Mass spectrometry captures off-target drug binding and provides mechanistic insights into the human metalloprotease ZMPSTE24.

Off-target binding of hydrophobic drugs can lead to unwanted side effects, either through specific or non-specific binding to unintended membrane protein targets. However, distinguishing the binding of drugs to membrane proteins from that of detergents, lipids and cofactors is challenging. Here, we use high-resolution mass spectrometry to study the effects of HIV protease inhibitors on the human zinc metalloprotease ZMPSTE24. This intramembrane protease plays a major role in converting prelamin A to mature lamin A. We monitored the proteolysis of farnesylated prelamin A peptide by ZMPSTE24 and unexpectedly found retention of the C-terminal peptide product with the enzyme. We also resolved binding of zinc, lipids and HIV protease inhibitors and showed that drug binding blocked prelamin A peptide cleavage and conferred stability to ZMPSTE24. Our results not only have relevance for the progeria-like side effects of certain HIV protease inhibitor drugs, but also highlight new approaches for documenting off-target drug binding

Distinguishing HIV-1 drug resistance, accessory, and viral fitness mutations using conditional selection pressure analysis of treated versus untreated patient samples

BACKGROUND: HIV can evolve drug resistance rapidly in response to new drug treatments, often through a combination of multiple mutations [1-3]. It would be useful to develop automated analyses of HIV sequence polymorphism that are able to predict drug resistance mutations, and to distinguish different types of functional roles among such mutations, for example, those that directly cause drug resistance, versus those that play an accessory role. Detecting functional interactions between mutations is essential for this classification. We have adapted a well-known measure of evolutionary selection pressure (K(a)/K(s)) and developed a conditional K(a)/K(s )approach to detect important interactions. RESULTS: We have applied this analysis to four independent HIV protease sequencing datasets: 50,000 clinical samples sequenced by Specialty Laboratories, Inc.; 1800 samples from patients treated with protease inhibitors; 2600 samples from untreated patients; 400 samples from untreated African patients. We have identified 428 mutation interactions in Specialty dataset with statistical significance and we were able to distinguish primary vs. accessory mutations for many well-studied examples. Amino acid interactions identified by conditional K(a)/K(s )matched 80 of 92 pair wise interactions found by a completely independent study of HIV protease (p-value for this match is significant: 10(-70)). Furthermore, K(a)/K(s )selection pressure results were highly reproducible among these independent datasets, both qualitatively and quantitatively, suggesting that they are detecting real drug-resistance and viral fitness mutations in the wild HIV-1 population. CONCLUSION: Conditional K(a)/K(s )analysis can detect mutation interactions and distinguish primary vs. accessory mutations in HIV-1. K(a)/K(s )analysis of treated vs. untreated patient data can distinguish drug-resistance vs. viral fitness mutations. Verification of these results would require longitudinal studies. The result provides a valuable resource for AIDS research and will be available for open access upon publication at REVIEWERS: This article was reviewed by Wen-Hsiung Li (nominated by Eugene V. Koonin), Robert Shafer (nominated by Eugene V. Koonin), and Shamil Sunyaev

Dynamic ploidy changes drive fluconazole resistance in human cryptococcal meningitis.

BACKGROUND: Cryptococcal meningitis (CM) causes an estimated 180,000 deaths annually, predominantly in sub-Saharan Africa, where most patients receive fluconazole (FLC) monotherapy. While relapse after FLC monotherapy with resistant strains is frequently observed, the mechanisms and impact of emergence of FLC resistance in human CM are poorly understood. Heteroresistance (HetR) - a resistant subpopulation within a susceptible strain - is a recently described phenomenon in Cryptococcus neoformans (Cn) and Cryptococcus gattii (Cg), the significance of which has not previously been studied in humans. METHODS: A cohort of 20 patients with HIV-associated CM in Tanzania was prospectively observed during therapy with either FLC monotherapy or in combination with flucytosine (5FC). Total and resistant subpopulations of Cryptococcus spp. were quantified directly from patient cerebrospinal fluid (CSF). Stored isolates underwent whole genome sequencing and phenotypic characterization. RESULTS: Heteroresistance was detectable in Cryptococcus spp. in the CSF of all patients at baseline (i.e., prior to initiation of therapy). During FLC monotherapy, the proportion of resistant colonies in the CSF increased during the first 2 weeks of treatment. In contrast, no resistant subpopulation was detectable in CSF by day 14 in those receiving a combination of FLC and 5FC. Genomic analysis revealed high rates of aneuploidy in heteroresistant colonies as well as in relapse isolates, with chromosome 1 (Chr1) disomy predominating. This is apparently due to the presence on Chr1 of ERG11, which is the FLC drug target, and AFR1, which encodes a drug efflux pump. In vitro efflux levels positively correlated with the level of heteroresistance. CONCLUSION: Our findings demonstrate for what we believe is the first time the presence and emergence of aneuploidy-driven FLC heteroresistance in human CM, association of efflux levels with heteroresistance, and the successful suppression of heteroresistance with 5FC/FLC combination therapy. FUNDING: This work was supported by the Wellcome Trust Strategic Award for Medical Mycology and Fungal Immunology 097377/Z/11/Z and the Daniel Turnberg Travel Fellowship

Deciphering HIV genetic variability and evolution by massive parallel pyrosequencing and bioinformatics

HIV-1 is a virus with a very variable genome and therefore has the ability to adapt to new environments which include escape from immune pressure and suboptimal antiretroviral treatment. Next-generation sequencing (NGS), especially ultra-deep pyrosequencing (UDPS), has enabled in-depth sequencing studies with a previously unattainable resolution. However, the technology is more error prone than traditional sequencing which makes it challenging to interpret UDPS results. In this thesis we carried out comprehensive work to identify, characterize and reduce errors as well as investigate the UDPS performance (Papers II, III and IV). In Papers IV and V we used UDPS to study HIV-1 minority variants. Novel primer design software was developed in Paper I and a new method to tag molecules was developed and evaluated in Paper VI. The design of primers is of special importance in NGS to avoid selective amplification which may skew estimates of variant frequencies. We developed a computer program, PrimerDesign, to meet the changed requirements for primer design. PrimerDesign is tailored to design primers from a multiple alignment and is suitable for all types of NGS that is preceded by amplification. The new Primer ID methodology has the potential to provide highly accurate deep sequencing. We identified three major challenges; a skewed resampling of Primer IDs, low recovery of templates and erroneous consensus sequences. Undetected this would lead to an underestimation in diversity of the quasispecies and cause a skewed and incorrect results. As many of our other findings, the methodology is not limited to HIV or virology. The resolution of UDPS analysis is primarily determined by the number of input DNA templates, the error frequency of the method and the efficiency of data cleaning. In Papers II and IV we therefore optimized the pre-UDPS protocol and investigated the characteristics and sources of errors that occurred when UDPS was used to sequence a fragment of the HIV-1 pol gene. UDPS introduced indel errors located in homopolymeric regions that were removed by our in-house data cleaning software. The remaining errors were primarily substitution errors that were introduced in the PCR that preceded UDPS. Transitions were significantly more frequent than transversions, which will limit detection of minor variants and mutations in HIV-1 as well as other species. Further, we evaluated the quality and reproducibility of the UDPS technology in analysis of the same pol gene fragment. We concluded that the UDPS repeatability was good for both major and minor variants. In our experimental settings, in vitro recombination and sequencing directions posed a minor problem, but still needs to be considered especially for studies of minor viral variants and linkage between mutations. Minority resistance mutations have been shown to impact the clinical outcome in treated patients. We examined the presence of pre-existing drug resistance mutations in treatment-naïve HIV-1 infected individuals and found very low levels of M184I, T215A and T215I, but no presence of M184V, Y181C, Y188C or T215Y/F. This indicates that the natural occurrence of these mutations is very low. When the same individuals experienced treatment failure or interruption, almost 100 % of the wild-type virus respective drug resistance variants were replaced. Other patients were followed from primary HIV infection (PHI) until their virus switched coreceptor use from CCR5 (R5) to CXCR4 (X4). We did not find any X4-using virus present as a minority population during PHI. The results indicate that the X4-using population most probably evolved in stepwise fashion from the R5-using populations in each of the three patients. In conclusion, we have developed and used new NGS and bioinformatic methods to study HIV-1 genetic variation. We have shown that UDPS can be used to gain new insights in HIV evolution and to detect minority drug resistance mutations as well as minority variants

Combining Kernel and Model Based Learning for HIV Therapy Selection

We present a mixture-of-experts approach for HIV therapy selection. The heterogeneity in patient data makes it difficult for one particular model to succeed at providing suitable therapy predictions for all patients. An appropriate means for addressing this heterogeneity is through combining kernel and model-based techniques. These methods capture different kinds of information: kernel-based methods are able to identify clusters of similar patients, and work well when modelling the viral response for these groups. In contrast, model-based methods capture the sequential process of decision making, and are able to find simpler, yet accurate patterns in response for patients outside these groups. We take advantage of this information by proposing a mixture-of-experts model that automatically selects between the methods in order to assign the most appropriate therapy choice to an individual. Overall, we verify that therapy combinations proposed using this approach significantly outperform previous methods

DR_SEQAN: a PC/Windows-based software to evaluate drug

This article is available from: http://www.biomedcentral.com/1471-2334/6/44[Background] Genotypic assays based on DNA sequencing of part or the whole reverse transcriptase (RT)- and protease (PR)-coding regions of the human immunodeficiency virus type 1 (HIV-1) genome have become part of the routine clinical management of HIV-infected individuals. However, the results are difficult to interpret due to complex interactions between mutations found in viral genes.[Results] DR_SEQAN is a tool to analyze RT and PR sequences. The program output includes a list containing all of the amino acid changes found in the query sequence in comparison with the sequence of a wild-type HIV-1 strain. Translation of codons containing nucleotide mixtures can result in potential ambiguities or heterogeneities in the amino acid sequence. The program identifies all possible combinations of 2 or 3 amino acids that derive from translation of triplets containing nucleotide mixtures. In addition, when ambiguities affect codons relevant for drug resistance, DR_SEQAN allows the user to select the appropriate mutation to be considered by the program's drug resistance interpretation algorithm. Resistance is predicted using a rule-based algorithm, whose efficiency and accuracy has been tested with a large set of drug susceptibility data. Drug resistance predictions given by DR_SEQAN were consistent with phenotypic data and coherent with predictions provided by other publicly available algorithms. In addition, the program output provides two tables showing published drug susceptibility data and references for mutations and combinations of mutations found in the analyzed sequence. These data are retrieved from an integrated relational database, implemented in Microsoft Access, which includes two sets of nonredundant core tables (one for combinations of mutations in the PR and the other for combinations in the RT)[Conclusion] DR_SEQAN is an easy to use off-line application that provides expert advice on HIV genotypic resistance interpretation. It is coded in Visual Basic for use in PC/Windows-based platforms. The program is freely available under the General Public License. The program (including the integrated database), documentation and a sample sequence can be downloaded from http:// www2.cbm.uam.es:8080/lmenendez/DR_SEQAN.zipThis work has been supported in part by the Fundación para la Investigación y Prevención del SIDA en España (FIPSE), through grants 36200/01 and 36460/05. An institutional grant of Fundación Ramón Areces to Centro de Biología Molecular "Severo Ochoa" is also acknowledged.Peer reviewe

Optimization of a Low Cost and Broadly Sensitive Genotyping Assay for HIV-1 Drug Resistance Surveillance and Monitoring in Resource-Limited Settings

Commercially available HIV-1 drug resistance (HIVDR) genotyping assays are expensive and have limitations in detecting non-B subtypes and circulating recombinant forms that are co-circulating in resource-limited settings (RLS). This study aimed to optimize a low cost and broadly sensitive in-house assay in detecting HIVDR mutations in the protease (PR) and reverse transcriptase (RT) regions of pol gene. The overall plasma genotyping sensitivity was 95.8% (N = 96). Compared to the original in-house assay and two commercially available genotyping systems, TRUGENE® and ViroSeq®, the optimized in-house assay showed a nucleotide sequence concordance of 99.3%, 99.6% and 99.1%, respectively. The optimized in-house assay was more sensitive in detecting mixture bases than the original in-house (N = 87, P<0.001) and TRUGENE® and ViroSeq® assays. When the optimized in-house assay was applied to genotype samples collected for HIVDR surveys (N = 230), all 72 (100%) plasma and 69 (95.8%) of the matched dried blood spots (DBS) in the Vietnam transmitted HIVDR survey were genotyped and nucleotide sequence concordance was 98.8%; Testing of treatment-experienced patient plasmas with viral load (VL) ≥ and <3 log10 copies/ml from the Nigeria and Malawi surveys yielded 100% (N = 46) and 78.6% (N = 14) genotyping rates, respectively. Furthermore, all 18 matched DBS stored at room temperature from the Nigeria survey were genotyped. Phylogenetic analysis of the 236 sequences revealed that 43.6% were CRF01_AE, 25.9% subtype C, 13.1% CRF02_AG, 5.1% subtype G, 4.2% subtype B, 2.5% subtype A, 2.1% each subtype F and unclassifiable, 0.4% each CRF06_CPX, CRF07_BC and CRF09_CPX