well as or better than any of the candidate learners. In this article we present the theory behind the super learner, and illustrate its performance using simulations. We further apply the super learner to a data example, in which we predict the phenotypic antiretroviral susceptibility of HIV based on viral genotype. Specifically, we apply the super learner to predict susceptibility to a specific protease inhibitor, nelfinavir, using a set of database-derived non-polymorphic treatment-selected mutations.

Identification of accessory mutations associated with high-level resistance in HIV-1 reverse transcriptase

OBJECTIVE

To identify accessory mutations associated with high levels of resistance to reverse transcriptase inhibitors (RTI).

DESIGN

HIV pol sequences from routine resistance tests from over 3000 patients who were treatment experienced and infected with subtype B HIV-1 were analysed. Changes relative to the wild-type amino acid for codons 1-400 of reverse transcriptase were determined in two series: (i) samples showing the accumulation of thymidine analogue mutations (TAMs); and (ii) samples showing the accumulation of non-nucleoside reverse transcriptase inhibitor (NNRTI) resistance mutations.

METHODS

Accessory mutations were identified as occurring in those codons in which there was a statistically significant association between the distribution of amino acids and the number of TAMs/NNRTI resistance mutations. Positions already established as drug resistance positions by the International AIDS Society - USA Panel were not included in this analysis.

RESULTS

Twenty-four positions were identified where accessory mutations were associated with the accumulation of TAMs (20, 35, 39, 43, 60, 83, 98, 101, 122, 135, 179, 196, 203, 208, 218, 223, 228, 284, 322, 356, 359, 360, 371 and 381). Likewise changes at 25 positions (6, 20, 35, 39, 43, 53, 68, 90, 98, 101, 122, 179, 200, 203, 208, 218, 221, 223, 228, 284, 318, 320, 348, 359 and 371) were associated with NNRTI mutations. The accumulation of accessory mutations correlated with increasing numbers of TAMs and NNRTI mutations.

CONCLUSION

The development of high-level resistance to RTI is associated not only with the accumulation of recognized mutations but also with accessory mutations.

Genotypic predictors of human immunodeficiency virus type 1 drug resistance

Understanding the genetic basis of HIV-1 drug resistance is essential to developing new antiretroviral drugs and optimizing the use of existing drugs. This understanding, however, is hampered by the large numbers of mutation patterns associated with cross-resistance within each antiretroviral drug class. We used five statistical learning methods (decision trees, neural networks, support vector regression, least-squares regression, and least angle regression) to relate HIV-1 protease and reverse transcriptase mutations to in vitro susceptibility to 16 antiretroviral drugs. Learning methods were trained and tested on a public data set of genotype-phenotype correlations by 5-fold cross-validation. For each learning method, four mutation sets were used as input features: a complete set of all mutations in > or =2 sequences in the data set, the 30 most common data set mutations, an expert panel mutation set, and a set of nonpolymorphic treatment-selected mutations from a public database linking protease and reverse transcriptase sequences to antiretroviral drug exposure. The nonpolymorphic treatment-selected mutations led to the best predictions: 80.1% accuracy at classifying sequences as susceptible, low/intermediate resistant, or highly resistant. Least angle regression predicted susceptibility significantly better than other methods when using the complete set of mutations. The three regression methods provided consistent estimates of the quantitative effect of mutations on drug susceptibility, identifying nearly all previously reported genotype-phenotype associations and providing strong statistical support for many new associations. Mutation regression coefficients showed that, within a drug class, cross-resistance patterns differ for different mutation subsets and that cross-resistance has been underestimated.

Rationale and uses of a public HIV drug-resistance database

Knowledge regarding the drug resistance of human immunodeficiency virus (HIV) is critical for surveillance of drug resistance, development of antiretroviral drugs, and management of infections with drug-resistant viruses. Such knowledge is derived from studies that correlate genetic variation in the targets of therapy with the antiretroviral treatments received by persons from whom the variant was obtained (genotype-treatment), with drug-susceptibility data on genetic variants (genotype-phenotype), and with virological and clinical response to a new treatment regimen (genotype-outcome). An HIV drug-resistance database is required to represent, store, and analyze the diverse forms of data underlying our knowledge of drug resistance and to make these data available to the broad community of researchers studying drug resistance in HIV and clinicians using HIV drug-resistance tests. Such genotype-treatment, genotype-phenotype, and genotype-outcome correlations are contained in the Stanford HIV RT and Protease Sequence Database and have specific usefulness.

Rate of viral evolution and risk of losing future drug options in heavily pretreated, HIV-infected patients who continue to receive a stable, partially suppressive treatment regimen

BACKGROUND

Many treatment-experienced, HIV-infected patients who have limited therapeutic options for complete viral suppression continue to receive a partially suppressive treatment regimen pending the availability of at least 2 new antiretroviral drugs. The major risk of this approach is ongoing viral evolution and the loss of future drug options.

METHODS

Antiretroviral-treated subjects with incomplete viral suppression were sampled from a clinic-based cohort. Inclusion criteria were receipt of a stable treatment regimen for > or = 120 days, a plasma HIV RNA load of > 500 copies/mL, and > or = 1 resistance mutation. Phenotypic and genotypic resistance testing was performed every 4 months.

RESULTS

The 106 patients who were eligible for the study had a median of 3 observations during a median of 11.3 months. An estimated 23% and 18% developed at least 1 new nucleoside analogue and 1 new protease inhibitor mutation at 1 year, respectively. An estimated 30% lost the phenotypic equivalent of 1 susceptible drug at 1 year. A lower number of total mutations at baseline was a significant predictor of developing a new nucleoside analogue mutation (P=.01). At 1 year, the probability that an existing mutation would become undetectable using population-based sequencing was 32%. There was a higher rate of change at nonresistance codons than at codons known to be associated with drug resistance.

CONCLUSIONS

Heavily pretreated patients with HIV infection who remain on a partially suppressive regimen have a measurable risk of losing future drug options, particularly those patients who have few baseline mutations. Resistance mutations vary over time, which suggests that the results of any single resistance test may not be representative of all mutations selected by a given treatment regimen.

Involvement of novel human immunodeficiency virus type 1 reverse transcriptase mutations in the regulation of resistance to nucleoside inhibitors

We characterized 16 additional mutations in human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT) whose role in drug resistance is still unknown by analyzing 1,906 plasma-derived HIV-1 subtype B pol sequences from 551 drug-naïve patients and 1,355 nucleoside RT inhibitor (NRTI)-treated patients. Twelve mutations positively associated with NRTI treatment strongly correlated both in pairs and in clusters with known NRTI resistance mutations on divergent evolutionary pathways. In particular, T39A, K43E/Q, K122E, E203K, and H208Y clustered with the nucleoside analogue mutation 1 cluster (NAM1; M41L+L210W+T215Y). Their copresence in this cluster was associated with an increase in thymidine analogue resistance. Moreover, treatment failure in the presence of K43E, K122E, or H208Y was significantly associated with higher viremia and lower CD4 cell count. Differently, D218E clustered with the NAM2 pathway (D67N+K70R+K219Q+T215F), and its presence in this cluster determined an increase in zidovudine resistance. In contrast, three mutations (V35I, I50V, and R83K) negatively associated with NRTI treatment showed negative correlations with NRTI resistance mutations and were associated with increased susceptibility to specific NRTIs. In particular, I50V negatively correlated with the lamivudine-selected mutation M184V and was associated with a decrease in M184V/lamivudine resistance, whereas R83K negatively correlated with both NAM1 and NAM2 clusters and was associated with a decrease in thymidine analogue resistance. Finally, the association pattern of the F214L polymorphism revealed its propensity for the NAM2 pathway and its strong negative association with the NAM1 pathway. Our study provides evidence of novel RT mutational patterns that regulate positively and/or negatively NRTI resistance and strongly suggests that other mutations beyond those currently known to confer resistance should be considered for improved prediction of clinical response to antiretroviral drugs.

Prevalence and Impact of HIV-1 Protease Codon 33 Mutations and Polymorphisms in Treatment-Naive and Treatment-Experienced Patients

Background

HIV-1 protease gene mutations at codon 33 have been associated with resistance to some but not all protease inhibitors (PIs). Little is known about the difference in prevalence of codon 33 mutations and polymorphisms between treatment-naive and treatment-experienced patients, and the effect of codon 33F on PI phenotypic resistance patterns.

Methods

Baseline genotypes (TRUGENE) from 772 patients participating in two different randomized clinical trials [504 antiretroviral treatment-naive patients and 268 antiretroviral treatment-experienced patients] were evaluated for the presence of protease codon 33 mutations and polymorphisms. Baseline phenotypes (Antivirogram), including fold-change in resistance for 16 antiretroviral drugs, were available for the 268 treatment-experienced patients. Multivariate linear regression models were used to determine factors associated with phenotypic fold-change for PIs.

Results

The prevalence of codon 33 mutations and polymorphisms was 5.2% in the naive cohort (0.2% 33F, 2.5% 33V, 2.5% 33I) and 34.7% in the experienced cohort (30.2% 33F, 1.5% 33V, 3.0% 33I). In the antiretroviral-experienced cohort (mean = 4.2 prior PIs, 10.6 prior antiretroviral drugs overall), a model adjusting for the presence of specific major protease and multi-PI resistance conferring mutations, the number of other minor PI mutations, prior PI drug exposure (current, prior only, never), and HIV transmission risk factor was used to estimate the phenotypic fold-change in resistance for those with and without mutation 33F. Those with 33F had a significantly higher fold-change for amprenavir (33 vs 19, P<0.0001), ritonavir (162 vs 82, P<0.0001), lopinavir (49 vs 38, P=0.04), and saquinavir (47 vs 41, P=0.02). The presence of the 33F was not a significant predictor of fold change in susceptibility for indinavir or nelfinavir.

Conclusions

At protease codon 33, the prevalences of polymorphisms 33V and 33I were similar for PI-naive and PI-experienced patients (<3.0%), but the prevalence of 33F was significantly different (0.2% versus 30.2%). In the treatment-experienced cohort, the differences in phenotypic fold-change for amprenavir, lopinavir, saquinavir, and ritonavir between those with and without 33F persist after adjustment for the presence of other major PI mutations and PI drug exposure history. Given the availability of newer PIs that may select for 33F, monitoring for the presence of this mutation should be ongoing for both treatment-naive and treatment-experienced patients.

Increasing prevalence of HIV-1 protease inhibitor-associated mutations correlates with long-term non-suppressive protease inhibitor treatment

Treatment of human immunodeficiency virus type 1 with protease inhibitors (PIs) is associated with the emergence of resistance-associated mutations. Treatment-characterized datasets have been used to identify novel treatment-associated protease mutations. In this study, we utilized two large reference laboratory databases (>115,000 viral sequences) to identify non-established resistance-associated protease mutations. We found 20 non-established protease mutations occurring in 82% of viruses with a PI resistance score of 4-7, 62% of viruses with a resistance score of 1-3, and 35% of viruses with no predicted PI resistance. We correlated mutational prevalence to treatment duration in a treatment-characterized dataset of 2161 patients undergoing non-suppressive PI therapy. In the non-suppressed dataset, 24 mutations became more prevalent and three mutations became less prevalent after more than 48 months of non-suppressive PI-therapy. Longer durations of non-suppressive treatment correlated with higher PI resistance scores. Mutations at eight non-established positions that were more common in viruses with the longest duration of non-suppressive therapy were also more common in viruses with the highest PI resistance score. Covariation analysis of 3036 protease amino acid substitutions identified 75 positive and nine negative correlations between resistance associated positions. Our findings support the utility of reference laboratory datasets for surveillance of mutation prevalence and covariation.

HIV-1 pol mutation frequency by subtype and treatment experience: extension of the HIVseq program to seven non-B subtypes

OBJECTIVE

HIVseq was developed in 2000 to make published data on the frequency of HIV-1 group M protease and reverse transcriptase (RT) mutations available in real time to laboratories and researchers sequencing these genes. Because most published protease and RT sequences belonged to subtype B, the initial version of HIVseq was based on this subtype. As additional non-B sequences from persons with well-characterized antiretroviral treatment histories have become available, the program has been extended to subtypes A, C, D, F, G, CRF01, and CRF02.

METHODS

The latest frequency of each protease and RT mutation according to subtype and drug-class exposure was calculated using published sequences in the Stanford HIV RT and Protease Sequence Database. Each mutation was hyperlinked to published reports of viruses containing the mutation.

RESULTS

As of September 2005, the mean number of protease sequences per non-B subtype was 534 from protease inhibitor-naive persons and 133 from protease inhibitor-treated persons, representing 13.2% and 2.3%, respectively, of the data available for subtype B. The mean number of RT sequences per non-B subtype was 373 from RT inhibitor-naive persons and 288 from RT inhibitor-treated persons, representing 17.9% and 3.8%, respectively, of the data available for subtype B.

CONCLUSIONS

HIVseq allows users to examine protease and RT mutations within the context of previously published sequences of these genes. The publication of additional non-B protease and RT sequences from persons with well-characterized treatment histories, however, will be required to perform the same types of analysis possible with the much larger number of subtype B sequences.

Prediction of HIV mutation changes based on treatment history

Few studies have investigated sequential HIV-1 mutation changes in the HIV gene in patients changing antiretroviral drugs. We analyze such data from the HIV Drug Resistance Database at Stanford University using three data mining methods: association rule analysis, logistic regression, and classification trees. Although the AUC measures of the overall prediction is not high, these methods can effectively identify strong predictors of mutation change and focus further analysis by domain experts.