Frequent Toggling between Alternative Amino Acids Is Driven by Selection in HIV-1
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{"title"=>"Frequent toggling between alternative amino acids is driven by selection in HIV-1", "type"=>"journal", "authors"=>[{"first_name"=>"Wayne", "last_name"=>"Delport", "scopus_author_id"=>"56531839800"}, {"first_name"=>"Konrad", "last_name"=>"Scheffler", "scopus_author_id"=>"13103633800"}, {"first_name"=>"Cathal", "last_name"=>"Seoighe", "scopus_author_id"=>"6603385032"}], "year"=>2008, "source"=>"PLoS Pathogens", "identifiers"=>{"pui"=>"354036754", "isbn"=>"1553-7374 (Electronic)", "issn"=>"15537366", "doi"=>"10.1371/journal.ppat.1000242", "sgr"=>"58149240271", "scopus"=>"2-s2.0-58149240271", "pmid"=>"19096508"}, "id"=>"84034b93-c6ea-369f-97b9-586c8a880f6e", "abstract"=>"Host immune responses against infectious pathogens exert strong selective pressures favouring the emergence of escape mutations that prevent immune recognition. Escape mutations within or flanking functionally conserved epitopes can occur at a significant cost to the pathogen in terms of its ability to replicate effectively. Such mutations come under selective pressure to revert to the wild type in hosts that do not mount an immune response against the epitope. Amino acid positions exhibiting this pattern of escape and reversion are of interest because they tend to coincide with immune responses that control pathogen replication effectively. We have used a probabilistic model of protein coding sequence evolution to detect sites in HIV-1 exhibiting a pattern of rapid escape and reversion. Our model is designed to detect sites that toggle between a wild type amino acid, which is susceptible to a specific immune response, and amino acids with lower replicative fitness that evade immune recognition. Through simulation, we show that this model has significantly greater power to detect selection involving immune escape and reversion than standard models of diversifying selection, which are sensitive to an overall increased rate of non-synonymous substitution. Applied to alignments of HIV-1 protein coding sequences, the model of immune escape and reversion detects a significantly greater number of adaptively evolving sites in env and nef. In all genes tested, the model provides a significantly better description of adaptively evolving sites than standard models of diversifying selection. Several of the sites detected are corroborated by association between Human Leukocyte Antigen (HLA) and viral sequence polymorphisms. Overall, there is evidence for a large number of sites in HIV-1 evolving under strong selective pressure, but exhibiting low sequence diversity. A phylogenetic model designed to detect rapid toggling between wild type and escape amino acids identifies a larger number of adaptively evolving sites in HIV-1, and can in some cases correctly identify the amino acid that is susceptible to the immune response.", "link"=>"http://www.mendeley.com/research/frequent-toggling-between-alternative-amino-acids-driven-selection-hiv1", "reader_count"=>63, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>12, "Researcher"=>19, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>14, "Student > Postgraduate"=>1, "Student > Master"=>6, "Other"=>1, "Student > Bachelor"=>3, "Lecturer"=>1, "Professor"=>2}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>12, "Researcher"=>19, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>14, "Student > Postgraduate"=>1, "Student > Master"=>6, "Other"=>1, "Student > Bachelor"=>3, "Lecturer"=>1, "Professor"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>4, "Biochemistry, Genetics and Molecular Biology"=>7, "Agricultural and Biological Sciences"=>45, "Medicine and Dentistry"=>2, "Veterinary Science and Veterinary Medicine"=>1, "Psychology"=>1, "Computer Science"=>2, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>2}, "Psychology"=>{"Psychology"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>45}, "Computer Science"=>{"Computer Science"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>7}, "Unspecified"=>{"Unspecified"=>4}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>1}}, "reader_count_by_country"=>{"Netherlands"=>1, "United States"=>2, "Denmark"=>1, "United Kingdom"=>1, "France"=>1, "Kenya"=>1, "Switzerland"=>1, "Spain"=>1}, "group_count"=>1}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/913042"], "description"=>"<p>Tree branches are coloured according to the codon category of the node at the right end of the branch for sites detected to be (A) diversifying selection or (B) toggling, and (C) a previously identified HLA-associated polymorphism in <i>gag</i> (TW10). Potential escape and reversion mutations are mapped as red and green arrows, respectively. <i>P,</i> likelihood ratio test statistic <i>p</i>-value; <i>D,</i> diversifying selection model; <i>T,</i> toggling model. Both <i>env</i> and <i>gag</i> trees are rooted on HIV-1 subtype B.</p>", "links"=>[], "tags"=>["toggling", "diversifying"], "article_id"=>583500, "categories"=>["Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Cathal Seoighe"], "doi"=>"https://dx.doi.org/10.1371/journal.ppat.1000242.g004", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evidence_of_toggling_and_diversifying_selection_in_real_data_/583500", "title"=>"Evidence of toggling and diversifying selection in real data.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-12-19 00:58:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/913210"], "description"=>"<p><i>ρ,</i> non-synonymous to synonymous rate ratio for mutations away from or towards wild type amino acid; <i>T,</i> toggling model where <i>ρ</i> is unconstrained in alternate; <i>D,</i> diversifying selection model.</p>", "links"=>[], "tags"=>["amino"], "article_id"=>583674, "categories"=>["Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Cathal Seoighe"], "doi"=>"https://dx.doi.org/10.1371/journal.ppat.1000242.t002", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_effect_of_tree_length_and_shape_on_the_power_to_detect_amino_acid_toggling_/583674", "title"=>"The effect of tree length and shape on the power to detect amino acid toggling.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2008-12-19 01:01:14"}
  • {"files"=>["https://ndownloader.figshare.com/files/912731"], "description"=>"<p>The immune escape and reversion model has three classes of codons: codons encoding the wild type amino acid (class x); codons separated from the wild type by a single nucleotide substitution (y); and codons separated from the wild type by more than one substitution (z). In the example shown, phenylalanine (F) is the wild type amino acid. Rates of substitution between F and each of the six amino acids within one nucleotide substitution of F or from these amino acids back to F are affected by the parameter <i>ρ</i>, the amino acid toggling rate. All other non-synonymous substitutions have a multiplier <i>ω</i> instead of <i>ρ</i>. Rates of all substitutions depend on the frequency parameters , where <i>c</i> represents the codon class. The parameters take account of the codon bias estimated across the entire alignment and free parameters <i>t<sub>c</sub></i> which describe the proportion of time spent by the site in each of the three codon classes.</p>", "links"=>[], "tags"=>["amino"], "article_id"=>583189, "categories"=>["Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Cathal Seoighe"], "doi"=>"https://dx.doi.org/10.1371/journal.ppat.1000242.g001", "stats"=>{"downloads"=>3, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Codon_model_of_amino_acid_toggling_/583189", "title"=>"Codon model of amino acid toggling.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-12-19 00:53:09"}
  • {"files"=>["https://ndownloader.figshare.com/files/913244"], "description"=>"<p><i>AIC,</i> Akaike Information Criterion; <i>T,</i> toggling model where <i>ρ</i> is unconstrained in alternate; <i>D,</i> diversifying selection model.</p>", "links"=>[], "tags"=>["diversifying", "compared", "toggling", "hiv-1"], "article_id"=>583700, "categories"=>["Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Cathal Seoighe"], "doi"=>"https://dx.doi.org/10.1371/journal.ppat.1000242.t003", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Fit_of_the_diversifying_selection_compared_to_the_toggling_model_for_HIV_1_sequences_/583700", "title"=>"Fit of the diversifying selection compared to the toggling model for HIV-1 sequences.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2008-12-19 01:01:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/912916"], "description"=>"<p>ROC curves indicating power and false positive rates for the detection of diversifying selection (left panel), diversifying selection and toggling (centre panel), and toggling (right panel) for each of the five parameter sets (<a href=\"http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1000242#ppat-1000242-t001\" target=\"_blank\">Table 1</a>) simulated.</p>", "links"=>[], "tags"=>["computational biology/evolutionary modeling", "virology/immune evasion"], "article_id"=>583375, "categories"=>["Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Cathal Seoighe"], "doi"=>"https://dx.doi.org/10.1371/journal.ppat.1000242.g003", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Evaluation_of_power_and_false_positives_/583375", "title"=>"Evaluation of power and false positives.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-12-19 00:56:15"}
  • {"files"=>["https://ndownloader.figshare.com/files/913183"], "description"=>"#<p>sites without HLA associated polymorphisms.</p>*<p>sites detected with diversifying selection model (D); <i>WT,</i> wild type states are amino acids for which there is a significant difference between null and alternate models in a likelihood ratio test (boldface indicates state with largest log likelihood); E, escape; R, reversion; <i>t<sub>c</sub></i>, proportion of time spent in class c (<a href=\"http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1000242#ppat-1000242-g001\" target=\"_blank\">Figure 1</a>) for wild type state with the largest likelihood.</p>", "links"=>[], "tags"=>["allele", "polymorphisms", "toggling"], "article_id"=>583639, "categories"=>["Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Cathal Seoighe"], "doi"=>"https://dx.doi.org/10.1371/journal.ppat.1000242.t004", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_HLA_allele_associated_polymorphisms_4_at_detected_toggling_sites_/583639", "title"=>"HLA allele associated polymorphisms [4] at detected toggling sites.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2008-12-19 01:00:39"}
  • {"files"=>["https://ndownloader.figshare.com/files/912808"], "description"=>"<p>Data was simulated under purifying selection, neutrality, diversifying selection, or toggling to evaluate power and false positives rates. (A) Amino acid sequence logos <a href=\"http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1000242#ppat.1000242-Crooks1\" target=\"_blank\">[73]</a> of ten randomly drawn codon sites for each category of simulated site. (B) Simulated toggling site mapped to HIV-1 phylogeny showing the occurrence of escape (red arrows) and reversion (green arrows) mutations. (C) Simulated diversifying selection site mapped to HIV-1 phylogeny.</p>", "links"=>[], "tags"=>["hiv-1"], "article_id"=>583269, "categories"=>["Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Cathal Seoighe"], "doi"=>"https://dx.doi.org/10.1371/journal.ppat.1000242.g002", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Simulation_along_HIV_1_nef_phylogeny_/583269", "title"=>"Simulation along HIV-1 <i>nef</i> phylogeny.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-12-19 00:54:29"}
  • {"files"=>["https://ndownloader.figshare.com/files/913275"], "description"=>"<p><i>ρ,</i> non-synonymous to synonymous rate ratio associated with mutations away from or towards wild type amino acid; <i>ω,</i> non-synonymous to synonymous rate ratio for mutations not involving wild type; <i>T,</i> toggling model where <i>ρ</i> is unconstrained in alternate; <i>T<sub>(u)</sub></i>, toggling model in which both <i>ρ</i> and <i>ω</i> are unconstrained; <i>D,</i> diversifying selection model.</p>", "links"=>[], "tags"=>["computational biology/evolutionary modeling", "virology/immune evasion"], "article_id"=>583734, "categories"=>["Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Cathal Seoighe"], "doi"=>"https://dx.doi.org/10.1371/journal.ppat.1000242.t001", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Power_to_detect_selection_with_alternative_models_/583734", "title"=>"Power (%) to detect selection with alternative models.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2008-12-19 01:02:14"}
  • {"files"=>["https://ndownloader.figshare.com/files/913114"], "description"=>"<p>Amino acid sequence logos <a href=\"http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1000242#ppat.1000242-Crooks1\" target=\"_blank\">[73]</a> of positively selected sites, diversifying selection (D), toggling (T), or both (D&T), indexed by HXB2 position in <i>nef</i> are shown.</p>", "links"=>[], "tags"=>["positively"], "article_id"=>583571, "categories"=>["Infectious Diseases"], "users"=>["Wayne Delport", "Konrad Scheffler", "Cathal Seoighe"], "doi"=>"https://dx.doi.org/10.1371/journal.ppat.1000242.g005", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Amino_acid_diversity_at_positively_selected_sites_/583571", "title"=>"Amino acid diversity at positively selected sites.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2008-12-19 00:59:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/451957", "https://ndownloader.figshare.com/files/451986", "https://ndownloader.figshare.com/files/452024", "https://ndownloader.figshare.com/files/452056", "https://ndownloader.figshare.com/files/452083", "https://ndownloader.figshare.com/files/452121"], "description"=>"<div><p>Host immune responses against infectious pathogens exert strong selective pressures favouring the emergence of escape mutations that prevent immune recognition. Escape mutations within or flanking functionally conserved epitopes can occur at a significant cost to the pathogen in terms of its ability to replicate effectively. Such mutations come under selective pressure to revert to the wild type in hosts that do not mount an immune response against the epitope. Amino acid positions exhibiting this pattern of escape and reversion are of interest because they tend to coincide with immune responses that control pathogen replication effectively. We have used a probabilistic model of protein coding sequence evolution to detect sites in HIV-1 exhibiting a pattern of rapid escape and reversion. Our model is designed to detect sites that toggle between a wild type amino acid, which is susceptible to a specific immune response, and amino acids with lower replicative fitness that evade immune recognition. Through simulation, we show that this model has significantly greater power to detect selection involving immune escape and reversion than standard models of diversifying selection, which are sensitive to an overall increased rate of non-synonymous substitution. Applied to alignments of HIV-1 protein coding sequences, the model of immune escape and reversion detects a significantly greater number of adaptively evolving sites in <em>env</em> and <em>nef</em>. In all genes tested, the model provides a significantly better description of adaptively evolving sites than standard models of diversifying selection. Several of the sites detected are corroborated by association between Human Leukocyte Antigen (HLA) and viral sequence polymorphisms. Overall, there is evidence for a large number of sites in HIV-1 evolving under strong selective pressure, but exhibiting low sequence diversity. A phylogenetic model designed to detect rapid toggling between wild type and escape amino acids identifies a larger number of adaptively evolving sites in HIV-1, and can in some cases correctly identify the amino acid that is susceptible to the immune response.</p></div>", "links"=>[], "tags"=>["toggling", "amino", "acids", "driven", "hiv-1"], "article_id"=>149055, "categories"=>["Cancer"], "users"=>["Wayne Delport", "Konrad Scheffler", "Cathal Seoighe"], "doi"=>["https://dx.doi.org/10.1371/journal.ppat.1000242.s001", "https://dx.doi.org/10.1371/journal.ppat.1000242.s002", "https://dx.doi.org/10.1371/journal.ppat.1000242.s003", "https://dx.doi.org/10.1371/journal.ppat.1000242.s004", "https://dx.doi.org/10.1371/journal.ppat.1000242.s005", "https://dx.doi.org/10.1371/journal.ppat.1000242.s006"], "stats"=>{"downloads"=>14, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Frequent_Toggling_between_Alternative_Amino_Acids_Is_Driven_by_Selection_in_HIV_1/149055", "title"=>"Frequent Toggling between Alternative Amino Acids Is Driven by Selection in HIV-1", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2008-12-19 02:30:55"}

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