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Mendeley | Further Information

{"title"=>"Reconstructing the Dynamics of HIV Evolution within Hosts from Serial Deep Sequence Data", "type"=>"journal", "authors"=>[{"first_name"=>"Art F.Y.", "last_name"=>"Poon", "scopus_author_id"=>"15073114700"}, {"first_name"=>"Luke C.", "last_name"=>"Swenson", "scopus_author_id"=>"25629830200"}, {"first_name"=>"Evelien M.", "last_name"=>"Bunnik", "scopus_author_id"=>"55892064600"}, {"first_name"=>"Diana", "last_name"=>"Edo-Matas", "scopus_author_id"=>"35620269000"}, {"first_name"=>"Hanneke", "last_name"=>"Schuitemaker", "scopus_author_id"=>"7006687551"}, {"first_name"=>"Angélique B.", "last_name"=>"van 't Wout", "scopus_author_id"=>"55918027300"}, {"first_name"=>"P. Richard", "last_name"=>"Harrigan", "scopus_author_id"=>"7004857656"}], "year"=>2012, "source"=>"PLoS Computational Biology", "identifiers"=>{"sgr"=>"84870666711", "doi"=>"10.1371/journal.pcbi.1002753", "pui"=>"366216209", "pmid"=>"23133358", "scopus"=>"2-s2.0-84870666711", "issn"=>"1553734X", "isbn"=>"1553-7358 (Electronic)\\r1553-734X (Linking)"}, "id"=>"94147cbc-345a-3ed5-bfc0-5b9f44c00c2e", "abstract"=>"At the early stage of infection, human immunodeficiency virus (HIV)-1 predominantly uses the CCR5 coreceptor for host cell entry. The subsequent emergence of HIV variants that use the CXCR4 coreceptor in roughly half of all infections is associated with an accelerated decline of CD4+ T-cells and rate of progression to AIDS. The presence of a ‘fitness valley’ separating CCR5- and CXCR4-using genotypes is postulated to be a biological determinant of whether the HIV coreceptor switch occurs. Using phylogenetic methods to reconstruct the evolutionary dynamics of HIV within hosts enables us to discriminate between competing models of this process. We have developed a phylogenetic pipeline for the molecular clock analysis, ancestral reconstruction, and visualization of deep sequence data. These data were generated by next-generation sequencing of HIV RNA extracted from longitudinal serum samples (median 7 time points) from 8 untreated subjects with chronic HIV infections (Amsterdam Cohort Studies on HIV-1 infection and AIDS). We used the known dates of sampling to directly estimate rates of evolution and to map ancestral mutations to a reconstructed timeline in units of days. HIV coreceptor usage was predicted from reconstructed ancestral sequences using the geno2pheno algorithm. We determined that the first mutations contributing to CXCR4 use emerged about 16 (per subject range 4 to 30) months before the earliest predicted CXCR4-using ancestor, which preceded the first positive cell-based assay of CXCR4 usage by 10 (range 5 to 25) months. CXCR4 usage arose in multiple lineages within 5 of 8 subjects, and ancestral lineages following alternate mutational pathways before going extinct were common. We observed highly patient-specific distributions and time-scales of mutation accumulation, implying that the role of a fitness valley is contingent on the genotype of the transmitted variant.", "link"=>"http://www.mendeley.com/research/reconstructing-dynamics-hiv-evolution-within-hosts-serial-deep-sequence-data", "reader_count"=>88, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>5, "Researcher"=>26, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>27, "Student > Postgraduate"=>3, "Student > Master"=>10, "Other"=>4, "Student > Bachelor"=>2, "Lecturer"=>3, "Professor"=>3}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>5, "Researcher"=>26, "Student > Doctoral Student"=>3, "Student > Ph. D. Student"=>27, "Student > Postgraduate"=>3, "Student > Master"=>10, "Other"=>4, "Student > Bachelor"=>2, "Lecturer"=>3, "Professor"=>3}, "reader_count_by_subject_area"=>{"Engineering"=>2, "Unspecified"=>5, "Environmental Science"=>2, "Biochemistry, Genetics and Molecular Biology"=>15, "Mathematics"=>3, "Agricultural and Biological Sciences"=>36, "Medicine and Dentistry"=>13, "Veterinary Science and Veterinary Medicine"=>1, "Physics and Astronomy"=>3, "Computer Science"=>6, "Immunology and Microbiology"=>2}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>2}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>13}, "Physics and Astronomy"=>{"Physics and Astronomy"=>3}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>36}, "Computer Science"=>{"Computer Science"=>6}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>15}, "Mathematics"=>{"Mathematics"=>3}, "Unspecified"=>{"Unspecified"=>5}, "Environmental Science"=>{"Environmental Science"=>2}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>1}}, "reader_count_by_country"=>{"Canada"=>4, "Hungary"=>1, "United States"=>5, "United Kingdom"=>1, "France"=>1, "India"=>1, "Spain"=>1}, "group_count"=>4}

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• http://doi.org/10.1093/molbev/msaa136
• http://doi.org/10.1128/AAC.00137-15
• http://doi.org/10.1093/molbev/msy088
• http://doi.org/10.1016/j.tree.2015.03.009
• http://doi.org/10.1093/nar/gku537
• http://doi.org/10.1371/journal.pone.0177033
• http://doi.org/10.1073/pnas.1802028115
• http://doi.org/10.1093/ije/dyu046
• http://doi.org/10.1371/journal.pone.0194148
• http://doi.org/10.1111/mec.13378
• http://doi.org/10.1038/nrmicro2949
• http://doi.org/10.1016/j.virol.2016.04.010
• http://doi.org/10.1128/JVI.00793-17
• http://doi.org/10.1534/genetics.115.177931
• http://doi.org/10.1089/aid.2012.0349
• http://doi.org/10.1371/journal.pone.0097899
• http://doi.org/10.1186/s12981-020-0263-x
• http://doi.org/10.1038/s41467-018-06843-5
• http://doi.org/10.1089/aid.2012.0173
• http://doi.org/10.1007/s13365-018-0633-5
• http://doi.org/10.1128/JVI.00483-14
• http://doi.org/10.1111/jeb.12329
• http://doi.org/10.1038/srep17607
• http://doi.org/10.1089/aid.2016.0153
• http://doi.org/10.3389/fimmu.2015.00506
• http://doi.org/10.1371/journal.pone.0102857
• http://doi.org/10.1371/journal.pcbi.1004763
• http://doi.org/10.7554/eLife.06193
• http://doi.org/10.1128/JVI.00193-20
• http://doi.org/10.1016/j.virol.2016.03.010
• http://doi.org/10.1016/j.virusres.2016.12.008
• http://doi.org/10.1016/j.bbagen.2018.12.003

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{"EMBL"=>2896, "UNIPROT"=>2854}

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• {"id"=>"264165274750681088", "text"=>"RT @RiseUpToHIV: Genetic sequencing of #HIV tries to shed light on the virus' ability to switch co-receptors leading to disease... http://t.co/jNNGujZj", "created_at"=>"2012-11-02T00:41:24Z", "user"=>"HandsomeMe727", "user_name"=>"Mario Pinna Ferri", "user_profile_image"=>"http://a0.twimg.com/profile_images/1392894761/pl_14_normal.jpg"}
• {"id"=>"264168296625102848", "text"=>"RT @RiseUpToHIV: Genetic sequencing of #HIV tries to shed light on the virus' ability to switch co-receptors leading to disease... http://t.co/jNNGujZj", "created_at"=>"2012-11-02T00:53:24Z", "user"=>"videodouble", "user_name"=>"Fake HIV", "user_profile_image"=>"http://a0.twimg.com/profile_images/2785597503/32890102aff8c2474ce1076ace321378_normal.jpeg"}
• {"id"=>"265820713498316800", "text"=>"New study from @PLOSCompBiol - Sequencing study of HIV evolution within host http://t.co/v9xSmgj7", "created_at"=>"2012-11-06T14:19:31Z", "user"=>"OHSUBCB", "user_name"=>"OHSU Bioinformatics", "user_profile_image"=>"http://a0.twimg.com/profile_images/1136136806/dna_data_normal.jpg"}
• {"id"=>"265828399325528064", "text"=>"RT @OHSUBCB: New study from @PLOSCompBiol - Sequencing study of HIV evolution within host http://t.co/v9xSmgj7", "created_at"=>"2012-11-06T14:50:03Z", "user"=>"agapow", "user_name"=>"Paul-Michael Agapow", "user_profile_image"=>"http://a0.twimg.com/profile_images/315101392/hay-on-wye-2002_normal.jpg"}

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• {"title"=>"Ancestral reconstruction", "url"=>"http://en.wikipedia.org/wiki/Ancestral_reconstruction", "timestamp"=>"2019-03-14T00:23:38Z"}

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• {"month"=>"8", "year"=>"2020", "pdf_views"=>"4", "xml_views"=>"1", "html_views"=>"4"}
• {"month"=>"9", "year"=>"2020", "pdf_views"=>"13", "xml_views"=>"0", "html_views"=>"24"}
• {"month"=>"10", "year"=>"2020", "pdf_views"=>"10", "xml_views"=>"1", "html_views"=>"33"}
• {"month"=>"11", "year"=>"2020", "pdf_views"=>"11", "xml_views"=>"2", "html_views"=>"22"}
• {"month"=>"12", "year"=>"2020", "pdf_views"=>"5", "xml_views"=>"1", "html_views"=>"1"}
• {"month"=>"1", "year"=>"2021", "pdf_views"=>"5", "xml_views"=>"0", "html_views"=>"4"}

Figshare

• {"files"=>["https://ndownloader.figshare.com/files/549210"], "description"=>"<p>Simulations were generated under a five-allele Moran model with mortality selection <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002753#pcbi.1002753-Muirhead1\" target=\"_blank\">[42]</a>, effective population size , forward mutation rate of per replication, and fitness vectors of (1, 1.025, 1.05, 1.075, 1.1) and (1, 0.999, 0.999, 0.999, 1.1) corresponding to gradual and valley landscapes, respectively. Note that the relatively rapid and complete fixation of the fifth variant is partly due to the model assumption of no back mutation, and is not consistent with the observation that CXCR4-using variants tend to remain a minority species in HIV infections.</p>", "links"=>[], "tags"=>["trajectories", "genotype", "frequencies", "dashed", "population-level", "coreceptor", "usage", "phenotype", "gradual", "models", "hiv"], "article_id"=>219687, "categories"=>["Biological Sciences", "Infectious Diseases"], "users"=>["Art F. Y. Poon", "Luke C. Swenson", "Evelien M. Bunnik", "Diana Edo-Matas", "Hanneke Schuitemaker", "Angélique B. van 't Wout", "P. Richard Harrigan"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002753.g001", "stats"=>{"downloads"=>3, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Simulated_trajectories_of_genotype_frequencies_solid_and_dashed_lines_and_population_level_coreceptor_usage_phenotype_shaded_regions_under_the_fitness_valley_and_gradual_models_of_HIV_coreceptor_usage_evolution_/219687", "title"=>"Simulated trajectories of genotype frequencies (solid and dashed lines) and population-level coreceptor usage phenotype (shaded regions) under the fitness valley and gradual models of HIV coreceptor usage evolution.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-01 02:41:27"}
• {"files"=>["https://ndownloader.figshare.com/files/549387"], "description"=>"<p>These excerpts emphasize the lineages that attained a CXCR4-using ancestral genotype (FPR3.5). Branches are coloured with respect to the predicted FPR value (see legend inset). Vertical lines indicate the times of the first serum sample (dashed) and first positive MT-2 assay (solid), respectively. Open circles indicate the start of the branch carrying mutations promoting CXCR4 usage, which otherwise cannot be distinguished because other branches that do not carry such mutations have been collapsed. Percentiles indicate the fraction of the most recent sample that descend from the corresponding lineage.</p>", "links"=>[], "tags"=>["trees", "hiv", "subjects", "ds2", "ds7", "reconstructed", "mutations", "mapped", "branches", "comprising", "ancestral", "v3", "derived"], "article_id"=>219860, "categories"=>["Biological Sciences", "Infectious Diseases"], "users"=>["Art F. Y. Poon", "Luke C. Swenson", "Evelien M. Bunnik", "Diana Edo-Matas", "Hanneke Schuitemaker", "Angélique B. van 't Wout", "P. Richard Harrigan"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002753.g003", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Excerpts_from_the_maximum_credibility_trees_for_HIV_evolution_within_subjects_DS2_and_DS7_with_reconstructed_mutations_mapped_to_individual_branches_labels_comprising_the_ancestral_residue_position_in_the_V3_loop_and_the_derived_residue_/219860", "title"=>"Excerpts from the maximum credibility trees for HIV evolution within subjects DS2 and DS7 with reconstructed mutations mapped to individual branches (labels comprising the ancestral residue, position in the V3 loop, and the derived residue).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-01 02:44:20"}
• {"files"=>["https://ndownloader.figshare.com/files/293031", "https://ndownloader.figshare.com/files/293098", "https://ndownloader.figshare.com/files/293159", "https://ndownloader.figshare.com/files/293254", "https://ndownloader.figshare.com/files/293310", "https://ndownloader.figshare.com/files/293459", "https://ndownloader.figshare.com/files/293522", "https://ndownloader.figshare.com/files/293574"], "description"=>"<div><p>At the early stage of infection, human immunodeficiency virus (HIV)-1 predominantly uses the CCR5 coreceptor for host cell entry. The subsequent emergence of HIV variants that use the CXCR4 coreceptor in roughly half of all infections is associated with an accelerated decline of CD4+ T-cells and rate of progression to AIDS. The presence of a ‘fitness valley’ separating CCR5- and CXCR4-using genotypes is postulated to be a biological determinant of whether the HIV coreceptor switch occurs. Using phylogenetic methods to reconstruct the evolutionary dynamics of HIV within hosts enables us to discriminate between competing models of this process. We have developed a phylogenetic pipeline for the molecular clock analysis, ancestral reconstruction, and visualization of deep sequence data. These data were generated by next-generation sequencing of HIV RNA extracted from longitudinal serum samples (median 7 time points) from 8 untreated subjects with chronic HIV infections (Amsterdam Cohort Studies on HIV-1 infection and AIDS). We used the known dates of sampling to directly estimate rates of evolution and to map ancestral mutations to a reconstructed timeline in units of days. HIV coreceptor usage was predicted from reconstructed ancestral sequences using the geno2pheno algorithm. We determined that the first mutations contributing to CXCR4 use emerged about 16 (per subject range 4 to 30) months before the earliest predicted CXCR4-using ancestor, which preceded the first positive cell-based assay of CXCR4 usage by 10 (range 5 to 25) months. CXCR4 usage arose in multiple lineages within 5 of 8 subjects, and ancestral lineages following alternate mutational pathways before going extinct were common. We observed highly patient-specific distributions and time-scales of mutation accumulation, implying that the role of a fitness valley is contingent on the genotype of the transmitted variant.</p> </div>", "links"=>[], "tags"=>["reconstructing", "hiv", "hosts", "serial", "data"], "article_id"=>117680, "categories"=>["Biological Sciences", "Cancer"], "users"=>["Art F. Y. Poon", "Luke C. Swenson", "Evelien M. Bunnik", "Diana Edo-Matas", "Hanneke Schuitemaker", "Angélique B. van 't Wout", "P. Richard Harrigan"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1002753.s001", "https://dx.doi.org/10.1371/journal.pcbi.1002753.s002", "https://dx.doi.org/10.1371/journal.pcbi.1002753.s003", "https://dx.doi.org/10.1371/journal.pcbi.1002753.s004", "https://dx.doi.org/10.1371/journal.pcbi.1002753.s005", "https://dx.doi.org/10.1371/journal.pcbi.1002753.s006", "https://dx.doi.org/10.1371/journal.pcbi.1002753.s007", "https://dx.doi.org/10.1371/journal.pcbi.1002753.s008"], "stats"=>{"downloads"=>19, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Reconstructing_the_Dynamics_of_HIV_Evolution_within_Hosts_from_Serial_Deep_Sequence_Data__/117680", "title"=>"Reconstructing the Dynamics of HIV Evolution within Hosts from Serial Deep Sequence Data", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-11-01 02:08:00"}
• {"files"=>["https://ndownloader.figshare.com/files/549478"], "description"=>"<p>The MARCS V3 sequence reconstructed at the MRCA of the maximum credibility tree is shown at the top of each plot. Residues highlighted in red correspond to mutations that arose in a CXCR4-using background (FPR3.5). The duration of HIV coreceptor evolution from to the first CXCR4-using ancestor is indicated in months alongside each plot (see text).</p>", "links"=>[], "tags"=>["v3", "comprising", "predominant", "pathway", "stratified"], "article_id"=>219965, "categories"=>["Biological Sciences", "Infectious Diseases"], "users"=>["Art F. Y. Poon", "Luke C. Swenson", "Evelien M. Bunnik", "Diana Edo-Matas", "Hanneke Schuitemaker", "Angélique B. van 't Wout", "P. Richard Harrigan"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002753.g004", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Mutations_within_the_V3_loop_comprising_the_predominant_pathway_for_each_subject_stratified_by_time_of_emergence_/219965", "title"=>"Mutations within the V3 loop comprising the predominant pathway for each subject, stratified by time of emergence.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-01 02:46:05"}
• {"files"=>["https://ndownloader.figshare.com/files/549286"], "description"=>"<p>Double vertical lines indicate the time of the earliest sample per patient.</p>", "links"=>[], "tags"=>["estimates", "shaded", "earliest", "cxcr4-using", "molecular", "analyses", "hiv"], "article_id"=>219772, "categories"=>["Biological Sciences", "Infectious Diseases"], "users"=>["Art F. Y. Poon", "Luke C. Swenson", "Evelien M. Bunnik", "Diana Edo-Matas", "Hanneke Schuitemaker", "Angélique B. van 't Wout", "P. Richard Harrigan"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002753.g002", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Kernel_density_estimates_of_the_distribution_of_solid_line_red_shaded_region_and_the_time_of_the_earliest_CXCR4_using_ancestor_defined_at_FPR_3_5_solid_region_based_on_molecular_clock_analyses_of_HIV_sequence_variation_from_each_subject_/219772", "title"=>"Kernel density estimates of the distribution of (solid line), (red shaded region) and the time of the earliest CXCR4-using ancestor (defined at FPR3.5; solid region) based on molecular clock analyses of HIV sequence variation from each subject.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-01 02:42:52"}
• {"files"=>["https://ndownloader.figshare.com/files/549568"], "description"=>"<p>The -axis corresponds to time intervals from to the first positive MT-2 assay (), rescaled for each subject. The -axis corresponds to the log-transformed FPR predictions for the ancestral sequences. Both axes were partitioned into 25 bins. Each cell is coloured with respect to its FPR value with opacity proportional to the square root of the number of data points in the corresponding bins, normalized by the total number of points in the time interval.</p>", "links"=>[], "tags"=>["histograms", "illustrating", "distributions", "g2p", "fpr", "predictions", "replicate", "ancestral", "reconstructions"], "article_id"=>220050, "categories"=>["Biological Sciences", "Infectious Diseases"], "users"=>["Art F. Y. Poon", "Luke C. Swenson", "Evelien M. Bunnik", "Diana Edo-Matas", "Hanneke Schuitemaker", "Angélique B. van 't Wout", "P. Richard Harrigan"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002753.g005", "stats"=>{"downloads"=>0, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Two_dimensional_histograms_illustrating_the_distributions_of_g2p_FPR_predictions_across_all_replicate_ancestral_reconstructions_on_the_maximum_credibility_tree_/220050", "title"=>"Two-dimensional histograms illustrating the distributions of g2p FPR predictions across all replicate ancestral reconstructions on the maximum credibility tree.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-11-01 00:00:50"}

PMC Usage Stats | Further Information

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• {"unique-ip"=>"8", "full-text"=>"2", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"2", "cited-by"=>"7", "year"=>"2015", "month"=>"12"}
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Relative Metric

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F1000Prime