Assessment of automated genotyping protocols as tools for surveillance of HIV-1 genetic diversity

Pervasive and non-random recombination in near full-length HIV genomes from Uganda

Recombination is an important feature of HIV evolution, occurring both within and between the major branches of diversity (subtypes). The Ugandan epidemic is primarily composed of two subtypes, A1 and D, that have been co-circulating for 50 years, frequently recombining in dually infected patients. Here, we investigate the frequency of recombinants in this population and the location of breakpoints along the genome. As part of the PANGEA-HIV consortium, 1,472 consensus genome sequences over 5 kb have been obtained from 1,857 samples collected by the MRC/UVRI & LSHTM Research unit in Uganda, 465 (31.6 per cent) of which were near full-length sequences (>8 kb). Using the subtyping tool SCUEAL, we find that of the near full-length dataset, 233 (50.1 per cent) genomes contained only one subtype, 30.8 per cent A1 (n = 143), 17.6 per cent D (n = 82), and 1.7 per cent C (n = 8), while 49.9 per cent (n = 232) contained more than one subtype (including A1/D (n = 164), A1/C (n = 13), C/D (n = 9); A1/C/D (n = 13), and 33 complex types). K-means clustering of the recombinant A1/D genomes revealed a section of envelope (C2gp120-TMgp41) is often inherited intact, whilst a generalized linear model was used to demonstrate significantly fewer breakpoints in the gag-pol and envelope C2-TM regions compared with accessory gene regions. Despite similar recombination patterns in many recombinants, no clearly supported circulating recombinant form (CRF) was found, there was limited evidence of the transmission of breakpoints, and the vast majority (153/164; 93 per cent) of the A1/D recombinants appear to be unique recombinant forms. Thus, recombination is pervasive with clear biases in breakpoint location, but CRFs are not a significant feature, characteristic of a complex, and diverse epidemic.

SNAPPy: A snakemake pipeline for scalable HIV-1 subtyping by phylogenetic pairing

Human immunodeficiency virus 1 (HIV-1) genome sequencing is routinely done for drug resistance monitoring in hospitals worldwide. Subtyping these extensive datasets of HIV-1 sequences is a critical first step in molecular epidemiology and evolution studies. The clinical relevance of HIV-1 subtypes is increasingly recognized. Several studies suggest subtype-related differences in disease progression, transmission route efficiency, immune evasion, and even therapeutic outcomes. HIV-1 subtyping is mainly done using web-servers. These tools have limitations in scalability and potential noncompliance with data protection legislation. Thus, the aim of this work was to develop an efficient method for large-scale local HIV-1 subtyping. We designed SNAPPy: a snakemake pipeline for scalable HIV-1 subtyping by phylogenetic pairing. It contains several tasks of phylogenetic inference and BLAST queries, which can be executed sequentially or in parallel, taking advantage of multiple-core processing units. Although it was built for subtyping, SNAPPy is also useful to perform extensive HIV-1 alignments. This tool facilitates large-scale sequence-based HIV-1 research by providing a local, resource efficient and scalable alternative for HIV-1 subtyping. It is capable of analyzing full-length genomes or partial HIV-1 genomic regions (GAG, POL, and ENV) and recognizes more than ninety circulating recombinant forms. SNAPPy is freely available at: https://github.com/PMMAraujo/snappy/releases.

Comparative Evaluation of Subtyping Tools for Surveillance of Newly Emerging HIV-1 Strains

HIV-1 non-B subtypes/circulating recombinant forms (CRFs) are increasing worldwide. Since subtype identification can be clinically relevant, we assessed the added value in HIV-1 subtyping using updated molecular phylogeny (Mphy) and the performance of routinely used automated tools. Updated Mphy (2015 updated reference sequences), used as a gold standard, was performed to subtype 13,116 HIV-1 protease/reverse transcriptase sequences and then compared with previous Mphy (reference sequences until 2014) and with COMET, REGA, SCUEAL, and Stanford subtyping tools. Updated Mphy classified subtype B as the most prevalent (73.4%), followed by CRF02_AG (7.9%), C (4.6%), F1 (3.4%), A1 (2.2%), G (1.6%), CRF12_BF (1.2%), and other subtypes (5.7%). A 2.3% proportion of sequences were reassigned as different subtypes or CRFs because of misclassification by previous Mphy. Overall, the tool most concordant with updated Mphy was Stanford-v8.1 (95.4%), followed by COMET (93.8%), REGA-v3 (92.5%), Stanford-old (91.1%), and SCUEAL (85.9%). All the tools had a high sensitivity (≥98.0%) and specificity (≥95.7%) for subtype B. Regarding non-B subtypes, Stanford-v8.1 was the best tool for C, D, and F subtypes and for CRFs 01, 02, 06, 11, and 36 (sensitivity, ≥92.6%; specificity, ≥99.1%). A1 and G subtypes were better classified by COMET (92.3%) and REGA-v3 (98.6%), respectively. Our findings confirm Mphy as the gold standard for accurate HIV-1 subtyping, although Stanford-v8.1, occasionally combined with COMET or REGA-v3, represents an effective subtyping approach in clinical settings. Periodic updating of HIV-1 reference sequences is fundamental to improving subtype characterization in the context of an effective epidemiological surveillance of non-B strains.

HIV diversity and drug resistance from plasma and non-plasma analytes in a large treatment programme in western Kenya

INTRODUCTION

Antiretroviral resistance leads to treatment failure and resistance transmission. Resistance data in western Kenya are limited. Collection of non-plasma analytes may provide additional resistance information.

METHODS

We assessed HIV diversity using the REGA tool, transmitted resistance by the WHO mutation list and acquired resistance upon first-line failure by the IAS-USA mutation list, at the Academic Model Providing Access to Healthcare (AMPATH), a major treatment programme in western Kenya. Plasma and four non-plasma analytes, dried blood-spots (DBS), dried plasma-spots (DPS), ViveST(TM)-plasma (STP) and ViveST-blood (STB), were compared to identify diversity and evaluate sequence concordance.

RESULTS

Among 122 patients, 62 were treatment-naïve and 60 treatment-experienced; 61% were female, median age 35 years, median CD4 182 cells/µL, median viral-load 4.6 log10 copies/mL. One hundred and ninety-six sequences were available for 107/122 (88%) patients, 58/62 (94%) treatment-naïve and 49/60 (82%) treated; 100/122 (82%) plasma, 37/78 (47%) attempted DBS, 16/45 (36%) attempted DPS, 14/44 (32%) attempted STP from fresh plasma and 23/34 (68%) from frozen plasma, and 5/42 (12%) attempted STB. Plasma and DBS genotyping success increased at higher VL and shorter shipment-to-genotyping time. Main subtypes were A (62%), D (15%) and C (6%). Transmitted resistance was found in 1.8% of plasma sequences, and 7% combining analytes. Plasma resistance mutations were identified in 91% of treated patients, 76% NRTI, 91% NNRTI; 76% dual-class; 60% with intermediate-high predicted resistance to future treatment options; with novel mutation co-occurrence patterns. Nearly 88% of plasma mutations were identified in DBS, 89% in DPS and 94% in STP. Of 23 discordant mutations, 92% in plasma and 60% in non-plasma analytes were mixtures. Mean whole-sequence discordance from frozen plasma reference was 1.1% for plasma-DBS, 1.2% plasma-DPS, 2.0% plasma-STP and 2.3% plasma-STB. Of 23 plasma-STP discordances, one mutation was identified in plasma and 22 in STP (p<0.05). Discordance was inversely significantly related to VL for DBS.

CONCLUSIONS

In a large treatment programme in western Kenya, we report high HIV-1 subtype diversity; low plasma transmitted resistance, increasing when multiple analytes were combined; and high-acquired resistance with unique mutation patterns. Resistance surveillance may be augmented by using non-plasma analytes for lower-cost genotyping in resource-limited settings.

COMET: adaptive context-based modeling for ultrafast HIV-1 subtype identification

Viral sequence classification has wide applications in clinical, epidemiological, structural and functional categorization studies. Most existing approaches rely on an initial alignment step followed by classification based on phylogenetic or statistical algorithms. Here we present an ultrafast alignment-free subtyping tool for human immunodeficiency virus type one (HIV-1) adapted from Prediction by Partial Matching compression. This tool, named COMET, was compared to the widely used phylogeny-based REGA and SCUEAL tools using synthetic and clinical HIV data sets (1,090,698 and 10,625 sequences, respectively). COMET's sensitivity and specificity were comparable to or higher than the two other subtyping tools on both data sets for known subtypes. COMET also excelled in detecting and identifying new recombinant forms, a frequent feature of the HIV epidemic. Runtime comparisons showed that COMET was almost as fast as USEARCH. This study demonstrates the advantages of alignment-free classification of viral sequences, which feature high rates of variation, recombination and insertions/deletions. COMET is free to use via an online interface.

Phylogenetic and geospatial evaluation of HIV-1 subtype diversity at the largest HIV center in Rhode Island

Individuals infected with HIV-1 non-B subtypes are understudied in the United States. Their characterization may augment prevention and treatment interventions. We examined the regional molecular epidemiology of non-B subtypes using a combined phylogenetic and geospatial approach. HIV-1 pol sequences and clinical data obtained for routine clinical care were aggregated from 2004 to 2011 at the largest HIV center in Rhode Island. Subtyping was performed by neighbor-joining and maximum-likelihood phylogeny and compared across eight commonly used tools (HIVdb, REGA, RIP, NCBI, Geno2Pheno, EuResist, jpHMM and STAR) using proportional odds ordinal regression. Individuals with non-B subtypes were characterized according to demographics and risk factors for infection, intra-subtype clustering by maximum-likelihood phylogeny, and geospatial hotspot analysis using Getis-Ord Gi(∗) statistics. Of 1277 unique sequences, phylogenetic subtyping demonstrated 8.3% (N=106, 95% CI 6.8-10%) non-B subtypes and circulating recombinant forms (CRFs): CRF02_AG=46; A=15; C=15; CRF01_AE=6; CRF06_CPX=5; CRF14_BG=5; G=3; CRF43_02G=3; D=3; CRF24_BG=3; CRF11_CPX=1; F1=1. Compared to phylogeny, Geno2Pheno was the most concordant (86% exact match) followed by REGA (85%), EuResist (85%) and STAR (82%). Of 106 individuals with non-B subtypes, 50% were male, 71% acquired infection through heterosexual transmission; 76%, were born in Africa, 6% Southeast Asia, 5% the United States, 3% Central America, 1% Europe, and 9% unknown. Eighty percent of CRF02_AG, 93% of A and 87% of C sequences were from African-born individuals. Twenty-two percent of non-B subtypes formed transmission clusters, including a significant number of younger individuals with perinatally-acquired infection. Geospatial analyses revealed hotspots of B and non-B subtypes in the state capital with a more concentrated focus among non-B subtypes. Molecular examination of regional HIV diversity revealed a larger than expected non-subtype B infected population, mostly born in Africa, with low ongoing regional transmission. Phylogenetic and geospatial characterization of infection clusters is helpful to identify targets for treatment and prevention interventions.

The increasing genetic diversity of HIV-1 in the UK, 2002-2010

Objective:

HIV-1 is typically categorized by genetically distinct viral subtypes. Viral subtypes are usually compartmentalized by ethnicity and transmission group and, thus, convey important epidemiological information, as well as possibly influencing the rate of disease progression. We aim to describe the prevalence and time trends of subtypes observed among key populations living with HIV-1 in the UK.

Design:

Analyses of reverse transcriptase and protease sequences generated from HIV-1-positive antiretroviral-naive patients as part of routine resistance testing between 2002 and 2010 in all public health and NHS laboratories in the UK.

Methods:

Subtype was assigned centrally using the SCUEAL algorithm. Subtyping results were combined with data from the UK Collaborative HIV Cohort Study and the UK HIV and AIDS Reporting System. Analyses adjusted for the number of national HIV-1 diagnoses made each year within demographic subgroups. Viral subtypes were described overall, over time and by demographic subgroup.

Results:

Subtype B diagnoses (39.9%) have remained stable since 2005, whereas subtype C diagnoses (34.3%) were found to decline in prevalence from 2004. Across most demographic subgroups, the prevalence of non-B non-C subtypes has increased over time, in particular novel recombinant forms (9.9%), subtype G (2.7%), and CRF01 AE (2.0%).

Conclusion:

HIV-1 subtypes are increasingly represented across all demographic subgroups and this could be evidence of sexual mixing. Between 2002 and 2010, the prevalence of novel recombinant forms has increased in all demographic subgroups. This increasing genetic diversity and the effect of subtype on disease progression may impact future HIV-1 treatment and prevention.

Automated subtyping of HIV-1 genetic sequences for clinical and surveillance purposes: performance evaluation of the new REGA version 3 and seven other tools

BACKGROUND

To investigate differences in pathogenesis, diagnosis and resistance pathways between HIV-1 subtypes, an accurate subtyping tool for large datasets is needed. We aimed to evaluate the performance of automated subtyping tools to classify the different subtypes and circulating recombinant forms using pol, the most sequenced region in clinical practice. We also present the upgraded version 3 of the Rega HIV subtyping tool (REGAv3).

METHODOLOGY

HIV-1 pol sequences (PR+RT) for 4674 patients retrieved from the Portuguese HIV Drug Resistance Database, and 1872 pol sequences trimmed from full-length genomes retrieved from the Los Alamos database were classified with statistical-based tools such as COMET, jpHMM and STAR; similarity-based tools such as NCBI and Stanford; and phylogenetic-based tools such as REGA version 2 (REGAv2), REGAv3, and SCUEAL. The performance of these tools, for pol, and for PR and RT separately, was compared in terms of reproducibility, sensitivity and specificity with respect to the gold standard which was manual phylogenetic analysis of the pol region.

RESULTS

The sensitivity and specificity for subtypes B and C was more than 96% for seven tools, but was variable for other subtypes such as A, D, F and G. With regard to the most common circulating recombinant forms (CRFs), the sensitivity and specificity for CRF01_AE was ~99% with statistical-based tools, with phylogenetic-based tools and with Stanford, one of the similarity based tools. CRF02_AG was correctly identified for more than 96% by COMET, REGAv3, Stanford and STAR. All the tools reached a specificity of more than 97% for most of the subtypes and the two main CRFs (CRF01_AE and CRF02_AG). Other CRFs were identified only by COMET, REGAv2, REGAv3, and SCUEAL and with variable sensitivity. When analyzing sequences for PR and RT separately, the performance for PR was generally lower and variable between the tools. Similarity and statistical-based tools were 100% reproducible, but this was lower for phylogenetic-based tools such as REGA (~99%) and SCUEAL (~96%).

CONCLUSIONS

REGAv3 had an improved performance for subtype B and CRF02_AG compared to REGAv2 and is now able to also identify all epidemiologically relevant CRFs. In general the best performing tools, in alphabetical order, were COMET, jpHMM, REGAv3, and SCUEAL when analyzing pure subtypes in the pol region, and COMET and REGAv3 when analyzing most of the CRFs. Based on this study, we recommend to confirm subtyping with 2 well performing tools, and be cautious with the interpretation of short sequences.

Genetic diversity and primary resistance among HIV-1-positive patients from Maringá, Paraná, Brazil

The objective of this study is to identify subtypes of Human Immunodeficiency Virus type 1 (HIV-1) and to analyze the presence of mutations associated to antiretroviral resistance in the protease (PR) and reverse transcriptase (RT) regions from 48 HIV-1 positive treatment naïve patients from an outpatient clinic in Maringá, Paraná, Brazil. Sequencing was conducted using PR, partial RT and group-specific antigen gene (gag) nested PCR products from retrotranscribed RNA. Transmitted resistance was determined according to the Surveillance Drug Resistance Mutation List (SDRM) algorithm. Phylogenetic and SimPlot analysis of concatenated genetic segments classified sequences as subtype B 19/48 (39.6%), subtype C 12/48 (25%), subtype F 4/48 (8.3%), with 13/48 (27.1%) recombinant forms. Most recombinant forms were B mosaics (B/F 12.5%, B/C 10.4%), with one C/F (2.1%) and one complex B/C/F mosaic (2.1%). Low levels of transmitted resistance were found in this study, 2/48 (2.1% to NRTIs and 2.1% for PI). This preliminary data may subsidize the monitoring of the HIV evolution in the region.

The Impact of HIV Genetic Polymorphisms and Subtype Differences on the Occurrence of Resistance to Antiretroviral Drugs

The vast majority of reports on drug resistance deal with subtype B infections in developed countries, and this is largely due to historical delays in access to antiretroviral therapy (ART) on a worldwide basis. This notwithstanding the concept that naturally occurring polymorphisms among different non-B subtypes can affect HIV-1 susceptibility to antiretroviral drugs (ARVs) is supported by both enzymatic and virological data. These findings suggest that such polymorphisms can affect both the magnitude of resistance conferred by some major mutations as well as the propensity to acquire certain resistance mutations, even though such differences are sometimes difficult to demonstrate in phenotypic assays. It is mandatory that tools are optimized to assure accurate measurements of drug susceptibility in non-B subtypes and to recognize that each subtype may have a distinct resistance profile and that differences in resistance pathways may also impact on cross-resistance and the choice of regimens to be used in second-line therapy. Although responsiveness to first-line therapy should not theoretically be affected by considerations of viral subtype and drug resistance, well-designed long-term longitudinal studies involving patients infected by viruses of different subtypes should be carried out.

Role of HIV Subtype Diversity in the Development of Resistance to Antiviral Drugs

Despite the fact that over 90% of HIV-1 infected people worldwide harbor non-subtype B variants of HIV-1, knowledge of resistance mutations in non-B HIV-1 and their clinical relevance is limited. Due to historical delays in access to antiretroviral therapy (ART) on a worldwide basis, the vast majority of reports on drug resistance deal with subtype B infections in developed countries. However, both enzymatic and virological data support the concept that naturally occurring polymorphisms among different nonB subtypes can affect HIV-1 susceptibility to antiretroviral drugs (ARVs), the magnitude of resistance conferred by major mutations, and the propensity to acquire some resistance mutations. Tools need to be optimized to assure accurate measurements of drug susceptibility of non-B subtypes. Furthermore, there is a need to recognize that each subtype may have a distinct resistance profile and that differences in resistance pathways may also impact on cross-resistance and the selection of second-line regimens. It will be essential to pay attention to newer drug combinations in well designed long-term longitudinal studies involving patients infected by viruses of different subtypes.

A classification approach for genotyping viral sequences based on multidimensional scaling and linear discriminant analysis

BACKGROUND

Accurate classification into genotypes is critical in understanding evolution of divergent viruses. Here we report a new approach, MuLDAS, which classifies a query sequence based on the statistical genotype models learned from the known sequences. Thus, MuLDAS utilizes full spectra of well characterized sequences as references, typically of an order of hundreds, in order to estimate the significance of each genotype assignment.

RESULTS

MuLDAS starts by aligning the query sequence to the reference multiple sequence alignment and calculating the subsequent distance matrix among the sequences. They are then mapped to a principal coordinate space by multidimensional scaling, and the coordinates of the reference sequences are used as features in developing linear discriminant models that partition the space by genotype. The genotype of the query is then given as the maximum a posteriori estimate. MuLDAS tests the model confidence by leave-one-out cross-validation and also provides some heuristics for the detection of 'outlier' sequences that fall far outside or in-between genotype clusters. We have tested our method by classifying HIV-1 and HCV nucleotide sequences downloaded from NCBI GenBank, achieving the overall concordance rates of 99.3% and 96.6%, respectively, with the benchmark test dataset retrieved from the respective databases of Los Alamos National Laboratory.

CONCLUSIONS

The highly accurate genotype assignment coupled with several measures for evaluating the results makes MuLDAS useful in analyzing the sequences of rapidly evolving viruses such as HIV-1 and HCV. A web-based genotype prediction server is available at http://www.muldas.org/MuLDAS/.

The HIV-1 subtype C epidemic in South America is linked to the United Kingdom

Background

The global spread of HIV-1 has been accompanied by the emergence of genetically distinct viral strains. Over the past two decades subtype C viruses, which predominate in Southern and Eastern Africa, have spread rapidly throughout parts of South America. Phylogenetic studies indicate that subtype C viruses were introduced to South America through a single founder event that occurred in Southern Brazil. However, the external route via which subtype C viruses spread to the South American continent has remained unclear.

Methodology/Principal Findings

We used automated genotyping to screen 8,309 HIV-1 subtype C pol gene sequences sampled within the UK for isolates genetically linked to the subtype C epidemic in South America. Maximum likelihood and Bayesian approaches were used to explore the phylogenetic relationships between 54 sequences identified in this screen, and a set of globally sampled subtype C reference sequences. Phylogenetic trees disclosed a robustly supported relationship between sequences from Brazil, the UK and East Africa. A monophyletic cluster comprised exclusively of sequences from the UK and Brazil was identified and dated to approximately the early 1980s using a Bayesian coalescent-based method. A sub-cluster of 27 sequences isolated from homosexual men of UK origin was also identified and dated to the early 1990s.

Conclusions

Phylogenetic, demographic and temporal data support the conclusion that the UK was a crucial staging post in the spread of subtype C from East Africa to South America. This unexpected finding demonstrates the role of diffuse international networks in the global spread of HIV-1 infection, and the utility of globally sampled viral sequence data in revealing these networks. Additionally, we show that subtype C viruses are spreading within the UK amongst men who have sex with men.

Resistance and viral subtypes: how important are the differences and why do they occur?

PURPOSE OF REVIEW

The global HIV-1 pandemic has evolved to include 11 subtypes and 34 circulating recombinant forms. Our knowledge of HIV-1 response to antiretroviral drugs and emergent drug resistance has, however, been limited to subtype B infections circulating in Europe and North America, with little comparative information on non-B subtypes representing approximately 90% of worldwide epidemics. This review summarizes publications in the past year that highlight intersubtype differences influencing viral susceptibility to antiretroviral drugs and emergent drug resistance.

RECENT FINDINGS

Cumulative findings from clinical studies suggest that antiretroviral therapy will be of benefit in the overall treatment of non-B subtype infections, and result in drug-resistance profiles comparable to those observed for subtype B infections. Nevertheless, the 10-15% sequence diversity in the Pol region contributes to intersubtype differences in response to particular nucleoside and non-nucleoside analogues, as well as protease inhibitors. Distinct signature mutations and mutational pathways are identified for specific non-B subtypes. The implications of subtype on clinical outcome and interpretative algorithms are described.

SUMMARY

Understanding intersubtype differences in drug resistance is important in optimizing treatment strategies in resource-poor settings. Hopefully, this may assist in the design of prophylactic approaches to prevent HIV-1 horizontal and vertical HIV-1 transmission.

An evolutionary model-based algorithm for accurate phylogenetic breakpoint mapping and subtype prediction in HIV-1

Genetically diverse pathogens (such as Human Immunodeficiency virus type 1, HIV-1) are frequently stratified into phylogenetically or immunologically defined subtypes for classification purposes. Computational identification of such subtypes is helpful in surveillance, epidemiological analysis and detection of novel variants, e.g., circulating recombinant forms in HIV-1. A number of conceptually and technically different techniques have been proposed for determining the subtype of a query sequence, but there is not a universally optimal approach. We present a model-based phylogenetic method for automatically subtyping an HIV-1 (or other viral or bacterial) sequence, mapping the location of breakpoints and assigning parental sequences in recombinant strains as well as computing confidence levels for the inferred quantities. Our Subtype Classification Using Evolutionary ALgorithms (SCUEAL) procedure is shown to perform very well in a variety of simulation scenarios, runs in parallel when multiple sequences are being screened, and matches or exceeds the performance of existing approaches on typical empirical cases. We applied SCUEAL to all available polymerase (pol) sequences from two large databases, the Stanford Drug Resistance database and the UK HIV Drug Resistance Database. Comparing with subtypes which had previously been assigned revealed that a minor but substantial (≈5%) fraction of pure subtype sequences may in fact be within- or inter-subtype recombinants. A free implementation of SCUEAL is provided as a module for the HyPhy package and the Datamonkey web server. Our method is especially useful when an accurate automatic classification of an unknown strain is desired, and is positioned to complement and extend faster but less accurate methods. Given the increasingly frequent use of HIV subtype information in studies focusing on the effect of subtype on treatment, clinical outcome, pathogenicity and vaccine design, the importance of accurate, robust and extensible subtyping procedures is clear.

There are nine different subtypes of the main group of HIV-1, each originating as a distinct subepidemic of HIV-1. The distribution of subtypes is often unique to a given geographic region of the world and constitutes a useful epidemiological and surveillance resource. The effects of viral subtype on disease progression, treatment outcome and vaccine design are being actively researched, and the importance of accurate subtyping procedures is clear. In HIV-1, subtype assignment is complicated by frequent recombination among co-circulating strains, creating new genetic mosaics or recombinant forms: 43 have been characterized to date, and many more likely exist. We present an automated phylogenetic method (SCUEAL) to accurately characterize both simple and complex HIV-1 mosaics. Using computer simulations and biological data we demonstrate that SCUEAL performs very well under various conditions, especially when some of the existing classification procedures fail. Furthermore, we show that a small, but noticeable proportion of subtype characterization stored in public databases may be incomplete or incorrect. The computational technique introduced here should provide a much more accurate characterization of HIV-1 strains, especially novel recombinants, and lead to new insights into molecular history, epidemiology and geographical distribution of the virus.

A standardized framework for accurate, high-throughput genotyping of recombinant and non-recombinant viral sequences

Human immunodeficiency virus type-1 (HIV-1), hepatitis B and C and other rapidly evolving viruses are characterized by extremely high levels of genetic diversity. To facilitate diagnosis and the development of prevention and treatment strategies that efficiently target the diversity of these viruses, and other pathogens such as human T-lymphotropic virus type-1 (HTLV-1), human herpes virus type-8 (HHV8) and human papillomavirus (HPV), we developed a rapid high-throughput-genotyping system. The method involves the alignment of a query sequence with a carefully selected set of pre-defined reference strains, followed by phylogenetic analysis of multiple overlapping segments of the alignment using a sliding window. Each segment of the query sequence is assigned the genotype and sub-genotype of the reference strain with the highest bootstrap (>70%) and bootscanning (>90%) scores. Results from all windows are combined and displayed graphically using color-coded genotypes. The new Virus-Genotyping Tools provide accurate classification of recombinant and non-recombinant viruses and are currently being assessed for their diagnostic utility. They have incorporated into several HIV drug resistance algorithms including the Stanford (http://hivdb.stanford.edu) and two European databases (http://www.umcutrecht.nl/subsite/spread-programme/ and http://www.hivrdb.org.uk/) and have been successfully used to genotype a large number of sequences in these and other databases. The tools are a PHP/JAVA web application and are freely accessible on a number of servers including: http://bioafrica.mrc.ac.za/rega-genotype/html/, http://lasp.cpqgm.fiocruz.br/virus-genotype/html/, http://jose.med.kuleuven.be/genotypetool/html/.

Discrepancies in assignment of subtype/recombinant forms by genotyping programs for HIV type 1 drug resistance testing may falsely predict superinfection

With the growing diversity of the HIV pandemic, routine genotyping is an important tool for monitoring viral subtype as well as drug resistance. In this regard, numerous subtyping tools and drug resistance algorithms are available online. However, there are discrepancies in the use of these online tools in the designation of HIV-1 subtypes or recombinant forms that may have an impact on drug susceptibility profiles. Indeed, inconsistencies in some of these tools may lead to a false designation of dual infection and/or superinfection. In this case study, we evaluated the sequence diversity of an infection that was referred to us as a potential case of superinfection as a result of variations in designation of subtype. We evaluated sequences using five different online tools and finally determined by phylogenetic analysis that the sequence was a unique A1/C intersubtype recombinant at baseline and not a case of superinfection.

Genomic diversity and evolution of the lyssaviruses

Lyssaviruses are RNA viruses with single-strand, negative-sense genomes responsible for rabies-like diseases in mammals. To date, genomic and evolutionary studies have most often utilized partial genome sequences, particularly of the nucleoprotein and glycoprotein genes, with little consideration of genome-scale evolution. Herein, we report the first genomic and evolutionary analysis using complete genome sequences of all recognised lyssavirus genotypes, including 14 new complete genomes of field isolates from 6 genotypes and one genotype that is completely sequenced for the first time. In doing so we significantly increase the extent of genome sequence data available for these important viruses. Our analysis of these genome sequence data reveals that all lyssaviruses have the same genomic organization. A phylogenetic analysis reveals strong geographical structuring, with the greatest genetic diversity in Africa, and an independent origin for the two known genotypes that infect European bats. We also suggest that multiple genotypes may exist within the diversity of viruses currently classified as 'Lagos Bat'. In sum, we show that rigorous phylogenetic techniques based on full length genome sequence provide the best discriminatory power for genotype classification within the lyssaviruses.

Consensus Drug Resistance Mutations for Epidemiological Surveillance: Basic Principles and Potential Controversies

Programmes that monitor local, national and regional levels of transmitted HIV-1 drug resistance inform treatment guidelines and provide feedback on the success of HIV-1 treatment and prevention programmes. The World Health Organization (WHO) has established a global programme for genotypic surveillance of HIV-1 drug resistance and has recommended the adoption of a consensus definition of genotypic drug resistance. Such a definition is necessary to accurately compare transmitted drug resistance rates across geographical regions and time periods. HIV-1 diversity and the large number of mutations associated with antiretroviral drug resistance complicate the development of a consensus definition for genotypic drug resistance. This paper reviews the data that must be considered to determine which of the many HIV-1 drug resistance mutations are likely to be both sensitive and specific indicators of transmitted drug resistance. The process used to create a previously published list of drug resistance mutations for HIV-1 surveillance is reviewed and alternative approaches to this process are discussed.

Phylogenetic surveillance of viral genetic diversity and the evolving molecular epidemiology of human immunodeficiency virus type 1

With ongoing generation of viral genetic diversity and increasing levels of migration, the global human immunodeficiency virus type 1 (HIV-1) epidemic is becoming increasingly heterogeneous. In this study, we investigate the epidemiological characteristics of 5,675 HIV-1 pol gene sequences sampled from distinct infections in the United Kingdom. These sequences were phylogenetically analyzed in conjunction with 976 complete-genome and 3,201 pol gene reference sequences sampled globally and representing the broad range of HIV-1 genetic diversity, allowing us to estimate the probable geographic origins of the various strains present in the United Kingdom. A statistical analysis of phylogenetic clustering in this data set identified several independent transmission chains within the United Kingdom involving recently introduced strains and indicated that strains more commonly associated with infections acquired heterosexually in East Africa are spreading among men who have sex with men. Coalescent approaches were also used and indicated that the transmission chains that we identify originated in the late 1980s to early 1990s. Similar changes in the epidemiological structuring of HIV epidemics are likely to be taking in place in other industrialized nations with large immigrant populations. The framework implemented here takes advantage of the vast amount of routinely generated HIV-1 sequence data and can provide epidemiological insights not readily obtainable through standard surveillance methods.

Evidence of a decline in transmitted HIV-1 drug resistance in the United Kingdom

OBJECTIVE

To examine recent trends in transmitted drug resistance (TDR) in the United Kingdom.

METHODS

Analysis of results of genotypic resistance tests reported to the UK HIV Drug Resistance Database, which includes virtually all tests conducted as part of routine clinical care nationally. Resistance was based on major mutations as defined in the 2005 International AIDS Society-USA guidelines. Analysis was restricted to persons who were antiretroviral treatment-naive at the time of sampling, and a test defined as relating to recent infection if the patient was co-enrolled in the UK Register of HIV Seroconverters and the sample taken within 18 months of a negative HIV antibody test.

RESULTS

A total of 4454 samples from treatment-naive patients between 1996 and 2004 were analysed, including 316 from patients recently infected at the time of the resistance test. After an initial rise, TDR declined from a peak of around 14% in 2001-2002 to around 8% by the end of 2004 (Ptrend < 0.001), largely driven by a decrease in nucleos(t)ide reverse transcriptase inhibitor (NRTI) mutations. Non-NRTI resistance has become increasingly important in relative terms and is now as common as NRTI resistance. Among patients with recent infection, an almost identical pattern was observed but shifted approximately 2 years earlier. A change in the distribution of viral subtypes did not explain these temporal trends.

CONCLUSIONS

This is the first clear evidence of a decrease in TDR at national level. The wider use of regimens that suppress viral concentration to below infectious levels is one of several plausible explanations for this finding.

Nucleotide composition string selection in HIV-1 subtyping using whole genomes

MOTIVATION

The availability of the whole genomic sequences of HIV-1 viruses provides an excellent resource for studying the HIV-1 phylogenies using all the genetic materials. However, such huge volumes of data create computational challenges in both memory consumption and CPU usage.

RESULTS

We propose the complete composition vector representation for an HIV-1 strain, and a string scoring method to extract the nucleotide composition strings that contain the richest evolutionary information for phylogenetic analysis. In this way, a large-scale whole genome phylogenetic analysis for thousands of strains can be done both efficiently and effectively. By using 42 carefully curated strains as references, we apply our method to subtype 1156 HIV-1 strains (10.5 million nucleotides in total), which include 825 pure subtype strains and 331 recombinants. Our results show that our nucleotide composition string selection scheme is computationally efficient, and is able to define both pure subtypes and recombinant forms for HIV-1 strains using the 5000 top ranked nucleotide strings.

AVAILABILITY

The Java executable and the HIV-1 datasets are accessible through 'http://www.cs.ualberta.ca/~ghlin/src/WebTools/hiv.php.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Evaluation of an in-house genotyping resistance test for HIV-1 drug resistance interpretation and genotyping

INTRODUCTION

The human immunodeficiency virus type 1 (HIV-1) genotyping resistance test (GRT) has been considered essential for HIV-1 drug resistance monitoring. However, it is not commonly used in some developing countries in Asia and Africa due to its high running cost.

OBJECTIVE

This study aims to evaluate a new low-cost in-house GRT for both subtype B and non-B HIV-1.

STUDY DESIGN

The in-house GRT sequenced the entire protease and 410 codons of reverse transcriptase (RT) in the pol gene. Its performance on drug resistance interpretation was evaluated against the FDA-approved ViroSeq HIV-1 Genotyping System. Particularly, a panel of 235 plasma samples from 205 HIV-1-infected patients in Hong Kong was investigated. The HIV-1 drug resistance-related mutations detected by the two systems were compared. The HIV-1 subtypes were analyzed through the REGA HIV-1 Genotyping Tool and env phylogenetic analysis.

RESULTS

Among the 235 samples, 229 (97.4%) were successfully amplified by both in-house and ViroSeq systems. All PCR-negative samples harbored viral RNA at <400 copies/mL. The in-house and ViroSeq system showed identical drug resistance-related mutation patterns in 216 out of 229 samples (94.3%). The REGA pol genotyping results showed 93.9% (215/229) concordance with the env phylogenetic results including HIV-1 subtype A1, B, C, D, G, CRF01_AE, CRF02_AG, CRF06_cpx, CRF07_BC, CRF08_BC, CRF15_01B and other recombinant strains. The cost of running the in-house GRT is only 25% of that for the commercial system, thus making it suitable for the developing countries in Asia and Africa.

CONCLUSIONS

Overall, our in-house GRT provided comparable results to those of the commercial ViroSeq genotyping system on diversified HIV-1 subtypes at a more affordable price which make it suitable for HIV-1 monitoring in developing countries.