The Saccharomyces cerevisiae strains widely used for industrial fuel-ethanol production have been developed by selection, but their underlying beneficial genetic polymorphisms remain unknown. Here, we report the draft whole-genome sequence of the S. cerevisiae strain CAT-1, which is a dominant fuel-ethanol fermentative strain from the sugarcane industry in Brazil. Our results indicate that strain CAT-1 is a highly heterozygous diploid yeast strain, and the ~12-Mb genome of CAT-1, when compared with the reference S228c genome, contains ~36,000 homozygous and ~30,000 heterozygous single nucleotide polymorphisms, exhibiting an uneven distribution among chromosomes due to large genomic regions of loss of heterozygosity (LOH). In total, 58 % of the 6,652 predicted protein-coding genes of the CAT-1 genome constitute different alleles when compared with the genes present in the reference S288c genome. The CAT-1 genome contains a reduced number of transposable elements, as well as several gene deletions and duplications, especially at telomeric regions, some correlated with several of the physiological characteristics of this industrial fuel-ethanol strain. Phylogenetic analyses revealed that some genes were likely associated with traits important for bioethanol production. Identifying and characterizing the allelic variations controlling traits relevant to industrial fermentation should provide the basis for a forward genetics approach for developing better fermenting yeast strains.

ABSTRACT: 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.

Objectives: 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.Methods: HIV-1 drug resistance genotyping was performed on 981 clinical samples at the Stanford Diagnostic Virology Laboratory. Sequencing trace files were first manually interpreted by a laboratory technician, and subsequently re-analyzed by RECall without intervention. The relative performance of the two methods was assessed by concordance of nucleotide basecalls, 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.Results: 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 vs. ∼6 computation-hours). Excellent concordance was obtained between human and automated RECall interpretation (99.7% over >1,000,000 bases compared). Nearly all discordances (99.4%) were due to nucleotide mixtures 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.Conclusions: 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.

(See the Editorial Commentary by Kuritzkes et al, on pages 876-7.) We systematically reviewed studies of the virological efficacy of the 4 new tenofovir (TDF)-containing regimens recommended for initial antiretroviral (ARV) therapy in the 2010 World Health Organization ARV Treatment Guidelines. Thirty-three studies assessed the efficacy of 1 or more TDF-containing regimens: TDF/lamivudine (3TC)/nevirapine (NVP)(n = 3), TDF/ emtricitabine (FTC)/NVP (n = 9), TDF/3TC/efavirenz (EFV)(n = 6), and TDF/FTC/EFV (n = 19). TDF/3TC/NVP was the least well-studied and appeared the least efficacious of the 4 regimens. In 2 comparative studies, TDF/3TC/NVP was associated with significantly more virological failure than AZT/3TC/NVP; a third study was terminated prematurely because of early virological failure. TDF/FTC/NVP was either equivalent or inferior to its comparator arms. TDF/3TC/EFV was equivalent to its comparator arms. TDF/FTC/EFV was equivalent or superior to its comparator arms. Possible explanations for these findings include the greater antiviral activity of EFV versus NVP and longer intracellular half-life of FTC-triphosphate versus 3TC-triphosphate. Further study of TDF/3TC/NVP is required before it is widely deployed for initial ARV therapy.

Determining the phenotypic impacts of reverse transcriptase (RT) mutations on individual nucleoside RT inhibitors (NRTIs) has remained a statistical challenge because clinical NRTI-resistant HIV-1 isolates usually contain multiple mutations, often in complex patterns, complicating the task of determining the relative contribution of each mutation to HIV drug resistance. Furthermore, the NRTIs have highly variable dynamic susceptibility ranges, making it difficult to determine the relative effect of an RT mutation on susceptibility to different NRTIs. In this study, we analyzed 1,273 genotyped HIV-1 isolates for which phenotypic results were obtained using the PhenoSense assay (Monogram, South San Francisco, CA). We used a parsimonious feature selection algorithm, LASSO, to assess the possible contributions of 177 mutations that occurred in 10 or more isolates in our data set. We then used least-squares regression to quantify the impact of each LASSO-selected mutation on each NRTI. Our study provides a comprehensive view of the most common NRTI resistance mutations. Because our results were standardized, the study provides the first analysis that quantifies the relative phenotypic effects of NRTI resistance mutations on each of the NRTIs. In addition, the study contains new findings on the relative impacts of thymidine analog mutations (TAMs) on susceptibility to abacavir and tenofovir; the impacts of several known but incompletely characterized mutations, including E40F, V75T, Y115F, and K219R; and a tentative role in reduced NRTI susceptibility for K64H, a novel NRTI resistance mutation.

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.

ABSTRACT: BACKGROUND: Great strides have been made in the effective treatment of HIV-1 with the development of second-generation protease inhibitors (PIs) that are effective against historically multi-PI-resistant HIV-1 variants. Nevertheless, mutation patterns that confer decreasing susceptibility to available PIs continue to arise within the population. Understanding the phenotypic and genotypic patterns responsible for multi-PI resistance is necessary for developing PIs that are active against clinically-relevant PI-resistant HIV-1 variants. RESULTS: In this work, we use globally optimal integer programming-based clustering techniques to elucidate multi-PI phenotypic resistance patterns using a data set of 398 HIV-1 protease sequences that have each been phenotyped for susceptibility toward the nine clinically-approved HIV-1 PIs. We validate the information content of the clusters by evaluating their ability to predict the level of decreased susceptibility to each of the available PIs using a cross validation procedure. We demonstrate the finding that as a result of phenotypic cross resistance, the considered clinical HIV-1 protease isolates are confined to ~6% or less of the clinically-relevant phenotypic space. Clustering and feature selection methods are used to find representative sequences and mutations for major resistance phenotypes to elucidate their genotypic signatures. We show that phenotypic similarity does not imply genotypic similarity, that different PI-resistance mutation patterns can give rise to HIV-1 isolates with similar phenotypic profiles. CONCLUSION: Rather than characterizing HIV-1 susceptibility toward each PI individually, our study offers a unique perspective on the phenomenon of PI class resistance by uncovering major multidrug-resistant phenotypic patterns and their often diverse genotypic determinants, providing a methodology that can be applied to understand clinically-relevant phenotypic patterns to aid in the design of novel inhibitors that target other rapidly evolving molecular targets as well.

The availability of 24 antiretroviral (ARV) drugs within six distinct drug classes has transformed HIV-1 infection (AIDS) into a treatable chronic disease. However, the ability of HIV-1 to develop resistance to multiple classes continues to present challenges to the treatment of many ARV treatment-experienced patients. In this case report, we describe the response to ibalizumab, an investigational CD4-binding monoclonal antibody (mAb), in a patient with advanced immunodeficiency and high-level five-class antiretroviral resistance. After starting an ibalizumab-based salvage regimen, the patient had an approximately 4.0 log(10) reduction in viral load. An inadvertently missed infusion at week 32 led to the rapid loss of virologic response and decreased susceptibility to the remainder of the patient's salvage therapy regimen. Following the reinstitution of ibalizumab, phenotypic and genotypic resistance to ibalizumab was detected. Nonetheless, plasma HIV-1 RNA levels stabilized at ∼2.0 log(10) copies/ml below pre-ibalizumab levels. Continued ARV drug development may yield additional clinical and public health benefits. This report illustrates the promise of mAbs for HIV-1 therapy in highly treatment-experienced patients. Therapeutic mAbs may also have a role in pre-exposure prophylaxis in high-risk uninfected populations and may facilitate directly observed therapy (DOT) if two or more synergistic long acting agents become available.

Dimerization of HIV protease is essential for the acquisition of protease's proteolytic activity. We previously identified a group of HIV protease dimerization inhibitors, including darunavir (DRV). In the present work, we examine whether loss of DRV's protease dimerization inhibition activity is associated with HIV development of DRV resistance. Single amino acid substitutions, including I3A, L5A, R8A/Q, L24A, T26A, D29N, R87K, T96A, L97A, and F99A, disrupted protease dimerization, as examined using an intermolecular fluorescence resonance energy transfer (FRET)-based HIV expression assay. All recombinant HIV(NL4-3)-based clones with such a protease dimerization-disrupting substitution failed to replicate. A highly DRV-resistant in vitro-selected HIV variant and clinical HIV strains isolated from AIDS patients failing to respond to DRV-containing antiviral regimens typically had the V32I, L33F, I54M, and I84V substitutions in common in protease. None of up to 3 of the 4 substitutions affected DRV's protease dimerization inhibition, which was significantly compromised by the four combined substitutions. Recombinant infectious clones containing up to 3 of the 4 substitutions remained sensitive to DRV, while a clonal HIV variant with all 4 substitutions proved highly resistant to DRV with a 205-fold 50% effective concentration (EC(50)) difference compared to HIV(NL4-3). The present data suggest that the loss of DRV activity to inhibit protease dimerization represents a novel mechanism contributing to HIV resistance to DRV. The finding that 4 substitutions in PR are required for significant loss of DRV's protease dimerization inhibition should at least partially explain the reason DRV has a high genetic barrier against HIV's acquisition of DRV resistance.

With the approval in 2007 of the first integrase inhibitor (INI), raltegravir, clinicians became better able to suppress virus replication in patients infected with human immunodeficiency virus type 1 (HIV-1) who were harboring many of the most highly drug-resistant viruses. Raltegravir also provided clinicians with additional options for first-line therapy and for the simplification of regimens in patients with stable virological suppression. Two additional INIs in advanced clinical development-elvitegravir and S/GSK1349572-may prove equally versatile. However, the INIs have a relatively low genetic barrier to resistance in that 1 or 2 mutations are capable of causing marked reductions in susceptibility to raltegravir and elvitegravir, the most well-studied INIs. This perspective reviews the genetic mechanisms of INI resistance and their implications for initial INI therapy, the treatment of antiretroviral-experienced patients, and regimen simplification.