Correction: Within-patient mutation frequencies reveal fitness costs of CpG dinucleotides and drastic amino acid changes in HIV.

[This corrects the article DOI: 10.1371/journal.pgen.1007420.].

Within-patient mutation frequencies reveal fitness costs of CpG dinucleotides and drastic amino acid changes in HIV.

HIV has a high mutation rate, which contributes to its ability to evolve quickly. However, we know little about the fitness costs of individual HIV mutations in vivo, their distribution and the different factors shaping the viral fitness landscape. We calculated the mean frequency of transition mutations at 870 sites of the pol gene in 160 patients, allowing us to determine the cost of these mutations. As expected, we found high costs for non-synonymous and nonsense mutations as compared to synonymous mutations. In addition, we found that non-synonymous mutations that lead to drastic amino acid changes are twice as costly as those that do not and mutations that create new CpG dinucleotides are also twice as costly as those that do not. We also found that G→A and C→T mutations are more costly than A→G mutations. We anticipate that our new in vivo frequency-based approach will provide insights into the fitness landscape and evolvability of not only HIV, but a variety of microbes.

VIRULIGN: fast codon-correct alignment and annotation of viral genomes.

SUMMARY: Virus sequence data are an essential resource for reconstructing spatiotemporal dynamics of viral spread as well as to inform treatment and prevention strategies. However, the potential benefit of these applications critically depends on accurate and correctly annotated alignments of genetically heterogeneous data. VIRULIGN was built for fast codon-correct alignments of large datasets, with standardized and formalized genome annotation and various alignment export formats. AVAILABILITY AND IMPLEMENTATION: VIRULIGN is freely available at https://github.com/rega-cev/virulign as an open source software project. SUPPLEMENTARY INFORMATION: Supplementary data is available at Bioinformatics online.

An Evolutionary Model-Based Approach To Quantify the Genetic Barrier to Drug Resistance in Fast-Evolving Viruses and Its Application to HIV-1 Subtypes and Integrase Inhibitors.

Viral pathogens causing global disease burdens are often characterized by high rates of evolutionary changes. The extensive viral diversity at baseline can shorten the time to escape from therapeutic or immune selective pressure and alter mutational pathways. The impact of genotypic background on the barrier to resistance can be difficult to capture, particularly for agents in experimental stages or that are recently approved or expanded into new patient populations. We developed an evolutionary model-based counting method to quickly quantify the population genetic potential to resistance and assess population differences. We demonstrate its applicability to HIV-1 integrase inhibitors, as their increasing use globally contrasts with limited availability of non-B subtype resistant sequence data and corresponding knowledge gap. A large sequence data set encompassing most prevailing HIV-1 subtypes and resistance-associated mutations of currently approved integrase inhibitors was investigated. A complex interplay between codon predominance, polymorphisms, and associated evolutionary costs resulted in a subtype-dependent varied genetic potential for 15 resistance mutations against integrase inhibitors. While we confirm the lower genetic barrier of subtype B for G140S, we convincingly discard a similar effect previously suggested for G140C. A supplementary analysis for HIV-1 reverse transcriptase inhibitors identified a lower genetic barrier for K65R in subtype C through differential codon usage not reported before. To aid evolutionary interpretations of genomic differences for antiviral strategies, we advanced existing counting methods with increased sensitivity to identify subtype dependencies of resistance emergence. Future applications include novel HIV-1 drug classes or vaccines, as well as other viral pathogens.

PhyloGeoTool: interactively exploring large phylogenies in an epidemiological context.

MOTIVATION: Clinicians, health officials and researchers are interested in the epidemic spread of pathogens in both space and time to support the optimization of intervention measures and public health policies. Large sequence databases of virus sequences provide an interesting opportunity to study this spread through phylogenetic analysis. To infer knowledge from large phylogenetic trees, potentially encompassing tens of thousands of virus strains, an efficient method for data exploration is required. The clades that are visited during this exploration should be annotated with strain characteristics (e.g. transmission risk group, tropism, drug resistance profile) and their geographic context. RESULTS: PhyloGeoTool implements a visual method to explore large phylogenetic trees and to depict characteristics of strains and clades, including their geographic context, in an interactive way. PhyloGeoTool also provides the possibility to position new virus strains relative to the existing phylogenetic tree, allowing users to gain insight in the placement of such new strains without the need to perform a de novo reconstruction of the phylogeny. AVAILABILITY AND IMPLEMENTATION: https://github.com/rega-cev/phylogeotool (Freely available: open source software project). CONTACT: phylogeotool@kuleuven.be. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

An integrated map of HIV genome-wide variation from a population perspective.

BACKGROUND: The HIV pandemic is characterized by extensive genetic variability, which has challenged the development of HIV drugs and vaccines. Although HIV genomes have been classified into different types, groups, subtypes and recombinants, a comprehensive study that maps HIV genome-wide diversity at the population level is still lacking to date. This study aims to characterize HIV genomic diversity in large-scale sequence populations, and to identify driving factors that shape HIV genome diversity. RESULTS: A total of 2996 full-length genomic sequences from 1705 patients infected with 16 major HIV groups, subtypes and circulating recombinant forms (CRFs) were analyzed along with structural, immunological and peptide inhibitor information. Average nucleotide diversity of HIV genomes was almost 50% between HIV-1 and HIV-2 types, 37.5% between HIV-1 groups, 14.7% between HIV-1 subtypes, 8.2% within individual HIV-1 subtypes and less than 1% within single patients. Along the HIV genome, diversity patterns and compositions of nucleotides and amino acids were highly similar across different groups, subtypes and CRFs. Current HIV-derived peptide inhibitors were predominantly derived from conserved, solvent accessible and intrinsically ordered structures in the HIV-1 subtype B genome. We identified these conserved regions in Capsid, Nucleocapsid, Protease, Integrase, Reverse transcriptase, Vpr and the GP41 N terminus as potential drug targets. In the analysis of factors that impact HIV-1 genomic diversity, we focused on protein multimerization, immunological constraints and HIV-human protein interactions. We found that amino acid diversity in monomeric proteins was higher than in multimeric proteins, and diversified positions were preferably located within human CD4 T cell and antibody epitopes. Moreover, intrinsic disorder regions in HIV-1 proteins coincided with high levels of amino acid diversity, facilitating a large number of interactions between HIV-1 and human proteins. CONCLUSIONS: This first large-scale analysis provided a detailed mapping of HIV genomic diversity and highlighted drug-target regions conserved across different groups, subtypes and CRFs. Our findings suggest that, in addition to the impact of protein multimerization and immune selective pressure on HIV-1 diversity, HIV-human protein interactions are facilitated by high variability within intrinsically disordered structures.

HIV-1 Gag C-terminal amino acid substitutions emerging under selective pressure of protease inhibitors in patient populations infected with different HIV-1 subtypes.

HIV-1 Gag amino acid substitutions associated with protease inhibitor (PI) treatment have mainly been reported in subtype B, while information on other subtypes is scarce. Using sequences from 11613 patients infected with different HIV-1 subtypes, we evaluated the prevalence of 93 Gag amino acid substitutions and their association with genotypic PI resistance. A significant association was found for 13 Gag substitutions, including A431V in both subtype B and CRF01_AE. K415R in subtype C and S451G in subtype B were newly identified. Most PI-associated Gag substitutions are located in the flexible C-terminal domain, revealing the key role this region plays in PI resistance.

RegaDB: community-driven data management and analysis for infectious diseases.

SUMMARY: RegaDB is a free and open source data management and analysis environment for infectious diseases. RegaDB allows clinicians to store, manage and analyse patient data, including viral genetic sequences. Moreover, RegaDB provides researchers with a mechanism to collect data in a uniform format and offers them a canvas to make newly developed bioinformatics tools available to clinicians and virologists through a user friendly interface. AVAILABILITY AND IMPLEMENTATION: Source code, binaries and documentation are available on http://rega.kuleuven.be/cev/regadb. RegaDB is written in the Java programming language, using a web-service-oriented architecture.

Functional conservation of HIV-1 Gag: implications for rational drug design.

BACKGROUND: HIV-1 replication can be successfully blocked by targeting gag gene products, offering a promising strategy for new drug classes that complement current HIV-1 treatment options. However, naturally occurring polymorphisms at drug binding sites can severely compromise HIV-1 susceptibility to gag inhibitors in clinical and experimental studies. Therefore, a comprehensive understanding of gag natural diversity is needed. FINDINGS: We analyzed the degree of functional conservation in 10862 full-length gag sequences across 8 major HIV-1 subtypes and identified the impact of natural variation on known drug binding positions targeted by more than 20 gag inhibitors published to date. Complete conservation across all subtypes was detected in 147 (29%) out of 500 gag positions, with the highest level of conservation observed in capsid protein. Almost half (41%) of the 136 known drug binding positions were completely conserved, but all inhibitors were confronted with naturally occurring polymorphisms in their binding sites, some of which correlated with HIV-1 subtype. Integration of sequence and structural information revealed one drug binding pocket with minimal genetic variability, which is situated at the N-terminal domain of the capsid protein. CONCLUSIONS: This first large-scale analysis of full-length HIV-1 gag provided a detailed mapping of natural diversity across major subtypes and highlighted the considerable variation in current drug binding sites. Our results contribute to the optimization of gag inhibitors in rational drug design, given that drug binding sites should ideally be conserved across all HIV-1 subtypes.

HIV-1 subtype distribution and its demographic determinants in newly diagnosed patients in Europe suggest highly compartmentalized epidemics.

BACKGROUND: Understanding HIV-1 subtype distribution and epidemiology can assist preventive measures and clinical decisions. Sequence variation may affect antiviral drug resistance development, disease progression, evolutionary rates and transmission routes. RESULTS: We investigated the subtype distribution of HIV-1 in Europe and Israel in a representative sample of patients diagnosed between 2002 and 2005 and related it to the demographic data available. 2793 PRO-RT sequences were subtyped either with the REGA Subtyping tool or by a manual procedure that included phylogenetic tree and recombination analysis. The most prevalent subtypes/CRFs in our dataset were subtype B (66.1%), followed by sub-subtype A1 (6.9%), subtype C (6.8%) and CRF02_AG (4.7%). Substantial differences in the proportion of new diagnoses with distinct subtypes were found between European countries: the lowest proportion of subtype B was found in Israel (27.9%) and Portugal (39.2%), while the highest was observed in Poland (96.2%) and Slovenia (93.6%). Other subtypes were significantly more diagnosed in immigrant populations. Subtype B was significantly more diagnosed in men than in women and in MSM > IDUs > heterosexuals. Furthermore, the subtype distribution according to continent of origin of the patients suggests they acquired their infection there or in Europe from compatriots. CONCLUSIONS: The association of subtype with demographic parameters suggests highly compartmentalized epidemics, determined by social and behavioural characteristics of the patients.

The demise of multidrug-resistant HIV-1: the national time trend in Portugal.

OBJECTIVES: Despite a decreasing mortality and morbidity in treated HIV-1 patients, highly active antiretroviral treatment (HAART) can still fail due to the development of drug resistance. Especially, multidrug-resistant viruses pose a threat to efficient therapy. We studied the changing prevalence of multidrug resistance (MDR) over time in a cohort of HIV-1-infected patients in Portugal. PATIENTS AND METHODS: We used data of 8065 HIV-1-infected patients followed from July 2001 up to April 2012 in 22 hospitals located in Portugal. MDR at a specific date of sampling was defined as no more than one fully active drug (excluding integrase and entry inhibitors) at that time authorized by the Portuguese National Authority of Medicines and Health Products (INFARMED), as interpreted with the Rega algorithm version 8.0.2. A generalized linear mixed model was used to study the time trend of the prevalence of MDR. RESULTS: We observed a statistically significant decrease in the prevalence of MDR over the last decade, from 6.9% (95% CI: 5.7-8.4) in 2001-03, 6.0% (95% CI: 4.9-7.2) in 2003-05, 3.7% (95% CI: 2.8-4.8) in 2005-07 and 1.6% (95% CI: 1.1-2.2) in 2007-09 down to 0.6% (95% CI: 0.3-0.9) in 2009-12 [OR=0.80 (95% CI: 0.75-0.86); P<0.001]. In July 2011 the last new case of MDR was seen. CONCLUSIONS: The prevalence of multidrug-resistant HIV-1 is decreasing over time in Portugal, reflecting the increasing efficiency of HAART and the availability of new drugs. Therefore, in designing a new drug, safety and practical aspects, e.g. less toxicity and ease of use, may need more attention than focusing mainly on efficacy against resistant strains.

Structural modifications induced by specific HIV-1 protease-compensatory mutations have an impact on the virological response to a first-line lopinavir/ritonavir-containing regimen.

OBJECTIVES: This study evaluates the impact of specific HIV-1 protease-compensatory mutations (wild-type amino acids in non-B subtypes) on virological response to a first-line lopinavir/ritonavir-containing regimen in an HIV-1 subtype B-infected population. PATIENTS AND METHODS: The prevalence of protease-compensatory mutations from 1997 to 2011 was calculated in 3063 drug-naive HIV-1 B-infected patients. The role of these mutations on virological outcome is estimated in a subgroup of 201 patients starting their first lopinavir/ritonavir-containing regimen by covariation and docking analyses. RESULTS: The number of HIV-1 B-infected patients with at least one protease-compensatory mutation increased over time (from 86.4% prior to 2001 to 92.6% after 2009, P = 0.02). Analysing 201 patients starting first-line lopinavir/ritonavir, the median time to virological failure was shorter in patients with at least one protease-compensatory mutation than in patients with no protease-compensatory mutations. By covariation and docking analyses, specific mutations were found to affect lopinavir affinity for HIV-1 protease and to impact virological failure. Specifically, the L10V + I13V + L63P + I93L cluster, related to fast virological failure, correlated with a decreased drug affinity for the enzyme in comparison with wild-type (ΔGmut = -30.0 kcal/mol versus ΔGwt = -42.3 kcal/mol). CONCLUSIONS: Our study shows an increased prevalence of specific protease-compensatory mutations in an HIV-1 B-infected population and confirms that their copresence can affect the virological outcome in patients starting a lopinavir/ritonavir-containing regimen.

Analyses of Early ZIKV Genomes Are Consistent with Viral Spread from Northeast Brazil to the Americas.

The Americas, particularly Brazil, were greatly impacted by the widespread Zika virus (ZIKV) outbreak in 2015 and 2016. Efforts were made to implement genomic surveillance of ZIKV as part of the public health responses. The accuracy of spatiotemporal reconstructions of the epidemic spread relies on the unbiased sampling of the transmission process. In the early stages of the outbreak, we recruited patients exhibiting clinical symptoms of arbovirus-like infection from Salvador and Campo Formoso, Bahia, in Northeast Brazil. Between May 2015 and June 2016, we identified 21 cases of acute ZIKV infection and subsequently recovered 14 near full-length sequences using the amplicon tiling multiplex approach with nanopore sequencing. We performed a time-calibrated discrete phylogeographic analysis to trace the spread and migration history of the ZIKV. Our phylogenetic analysis supports a consistent relationship between ZIKV migration from Northeast to Southeast Brazil and its subsequent dissemination beyond Brazil. Additionally, our analysis provides insights into the migration of ZIKV from Brazil to Haiti and the role Brazil played in the spread of ZIKV to other countries, such as Singapore, the USA, and the Dominican Republic. The data generated by this study enhances our understanding of ZIKV dynamics and supports the existing knowledge, which can aid in future surveillance efforts against the virus.

Treatment-associated polymorphisms in protease are significantly associated with higher viral load and lower CD4 count in newly diagnosed drug-naive HIV-1 infected patients.

BACKGROUND: The effect of drug resistance transmission on disease progression in the newly infected patient is not well understood. Major drug resistance mutations severely impair viral fitness in a drug free environment, and therefore are expected to revert quickly. Compensatory mutations, often already polymorphic in wild-type viruses, do not tend to revert after transmission. While compensatory mutations increase fitness during treatment, their presence may also modulate viral fitness and virulence in absence of therapy and major resistance mutations. We previously designed a modeling technique that quantifies genotypic footprints of in vivo treatment selective pressure, including both drug resistance mutations and polymorphic compensatory mutations, through the quantitative description of a fitness landscape from virus genetic sequences. RESULTS: Genotypic correlates of viral load and CD4 cell count were evaluated in subtype B sequences from recently diagnosed treatment-naive patients enrolled in the SPREAD programme. The association of surveillance drug resistance mutations, reported compensatory mutations and fitness estimated from drug selective pressure fitness landscapes with baseline viral load and CD4 cell count was evaluated using regression techniques. Protease genotypic variability estimated to increase fitness during treatment was associated with higher viral load and lower CD4 cell counts also in treatment-naive patients, which could primarily be attributed to well-known compensatory mutations at highly polymorphic positions. By contrast, treatment-related mutations in reverse transcriptase could not explain viral load or CD4 cell count variability. CONCLUSIONS: These results suggest that polymorphic compensatory mutations in protease, reported to be selected during treatment, may improve the replicative capacity of HIV-1 even in absence of drug selective pressure or major resistance mutations. The presence of this polymorphic variation may either reflect a history of drug selective pressure, i.e. transmission from a treated patient, or merely be a result of diversity in wild-type virus. Our findings suggest that transmitted drug resistance has the potential to contribute to faster disease progression in the newly infected host and to shape the HIV-1 epidemic at a population level.

Genome-wide diversity of Zika virus: Exploring spatio-temporal dynamics to guide a new nomenclature proposal.

The Zika virus (ZIKV) disease caused a public health emergency of international concern that started in February 2016. The overall number of ZIKV-related cases increased until November 2016, after which it declined sharply. While the evaluation of the potential risk and impact of future arbovirus epidemics remains challenging, intensified surveillance efforts along with a scale-up of ZIKV whole-genome sequencing provide an opportunity to understand the patterns of genetic diversity, evolution, and spread of ZIKV. However, a classification system that reflects the true extent of ZIKV genetic variation is lacking. Our objective was to characterize ZIKV genetic diversity and phylodynamics, identify genomic footprints of differentiation patterns, and propose a dynamic classification system that reflects its divergence levels. We analysed a curated dataset of 762 publicly available sequences spanning the full-length coding region of ZIKV from across its geographical span and collected between 1947 and 2021. The definition of genetic groups was based on comprehensive evolutionary dynamics analyses, which included recombination and phylogenetic analyses, within- and between-group pairwise genetic distances comparison, detection of selective pressure, and clustering analyses. Evidence for potential recombination events was detected in a few sequences. However, we argue that these events are likely due to sequencing errors as proposed in previous studies. There was evidence of strong purifying selection, widespread across the genome, as also detected for other arboviruses. A total of 50 sites showed evidence of positive selection, and for a few of these sites, there was amino acid (AA) differentiation between genetic clusters. Two main genetic clusters were defined, ZA and ZB, which correspond to the already characterized 'African' and 'Asian' genotypes, respectively. Within ZB, two subgroups, ZB.1 and ZB.2, represent the Asiatic and the American (and Oceania) lineages, respectively. ZB.1 is further subdivided into ZB.1.0 (a basal Malaysia sequence sampled in the 1960s and a recent Indian sequence), ZB.1.1 (South-Eastern Asia, Southern Asia, and Micronesia sequences), and ZB.1.2 (very similar sequences from the outbreak in Singapore). ZB.2 is subdivided into ZB.2.0 (basal American sequences and the sequences from French Polynesia, the putative origin of South America introduction), ZB.2.1 (Central America), and ZB.2.2 (Caribbean and North America). This classification system does not use geographical references and is flexible to accommodate potential future lineages. It will be a helpful tool for studies that involve analyses of ZIKV genomic variation and its association with pathogenicity and serve as a starting point for the public health surveillance and response to on-going and future epidemics and to outbreaks that lead to the emergence of new variants.

Estimating the individualized HIV-1 genetic barrier to resistance using a nelfinavir fitness landscape.

BACKGROUND: Failure on Highly Active Anti-Retroviral Treatment is often accompanied with development of antiviral resistance to one or more drugs included in the treatment. In general, the virus is more likely to develop resistance to drugs with a lower genetic barrier. Previously, we developed a method to reverse engineer, from clinical sequence data, a fitness landscape experienced by HIV-1 under nelfinavir (NFV) treatment. By simulation of evolution over this landscape, the individualized genetic barrier to NFV resistance may be estimated for an isolate. RESULTS: We investigated the association of estimated genetic barrier with risk of development of NFV resistance at virological failure, in 201 patients that were predicted fully susceptible to NFV at baseline, and found that a higher estimated genetic barrier was indeed associated with lower odds for development of resistance at failure (OR 0.62 (0.45 - 0.94), per additional mutation needed, p = .02). CONCLUSIONS: Thus, variation in individualized genetic barrier to NFV resistance may impact effective treatment options available after treatment failure. If similar results apply for other drugs, then estimated genetic barrier may be a new clinical tool for choice of treatment regimen, which allows consideration of available treatment options after virological failure.

Increasing Prevalence of HIV-1 Transmitted Drug Resistance in Portugal: Implications for First Line Treatment Recommendations.

INTRODUCTION: Treatment for All recommendations have allowed access to antiretroviral (ARV) treatment for an increasing number of patients. This minimizes the transmission of infection but can potentiate the risk of transmitted (TDR) and acquired drug resistance (ADR). OBJECTIVE: To study the trends of TDR and ADR in patients followed up in Portuguese hospitals between 2001 and 2017. METHODS: In total, 11,911 patients of the Portuguese REGA database were included. TDR was defined as the presence of one or more surveillance drug resistance mutation according to the WHO surveillance list. Genotypic resistance to ARV was evaluated with Stanford HIVdb v7.0. Patterns of TDR, ADR and the prevalence of mutations over time were analyzed using logistic regression. RESULTS AND DISCUSSION: The prevalence of TDR increased from 7.9% in 2003 to 13.1% in 2017 (p < 0.001). This was due to a significant increase in both resistance to nucleotide reverse transcriptase inhibitors (NRTIs) and non-nucleotide reverse transcriptase inhibitors (NNRTIs), from 5.6% to 6.7% (p = 0.002) and 2.9% to 8.9% (p < 0.001), respectively. TDR was associated with infection with subtype B, and with lower viral load levels (p < 0.05). The prevalence of ADR declined from 86.6% in 2001 to 51.0% in 2017 (p < 0.001), caused by decreasing drug resistance to all antiretroviral (ARV) classes (p < 0.001). CONCLUSIONS: While ADR has been decreasing since 2001, TDR has been increasing, reaching a value of 13.1% by the end of 2017. It is urgently necessary to develop public health programs to monitor the levels and patterns of TDR in newly diagnosed patients.

A collaborative environment allowing clinical investigations on integrated biomedical databases.

In order to perform clinical investigations on integrated biomedical data sets and to predict virological and epidemiological outcome, medical experts require an IT-based collaborative environment that provides them a user-friendly space for building and executing their complex studies and workflows on largely available and high-quality data repositories. In this paper, the authors introduce such a novel collaborative working environment a so-called virtual laboratory for clinicians and medical researchers, which allows users to interactively access and browse several biomedical research databases and re-use relevant data sets within own designed experiments. Firstly, technical details on the integration of relevant data resources into the virtual laboratory infrastructure and specifically developed user interfaces are briefly explained. The second part describes research possibilities for medical scientists including potential application fields and benefits as using the virtual laboratory functionalities for a particular exemplary study.

Advances in Visualization Tools for Phylogenomic and Phylodynamic Studies of Viral Diseases.

Genomic and epidemiological monitoring have become an integral part of our response to emerging and ongoing epidemics of viral infectious diseases. Advances in high-throughput sequencing, including portable genomic sequencing at reduced costs and turnaround time, are paralleled by continuing developments in methodology to infer evolutionary histories (dynamics/patterns) and to identify factors driving viral spread in space and time. The traditionally static nature of visualizing phylogenetic trees that represent these evolutionary relationships/processes has also evolved, albeit perhaps at a slower rate. Advanced visualization tools with increased resolution assist in drawing conclusions from phylogenetic estimates and may even have potential to better inform public health and treatment decisions, but the design (and choice of what analyses are shown) is hindered by the complexity of information embedded within current phylogenetic models and the integration of available meta-data. In this review, we discuss visualization challenges for the interpretation and exploration of reconstructed histories of viral epidemics that arose from increasing volumes of sequence data and the wealth of additional data layers that can be integrated. We focus on solutions that address joint temporal and spatial visualization but also consider what the future may bring in terms of visualization and how this may become of value for the coming era of real-time digital pathogen surveillance, where actionable results and adequate intervention strategies need to be obtained within days.