The HIV positive selection mutation database

Navigating the Landscape: A Comprehensive Review of Current Virus Databases

Viruses are abundant and diverse entities that have important roles in public health, ecology, and agriculture. The identification and surveillance of viruses rely on an understanding of their genome organization, sequences, and replication strategy. Despite technological advancements in sequencing methods, our current understanding of virus diversity remains incomplete, highlighting the need to explore undiscovered viruses. Virus databases play a crucial role in providing access to sequences, annotations and other metadata, and analysis tools for studying viruses. However, there has not been a comprehensive review of virus databases in the last five years. This study aimed to fill this gap by identifying 24 active virus databases and included an extensive evaluation of their content, functionality and compliance with the FAIR principles. In this study, we thoroughly assessed the search capabilities of five database catalogs, which serve as comprehensive repositories housing a diverse array of databases and offering essential metadata. Moreover, we conducted a comprehensive review of different types of errors, encompassing taxonomy, names, missing information, sequences, sequence orientation, and chimeric sequences, with the intention of empowering users to effectively tackle these challenges. We expect this review to aid users in selecting suitable virus databases and other resources, and to help databases in error management and improve their adherence to the FAIR principles. The databases listed here represent the current knowledge of viruses and will help aid users find databases of interest based on content, functionality, and scope. The use of virus databases is integral to gaining new insights into the biology, evolution, and transmission of viruses, and developing new strategies to manage virus outbreaks and preserve global health.

Switching to coformulated bictegravir, emtricitabine, and tenofovir alafenamide maintained viral suppression in adults with historical virological failures and K65N/R mutation

OBJECTIVES

Real-world experience with coformulated bictegravir, emtricitabine, and tenofovir alafenamide (BIC/FTC/TAF) is sparse as a switch regimen among people living with HIV (PLWH) having achieved viral suppression after previous virologic failures with the emergence of K65N/R.

METHODS

In this retrospective study, PLWH aged ≥20 years who had previous virologic failures with emergent K65N/R were included for switching to BIC/FTC/TAF after having achieved plasma HIV RNA load (PVL) <200 copies/ml for ≥3 months. PLWH were excluded if integrase inhibitor resistance-associated mutations were detected. The primary end point was losing virologic control (PVL >50 copies/ml) at week 48 using a modified US Food and Drug Administration snapshot algorithm.

RESULTS

A total of 72 PLWH with K65N/R who switched to BIC/FTC/TAF were identified. A total of 42 (59.7%) had concurrent M184V/I, and 9 (12.5%) had ≥1 thymidine analog mutations. The median duration of viral suppression was 4.7 years (interquartile range 2.3-5.8), and 97.2% (n = 70) had PVL <50 copies/ml before switching. After a median observation of 98.6 weeks (interquartile range 77.9-120.3), 94.4% (n = 68) continued BIC/FTC/TAF. At week 48, the rate of losing virologic control was 2.8% (2/72). M184V/I was not associated with viral rebound.

CONCLUSION

Despite the emergence of K65N/R +/- M184V/I after virologic failures, BIC/FTC/TAF could be an option for simplification after viral suppression.

DRESIS: the first comprehensive landscape of drug resistance information

Widespread drug resistance has become the key issue in global healthcare. Extensive efforts have been made to reveal not only diverse diseases experiencing drug resistance, but also the six distinct types of molecular mechanisms underlying this resistance. A database that describes a comprehensive list of diseases with drug resistance (not just cancers/infections) and all types of resistance mechanisms is now urgently needed. However, no such database has been available to date. In this study, a comprehensive database describing drug resistance information named 'DRESIS' was therefore developed. It was introduced to (i) systematically provide, for the first time, all existing types of molecular mechanisms underlying drug resistance, (ii) extensively cover the widest range of diseases among all existing databases and (iii) explicitly describe the clinically/experimentally verified resistance data for the largest number of drugs. Since drug resistance has become an ever-increasing clinical issue, DRESIS is expected to have great implications for future new drug discovery and clinical treatment optimization. It is now publicly accessible without any login requirement at: https://idrblab.org/dresis/.

Mapping the drivers of within-host pathogen evolution using massive data sets

Differences among hosts, resulting from genetic variation in the immune system or heterogeneity in drug treatment, can impact within-host pathogen evolution. Genetic association studies can potentially identify such interactions. However, extensive and correlated genetic population structure in hosts and pathogens presents a substantial risk of confounding analyses. Moreover, the multiple testing burden of interaction scanning can potentially limit power. We present a Bayesian approach for detecting host influences on pathogen evolution that exploits vast existing data sets of pathogen diversity to improve power and control for stratification. The approach models key processes, including recombination and selection, and identifies regions of the pathogen genome affected by host factors. Our simulations and empirical analysis of drug-induced selection on the HIV-1 genome show that the method recovers known associations and has superior precision-recall characteristics compared to other approaches. We build a high-resolution map of HLA-induced selection in the HIV-1 genome, identifying novel epitope-allele combinations.

Identification and Characterization of Positively Selected Mutations in Nef of Four HIV-1 Major Subtypes from Los Alamos National Laboratory

BACKGROUND

Human immunodeficiency virus-1 (HIV-1) mutates rapidly to escape host immune pressure. This results in the generation of positively selected mutations (PSM) throughout the viral genome. Escape mutations in Nef, one of the accessory proteins of HIV-1, which plays an important role in viral pathogenicity have previously been identified in several large cohort studies, but the evolution of PSMs overtime in various HIV-1 subtypes remains unknown.

METHODS

161 clade A1, 3093 clade B, 647 clade C and 115 clade D HIV-1 nef sequences were obtained from the HIV Database of Los Alamos National Laboratory and aligned using MEGA 6.0. The sequences from each clade were grouped based on the year of collection. Quasi analysis was used to identify PSMs and the number and locations of PSMs were compared among different subtypes.

RESULTS

PSMs for all four subtypes were distributed across the sequence of Nef, and conserved residues F90, W113, PxxPxR (a.a 72-77) remain unaltered overtime. The frequency of PSMs was stable among subtype B sequences but increased overtime for other subtypes. Phylogenetic analysis shows that sequences containing PSMs tend to cluster together at both inter and intra- subtype levels.

CONCLUSION

Identification of PSMs and their changes overtime within various subtypes of HIV-1 is important in defining global viral evolutionary patterns that can provide insights for designing therapeutic strategies.

Mutation and recombination in pathogen evolution: Relevance, methods and controversies

Mutation and recombination drive the evolution of most pathogens by generating the genetic variants upon which selection operates. Those variants can, for example, confer resistance to host immune systems and drug therapies or lead to epidemic outbreaks. Given their importance, diverse evolutionary studies have investigated the abundance and consequences of mutation and recombination in pathogen populations. However, some controversies persist regarding the contribution of each evolutionary force to the development of particular phenotypic observations (e.g., drug resistance). In this study, we revise the importance of mutation and recombination in the evolution of pathogens at both intra-host and inter-host levels. We also describe state-of-the-art analytical methodologies to detect and quantify these two evolutionary forces, including biases that are often ignored in evolutionary studies. Finally, we present some of our former studies involving pathogenic taxa where mutation and recombination played crucial roles in the recovery of pathogenic fitness, the generation of interspecific genetic diversity, or the design of centralized vaccines. This review also illustrates several common controversies and pitfalls in the analysis and in the evaluation and interpretation of mutation and recombination outcomes.

Polymorphisms and Mutational Covariation Associated with Death in a Prospective Cohort of HIV/AIDS Patients Receiving Long-Term ART in China

Background

HIV drug resistance is associated with faster clinical progression of AIDS. However, the effect of significant polymorphisms and mutational covariation on mortality among HIV/AIDS patients receiving long-term antiretroviral therapy (ART), have rarely been studied.

Methods

In this prospective cohort study from December 2003 to December 2014, we present a new computational modelling approach based on bioinformatics-based models and several statistical methods to elucidate the molecular mechanisms involved in the acquisition of polymorphisms and mutations on death in HIV/AIDS patients receiving long-term ART in China.

Results

This study involved 654 ART-treated patients, who had been followed for 5473.4 person-years, a median of 9.8 years, and 178 died (25.2%, 3.3/100 person-years). The first regimens included AZT/d4T + NVP+ ddI (78.9%) or AZT/d4T + NVP+ 3TC (20.0%). We calculated an individual Ka/Ks value for each specific amino acid mutation. Result showed that 20 polymorphisms (E6D, Q18H, E35D, S37N, T39A, K43E, S68N, L74I, I93L, K103N, V106A, E169D, Y181C, G190A, Q197K, T200V, T200E, T215I, E224D and P225H) were strongly associated with AIDS related deaths. Among them, 7 polymorphisms (L74I, K103N, V106A, Y181C, G190A, T215I and P225H) were known to be drug resistance mutations, 7 polymorphisms (E6D, E35D, S37N, I93L, E169D, T200V and T200E were considered to be potential drug resistance mutations, and 6 polymorphisms (T39A, K43E, S68N, Q197K, T200V and E224D) were newly found to have an association with drug resistance mutations, which formed a complex network of relationships.

Conclusions

Some polymorphisms and mutational covariation may be the important influencing factors in the failure of treatment. Understanding these mechanisms is essential for the development of new therapies, designing optimal drug combinations, and determining effective clinical management of individual patients.

HIV-1 drug resistance mutations emerging on darunavir therapy in PI-naive and -experienced patients in the UK

BACKGROUND

Darunavir is considered to have a high genetic barrier to resistance. Most darunavir-associated drug resistance mutations (DRMs) have been identified through correlation of baseline genotype with virological response in clinical trials. However, there is little information on DRMs that are directly selected by darunavir in clinical settings.

OBJECTIVES

We examined darunavir DRMs emerging in clinical practice in the UK.

PATIENTS AND METHODS

Baseline and post-exposure protease genotypes were compared for individuals in the UK Collaborative HIV Cohort Study who had received darunavir; analyses were stratified for PI history. A selection analysis was used to compare the evolution of subtype B proteases in darunavir recipients and matched PI-naive controls.

RESULTS

Of 6918 people who had received darunavir, 386 had resistance tests pre- and post-exposure. Overall, 2.8% (11/386) of these participants developed emergent darunavir DRMs. The prevalence of baseline DRMs was 1.0% (2/198) among PI-naive participants and 13.8% (26/188) among PI-experienced participants. Emergent DRMs developed in 2.0% of the PI-naive group (4 mutations) and 3.7% of the PI-experienced group (12 mutations). Codon 77 was positively selected in the PI-naive darunavir cases, but not in the control group.

CONCLUSIONS

Our findings suggest that although emergent darunavir resistance is rare, it may be more common among PI-experienced patients than those who are PI-naive. Further investigation is required to explore whether codon 77 is a novel site involved in darunavir susceptibility.

Genetic Consequences of Antiviral Therapy on HIV-1

A variety of enzyme inhibitors have been developed in combating HIV-1, however the fast evolutionary rate of this virus commonly leads to the emergence of resistance mutations that finally allows the mutant virus to survive. This review explores the main genetic consequences of HIV-1 molecular evolution during antiviral therapies, including the viral genetic diversity and molecular adaptation. The role of recombination in the generation of drug resistance is also analyzed. Besides the investigation and discussion of published works, an evolutionary analysis of protease-coding genes collected from patients before and after treatment with different protease inhibitors was included to validate previous studies. Finally, the review discusses the importance of considering genetic consequences of antiviral therapies in models of HIV-1 evolution that could improve current genotypic resistance testing and treatments design.

Unraveling the web of viroinformatics: computational tools and databases in virus research

The beginning of the second century of research in the field of virology (the first virus was discovered in 1898) was marked by its amalgamation with bioinformatics, resulting in the birth of a new domain--viroinformatics. The availability of more than 100 Web servers and databases embracing all or specific viruses (for example, dengue virus, influenza virus, hepatitis virus, human immunodeficiency virus [HIV], hemorrhagic fever virus [HFV], human papillomavirus [HPV], West Nile virus, etc.) as well as distinct applications (comparative/diversity analysis, viral recombination, small interfering RNA [siRNA]/short hairpin RNA [shRNA]/microRNA [miRNA] studies, RNA folding, protein-protein interaction, structural analysis, and phylotyping and genotyping) will definitely aid the development of effective drugs and vaccines. However, information about their access and utility is not available at any single source or on any single platform. Therefore, a compendium of various computational tools and resources dedicated specifically to virology is presented in this article.

Identification of the critical sites of NNRTI-resistance in reverse transcriptase of HIV-1 CRF_BC strains

Background

The polymorphisms involved in drug resistance to non-nucleoside reverse transcriptase inhibitors (NNRTIs) in HIV-1 CRF_BC, the most prevalent HIV-1 strain in China, have been poorly characterized.

Results

To reveal the drug resistance mutations, we compared the gene sequences of pol region of HIV-1 CRF_BC from 631 treatment-naïve and 363 treatment-experienced patients using the selection pressure-based method. We calculated an individual Ka/Ks value for each specific amino acid mutation. Result showed that eight polymorphic mutations (W88C, K101Q, I132L, R135L, T139K/R, H221Y and L228R) in RT for treatment-experienced patients were identified, while they, except for R135L, were completely absent in those from treatment-naïve patients. The I132L and T139K/R mutants exhibited high-level resistance to DLV and NVP and moderate resistance to TMC-125 and EFV, while the K101Q and H221Y mutants exhibited an increased resistance to all four NNRTIs tested. The W88C, R135L, and L228R may be RTI-induced adaptive mutations. Y181C+K101Q mutant showed a 2.5-, 4.4-, and 4.7-fold higher resistance to TMC-125, NVP and EFV, respectively, than Y181C alone mutant, while Y181C+H221Y or K103N+H221Y mutants had significantly higher resistance to all four NNRTIs than Y181C or K103N mutants. K103N+T139K and G190A+T139K mutant induce higher resistance (2.0∼14.2-fold and 1.5∼7.2-fold, respectively) to all four NNRTIs than K103N or G190A alone mutation.

Conclusions

I132L and T139K/R are rare but critical mutations associated with NNRTI-resistance for some NNRTIs. K101Q, H221Y and T139K can enhance K103N/Y181C/G190A-assocated NNRTI-resistance. Monitoring these mutations will provide useful information for rational design of the NNRTI-based antiretroviral regimen for HIV-1 CRF_BC-infected patients.

Natural polymorphisms and unusual mutations in HIV-1 protease with potential antiretroviral resistance: a bioinformatic analysis

Background

The correlations of genotypic and phenotypic tests with treatment, clinical history and the significance of mutations in viruses of HIV-infected patients are used to establish resistance mutations to protease inhibitors (PIs). Emerging mutations in human immunodeficiency virus type 1 (HIV-1) protease confer resistance to PIs by inducing structural changes at the ligand interaction site. The aim of this study was to establish an in silico structural relationship between natural HIV-1 polymorphisms and unusual HIV-1 mutations that confer resistance to PIs.

Results

Protease sequences isolated from 151 Mexican HIV-1 patients that were naïve to, or subjected to antiretroviral therapy, were examined. We identified 41 unrelated resistance mutations with a prevalence greater than 1%. Among these mutations, nine exhibited positive selection, three were natural polymorphisms (L63S/V/H) in a codon associated with drug resistance, and six were unusual mutations (L5F, D29V, L63R/G, P79L and T91V). The D29V mutation, with a prevalence of 1.32% in the studied population, was only found in patients treated with antiretroviral drugs. Using in silico modelling, we observed that D29V formed unstable protease complexes when were docked with lopinavir, saquinavir, darunavir, tipranavir, indinavir and atazanavir.

Conclusions

The structural correlation of natural polymorphisms and unusual mutations with drug resistance is useful for the identification of HIV-1 variants with potential resistance to PIs. The D29V mutation likely confers a selection advantage in viruses; however, in silico, presence of this mutation results in unstable enzyme/PI complexes, that possibly induce resistance to PIs.

A coordinated proteomic approach for identifying proteins that interact with the E. coli ribosomal protein S12

The bacterial ribosomal protein S12 contains a universally conserved D88 residue on a loop region thought to be critically involved in translation due to its proximal location to the A site of the 30S subunit. While D88 mutants are lethal this residue has been found to be post-translationally modified to β-methylthioaspartic acid, a post-translational modification (PTM) identified in S12 orthologs from several phylogenetically distinct bacteria. In a previous report focused on characterizing this PTM, our results provided evidence that this conserved loop region might be involved in forming multiple proteins-protein interactions ( Strader , M. B. ; Costantino , N. ; Elkins , C. A. ; Chen , C. Y. ; Patel , I. ; Makusky , A. J. ; Choy , J. S. ; Court , D. L. ; Markey , S. P. ; Kowalak , J. A. A proteomic and transcriptomic approach reveals new insight into betamethylthiolation of Escherichia coli ribosomal protein S12. Mol. Cell. Proteomics 2011 , 10 , M110 005199 ). To follow-up on this study, the D88 containing loop was probed to identify candidate binders employing a two-step complementary affinity purification strategy. The first involved an endogenously expressed S12 protein containing a C-terminal tag for capturing S12 binding partners. The second strategy utilized a synthetic biotinylated peptide representing the D88 conserved loop region for capturing S12 loop interaction partners. Captured proteins from both approaches were detected by utilizing SDS-PAGE and one-dimensional liquid chromatography-tandem mass spectrometry. The results presented in this report revealed proteins that form direct interactions with the 30S subunit and elucidated which are likely to interact with S12. In addition, we provide evidence that two proteins involved in regulating ribosome and/or mRNA transcript levels under stress conditions, RNase R and Hfq, form direct interactions with the S12 conserved loop, suggesting that it is likely part of a protein binding interface.

Computational analysis of HIV-1 protease protein binding pockets

Mutations that arise in HIV-1 protease after exposure to various HIV-1 protease inhibitors have proved to be a difficult aspect in the treatment of HIV. Mutations in the binding pocket of the protease can prevent the protease inhibitor from binding to the protein effectively. In the present study, the crystal structures of 68 HIV-1 proteases complexed with one of the nine FDA approved protease inhibitors from the Protein Data Bank (PDB) were analyzed by (a) identifying the mutational changes with the aid of a developed mutation map and (b) correlating the structure of the binding pockets with the complexed inhibitors. The mutations of each crystal structure were identified by comparing the amino acid sequence of each structure against the HIV-1 wild-type strain HXB2. These mutations were visually presented in the form of a mutation map to analyze mutation patterns corresponding to each protease inhibitor. The crystal structure mutation patterns of each inhibitor (in vitro) were compared against the mutation patterns observed in in vivo data. The in vitro mutation patterns were found to be representative of most of the major in vivo mutations. We then performed a data mining analysis of the binding pockets from each crystal structure in terms of their chemical descriptors to identify important structural features of the HIV-1 protease protein with respect to the binding conformation of the HIV-1 protease inhibitors. Data mining analysis is performed using several classification techniques: Random Forest (RF), linear discriminant analysis (LDA), and logistic regression (LR). We developed two hybrid models, RF-LDA and RF-LR. Random Forest is used as a feature selection proxy, reducing the descriptor space to a few of the most relevant descriptors determined by the classifier. These descriptors are then used to develop the subsequent LDA, LR, and hierarchical classification models. Clustering analysis of the binding pockets using the selected descriptors used to produce the optimal classification models reveals conformational similarities of the ligands in each cluster. This study provides important information in understanding the structural features of HIV-1 protease which cannot be studied by other existing in vivo genomic data sets.

TIA1 prevents skipping of a critical exon associated with spinal muscular atrophy

Prevention of skipping of exon 7 during pre-mRNA splicing of Survival Motor Neuron 2 (SMN2) holds the promise for cure of spinal muscular atrophy (SMA), a leading genetic cause of infant mortality. Here, we report T-cell-restricted intracellular antigen 1 (TIA1) and TIA1-related (TIAR) proteins as intron-associated positive regulators of SMN2 exon 7 splicing. We show that TIA1/TIAR stimulate exon recognition in an entirely novel context in which intronic U-rich motifs are separated from the 5' splice site by overlapping inhibitory elements. TIA1 and TIAR are modular proteins with three N-terminal RNA recognition motifs (RRMs) and a C-terminal glutamine-rich (Q-rich) domain. Our results reveal that any one RRM in combination with a Q domain is necessary and sufficient for TIA1-associated regulation of SMN2 exon 7 splicing in vivo. We also show that increased expression of TIA1 counteracts the inhibitory effect of polypyrimidine tract binding protein, a ubiquitously expressed factor recently implicated in regulation of SMN exon 7 splicing. Our findings expand the scope of TIA1/TIAR in genome-wide regulation of alternative splicing under normal and pathological conditions.

JCoDA: a tool for detecting evolutionary selection

BACKGROUND

The incorporation of annotated sequence information from multiple related species in commonly used databases (Ensembl, Flybase, Saccharomyces Genome Database, Wormbase, etc.) has increased dramatically over the last few years. This influx of information has provided a considerable amount of raw material for evaluation of evolutionary relationships. To aid in the process, we have developed JCoDA (Java Codon Delimited Alignment) as a simple-to-use visualization tool for the detection of site specific and regional positive/negative evolutionary selection amongst homologous coding sequences.

RESULTS

JCoDA accepts user-inputted unaligned or pre-aligned coding sequences, performs a codon-delimited alignment using ClustalW, and determines the dN/dS calculations using PAML (Phylogenetic Analysis Using Maximum Likelihood, yn00 and codeml) in order to identify regions and sites under evolutionary selection. The JCoDA package includes a graphical interface for Phylip (Phylogeny Inference Package) to generate phylogenetic trees, manages formatting of all required file types, and streamlines passage of information between underlying programs. The raw data are output to user configurable graphs with sliding window options for straightforward visualization of pairwise or gene family comparisons. Additionally, codon-delimited alignments are output in a variety of common formats and all dN/dS calculations can be output in comma-separated value (CSV) format for downstream analysis. To illustrate the types of analyses that are facilitated by JCoDA, we have taken advantage of the well studied sex determination pathway in nematodes as well as the extensive sequence information available to identify genes under positive selection, examples of regional positive selection, and differences in selection based on the role of genes in the sex determination pathway.

CONCLUSIONS

JCoDA is a configurable, open source, user-friendly visualization tool for performing evolutionary analysis on homologous coding sequences. JCoDA can be used to rapidly screen for genes and regions of genes under selection using PAML. It can be freely downloaded at http://www.tcnj.edu/~nayaklab/jcoda.

ORION-VIRCAT: a tool for mapping ICTV and NCBI taxonomies

Viruses, viroids and prions are the smallest infectious biological entities that depend on their host for replication. The number of pathogenic viruses is considerably large and their impact in human global health is well documented. Currently, the International Committee on the Taxonomy of Viruses (ICTV) has classified approximately 4379 virus species while the National Center for Biotechnology Information Viral Genomes Resource (NCBI-VGR) database has mapped 617 705 proteins to eight large taxonomic groups. Despite these efforts, an automated approach for mapping the ICTV master list and its officially accepted virus naming to the NCBI-VGR's taxonomical classification is not available. Due to metagenomic sequencing, it is likely that the discovery and naming of new viral species will increase by at least ten fold. Unfortunately, existing viral databases are not adequately prepared to scale, maintain and annotate automatically ultra-high throughput sequences and place this information into specific taxonomic categories. ORION-VIRCAT is a scalable and interoperable object-relational database designed to serve as a resource for the integration and verification of taxonomical classifications generated by the ICTV and NCBI-VGR. The current release (v1.0) of ORION-VIRCAT is implemented in PostgreSQL and it has been extended to ORACLE, MySQL and SyBase. ORION-VIRCAT automatically mapped and joined 617 705 entries from the NCBI-VGR to the viral naming of the ICTV. This detailed analysis revealed that 399 095 entries from the NCBI-VGR can be mapped to the ICTV classification and that one Order, 10 families, 35 genera and 503 species listed in the ICTV disagree with the the NCBI-VGR classification schema. Nevertheless, we were eable to correct several discrepancies mapping 234 000 additional entries.Database URL:http://www.orionbiosciences.com/research/orion-vircat.html.

A phylogenetic and Markov model approach for the reconstruction of mutational pathways of drug resistance

MOTIVATION

Modern HIV-1, hepatitis B virus and hepatitis C virus antiviral therapies have been successful at keeping viruses suppressed for prolonged periods of time, but therapy failures attributable to the emergence of drug resistant mutations continue to be a distressing reminder that no therapy can fully eradicate these viruses from their host organisms. To better understand the emergence of drug resistance, we combined phylogenetic and statistical models of viral evolution in a 2-phase computational approach that reconstructs mutational pathways of drug resistance.

RESULTS

The first phase of the algorithm involved the modeling of the evolution of the virus within the human host environment. The inclusion of longitudinal clonal sequence data was a key aspect of the model due to the progressive fashion in which multiple mutations become linked in the same genome creating drug resistant genotypes. The second phase involved the development of a Markov model to calculate the transition probabilities between the different genotypes. The proposed method was applied to data from an HIV-1 Efavirenz clinical trial study. The obtained model revealed the direction of evolution over time with greater detail than previous models. Our results show that the mutational pathways facilitate the identification of fast versus slow evolutionary pathways to drug resistance.

AVAILABILITY

Source code for the algorithm is publicly available at http://biorg.cis.fiu.edu/vPhyloMM/

Identification of HCV protease inhibitor resistance mutations by selection pressure-based method

A major challenge to successful antiviral therapy is the emergence of drug-resistant viruses. Recent studies have developed several automated analyses of HIV sequence polymorphism based on calculations of selection pressure (K_a/K_s) to predict drug resistance mutations. Similar resistance analysis programs for HCV inhibitors are not currently available. Taking advantage of the recently available sequence data of patient HCV samples from a Phase II clinical study of protease inhibitor boceprevir, we calculated the selection pressure for all codons in the HCV protease region (amino acid 1–181) to identify potential resistance mutations. The correlation between mutations was also calculated to evaluate linkage between any two mutations. Using this approach, we identified previously known major resistant mutations, including a recently reported mutation V55A. In addition, a novel mutation V158I was identified, and we further confirmed its resistance to boceprevir in protease enzyme and replicon assay. We also extended the approach to analyze potential interactions between individual mutations and identified three pairs of correlated changes. Our data suggests that selection pressure-based analysis and correlation mapping could provide useful tools to analyze large amount of sequencing data from clinical samples and to identify new drug resistance mutations as well as their linkage and correlations.

Evidence of a novel RNA secondary structure in the coding region of HIV-1 pol gene

RNA secondary structures play several important roles in the human immunodeficiency virus (HIV) life cycle. To assess whether RNA secondary structure might affect the function of the HIV protease and reverse transcriptase genes, which are the main targets of anti-HIV drugs, we applied a series of different computational approaches to detect RNA secondary structures, including thermodynamic RNA folding predictions, synonymous variability analysis, and covariance analysis. Each method independently revealed strong evidence of a novel RNA secondary structure at the junction of the protease and reverse transcriptase genes, consisting of a 107-nucleotide region containing three stems, A, B, and C. First, RNA folding calculations by mfold and RNAfold both predicted the secondary structure with high confidence. Moreover, the same structure was predicted in a diverse set of reference sequences in HIV-1 group M, indicating that it is conserved across this group. Second, the predicted base-pairing regions displayed markedly reduced synonymous variation (approximately threefold lower than average) in a data set of 20,000 HIV-1 subtype B sequences from clinical samples. Third, independent analysis of covariation between synonymous mutations in this data set identified 10 covariant mutation pairs forming two diagonals that corresponded exactly to the sites predicted to base-pair in stems A and B. Finally, this structure was validated experimentally using selective 2'-hydroxyl acylation and primer extension (SHAPE). Discovery of this novel secondary structure suggests many directions for further functional investigation.

SRp20 and CUG-BP1 modulate insulin receptor exon 11 alternative splicing

The insulin receptor (IR) exists as two isoforms, IR-A and IR-B, which result from alternative splicing of exon 11 in the primary transcript. This alternative splicing is cell specific, and the relative proportions of exon 11 isoforms also vary during development, aging, and different disease states. We have previously demonstrated that both intron 10 and exon 11 contain regulatory sequences that affect IR splicing both positively and negatively. In this study, we sought to define the precise sequence elements within exon 11 that control exon recognition and cellular factors that recognize these elements. Using minigenes carrying linker-scanning mutations within exon 11, we detected both exonic splicing enhancer and exonic splicing silencer elements. We identified binding of SRp20 and SF2/ASF to the exonic enhancers and CUG-BP1 to the exonic silencer by RNA affinity chromatography. Overexpression and knockdown studies with hepatoma and embryonic kidney cells demonstrated that SRp20 and SF2/ASF increase exon inclusion but that CUG-BP1 causes exon skipping. We found that CUG-BP1 also binds to an additional intronic splicing silencer, located at the 3' end of intron 10, to promote exon 11 skipping. Thus, we propose that SRp20, SF2/ASF, and CUG-BP1 act antagonistically to regulate IR alternative splicing in vivo and that the relative ratios of SRp20 and SF2/ASF to CUG-BP1 in different cells determine the degree of exon inclusion.

The RNA binding protein hnRNP Q modulates the utilization of exon 7 in the survival motor neuron 2 (SMN2) gene

Spinal muscular atrophy (SMA) is a recessive neuromuscular disorder caused by the homozygous loss of the SMN1 gene. The human SMN2 gene has a C-to-T transition at position +6 of exon 7 and thus produces exon 7-skipping mRNAs. However, we observed an unexpectedly high level of exon 7-containing SMN2 transcripts as well as SMN protein in testis of smn(-/-) SMN2 transgenic mice. Using affinity chromatography, we identified several SMN RNA-associating proteins in mouse testis and human HeLa cells, including hnRNP Q. The major hnRNP Q isoform, Q1, directly bound SMN exon 7 in the vicinity of nucleotide +6. Overexpression of hnRNP Q1 promoted the inclusion of exon 7 in SMN2, probably by activating the use of its upstream 3' splice site. However, the minor isoforms Q2/Q3 could antagonize the activity of hnRNP Q1 and induced exon 7 exclusion. Intriguingly, enhanced exon 7 inclusion was also observed upon concomitant depletion of three hnRNP Q isoforms. Thus, differential expression of hnRNP Q isoforms may result in intricate control of SMN precursor mRNA splicing. Here, we demonstrate that hnRNP Q is a splicing modulator of SMN, further underscoring the potential of hnRNP Q as a therapeutic target for SMA.

Relating sequence evolution of HIV1-protease to its underlying molecular mechanics

We investigate the connection between sequence evolution of the human immunodeficiency virus (HIV) type 1 protease under neutral selection or selective pressure induced by protease inhibitors and the functional and molecular-stability characteristics of the molecule in the physical domain. To this end we analyze sequence data on more than 45,000 patients with bioinformatical tools, namely mutual information between residue pairings. In addition we perform extensive computations on the molecular mechanics of the molecule subject to artificial mutations. The changes in the mechanics and dynamics of the molecule in three-dimensional space upon perturbation are then related to the sequence stability as described by the mutual information. We distinguish physical interactions by their evolutionary background and give hints for potential new drug targets. In addition we discuss how such targets can be efficiently chosen to give the HI virus less opportunity to develop resistance towards such drugs while maintaining the protease function at the same time. The interactions between residue no. 28 and 23' in different chains as well as the interaction between residue no. 92 and 94 within one chain were identified as particular crucial. In addition we find interactions in the beta-sheet-dimerization interface to be important for conserving the protein function and stability while these are at the same time evolutionary conserved - implications of and comparisons to experimental results are finally discussed.

Positive selection on HIV accessory proteins and the analysis of molecular adaptation after interspecies transmission

Studies examining positive selection on accessory proteins of HIV are rare, although these proteins play an important role in pathogenesis in vivo. Moreover, despite the biological relevance of analyses of molecular adaptation after viral transmission between species, the issue is still poorly studied. Here we present evidence that accessory proteins are subjected to positive selective forces exclusively in HIV. This scenario suggests that accessory protein genes are under adaptive evolution in HIV clades, while in SIVcpz such a phenomenon could not be detected. As a result, we show that comparative studies are critical to carry out functional investigation of positively selected protein sites, as they might help to achieve a better comprehension of the biology of HIV pathogenesis.

RNA structure modulates splicing efficiency at the human immunodeficiency virus type 1 major splice donor

The untranslated leader of the human immunodeficiency virus type 1 (HIV-1) RNA genome encodes essential sequence and structural motifs that control various replication steps. The 5' splice site or splice donor (SD) is embedded in a semistable hairpin, but the function of this structure is unknown. We stabilized this SD hairpin by creating an additional base pair and demonstrated a severe HIV-1 replication defect. A splicing defect was apparent in RNA analyses of virus-infected cells and cells transfected with appropriate reporter constructs. We selected multiple virus revertants in search for interesting second-site escape pathways. Most revertants acquired an additional mutation that modulated the stability of the mutant SD hairpin. One revertant acquired a single nucleotide change in the upstream DIS hairpin. We demonstrate that a novel SD site is created by this upstream mutation, which obviously reduces the number of leader nucleotides that are included in spliced HIV-1 transcripts. These results suggest a novel role of RNA structure in the regulation of HIV-1 splicing.

Distinguishing functional amino acid covariation from background linkage disequilibrium in HIV protease and reverse transcriptase

Correlated amino acid mutation analysis has been widely used to infer functional interactions between different sites in a protein. However, this analysis can be confounded by important phylogenetic effects broadly classifiable as background linkage disequilibrium (BLD). We have systematically separated the covariation induced by selective interactions between amino acids from background LD, using synonymous (S) vs. amino acid (A) mutations. Covariation between two amino acid mutations, (A,A), can be affected by selective interactions between amino acids, whereas covariation within (A,S) pairs or (S,S) pairs cannot. Our analysis of the pol gene — including the protease and the reverse transcriptase genes — in HIV reveals that (A,A) covariation levels are enormously higher than for either (A,S) or (S,S), and thus cannot be attributed to phylogenetic effects. The magnitude of these effects suggests that a large portion of (A,A) covariation in the HIV pol gene results from selective interactions. Inspection of the most prominent (A,A) interactions in the HIV pol gene showed that they are known sites of independently identified drug resistance mutations, and physically cluster around the drug binding site. Moreover, the specific set of (A,A) interaction pairs was reproducible in different drug treatment studies, and vanished in untreated HIV samples. The (S,S) covariation curves measured a low but detectable level of background LD in HIV.