24 Hours in the Life of HIV-1 in a T Cell Line
Publication Date
January 31, 2013
Journal
PLOS Pathogens
Authors
Pejman Mohammadi, Sébastien Desfarges, István Bartha, Beda Joos, et al
Volume
9
Issue
1
Pages
e1003161
DOI
http://doi.org/10.1371/journal.ppat.1003161
Publisher URL
http://journals.plos.org/plospathogens/article?id=10.1371%2Fjournal.ppat.1003161
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/23382686
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3561177
Europe PMC
http://europepmc.org/abstract/MED/23382686
Web of Science
000314464600055
Scopus
84875082482
Mendeley
http://www.mendeley.com/research/24-hours-life-hiv1-t-cell-line
Events
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Mendeley | Further Information

{"title"=>"24 Hours in the Life of HIV-1 in a T Cell Line", "type"=>"journal", "authors"=>[{"first_name"=>"Pejman", "last_name"=>"Mohammadi", "scopus_author_id"=>"55624611000"}, {"first_name"=>"Sébastien", "last_name"=>"Desfarges", "scopus_author_id"=>"15725123800"}, {"first_name"=>"István", "last_name"=>"Bartha", "scopus_author_id"=>"24334221500"}, {"first_name"=>"Beda", "last_name"=>"Joos", "scopus_author_id"=>"7004143325"}, {"first_name"=>"Nadine", "last_name"=>"Zangger", "scopus_author_id"=>"26538401500"}, {"first_name"=>"Miguel", "last_name"=>"Muñoz", "scopus_author_id"=>"21737624800"}, {"first_name"=>"Huldrych F.", "last_name"=>"Günthard", "scopus_author_id"=>"7005951278"}, {"first_name"=>"Niko", "last_name"=>"Beerenwinkel", "scopus_author_id"=>"9238131100"}, {"first_name"=>"Amalio", "last_name"=>"Telenti", "scopus_author_id"=>"36101797600"}, {"first_name"=>"Angela", "last_name"=>"Ciuffi", "scopus_author_id"=>"9534445600"}], "year"=>2013, "source"=>"PLoS Pathogens", "identifiers"=>{"isbn"=>"1553-7374 (Electronic)\\r1553-7366 (Linking)", "scopus"=>"2-s2.0-84875082482", "sgr"=>"84875082482", "pui"=>"368538290", "doi"=>"10.1371/journal.ppat.1003161", "pmid"=>"23382686", "issn"=>"15537366"}, "id"=>"c8cd261f-d53f-3241-8ac4-a7ddf2107832", "abstract"=>"HIV-1 infects CD4+ T cells and completes its replication cycle in approximately 24 hours. We employed repeated measurements in a standardized cell system and rigorous mathematical modeling to characterize the emergence of the viral replication intermediates and their impact on the cellular transcriptional response with high temporal resolution. We observed 7,991 (73%) of the 10,958 expressed genes to be modulated in concordance with key steps of viral replication. Fifty-two percent of the overall variability in the host transcriptome was explained by linear regression on the viral life cycle. This profound perturbation of cellular physiology was investigated in the light of several regulatory mechanisms, including transcription factors, miRNAs, host-pathogen interaction, and proviral integration. Key features were validated in primary CD4+ T cells, and with viral constructs using alternative entry strategies. We propose a model of early massive cellular shutdown and progressive upregulation of the cellular machinery to complete the viral life cycle.", "link"=>"http://www.mendeley.com/research/24-hours-life-hiv1-t-cell-line", "reader_count"=>135, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>3, "Student > Doctoral Student"=>3, "Researcher"=>33, "Student > Ph. D. Student"=>43, "Student > Postgraduate"=>4, "Other"=>6, "Student > Master"=>19, "Student > Bachelor"=>15, "Lecturer"=>1, "Professor"=>6}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>3, "Student > Doctoral Student"=>3, "Researcher"=>33, "Student > Ph. D. Student"=>43, "Student > Postgraduate"=>4, "Other"=>6, "Student > Master"=>19, "Student > Bachelor"=>15, "Lecturer"=>1, "Professor"=>6}, "reader_count_by_subject_area"=>{"Unspecified"=>4, "Engineering"=>1, "Biochemistry, Genetics and Molecular Biology"=>14, "Mathematics"=>1, "Agricultural and Biological Sciences"=>78, "Medicine and Dentistry"=>17, "Physics and Astronomy"=>1, "Chemistry"=>1, "Social Sciences"=>1, "Computer Science"=>2, "Immunology and Microbiology"=>14, "Pharmacology, Toxicology and Pharmaceutical Science"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>17}, "Chemistry"=>{"Chemistry"=>1}, "Social Sciences"=>{"Social Sciences"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>14}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>78}, "Computer Science"=>{"Computer Science"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>14}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>4}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}}, "reader_count_by_country"=>{"Venezuela"=>1, "Hungary"=>1, "Norway"=>1, "United States"=>1, "Brazil"=>1, "United Kingdom"=>2, "South Africa"=>1, "France"=>3, "Switzerland"=>4, "Peru"=>1, "Germany"=>1, "Spain"=>2}, "group_count"=>3}

CrossRef

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/498047"], "description"=>"<p>Principal component analysis is used to explore the overall variance structure of the transcriptome datasets. With each point representing a whole transcriptome sample, the figure presents the transcriptome of cells that were universally infected (HIV), cells exposed to heat-inactivated virus (Heat-inactivated), cells exposed to a mixture of 1∶10 infectious/heat-inactivated virus (HIV[1/10]), and non-infected cells (Mock). One mock sample failed and is not plotted. The transcriptome of mock cells and that of cells exposed to heat-inactivated viruses clustered together across the top principal components. Infected cells, on the other hand, spread away from the mock space as infection progressed, with the most distant dot corresponding to the latest time point (24 h). The mixture 1/10 infectious/noninfectious material occupies the intermediate space. Clustering of the two hours samples corresponds to end of cell exposure to the virus or control materials.</p>", "links"=>[], "tags"=>["changes", "infectious", "non-infectious", "viral"], "article_id"=>168557, "categories"=>["Microbiology", "Virology", "Information And Computing Sciences", "Mathematics", "Biological Sciences", "Genetics"], "users"=>["Pejman Mohammadi", "Sébastien Desfarges", "István Bartha", "Beda Joos", "Nadine Zangger", "Miguel Muñoz", "Huldrych F. Günthard", "Niko Beerenwinkel", "Amalio Telenti", "Angela Ciuffi"], "doi"=>"https://dx.doi.org/10.1371/journal.ppat.1003161.g004", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Transcriptome_changes_upon_exposure_to_infectious_and_non_infectious_viral_particles_/168557", "title"=>"Transcriptome changes upon exposure to infectious and non-infectious viral particles.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-01-31 02:22:37"}
  • {"files"=>["https://ndownloader.figshare.com/files/497773"], "description"=>"<p>(<b>A</b>) Raw data of measured viral replication intermediates (mean [dots] with one standard error) and curves of fitted progression model (solid lines). The temporal dynamics of each step in the viral life cycle was generated individually by modeling the net effect of production, decay, initial viral input, and experimental noise of the corresponding marker intermediate (<b><a href=\"http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003161#ppat.1003161.s001\" target=\"_blank\">Text S1</a></b> and <b>Figure S4</b> and <b>S5 in <a href=\"http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003161#ppat.1003161.s001\" target=\"_blank\">Text S1</a></b>). (<b>B</b>) Activity profile of individual steps of the viral life cycle estimated from the progression model. Each violin spans the 98% quantile of the viral step with width proportional to activity level at each given point in time. The plus symbol (‘+’) denotes the peak of the activity and the inner white violin its 95% bootstrap confidence interval. In the shaded area, expected values extrapolated beyond the last observed time point (24 h, dashed line) are shown.</p>", "links"=>[], "tags"=>["viral"], "article_id"=>168283, "categories"=>["Microbiology", "Virology", "Information And Computing Sciences", "Mathematics", "Biological Sciences", "Genetics"], "users"=>["Pejman Mohammadi", "Sébastien Desfarges", "István Bartha", "Beda Joos", "Nadine Zangger", "Miguel Muñoz", "Huldrych F. Günthard", "Niko Beerenwinkel", "Amalio Telenti", "Angela Ciuffi"], "doi"=>"https://dx.doi.org/10.1371/journal.ppat.1003161.g001", "stats"=>{"downloads"=>2, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Modeling_of_the_viral_life_cycle_/168283", "title"=>"Modeling of the viral life cycle.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-01-31 02:18:03"}
  • {"files"=>["https://ndownloader.figshare.com/files/498131"], "description"=>"<p>RT-qPCR was used to validate key patterns of expression using heat-inactivated virus, primary cells, and natural viral envelope. (<b>A</b>) Analysis of 14 representative genes using competent or heat-inactivated HIV-based vector. The graphs depict the 24 dynamics of expression (log<sub>2</sub> fold change of VSV.G pseudotyped HIV-infected over mock) of eight upregulated genes (red lines), five downregulated genes (blue), and one control (<i>RPL31</i>, black line) in SupT1 cells exposed to similar amount of viral particles, only competent HIV (top panel), 1∶10 competent HIV∶heat-inactivated HIV (middle panel), and only heat-inactivated HIV (bottom panel). (<b>B</b>) Analysis in primary CD4+ T cells isolated from two healthy blood donors. Depicted are the 24 dynamics of expression (log<sub>2</sub> fold change of VSV.G pseudotyped HIV-infected over mock) of the upregulated (red), downregulated (blue), and control (black) genes. (<b>C</b>) Correlation analysis of RT-qPCR for the 14 representative genes at all time points in primary cells (donor 1) infected by VSV.G or CXCR4 pseudotyped HIV. Log<sub>2</sub> fold change linear regression yielded <i>r<sup>2</sup></i> = 0.22, <i>p</i><10<sup>−4</sup>.</p>", "links"=>[], "tags"=>["genetics and genomics", "Virology", "microbiology", "Computational biology", "computer science", "mathematics"], "article_id"=>168636, "categories"=>["Microbiology", "Virology", "Information And Computing Sciences", "Mathematics", "Biological Sciences", "Genetics"], "users"=>["Pejman Mohammadi", "Sébastien Desfarges", "István Bartha", "Beda Joos", "Nadine Zangger", "Miguel Muñoz", "Huldrych F. Günthard", "Niko Beerenwinkel", "Amalio Telenti", "Angela Ciuffi"], "doi"=>"https://dx.doi.org/10.1371/journal.ppat.1003161.g005", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Core_gene_validation_/168636", "title"=>"Core gene validation.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-01-31 02:23:56"}
  • {"files"=>["https://ndownloader.figshare.com/files/497957"], "description"=>"<p>(<b>A</b>) Distribution of observed rates of integration: six gene groups (color coded) were defined based on the number of integrations per megabasepair (Mbp). Genes with no observed integration are depicted in grey. (<b>B</b>) Average level of expression of the six gene groups in Mock and HIV-infected cells during the 24-hour experiment. (<b>C</b>) Expected number of integration events in individual genes based on an empiric integration rate of 5.5 proviruses per haploid genome and on 40,430 observed unique integration sites (approx. 1% of all events).</p>", "links"=>[], "tags"=>["viral"], "article_id"=>168473, "categories"=>["Microbiology", "Virology", "Information And Computing Sciences", "Mathematics", "Biological Sciences", "Genetics"], "users"=>["Pejman Mohammadi", "Sébastien Desfarges", "István Bartha", "Beda Joos", "Nadine Zangger", "Miguel Muñoz", "Huldrych F. Günthard", "Niko Beerenwinkel", "Amalio Telenti", "Angela Ciuffi"], "doi"=>"https://dx.doi.org/10.1371/journal.ppat.1003161.g003", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Host_gene_expression_and_viral_integration_/168473", "title"=>"Host gene expression and viral integration.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-01-31 02:21:13"}
  • {"files"=>["https://ndownloader.figshare.com/files/497850"], "description"=>"<p>Temporal expression patterns of 7,991 genes modulated in concordance with key steps of viral replication (panel <b>A</b>) were grouped into 18 clusters with differential expression profiles at three phases of the viral life cycle, namely reverse transcription, integration, and late phase. The cluster code characters ‘+’ and ‘−’ mark significant (<i>p</i><10<sup>−2</sup>) upregulation and downregulation, respectively, while ‘o’ indicates no significant deviation from zero. For example, the cluster ‘−+o’ contains 373 genes downregulated during reverse transcription, upregulated during integration, and unregulated during the late phase. In total, six upregulated clusters (<b>B</b>), four clusters with mixed patterns of regulation (<b>C</b>), and eight downregulated clusters (<b>D</b>) were found. Details of clusters are available at the dedicated web resource <a href=\"http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1003161#ppat.1003161-Bartha1\" target=\"_blank\">[6]</a>.</p>", "links"=>[], "tags"=>["genes", "correlated", "viral"], "article_id"=>168362, "categories"=>["Microbiology", "Virology", "Information And Computing Sciences", "Mathematics", "Biological Sciences", "Genetics"], "users"=>["Pejman Mohammadi", "Sébastien Desfarges", "István Bartha", "Beda Joos", "Nadine Zangger", "Miguel Muñoz", "Huldrych F. Günthard", "Niko Beerenwinkel", "Amalio Telenti", "Angela Ciuffi"], "doi"=>"https://dx.doi.org/10.1371/journal.ppat.1003161.g002", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Clusters_of_host_genes_correlated_with_viral_progression_/168362", "title"=>"Clusters of host genes correlated with viral progression.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-01-31 02:19:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/481215"], "description"=>"<div><p>HIV-1 infects CD4+ T cells and completes its replication cycle in approximately 24 hours. We employed repeated measurements in a standardized cell system and rigorous mathematical modeling to characterize the emergence of the viral replication intermediates and their impact on the cellular transcriptional response with high temporal resolution. We observed 7,991 (73%) of the 10,958 expressed genes to be modulated in concordance with key steps of viral replication. Fifty-two percent of the overall variability in the host transcriptome was explained by linear regression on the viral life cycle. This profound perturbation of cellular physiology was investigated in the light of several regulatory mechanisms, including transcription factors, miRNAs, host-pathogen interaction, and proviral integration. Key features were validated in primary CD4+ T cells, and with viral constructs using alternative entry strategies. We propose a model of early massive cellular shutdown and progressive upregulation of the cellular machinery to complete the viral life cycle.</p> </div>", "links"=>[], "tags"=>["24", "hours", "hiv-1", "line"], "article_id"=>155286, "categories"=>["Microbiology", "Virology", "Information And Computing Sciences", "Mathematics", "Biological Sciences", "Genetics"], "users"=>["Pejman Mohammadi", "Sébastien Desfarges", "István Bartha", "Beda Joos", "Nadine Zangger", "Miguel Muñoz", "Huldrych F. Günthard", "Niko Beerenwinkel", "Amalio Telenti", "Angela Ciuffi"], "doi"=>"https://dx.doi.org/10.1371/journal.ppat.1003161", "stats"=>{"downloads"=>7, "page_views"=>52, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/24_Hours_in_the_Life_of_HIV_1_in_a_T_Cell_Line__/155286", "title"=>"24 Hours in the Life of HIV-1 in a T Cell Line", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-01-31 01:28:06"}

PMC Usage Stats | Further Information

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