Positive selection detection in 40,000 human immunodeficiency virus (HIV) type 1 sequences automatically identifies drug resistance and positive fitness mutations in HIV protease and reverse transcriptase

Lack of Resistance Mutations to the Novel HIV-1 Capsid Inhibitor Lenacapavir Among People Living with HIV in Guangdong, China

Background

The capsid inhibitor (CAI) lenacapavir (LEN) was approved for use in 2022, yet there are few reports about its drug resistance mutations (DRMs) and sensitivity.

Purpose

To delineate the prevalence of CAI DRMs and drug susceptibility among HIV-1 infected individuals living in Guangdong, China.

Patients and Methods

A total of 1035 individuals with HIV-1 infection, including 660 highly Active Anti-Retroviral Therapy (HAART) naive individuals and 375 hAART experienced individuals whose protease (PR)/ reverse transcriptase (RT) fragments were amplified successfully during drug resistance surveillance between October 2021 and December 2023, were randomly included in this study. The entire HIV-1 gag gene was amplified from plasma in LEN-naive individuals with or without antiretroviral therapy. The epidemiological and demographic information of the enrolled individuals were collected. The Stanford HIV Drug Resistance Database HIVdb program for Capsid was used to interpret the CAI DRMs and the LEN susceptibility.

Results

Among 1035 samples, 805 gag sequences were amplified, sequenced and assembled successfully from 518 hAART drugs naive individuals and 287 hAART drugs experienced individuals. Among them, 0.50% (4/805) carried at least one CAI DRM, of which 0.19% (1/518) from HAART naive individuals and 1.05% (3/287) from HAART experienced individuals. Among the individuals with CAI DRMs, two patients carried CAI major mutations (Q67H) conferring intermediate resistance to LEN and two patients carried CAI accessory mutation (T107A) conferring low level resistance to LEN.

Conclusion

Extremely low prevalence of CAI DRMs was detected among people living with HIV (PLWH) in Guangdong, China. Our observations indicate that LEN application may be promising when used in clinical practice in China. Before the administration of LEN, there is no need to consider detecting CAI mutations in PLWH through DRM examination for the time being.

Human Immunodeficiency Virus Type-1 Genetic Diversity and Drugs Resistance Mutations among People Living with HIV in Karachi, Pakistan

The human immunodeficiency virus type-1 epidemic in Pakistan has significantly increased over the last two decades. In Karachi, Pakistan, there is a lack of updated information on the complexity of HIV-1 genetic diversity and the burden of drug resistance mutations (DRMs) that can contribute to ART failure and poor treatment outcomes. This study aimed to determine HIV-1 genetic diversity and identify drug-resistance mutations among people living with HIV in Karachi. A total of 364 HIV-positive individuals, with a median age of 36 years, were enrolled in the study. The HIV-1 partial pol gene was successfully sequenced from 268 individuals. The sequences were used to generate phylogenetic trees to determine clade diversity and also to assess the burden of DRMs. Based on the partial pol sequences, 13 distinct HIV-1 subtypes and recombinant forms were identified. Subtype A1 was the most common clade (40%), followed by CRF02_AG (33.2%). Acquired DRMs were found in 30.6% of the ART-experienced patients, of whom 70.7%, 20.7%, and 8.5% were associated with resistance to NNRTIs, NRTIs, and PIs, respectively. Transmitted DRMs were found in 5.6% of the ART-naïve patients, of whom 93% were associated with resistance against NNRTIs and 7% to PIs. The high prevalence of DRMs in ART-experienced patients poses significant challenges to the long-term benefits and sustainability of the ART program. This study emphasizes the importance of continuous HIV molecular epidemiology and drug resistance surveillance to support evidence-based HIV prevention, precise ART, and targeted AIDS care.

Genetic and antiretroviral drug resistance mutations analysis of reverse transcriptase and protease gene from Pakistani people living with HIV-1

BACKGROUND

Antiretroviral therapy (ART) effectiveness is compromised by the emergence of HIV drug resistance mutations (DRM) and can lead to the failure of ART. Apart from intrinsic viral factors, non-compliance with drugs and/or the use of sub-optimum therapy can lead to the emergence of DRMs. In Pakistan HIV currently exists as a concentrated epidemic, however, ART coverage is very low, and drug adherence is poor. ART is selected assuming without baseline genotyping. Pakistan has recently seen a rise in treatment failures, but the country's actual burden of DRM is still unknown. In this study, we perform the genetic and drug resistance analysis of the pol gene from Pakistani HIV-positive ART-naïve and ART-experienced individuals.

METHODS

In this study, HIV-1 pol was sequenced from 146 HIV-1 positive individuals, divided into ART-naïve (n = 37) and ART-experienced (n = 109). The sequences were also used to determine HIV-1 subtypes, the prevalence of DRM, and pol genetic variability.

RESULTS

DRM analysis identified numerous DRMs against reverse transcriptase inhibitors in both ART-naïve and ART-experienced groups, including a few that are classified as rare. Additionally, the ART-experienced group showed mutations associated with resistance to protease inhibitors. Genetic analysis showed negative selection pressure in both groups, but a higher rate of evolution in the ART-naïve group.

CONCLUSION

High prevalence of DRMs, especially against previous first-line treatment in ART- naïve and the accumulation of DRMs in ART-experienced groups is concerning and warrants that a more extensive DRM survey be carried out to inform first-line and second-line ART regimen recommendations.

EvoRator2: Predicting Site-specific Amino Acid Substitutions Based on Protein Structural Information Using Deep Learning

Multiple sequence alignments (MSAs) are the workhorse of molecular evolution and structural biology research. From MSAs, the amino acids that are tolerated at each site during protein evolution can be inferred. However, little is known regarding the repertoire of tolerated amino acids in proteins when only a few or no sequence homologs are available, such as orphan and de novo designed proteins. Here we present EvoRator2, a deep-learning algorithm trained on over 15,000 protein structures that can predict which amino acids are tolerated at any given site, based exclusively on protein structural information mined from atomic coordinate files. We show that EvoRator2 obtained satisfying results for the prediction of position-weighted scoring matrices (PSSM). We further show that EvoRator2 obtained near state-of-the-art performance on proteins with high quality structures in predicting the effect of mutations in deep mutation scanning (DMS) experiments and that for certain DMS targets, EvoRator2 outperformed state-of-the-art methods. We also show that by combining EvoRator2's predictions with those obtained by a state-of-the-art deep-learning method that accounts for the information in the MSA, the prediction of the effect of mutation in DMS experiments was improved in terms of both accuracy and stability. EvoRator2 is designed to predict which amino-acid substitutions are tolerated in such proteins without many homologous sequences, including orphan or de novo designed proteins. We implemented our approach in the EvoRator web server (https://evorator.tau.ac.il).

OBI: A computational tool for the analysis and systematization of the positive selection in proteins

There are multiple tools for positive selection analysis, including vaccine design and detection of variants of circulating drug-resistant pathogens in population selection. However, applying these tools to analyze a large number of protein families or as part of a comprehensive phylogenomics pipeline could be challenging. Since many standard bioinformatics tools are only available as executables, integrating them into complex Bioinformatics pipelines may not be possible.

We have developed OBI, an open-source tool aimed to facilitate positive selection analysis on a large scale. It can be used as a stand-alone command-line app that can be easily installed and used as a Conda package.

Some advantages of using OBI are:•

It speeds up the analysis by automating the entire process

•

It allows multiple starting points and customization for the analysis

•

It allows the retrieval and linkage of structural and evolutive data for a protein through

We hope to provide with OBI a solution for reliably speeding up large-scale protein evolutionary and structural analysis.

Predominance of positive epistasis among drug resistance-associated mutations in HIV-1 protease

Drug-resistant mutations often have deleterious impacts on replication fitness, posing a fitness cost that can only be overcome by compensatory mutations. However, the role of fitness cost in the evolution of drug resistance has often been overlooked in clinical studies or in vitro selection experiments, as these observations only capture the outcome of drug selection. In this study, we systematically profile the fitness landscape of resistance-associated sites in HIV-1 protease using deep mutational scanning. We construct a mutant library covering combinations of mutations at 11 sites in HIV-1 protease, all of which are associated with resistance to protease inhibitors in clinic. Using deep sequencing, we quantify the fitness of thousands of HIV-1 protease mutants after multiple cycles of replication in human T cells. Although the majority of resistance-associated mutations have deleterious effects on viral replication, we find that epistasis among resistance-associated mutations is predominantly positive. Furthermore, our fitness data are consistent with genetic interactions inferred directly from HIV sequence data of patients. Fitness valleys formed by strong positive epistasis reduce the likelihood of reversal of drug resistance mutations. Overall, our results support the view that strong compensatory effects are involved in the emergence of clinically observed resistance mutations and provide insights to understanding fitness barriers in the evolution and reversion of drug resistance.

Survey for positively selected coding regions in the genome of the hematophagous tsetse fly Glossina morsitans identifies candidate genes associated with feeding habits and embryonic development

Tsetse flies are responsible for the transmission of Trypanossoma sp. to vertebrate animals in Africa causing huge health issues and economic loss. The availability of the genome sequence of Glossina morsitans enabled the discovery of several genes related to medically important phenotypes and novel physiological features. However, a genome-wide scan for coding regions that underwent positive selection is still missing, which is surprising given the evolution of traits associated with the hematophagy in this lineage. In this study, we employed an experimental design that controlled for the rate of false positives and we performed a scan of 3,318 G. morsitans genes. We found 145 genes with significant historical signal of positive selection. These genes were categorized into 18 functional classes after careful manual annotation. Based on their attributed functions, we identified candidate genes related with feeding habits and embryonic development. When our results were contrasted with gene expression data, we confirmed that most genes that underwent adaptive molecular evolution were frequently expressed in organs associated with key physiological evolutionary innovations in the G. morsitans lineage, namely, the salivary gland, the midgut, fat body tissue, and in the spermatophore.

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.

Genetic divergence of HIV-1 B subtype in Italy over the years 2003-2016 and impact on CTL escape prevalence

HIV-1 is characterized by high genetic variability, with implications for spread, and immune-escape selection. Here, the genetic modification of HIV-1 B subtype over time was evaluated on 3,328 pol and 1,152 V3 sequences belonging to B subtype and collected from individuals diagnosed in Italy between 2003 and 2016. Sequences were analyzed for genetic-distance from consensus-B (Tajima-Nei), non-synonymous and synonymous rates (dN and dS), CTL escapes, and intra-host evolution over four time-spans (2003–2006, 2007–2009, 2010–2012, 2013–2016). Genetic-distance increased over time for both pol and V3 sequences (P < 0.0001 and 0.0003). Similar results were obtained for dN and dS. Entropy-value significantly increased at 16 pol and two V3 amino acid positions. Seven of them were CTL escape positions (protease: 71; reverse-transcriptase: 35, 162, 177, 202, 207, 211). Sequences with ≥3 CTL escapes increased from 36.1% in 2003–2006 to 54.0% in 2013–2016 (P < 0.0001), and showed better intra-host adaptation than those containing ≤2 CTL escapes (intra-host evolution: 3.0 × 10⁻³ [2.9 × 10⁻³–3.1 × 10⁻³] vs. 4.3 × 10⁻³ [4.0 × 10⁻³–5.0 × 10⁻³], P[LRT] < 0.0001[21.09]). These data provide evidence of still ongoing modifications, involving CTL escape mutations, in circulating HIV-1 B subtype in Italy. These modifications might affect the process of HIV-1 adaptation to the host, as suggested by the slow intra-host evolution characterizing viruses with a high number of CTL escapes.

Molecular evolution of HIV-1 integrase during the 20 years prior to the first approval of integrase inhibitors

BACKGROUND

Detailed knowledge of the evolutionary potential of polymorphic sites in a viral protein is important for understanding the development of drug resistance in the presence of an inhibitor. We therefore set out to analyse the molecular evolution of the HIV-1 subtype B integrase at the inter-patient level in Germany during a 20-year period prior to the first introduction of integrase strand inhibitors (INSTIs).

METHODS

We determined 337 HIV-1 integrase subtype B sequences (amino acids 1-278) from stored plasma samples of antiretroviral treatment-naïve individuals newly diagnosed with HIV-1 between 1986 and 2006. Shannon entropy was calculated to determine the variability at each amino acid position. Time trends in the frequency of amino acid variants were identified by linear regression. Direct coupling analysis was applied to detect covarying sites.

RESULTS

Twenty-two time trends in the frequency of amino acid variants demonstrated either single amino acid exchanges or variation in the degree of polymorphy. Covariation was observed for 17 amino acid variants with a temporal trend. Some minor INSTI resistance mutations (T124A, V151I, K156 N, T206S, S230 N) and some INSTI-selected mutations (M50I, L101I, T122I, T124 N, T125A, M154I, G193E, V201I) were identified at overall frequencies >5%. Among these, the frequencies of L101I, T122I, and V201I increased over time, whereas the frequency of M154I decreased. Moreover, L101I, T122I, T124A, T125A, M154I, and V201I covaried with non-resistance-associated variants.

CONCLUSIONS

Time-trending, covarying polymorphisms indicate that long-term evolutionary changes of the HIV-1 integrase involve defined clusters of possibly structurally or functionally associated sites independent of selective pressure through INSTIs at the inter-patient level. Linkage between polymorphic resistance- and non-resistance-associated sites can impact the selection of INSTI resistance mutations in complex ways. Identification of these sites can help in improving genotypic resistance assays, resistance prediction algorithms, and the development of new integrase inhibitors.

One Year Genome Evolution of Lausannevirus in Allopatric versus Sympatric Conditions

Amoeba-resisting microorganisms raised a great interest during the last decade. Among them, some large DNA viruses present huge genomes up to 2.5 Mb long, exceeding the size of small bacterial genomes. The rate of genome evolution in terms of mutation, deletion, and gene acquisition in these genomes is yet unknown. Given the suspected high plasticity of viral genomes, the microevolution of the 346 kb genome of Lausannevirus, a member of Megavirales, was studied. Hence, Lausannevirus was co-cultured within the amoeba Acanthamoeba castellanii over one year. Despite a low number of mutations, the virus showed a genome reduction of 3.7% after 12 months. Lausannevirus genome evolution in sympatric conditions was investigated by its co-culture with Estrella lausannensis, an obligate intracellular bacterium, in the amoeba A. castellanii during one year. Cultures were split every 3 months. Genome sequencing revealed that in these conditions both, Lausannevirus and E. lausannensis, show stable genome, presenting no major rearrangement. In fact, after one year they acquired from 2 to 7 and from 4 to 10 mutations per culture for Lausannevirus and E. lausannensis, respectively. Interestingly, different mutations in the endonuclease encoding genes of Lausannevirus were observed in different subcultures, highlighting the importance of this gene product in the replication of Lausannevirus. Conversely, mutations in E. lausannensis were mainly located in a gene encoding for a phosphoenolpyruvate–protein phosphotransferase (PtsI), implicated in sugar metabolism. Moreover, in our conditions and with our analyses we detected no horizontal gene transfer during one year of co-culture.

Adaptive HIV-1 evolutionary trajectories are constrained by protein stability

Despite the use of combination antiretroviral drugs for the treatment of HIV-1 infection, the emergence of drug resistance remains a problem. Resistance may be conferred either by a single mutation or a concerted set of mutations. The involvement of multiple mutations can arise due to interactions between sites in the amino acid sequence as a consequence of the need to maintain protein structure. To better understand the nature of such epistatic interactions, we reconstructed the ancestral sequences of HIV-1’s Pol protein, and traced the evolutionary trajectories leading to mutations associated with drug resistance. Using contemporary and ancestral sequences we modelled the effects of mutations (i.e. amino acid replacements) on protein structure to understand the functional effects of residue changes. Although the majority of resistance-associated sequences tend to destabilise the protein structure, we find there is a general tendency for protein stability to decrease across HIV-1’s evolutionary history. That a similar pattern is observed in the non-drug resistance lineages indicates that non-resistant mutations, for example, associated with escape from the immune response, also impacts on protein stability. Maintenance of optimal protein structure therefore represents a major constraining factor to the evolution of HIV-1.

Escape from humoral immunity is associated with treatment failure in HIV-1-infected patients receiving long-term antiretroviral therapy

Interindividual heterogeneity in the disease progression of HIV-1-infected patients receiving long-term antiretroviral therapy suggests that some host-related factors may have limited treatment efficacy. To understand the nature of factors contributing to treatment failure, we performed a retrospective cohort study of 45 chronically HIV-1-infected individuals sharing a similar demographics and route of infection, compared the differences between virologically suppressed (VS) and treatment failure (TF) patients with respect to clinical, immunological and virological characteristics. We found that the baseline diversity of HIV-1 env quasispecies was the major difference between VS and TF group, and higher baseline diversity in TF patients. We further predicted TF-related env mutations using a selection pressure-based approach, followed by an analysis of these mutations based on the available three-dimensional structures of gp120/gp41 or their complexes with neutralizing antibodies. Notably, almost all of the identified residues could be mapped to the epitopes of known HIV-1 neutralizing antibodies, especially the epitopes of broadly neutralizing antibodies, and these mutations tended to compromise antibody-antigen interactions. These results indicate that the escape of HIV-1 from host humoral immunity may play a direct role in TF in long-term antiretroviral-experienced patients and that based on env gene sequence of the viruses in the patients.

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.

Changes in selective pressures associated with human population expansion may explain metabolic and immune related pathways enriched for signatures of positive selection

Background

The study of local adaptation processes is a very important research topic in the field of population genomics. There is a particular interest in the study of human populations because they underwent a process of rapid spatial expansion and faced important environmental changes that translated into changes in selective pressures. New mutations may have been selected for in the new environment and previously existing genetic variants may have become detrimental. Immune related genes may have been released from the selective pressure exerted by pathogens in the ancestral environment and new variants may have been positively selected due to pathogens present in the newly colonized habitat. Also, variants that had a selective advantage in past environments may have become deleterious in the modern world due to external stimuli including climatic, dietary and behavioral changes, which could explain the high prevalence of some polygenic diseases such as diabetes and obesity.

Results

We performed an enrichment analysis to identify gene sets enriched for signals of positive selection in humans. We used two genome scan methods, XPCLR and iHS to detect selection using a dense coverage of SNP markers combined with two gene set enrichment approaches. We identified immune related gene sets that could be involved in the protection against pathogens especially in the African population. We also identified the glycolysis & gluconeogenesis gene set, related to metabolism, which supports the thrifty genotype hypothesis invoked to explain the current high prevalence of diseases such as diabetes and obesity. Extending our analysis to the gene level, we found signals for 23 candidate genes linked to metabolic syndrome, 13 of which are new candidates for positive selection.

Conclusions

Our study provides a list of genes and gene sets associated with immunity and metabolic syndrome that are enriched for signals of positive selection in three human populations (Europeans, Africans and Asians). Our results highlight differences in the relative importance of pathogens as drivers of local adaptation in different continents and provide new insights into the evolution and high incidence of metabolic syndrome in modern human populations.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2783-2) contains supplementary material, which is available to authorized users.

Identification of drug resistance mutations in HIV from constraints on natural evolution

Human immunodeficiency virus (HIV) evolves with extraordinary rapidity. However, its evolution is constrained by interactions between mutations in its fitness landscape. Here we show that an Ising model describing these interactions, inferred from sequence data obtained prior to the use of antiretroviral drugs, can be used to identify clinically significant sites of resistance mutations. Successful predictions of the resistance sites indicate progress in the development of successful models of real viral evolution at the single residue level and suggest that our approach may be applied to help design new therapies that are less prone to failure even where resistance data are not yet available.

Mutations Proximal to Sites of Autoproteolysis and the α-Helix That Co-evolve under Drug Pressure Modulate the Autoprocessing and Vitality of HIV-1 Protease

N-Terminal self-cleavage (autoprocessing) of the HIV-1 protease precursor is crucial for liberating the active dimer. Under drug pressure, evolving mutations are predicted to modulate autoprocessing, and the reduced catalytic activity of the mature protease (PR) is likely compensated by enhanced conformational/dimer stability and reduced susceptibility to self-degradation (autoproteolysis). One such highly evolved, multidrug resistant protease, PR20, bears 19 mutations contiguous to sites of autoproteolysis in retroviral proteases, namely clusters 1-3 comprising residues 30-37, 60-67, and 88-95, respectively, accounting for 11 of the 19 mutations. By systematically replacing corresponding clusters in PR with those of PR20, and vice versa, we assess their influence on the properties mentioned above and observe no strict correlation. A 10-35-fold decrease in the cleavage efficiency of peptide substrates by PR20, relative to PR, is reflected by an only ∼4-fold decrease in the rate of Gag processing with no change in cleavage order. Importantly, optimal N-terminal autoprocessing requires all 19 PR20 mutations as evaluated in vitro using the model precursor TFR-PR20 in which PR is flanked by the transframe region. Substituting PR20 cluster 3 into TFR-PR (TFR-PR(PR20-3)) requires the presence of PR20 cluster 1 and/or 2 for autoprocessing. In accordance, substituting PR clusters 1 and 2 into TFR-PR20 affects the rate of autoprocessing more drastically (>300-fold) compared to that of TFR-PR(PR20-3) because of the cumulative effect of eight noncluster mutations present in TFR-PR20(PR-12). Overall, these studies imply that drug resistance involves a complex synchronized selection of mutations modulating all of the properties mentioned above governing PR regulation and function.

Novel Neuroimaging Methods to Understand How HIV Affects the Brain

In much of the developed world, the HIV epidemic has largely been controlled by antiretroviral treatment. Even so, there is growing concern that HIV-infected individuals may be at risk for accelerated brain aging and a range of cognitive impairments. What promotes or resists these changes is largely unknown. There is also interest in discovering factors that promote resilience to HIV and combat its adverse effects in children. Here, we review recent developments in brain imaging that reveal how the virus affects the brain. We relate these brain changes to changes in blood markers, cognitive function, and other patient outcomes or symptoms, such as apathy or neuropathic pain. We focus on new and emerging techniques, including new variants of brain MRI. Diffusion tensor imaging, for example, can map the brain's structural connections, while fMRI can uncover functional connections. Finally, we suggest how large-scale global research alliances, such as ENIGMA, may resolve controversies over effects where evidence is now lacking. These efforts pool scans from tens of thousands of individuals and offer a source of power not previously imaginable for brain imaging studies.

Recovery of the wild type atomic flexibility in the HIV-1 protease double mutants

The emergence of drug resistant mutations due to the selective pressure exerted by antiretrovirals, including protease inhibitors (PIs), remains a major problem in the treatment of AIDS. During PIs therapy, the occurrence of primary mutations in the wild type HIV-1 protease reduces both the affinity for the inhibitors and the viral replicative capacity compared to the wild type (WT) protein, but additional mutations compensate for this reduced viral fitness. To investigate this phenomenon from the structural point of view, we combined Molecular Dynamics and Normal Mode Analysis to analyze and compare the variations of the flexibility of C-alpha atoms and the differences in hydrogen bond (h-bond) network between the WT and double mutants. In most cases, the flexibility profile of the double mutants was more often similar to that of the WT than to that of the related single base mutants. All single mutants showed a significant alteration in h-bond formation compared to WT. Most of the significant changes occur in the border between the flap and cantilever regions. We found that all the considered double mutants have their h-bond pattern significantly altered in comparison to the respective single base mutants affecting their flexibility profile that becomes more similar to that of WT. This WT flexibility restoration in the double mutants appears as an important factor for the HIV-1 fitness recovery observed in patients.

HIV-1 transmitted drug resistance-associated mutations and mutation co-variation in HIV-1 treatment-naïve MSM from 2011 to 2013 in Beijing, China

Background

Transmitted drug resistance (TDR) is an important public health issue, because TDR-associated mutation may affect the outcome of antiretroviral treatment potentially or directly. Men who have sex with men (MSM) constitute a major risk group for HIV transmission. However, current reports are scarce on HIV TDR-associated mutations and their co-variation among MSM.

Methods

Blood samples from 262 newly diagnosed HIV-positive, antiretroviral therapy (ART)-naïve MSM, were collected from January 2011 and December 2013 in Beijing. The polymerase viral genes were sequenced to explore TDR-associated mutations and mutation co-variation.

Results

A total of 223 samples were sequenced and analyzed. Among them, HIV-1 CRF01_AE are accounted for 60.5%, followed by CRF07_BC (27.8%), subtype B (9.9%), and others. Fifty-seven samples had at least one TDR-associated mutation, mainly including L10I/V (6.3%), A71L/T/V (6.3%), V179D/E (5.4%), and V106I (2.7%), with different distributions of TDR-associated mutations by different HIV-1 subtypes and by each year. Moreover, eight significant co-variation pairs were found between TDR-associated mutations (V179D/E) and seven overlapping polymorphisms in subtype CRF01_AE.

Conclusions

To date, this work consists the most comprehensive genetic characterization of HIV-1 TDR-associated mutations prevalent among MSM. It provides important information for understanding TDR and viral evolution among Chinese MSM, a population currently at particularly high risk of HIV transmission.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-014-0689-7) contains supplementary material, which is available to authorized users.

The development of drug resistance mutations K103N Y181C and G190A in long term Nevirapine-containing antiviral therapy

Objective

We built a cohort study of HIV patients taking long-term first-line Antiretroviral Therapy in 2003. In this assay, we focused on the development of primary drug resistance mutations against Non-Nucleoside Reverse Transcriptase Inhibitor (NNRTI), K103N, Y181C and G190A.

Method

The cohort study was built in Henan province, China. We used Single Genome Amplification (SGA) to analyze the frequency of K103N, Y181C and G190A in serial plasma samples of three individual patients. We also performed standard genotype HIV drug resistance assay in 204 patients of this cohort study to analyze the frequency of these mutations.

Result

In the SGA sequences, the K103N decreased and vanished, while the frequency of Y181C and G190A increased in individual patient receiving long-term Antiretroviral Therapy (ART). In the sequences of standard genotype HIV drug resistance assay, the frequency of K103N, Y181C and G190A had the similar pattern with that in SGA sequences. Among these patients, the viral suppression were still sufficient after receiving ART for 72 months, and 78.6% (160/204) patients could have their CD4 count over than 200cells/ul.

Conclusion

In some patients, first-line ART had the possibility to provide sufficient treatment effect for over than 72 months, but in long-term treatment, the dominant NNRTI drug resistance mutation K103N could reduced, while the proportion of variants with mutation Y181C or G190A may increased. This result was not similar with that in vitro study, which state that variant with K103N or Y181C had an equal viral fitness with wild type.

Single genome analysis reveals genetic characteristics of Neuroadaptation across HIV-1 envelope

Background

The widespread use of highly effective, combination antiretroviral therapy (cART) has led to a significant reduction in the incidence of HIV-associated dementia (HAD). Despite these advances, the prevalence of HIV-1 associated neurocognitive disorders (HANDs) has been estimated at approximately 40%-50%. In the cART era, the majority of this disease burden is represented by asymptomatic neurocognitive impairment and mild neurocognitive disorder (ANI and MND respectively). Although less severe than HAD, these diagnoses carry with them substantial morbidity.

Results

In this cross-sectional study, single genome amplification (SGA) was used to sequence 717 full-length HIV-1 envelope (env) clade B variants from the paired cerebrospinal fluid (CSF) and blood plasma samples of fifteen chronically infected HIV-positive individuals with normal neurocognitive performance (NCN), ANI and MND. Various degrees of compartmentalization were found across disease states and history of cART utilization. In individuals with compartmentalized virus, mean HIV-1 env population diversity was lower in the CSF than plasma-derived variants. Overall, mean V1V2 loop length was shorter in CSF-derived quasispecies when compared to contemporaneous plasma populations, and this was found to correlate with a lower mean number of N-linked glycosylation sites in this region. A number of discrete amino acid positions that correlate strongly with compartmentalization in the CSF were identified in both variable and constant regions of gp120 as well as in gp41. Correlated mutation analyses further identified that a subset of amino acid residues in these compartmentalization “hot spot” positions were strongly correlated with one another, suggesting they may play an important, definable role in the adaptation of viral variants to the CSF. Analysis of these hot spots in the context of a well-supported crystal structure of HIV-1 gp120 suggests mechanisms through which amino acid differences at the identified residues might contribute to viral compartmentalization in the CSF.

Conclusions

The detailed analyses of SGA-derived full length HIV-1 env from subjects with both normal neurocognitive performance and the most common HAND diagnoses in the cART era allow us to identify novel and confirm previously described HIV-1 env genetic determinants of neuroadaptation and relate potential motifs to HIV-1 env structure and function.

Electronic supplementary material

The online version of this article (doi:10.1186/s12977-014-0065-0) contains supplementary material, which is available to authorized users.

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.

CorMut: an R/Bioconductor package for computing correlated mutations based on selection pressure

Correlated mutations constitute a fundamental idea in evolutionary biology, and understanding correlated mutations will, in turn, facilitate an understanding of the genetic mechanisms governing evolution. CorMut is an R package designed to compute correlated mutations in the unit of codon or amino acid mutation. Three classical methods were incorporated, and the computation results can be represented as correlation mutation networks. CorMut also enables the comparison of correlated mutations between two different evolutionary conditions.

AVAILABILITY AND IMPLEMENTATION

CorMut is released under the GNU General Public License within bioconductor project, and freely available at http://bioconductor.org/packages/release/bioc/html/CorMut.html.

Differential selection in HIV-1 gp120 between subtype B and East Asian variant B'

HIV-1 evolves strongly and undergoes geographic differentiation as it spreads in diverse host populations around the world. For instance, distinct genomic backgrounds can be observed between the pandemic subtype B, prevalent in Europe and North-America, and its offspring clade B' in East Asia. Here we ask whether this differentiation affects the selection pressure experienced by the virus. To answer this question we evaluate selection pressure on the HIV-1 envelope protein gp120 at the level of individual codons using a simple and fast estimation method based on the ratio k a /k s of amino acid changes to synonymous changes. To validate the approach we compare results to those from a state-of-the-art mixed-effect method. The agreement is acceptable, but the analysis also demonstrates some limitations of the simpler approach. Further, we find similar distributions of codons under stabilizing and directional selection pressure in gp120 for subtypes B and B' with more directional selection pressure in variable loops and more stabilizing selection in the constant regions. Focusing on codons with increased k a /k s values in B', we show that these codons are scattered over the whole of gp120, with remarkable clusters of higher density in regions flanking the variable loops. We identify a significant statistical association of glycosylation sites and codons with increased k a /k s values.

Directional Darwinian Selection in proteins

Background

Molecular evolution is a very active field of research, with several complementary approaches, including dN/dS, HON90, MM01, and others. Each has documented strengths and weaknesses, and no one approach provides a clear picture of how natural selection works at the molecular level. The purpose of this work is to present a simple new method that uses quantitative amino acid properties to identify and characterize directional selection in proteins.

Methods

Inferred amino acid replacements are viewed through the prism of a single physicochemical property to determine the amount and direction of change caused by each replacement. This allows the calculation of the probability that the mean change in the single property associated with the amino acid replacements is equal to zero (H₀: μ = 0; i.e., no net change) using a simple two-tailed t-test.

Results

Example data from calanoid and cyclopoid copepod cytochrome oxidase subunit I sequence pairs are presented to demonstrate how directional selection may be linked to major shifts in adaptive zones, and that convergent evolution at the whole organism level may be the result of convergent protein adaptations.

Conclusions

Rather than replace previous methods, this new method further complements existing methods to provide a holistic glimpse of how natural selection shapes protein structure and function over evolutionary time.

Quantifying selection against synonymous mutations in HIV-1 env evolution

Intrapatient evolution of human immunodeficiency virus type 1 (HIV-1) is driven by the adaptive immune system resulting in rapid change of HIV-1 proteins. When cytotoxic CD8(+) T cells or neutralizing antibodies target a new epitope, the virus often escapes via nonsynonymous mutations that impair recognition. Synonymous mutations do not affect this interplay and are often assumed to be neutral. We test this assumption by tracking synonymous mutations in longitudinal intrapatient data from the C2-V5 part of the env gene. We find that most synonymous variants are lost even though they often reach high frequencies in the viral population, suggesting a cost to the virus. Using published data from SHAPE (selective 2'-hydroxyl acylation analyzed by primer extension) assays, we find that synonymous mutations that disrupt base pairs in RNA stems flanking the variable loops of gp120 are more likely to be lost than other synonymous changes: these RNA hairpins might be important for HIV-1. Computational modeling indicates that, to be consistent with the data, a large fraction of synonymous mutations in this genomic region need to be deleterious with a cost on the order of 0.002 per day. This weak selection against synonymous substitutions does not result in a strong pattern of conservation in cross-sectional data but slows down the rate of evolution considerably. Our findings are consistent with the notion that large-scale patterns of RNA structure are functionally relevant, whereas the precise base pairing pattern is not.

Synonymous site conservation in the HIV-1 genome

BACKGROUND

Synonymous or silent mutations are usually thought to evolve neutrally. However, accumulating recent evidence has demonstrated that silent mutations may destabilize RNA structures or disrupt cis regulatory motifs superimposed on coding sequences. Such observations suggest the existence of stretches of codon sites that are evolutionary conserved at both DNA-RNA and protein levels. Such stretches may point to functionally important regions within protein coding sequences not necessarily reflecting functional constraints on the amino-acid sequence. The HIV-1 genome is highly compact, and often harbors overlapping functional elements at the protein, RNA, and DNA levels. This superimposition of functions leads to complex selective forces acting on all levels of the genome and proteome. Considering the constraints on HIV-1 to maintain such a highly compact genome, we hypothesized that stretches of synonymous conservation would be common within its genome.

RESULTS

We used a combined computational-experimental approach to detect and characterize regions exhibiting strong purifying selection against synonymous substitutions along the HIV-1 genome. Our methodology is based on advanced probabilistic evolutionary models that explicitly account for synonymous rate variation among sites and rate dependencies among adjacent sites. These models are combined with a randomization procedure to automatically identify the most statistically significant regions of conserved synonymous sites along the genome. Using this procedure we identified 21 conserved regions. Twelve of these are mapped to regions within overlapping genes, seven correlate with known functional elements, while the functions of the remaining four are yet unknown. Among these four regions, we chose the one that deviates most from synonymous rate homogeneity for in-depth computational and experimental characterization. In our assays aiming to quantify viral fitness in both early and late stages of the replication cycle, no differences were observed between the mutated and the wild type virus following the introduction of synonymous mutations.

CONCLUSIONS

The contradiction between the inferred purifying selective forces and the lack of effect of these mutations on viral replication may be explained by the fact that the phenotype was measured in single-cycle infection assays in cell culture. Such a system does not account for the complexity of HIV-1 infections in vivo, which involves multiple infection cycles and interaction with the host immune system.

Pathway-based screening strategy for multitarget inhibitors of diverse proteins in metabolic pathways

Many virtual screening methods have been developed for identifying single-target inhibitors based on the strategy of “one–disease, one–target, one–drug”. The hit rates of these methods are often low because they cannot capture the features that play key roles in the biological functions of the target protein. Furthermore, single-target inhibitors are often susceptible to drug resistance and are ineffective for complex diseases such as cancers. Therefore, a new strategy is required for enriching the hit rate and identifying multitarget inhibitors. To address these issues, we propose the pathway-based screening strategy (called PathSiMMap) to derive binding mechanisms for increasing the hit rate and discovering multitarget inhibitors using site-moiety maps. This strategy simultaneously screens multiple target proteins in the same pathway; these proteins bind intermediates with common substructures. These proteins possess similar conserved binding environments (pathway anchors) when the product of one protein is the substrate of the next protein in the pathway despite their low sequence identity and structure similarity. We successfully discovered two multitarget inhibitors with IC₅₀ of <10 µM for shikimate dehydrogenase and shikimate kinase in the shikimate pathway of Helicobacter pylori. Furthermore, we found two selective inhibitors (IC₅₀ of <10 µM) for shikimate dehydrogenase using the specific anchors derived by our method. Our experimental results reveal that this strategy can enhance the hit rates and the pathway anchors are highly conserved and important for biological functions. We believe that our strategy provides a great value for elucidating protein binding mechanisms and discovering multitarget inhibitors.

Many drug development strategies focus on designing inhibitors for single targets. These inhibitors often lose potency owing to mutations in the protein binding sites and are ineffective for complex diseases. Multitarget inhibitors can decrease probability of drug resistance and enhance the therapeutic efficiency; however, identifying them is still a challenge because targets often have low sequence and structure similarities in their binding sites. Here we propose a pathway-based screening strategy that simultaneously screens proteins in a metabolic pathway for discovering multitarget inhibitors. Because these proteins interact with similar metabolites and modify them step-by-step, the proteins share similarities in binding sites. We developed pathway site-moiety maps that present the conserved binding environments of the proteins without relying on the sequence or structure alignment. Compounds that bind these conserved binding environments are often multitarget inhibitors. We applied this strategy to the shikimate pathway of Helicobacter pylori, and discovered two multitarget inhibitors (IC₅₀<10 µM) for shikimate dehydrogenase and shikimate kinase. In addition, we found two selective inhibitors based on specific binding environments for shikimate dehydrogenase. Thus the pathway-based screening strategy is useful for identifying multitarget inhibitors and elucidating protein-ligand binding mechanisms and has the potential to be applied to human diseases.

Parallel screening of wild-type and drug-resistant targets for anti-resistance neuraminidase inhibitors

Infection with influenza virus is a major public health problem, causing serious illness and death each year. Emergence of drug-resistant influenza virus strains limits the effectiveness of drug treatment. Importantly, a dual H275Y/I223R mutation detected in the pandemic influenza A 2009 virus strain results in multidrug resistance to current neuraminidase (NA) drugs. Therefore, discovery of new agents for treating multiple drug-resistant (MDR) influenza virus infections is important. Here, we propose a parallel screening strategy that simultaneously screens wild-type (WT) and MDR NAs, and identifies inhibitors matching the subsite characteristics of both NA-binding sites. These may maintain their potency when drug-resistant mutations arise. Initially, we analyzed the subsite of the dual H275Y/I223R NA mutant. Analysis of the site-moiety maps of NA protein structures show that the mutant subsite has a relatively small volume and is highly polar compared with the WT subsite. Moreover, the mutant subsite has a high preference for forming hydrogen-bonding interactions with polar moieties. These changes may drive multidrug resistance. Using this strategy, we identified a new inhibitor, Remazol Brilliant Blue R (RB19, an anthraquinone dye), which inhibited WT NA and MDR NA with IC₅₀ values of 3.4 and 4.5 µM, respectively. RB19 comprises a rigid core scaffold and a flexible chain with a large polar moiety. The former interacts with highly conserved residues, decreasing the probability of resistance. The latter forms van der Waals contacts with the WT subsite and yields hydrogen bonds with the mutant subsite by switching the orientation of its flexible side chain. Both scaffolds of RB19 are good starting points for lead optimization. The results reveal a parallel screening strategy for identifying resistance mechanisms and discovering anti-resistance neuraminidase inhibitors. We believe that this strategy may be applied to other diseases with high mutation rates, such as cancer and human immunodeficiency virus type 1.

Directional evolution of Chlamydia trachomatis towards niche-specific adaptation

On behalf of the host-pathogen "arms race," a cutting-edge approach for elucidating genotype-phenotype relationships relies on the identification of positively selected loci involved in pathoadaptation. We studied the obligate intracellular bacterium Chlamydia trachomatis, for which same-species strains display a nearly identical core and pan genome, while presenting a wide range of tissue tropism and ecological success. We sought to evaluate the evolutionary patterns underlying species separation (divergence) and C. trachomatis serovar radiation (polymorphism) and to establish genotype-phenotype associations. By analyzing 60 Chlamydia strains, we detected traces of Muller's ratchet as a result of speciation and identified positively selected genes and codons hypothetically involved in the infection of different human cell types (e.g., columnar epithelial cells of ocular or genital mucosae and mononuclear phagocytes) and also events likely driving pathogenic and ecological success dissimilarities. In general, these genes code for proteins involved in immune response elicitation, proteolysis, and the subversion of host-cell functions, and also for proteins with unknown function(s). Several genes are potentially involved in more than one adaptive process, suggesting multiple functions or a distinct modus operandi for a specific function, and thus should be considered as crucial research targets. In addition, six of the nine genes encoding the putative antigen/adhesin polymorphic membrane proteins seem to be under positive selection along specific serovars, which sustains an essential biological role of this extra-large paralogue family in chlamydial pathobiology. This study provides insight into how evolutionary inferences illuminate ecological processes such as adaptation to different niches, pathogenicity, or ecological success driven by arms races.

Correlated electrostatic mutations provide a reservoir of stability in HIV protease

HIV protease, an aspartyl protease crucial to the life cycle of HIV, is the target of many drug development programs. Though many protease inhibitors are on the market, protease eventually evades these drugs by mutating at a rapid pace and building drug resistance. The drug resistance mutations, called primary mutations, are often destabilizing to the enzyme and this loss of stability has to be compensated for. Using a coarse-grained biophysical energy model together with statistical inference methods, we observe that accessory mutations of charged residues increase protein stability, playing a key role in compensating for destabilizing primary drug resistance mutations. Increased stability is intimately related to correlations between electrostatic mutations – uncorrelated mutations would strongly destabilize the enzyme. Additionally, statistical modeling indicates that the network of correlated electrostatic mutations has a simple topology and has evolved to minimize frustrated interactions. The model's statistical coupling parameters reflect this lack of frustration and strongly distinguish like-charge electrostatic interactions from unlike-charge interactions for of the most significantly correlated double mutants. Finally, we demonstrate that our model has considerable predictive power and can be used to predict complex mutation patterns, that have not yet been observed due to finite sample size effects, and which are likely to exist within the larger patient population whose virus has not yet been sequenced.

HIV is incurable because its enzymes evolve rapidly by developing resistance mutations to retroviral inhibitors. Most of these mutations work synergistically, but the biophysical basis behind their cooperation is not well understood. Our work addresses these important issues by bridging the gap between the statistical modeling of HIV protease subtype B sequences with the energetics of mutations involving charged amino acids by showing that electrostatic stability is intimately related to correlations. Moreover, we demonstrate that our statistical model has considerable predictive power and can be used to predict complex mutation patterns that have not yet been observed due to the finite sizes of the current sequence databases. In other words, as the database size increases, our model has the ability to predict the identities of the high probability mutations patterns, which are more likely to be observed. Knowing which currently unobserved mutations are more likely to be observed can be very advantageous in combating the disease.

Modeling HIV-1 drug resistance as episodic directional selection

The evolution of substitutions conferring drug resistance to HIV-1 is both episodic, occurring when patients are on antiretroviral therapy, and strongly directional, with site-specific resistant residues increasing in frequency over time. While methods exist to detect episodic diversifying selection and continuous directional selection, no evolutionary model combining these two properties has been proposed. We present two models of episodic directional selection (MEDS and EDEPS) which allow the a priori specification of lineages expected to have undergone directional selection. The models infer the sites and target residues that were likely subject to directional selection, using either codon or protein sequences. Compared to its null model of episodic diversifying selection, MEDS provides a superior fit to most sites known to be involved in drug resistance, and neither one test for episodic diversifying selection nor another for constant directional selection are able to detect as many true positives as MEDS and EDEPS while maintaining acceptable levels of false positives. This suggests that episodic directional selection is a better description of the process driving the evolution of drug resistance.

When exposed to treatment, HIV-1 and other rapidly evolving viruses have the capacity to acquire drug resistance mutations (DRAMs), which limit the efficacy of antivirals. There are a number of experimentally well characterized HIV-1 DRAMs, but many mutations whose roles are not fully understood have also been reported. In this manuscript we construct evolutionary models that identify the locations and targets of mutations conferring resistance to antiretrovirals from viral sequences sampled from treated and untreated individuals. While the evolution of drug resistance is a classic example of natural selection, existing analyses fail to detect the majority of DRAMs. We show that, in order to identify resistance mutations from sequence data, it is necessary to recognize that in this case natural selection is both episodic (it only operates when the virus is exposed to the drugs) and directional (only mutations to a particular amino-acid confer resistance while allowing the virus to continue replicating). The new class of models that allow for the episodic and directional nature of adaptive evolution performs very well at recovering known DRAMs, can be useful at identifying unknown resistance-associated mutations, and is generally applicable to a variety of biological scenarios where similar selective forces are at play.

The evolution of HIV: inferences using phylogenetics

Molecular phylogenetics has revolutionized the study of not only evolution but also disparate fields such as genomics, bioinformatics, epidemiology, ecology, microbiology, molecular biology and biochemistry. Particularly significant are its achievements in population genetics as a result of the development of coalescent theory, which have contributed to more accurate model-based parameter estimation and explicit hypothesis testing. The study of the evolution of many microorganisms, and HIV in particular, have benefited from these new methodologies. HIV is well suited for such sophisticated population analyses because of its large population sizes, short generation times, high substitution rates and relatively small genomes. All these factors make HIV an ideal and fascinating model to study molecular evolution in real time. Here we review the significant advances made in HIV evolution through the application of phylogenetic approaches. We first examine the relative roles of mutation and recombination on the molecular evolution of HIV and its adaptive response to drug therapy and tissue allocation. We then review some of the fundamental questions in HIV evolution in relation to its origin and diversification and describe some of the insights gained using phylogenies. Finally, we show how phylogenetic analysis has advanced our knowledge of HIV dynamics (i.e., phylodynamics).

A multifaceted analysis of HIV-1 protease multidrug resistance phenotypes

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.

An inducible cell-cell fusion system with integrated ability to measure the efficiency and specificity of HIV-1 entry inhibitors

HIV-1 envelope glycoproteins (Envs) mediate virus entry by fusing the viral and target cell membranes, a multi-step process that represents an attractive target for inhibition. Entry inhibitors with broad-range activity against diverse isolates of HIV-1 may be extremely useful as lead compounds for the development of therapies or prophylactic microbicides. To facilitate the identification of such inhibitors, we have constructed a cell-cell fusion system capable of simultaneously monitoring inhibition efficiency and specificity. In this system, effector cells stably express a tetracycline-controlled transactivator (tTA) that enables tightly inducible expression of both HIV-1 Env and the Renilla luciferase (R-Luc) reporter protein. Target cells express the HIV-1 receptors, CD4 and CCR5, and carry the firefly luciferase (F-Luc) reporter gene under the control of a tTA-responsive promoter. Thus, Env-mediated fusion of these two cell types allows the tTA to diffuse to the target cell and activate the expression of the F-Luc protein. The efficiency with which an inhibitor blocks cell-cell fusion is measured by a decrease in the F-Luc activity, while the specificity of the inhibitor is evaluated by its effect on the R-Luc activity. The system exhibited a high dynamic range and high Z'-factor values. The assay was validated with a reference panel of inhibitors that target different steps in HIV-1 entry, yielding inhibitory concentrations comparable to published virus inhibition data. Our system is suitable for large-scale screening of chemical libraries and can also be used for detailed characterization of inhibitory and cytotoxic properties of known entry inhibitors.

Genetic draft and quasi-neutrality in large facultatively sexual populations

Large populations may contain numerous simultaneously segregating polymorphisms subject to natural selection. Since selection acts on individuals whose fitness depends on many loci, different loci affect each other's dynamics. This leads to stochastic fluctuations of allele frequencies above and beyond genetic drift-an effect known as genetic draft. Since recombination disrupts associations between alleles, draft is strong when recombination is rare. Here, we study a facultatively outcrossing population in a regime where the frequency of outcrossing and recombination, r, is small compared to the characteristic scale of fitness differences σ. In this regime, fit genotypes expand clonally, leading to large fluctuations in the number of recombinant offspring genotypes. The power law tail in the distribution of the latter makes it impossible to capture the dynamics of draft by an effective neutral model. Instead, we find that the fixation time of a neutral allele increases only slowly with the population size but depends sensitively on the ratio r/σ. The efficacy of selection is reduced dramatically and alleles behave "quasi-neutrally" even for Ns≫1, provided that |s| < s(c), where s(c) depends strongly on r/σ, but only weakly on population size N. In addition, the anomalous fluctuations due to draft change the spectrum of (quasi)-neutral alleles from f(ν) ∼ ν(-1), corresponding to drift, to ∼ ν(-2). Finally, draft accelerates the rate of two-step adaptations through deleterious intermediates.

Dynamical basis for drug resistance of HIV-1 protease

Background

Protease inhibitors designed to bind to protease have become major anti-AIDS drugs. Unfortunately, the emergence of viral mutations severely limits the long-term efficiency of the inhibitors. The resistance mechanism of these diversely located mutations remains unclear.

Results

Here I use an elastic network model to probe the connection between the global dynamics of HIV-1 protease and the structural distribution of drug-resistance mutations. The models for study are the crystal structures of unbounded and bound (with the substrate and nine FDA approved inhibitors) forms of HIV-1 protease. Coarse-grained modeling uncovers two groups that couple either with the active site or the flap. These two groups constitute a majority of the drug-resistance residues. In addition, the significance of residues is found to be correlated with their dynamical changes in binding and the results agree well with the complete mutagenesis experiment of HIV-1 protease.

Conclusions

The dynamic study of HIV-1 protease elucidates the functional importance of common drug-resistance mutations and suggests a unifying mechanism for drug-resistance residues based on their dynamical properties. The results support the robustness of the elastic network model as a potential predictive tool for drug resistance.

A systems analysis of mutational effects in HIV-1 protease and reverse transcriptase

The development of a quantitative understanding of viral evolution and the fitness landscape in HIV-1 drug resistance is a formidable challenge given the large number of available drugs and drug resistance mutations. We analyzed a dataset measuring the in vitro fitness of 70,081 virus samples isolated from HIV-1 subtype B infected individuals undergoing routine drug resistance testing. We assayed virus samples for in vitro replicative capacity in the absence of drugs as well as in the presence of 15 individual drugs. We employed a generalized kernel ridge regression to estimate main fitness effects and epistatic interactions of 1,859 single amino acid variants found within the HIV-1 protease and reverse transcriptase sequences. Models including epistatic interactions predict an average of 54.8% of the variance in replicative capacity across the 16 different environments and substantially outperform models based on main fitness effects only. We find that the fitness landscape of HIV-1 protease and reverse transcriptase is characterized by strong epistasis.

BioPhysConnectoR: Connecting sequence information and biophysical models

Background

One of the most challenging aspects of biomolecular systems is the understanding of the coevolution in and among the molecule(s).

A complete, theoretical picture of the selective advantage, and thus a functional annotation, of (co-)mutations is still lacking. Using sequence-based and information theoretical inspired methods we can identify coevolving residues in proteins without understanding the underlying biophysical properties giving rise to such coevolutionary dynamics. Detailed (atomistic) simulations are prohibitively expensive. At the same time reduced molecular models are an efficient way to determine the reduced dynamics around the native state. The combination of sequence based approaches with such reduced models is therefore a promising approach to annotate evolutionary sequence changes.

Results

With the R package BioPhysConnectoR we provide a framework to connect the information theoretical domain of biomolecular sequences to biophysical properties of the encoded molecules - derived from reduced molecular models. To this end we have integrated several fragmented ideas into one single package ready to be used in connection with additional statistical routines in R. Additionally, the package leverages the power of modern multi-core architectures to reduce turn-around times in evolutionary and biomolecular design studies. Our package is a first step to achieve the above mentioned annotation of coevolution by reduced dynamics around the native state of proteins.

Conclusions

BioPhysConnectoR is implemented as an R package and distributed under GPL 2 license. It allows for efficient and perfectly parallelized functional annotation of coevolution found at the sequence level.

Combinations of mutations in the connection domain of human immunodeficiency virus type 1 reverse transcriptase: assessing the impact on nucleoside and nonnucleoside reverse transcriptase inhibitor resistance

Recent reports have described the effect of mutations in the connection and RNase H domains of reverse transcriptase (RT) on nucleoside and nonnucleoside reverse transcriptase inhibitor (NRTI and NNRTI, respectively) resistance in the presence of thymidine analog resistance mutations (TAMs) and NNRTI mutations (J. H. Brehm, D. Koontz, J. D. Meteer, V. Pathak, N. Sluis-Cremer, and J. W. Mellors, J. Virol. 81:7852-7859, 2007; K. A. Delviks-Frankenberry, G. N. Nikolenko, R. Barr, and V. K. Pathak, J. Virol. 81:6837-6845, 2007; G. N. Nikolenko, K. A. Delviks-Frankenberry, S. Palmer, F. Maldarelli, M. J. Fivash, Jr., J. M. Coffin, and V. K. Pathak, Proc. Natl. Acad. Sci. U. S. A. 104:317-322, 2007; G. N. Nikolenko, S. Palmer, F. Maldarelli, J. W. Mellors, J. M. Coffin, and V. K. Pathak, Proc. Natl. Acad. Sci. U. S. A. 102:2093-2098, 2005; and S. H. Yap, C. W. Sheen, J. Fahey, M. Zanin, D. Tyssen, V. D. Lima, B. Wynhoven, M. Kuiper, N. Sluis-Cremer, P. R. Harrigan, and G. Tachedjian, PLoS Med. 4:e335, 2007). In the present study, novel mutations in the connection domain of RT (T369I/V), first identified in patient-derived viruses, were characterized, and their effects on NNRTI and NNRTI susceptibility were determined. Furthermore, the effect of N348I on NRTI and NNRTI resistance was confirmed. HIV-1 with either N348I or T369I/V demonstrated reduced susceptibility to nevirapine (NVP), efavirenz (EFV), delaviridine (DLV), and zidovudine (ZDV) compared to wild-type HIV-1. However, HIV-1 with T369I and N348I demonstrated 10- to 60-fold resistance to these same drugs. In clinical samples, these two connection domain RT mutations were predominantly observed in viruses containing TAMs and NNRTI mutations and did not alter the susceptible-resistant classifications of these samples. Introduction of T369I, N348I, or T369I/N348I also reduced replication capacity (RC). These observations suggest that it may be of scientific interest to test these mutations against new NNRTI candidates.

Recombination rate and selection strength in HIV intra-patient evolution

The evolutionary dynamics of HIV during the chronic phase of infection is driven by the host immune response and by selective pressures exerted through drug treatment. To understand and model the evolution of HIV quantitatively, the parameters governing genetic diversification and the strength of selection need to be known. While mutation rates can be measured in single replication cycles, the relevant effective recombination rate depends on the probability of coinfection of a cell with more than one virus and can only be inferred from population data. However, most population genetic estimators for recombination rates assume absence of selection and are hence of limited applicability to HIV, since positive and purifying selection are important in HIV evolution. Yet, little is known about the distribution of selection differentials between individual viruses and the impact of single polymorphisms on viral fitness. Here, we estimate the rate of recombination and the distribution of selection coefficients from time series sequence data tracking the evolution of HIV within single patients. By examining temporal changes in the genetic composition of the population, we estimate the effective recombination to be rho = 1.4+/-0.6 x 10(-5) recombinations per site and generation. Furthermore, we provide evidence that the selection coefficients of at least 15% of the observed non-synonymous polymorphisms exceed 0.8% per generation. These results provide a basis for a more detailed understanding of the evolution of HIV. A particularly interesting case is evolution in response to drug treatment, where recombination can facilitate the rapid acquisition of multiple resistance mutations. With the methods developed here, more precise and more detailed studies will be possible as soon as data with higher time resolution and greater sample sizes are available.

HIV-I reverse transcriptase variation in plasma and genital secretion of antiretroviral-naive females

The reverse transcriptase (RT) enzyme of HIV type 1 (HIV-1) is largely targeted by the host immune selection pressure and would differ in the anatomical compartments, thereby having a drastic impact on viral quasi-species evolution. The HIV-1 RT region sequenced from plasma and genital secretions of 8 antiretroviral treatment (ART)-naive females was analyzed for the pattern of amino acid mutations and the ratio of synonymous and nonsynonymous substitutions to determine whether it is under different selection pressure in both the compartments. Phylogenetic and mutational analysis of the HIV-1 RT in plasma and genital secretions of HIV-1-infected ART-naive females showed limited variation likely reflecting the absence of differential selection pressure and therefore genetic variation in these compartments.

Positive selection pressure introduces secondary mutations at Gag cleavage sites in human immunodeficiency virus type 1 harboring major protease resistance mutations

Human immunodeficiency virus type 1 (HIV-1) protease inhibitors (PIs) specifically target the HIV-1 protease enzyme. Mutations in the enzyme can result in PI resistance (termed PI mutations); however, mutations in the HIV-1 gag region, the substrate for the protease enzyme, might also lead to PI resistance. We analyzed gag and pol sequence data from the following 313 HIV-1-infected patients: 160 treatment-naïve patients, 93 patients failing antiretroviral treatment that included a PI (with no major PI mutations), and 60 patients failing antiretroviral treatment that included a PI (with major PI mutations). Additional sequences from 13 patients were included for longitudinal analysis. We assessed positive selection pressure on the gag/protease region using a test for the overall influence of positive selection and a total of five tests to identify positively selected single codons. We found that positive selection pressure was the driving evolutionary force for the gag region in all three patient groups. An increase in positive selection was observed in gag cleavage site regions p7/p1/p6 only after the acquisition of major PI mutations, suggesting that amino acids in gag cleavage sites under positive selection pressure could function as compensatory mutations for major PI mutations in the protease region. Isolated gag mutations did not appear to confer PI resistance, but mutations in the gag cleavage sites could substitute for minor PI resistance mutations in the protease region.

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.

Pervasive, genome-wide positive selection leading to functional divergence in the bacterial genus Campylobacter

An open question in bacterial genomics is the role that adaptive evolution of the core genome plays in diversification and adaptation of bacterial species, and how this might differ between groups of bacteria occupying different environmental circumstances. The genus Campylobacter encompasses several important human and animal enteric pathogens, with genome sequence data available for eight species. We estimate the Campylobacter core genome at 647 genes, with 92.5% of the nonrecombinant core genome loci under positive selection in at least one lineage and the same gene frequently under positive selection in multiple lineages. Tests are provided that reject recombination, saturation, and variation in codon usage bias as factors contributing to this high level of selection. We suggest this genome-wide adaptive evolution may result from a Red Queen macroevolutionary dynamic, in which species are involved in competition for resources within the mammalian and/or vertebrate gastrointestinal tract. Much reduced levels of positive selection evident in Streptococcus, as reported by the authors in an earlier work, may be a consequence of these taxa inhabiting less species-rich habitats, and more unique niches. Despite many common loci under positive selection in multiple Campylobacter lineages, we found no evidence for molecular adaptive convergence at the level of the same or adjacent codons, or even protein domains. Taken collectively, these results describe the diversification of a bacterial genus that involves pervasive natural selection pressure across virtually the entire genome, with this adaptation occurring in different ways in different lineages, despite the species tendency toward a common gastrointestinal habitat.