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      A high HIV-1 strain variability in London, UK, revealed by full-genome analysis: Results from the ICONIC project

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background & methods

          The ICONIC project has developed an automated high-throughput pipeline to generate HIV nearly full-length genomes (NFLG, i.e. from gag to nef) from next-generation sequencing (NGS) data. The pipeline was applied to 420 HIV samples collected at University College London Hospitals NHS Trust and Barts Health NHS Trust (London) and sequenced using an Illumina MiSeq at the Wellcome Trust Sanger Institute (Cambridge). Consensus genomes were generated and subtyped using COMET, and unique recombinants were studied with jpHMM and SimPlot. Maximum-likelihood phylogenetic trees were constructed using RAxML to identify transmission networks using the Cluster Picker.

          Results

          The pipeline generated sequences of at least 1Kb of length (median = 7.46Kb, IQR = 4.01Kb) for 375 out of the 420 samples (89%), with 174 (46.4%) being NFLG. A total of 365 sequences (169 of them NFLG) corresponded to unique subjects and were included in the down-stream analyses. The most frequent HIV subtypes were B (n = 149, 40.8%) and C (n = 77, 21.1%) and the circulating recombinant form CRF02_AG (n = 32, 8.8%). We found 14 different CRFs (n = 66, 18.1%) and multiple URFs (n = 32, 8.8%) that involved recombination between 12 different subtypes/CRFs. The most frequent URFs were B/CRF01_AE (4 cases) and A1/D, B/C, and B/CRF02_AG (3 cases each). Most URFs (19/26, 73%) lacked breakpoints in the PR+RT pol region, rendering them undetectable if only that was sequenced. Twelve (37.5%) of the URFs could have emerged within the UK, whereas the rest were probably imported from sub-Saharan Africa, South East Asia and South America. For 2 URFs we found highly similar pol sequences circulating in the UK. We detected 31 phylogenetic clusters using the full dataset: 25 pairs (mostly subtypes B and C), 4 triplets and 2 quadruplets. Some of these were not consistent across different genes due to inter- and intra-subtype recombination. Clusters involved 70 sequences, 19.2% of the dataset.

          Conclusions

          The initial analysis of genome sequences detected substantial hidden variability in the London HIV epidemic. Analysing full genome sequences, as opposed to only PR+RT, identified previously undetected recombinants. It provided a more reliable description of CRFs (that would be otherwise misclassified) and transmission clusters.

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          Most cited references 37

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          Full-length human immunodeficiency virus type 1 genomes from subtype C-infected seroconverters in India, with evidence of intersubtype recombination.

          The development of an effective human immunodeficiency virus type 1 (HIV-1) vaccine is likely to depend on knowledge of circulating variants of genes other than the commonly sequenced gag and env genes. In addition, full-genome data are particularly limited for HIV-1 subtype C, currently the most commonly transmitted subtype in India and worldwide. Likewise, little is known about sequence variation of HIV-1 in India, the country facing the largest burden of HIV worldwide. Therefore, the objective of this study was to clone and characterize the complete genome of HIV-1 from seroconverters infected with subtype C variants in India. Cocultured HIV-1 isolates were obtained from six seroincident individuals from Pune, India, and virtually full-length HIV-1 genomes were amplified, cloned, and sequenced from each. Sequence analysis revealed that five of the six genomes were of subtype C, while one was a mosaic of subtypes A and C, with multiple breakpoints in env, nef, and the 3' long terminal repeat as determined by both maximal chi2 analysis and phylogenetic bootstrapping. Sequences were compared for preservation of known cytotoxic T lymphocyte (CTL) epitopes. Compared with those of the HIV-1LAI sequence, 38% of well-defined CTL epitopes were identical. The proportion of nonconservative substitutions for Env, at 61%, was higher (P < 0.001) than those for Gag (24%), Pol (18%), and Nef (32%). Therefore, characterized CTL epitopes demonstrated substantial differences from subtype B laboratory strains, which were most pronounced in Env. Because these clones were obtained from Indian seroconverters, they are likely to facilitate vaccine-related efforts in India by providing potential antigens for vaccine candidates as well as for assays of vaccine responsiveness.
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            RDP4: Detection and analysis of recombination patterns in virus genomes

            RDP4 is the latest version of recombination detection program (RDP), a Windows computer program that implements an extensive array of methods for detecting and visualising recombination in, and stripping evidence of recombination from, virus genome sequence alignments. RDP4 is capable of analysing twice as many sequences (up to 2,500) that are up to three times longer (up to 10 Mb) than those that could be analysed by older versions of the program. RDP4 is therefore also applicable to the analysis of bacterial full-genome sequence datasets. Other novelties in RDP4 include (1) the capacity to differentiate between recombination and genome segment reassortment, (2) the estimation of recombination breakpoint confidence intervals, (3) a variety of ‘recombination aware’ phylogenetic tree construction and comparison tools, (4) new matrix-based visualisation tools for examining both individual recombination events and the overall phylogenetic impacts of multiple recombination events and (5) new tests to detect the influences of gene arrangements, encoded protein structure, nucleic acid secondary structure, nucleotide composition, and nucleotide diversity on recombination breakpoint patterns. The key feature of RDP4 that differentiates it from other recombination detection tools is its flexibility. It can be run either in fully automated mode from the command line interface or with a graphically rich user interface that enables detailed exploration of both individual recombination events and overall recombination patterns.
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              Global trends in molecular epidemiology of HIV-1 during 2000-2007.

              To estimate the global and regional distribution of HIV-1 subtypes and recombinants between 2000 and 2007. Country-specific HIV-1 molecular epidemiology data were combined with estimates of the number of HIV-infected people in each country. Cross-sectional HIV-1 subtyping data were collected from 65 913 samples in 109 countries between 2000 and 2007. The distribution of HIV-1 subtypes in individual countries was weighted according to the number of HIV-infected people in each country to generate estimates of regional and global HIV-1 subtype distribution for the periods 2000-2003 and 2004-2007. Analysis of the global distribution of HIV-1 subtypes and recombinants in the two periods indicated a broadly stable distribution of HIV-1 subtypes worldwide with a notable increase in the proportion of circulating recombinant forms (CRFs), a decrease in unique recombinant forms (URFs) and an overall increase in recombinants. In 2004-2007, subtype C accounted for nearly half (48%) of all global infections, followed by subtypes A (12%) and B (11%), CRF02_AG (8%), CRF01_AE (5%), subtype G (5%) and D (2%). Subtypes F, H, J and K together cause fewer than 1% of infections worldwide. Other CRFs and URFs are each responsible for 4% of global infections, bringing the combined total of worldwide CRFs to 16% and all recombinants (CRFs along with URFs) to 20%. The global and regional distributions of individual subtypes and recombinants are broadly stable, although CRFs may play an increasing role in the HIV pandemic. The global diversity of HIV-1 poses a formidable challenge to HIV vaccine development.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Writing – review & editing
                Role: Formal analysisRole: Writing – review & editing
                Role: Data curationRole: ResourcesRole: Writing – review & editing
                Role: Data curationRole: ResourcesRole: Writing – review & editing
                Role: Data curationRole: ResourcesRole: Writing – review & editing
                Role: Data curationRole: ResourcesRole: Writing – review & editing
                Role: ResourcesRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: ResourcesRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: ResourcesRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: ResourcesRole: Writing – review & editing
                Role: Data curationRole: Funding acquisitionRole: ResourcesRole: Writing – review & editing
                Role: Data curationRole: ResourcesRole: Writing – review & editing
                Role: Data curationRole: ResourcesRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                1 February 2018
                2018
                : 13
                : 2
                Affiliations
                [1 ] Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom
                [2 ] UCL Division of Infection and Immunity, Faculty of Medical Sciences, London, United Kingdom
                [3 ] Department of Clinical Virology, UCL Hospital NHS Foundation Trust, London, United Kingdom
                [4 ] Department of Virology, Barts Health NHS Trust, London, United Kingdom
                [5 ] NIHR UCLH/UCL Biomedical Research Centre, London, United Kingdom
                [6 ] Department of HIV Medicine, Mortimer Market Centre, Central & North West London NHS Trust, London, United Kingdom
                [7 ] Queen Mary University, London, United Kingdom
                [8 ] UCL Institute of Disease Informatics, Farr Institute of Health Informatics Research, London, United Kingdom
                [9 ] UCL Institute of Epidemiology and Health Care, London, United Kingdom
                [10 ] Division of Infectious Diseases, Department of Medicine, Imperial College London, London, United Kingdom
                [11 ] School of Life Sciences, University of Glasgow. Glasgow, United Kingdom
                [12 ] Department of Population, Policy and Practice, UCL GOS Institute of Child Health, London, United Kingdom
                National and Kapodistrian University of Athens, GREECE
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                ¶ Membership of the ICONIC Consortium is provided in the Acknowledgments.

                Article
                PONE-D-17-31974
                10.1371/journal.pone.0192081
                5794160
                29389981
                © 2018 Yebra et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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                Figures: 5, Tables: 0, Pages: 18
                Product
                Funding
                This work was supported by the ICONIC project (supported by the Health Innovation Challenge Fund T5-344, a parallel funding partnership between the Department of Health and Wellcome Trust).
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                Custom metadata
                The 375 assembled HIV-1 genomes were deposited in GenBank under the accession numbers MF109352 to MF109726. All the raw paired-end short reads were deposited in the European Nucleotide Archive (ENA) under the study accession number PRJEB6008.

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