Contextualization Procedure and Modeling of Monocyte Specific TLR Signaling
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{"title"=>"Contextualization Procedure and Modeling of Monocyte Specific TLR Signaling", "type"=>"journal", "authors"=>[{"first_name"=>"Maike K.", "last_name"=>"Aurich", "scopus_author_id"=>"56587738000"}, {"first_name"=>"Ines", "last_name"=>"Thiele", "scopus_author_id"=>"9037011100"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"scopus"=>"2-s2.0-84870853302", "sgr"=>"84870853302", "issn"=>"19326203", "pmid"=>"23236359", "doi"=>"10.1371/journal.pone.0049978", "pui"=>"366234617"}, "id"=>"9430199c-e940-3e90-81cb-3a6798173af4", "abstract"=>"Innate immunity is the first line of defense against invasion of pathogens. Toll-like receptor (TLR) signaling is involved in a variety of human diseases extending far beyond immune system-related diseases, affecting a number of different tissues and cell-types. Computational models often do not account for cell-type specific differences in signaling networks. Investigation of these differences and its phenotypic implications could increase understanding of cell signaling and processes such as inflammation. The wealth of knowledge for TLR signaling has been recently summarized in a stoichiometric signaling network applicable for constraint-based modeling and analysis (COBRA). COBRA methods have been applied to investigate tissue-specific metabolism using omics data integration. Comparable approaches have not been conducted using signaling networks. In this study, we present ihsTLRv2, an updated TLR signaling network accounting for the association of 314 genes with 558 network reactions. We present a mapping procedure for transcriptomic data onto signaling networks and demonstrate the generation of a monocyte-specific TLR network. The generated monocyte network is characterized through expression of a specific set of isozymes rather than reduction of pathway contents. While further tailoring the network to a specific stimulation condition, we observed that the quantitative changes in gene expression due to LPS stimulation affected the tightly connected set of genes. Differential expression influenced about one third of the entire TLR signaling network, in particular, NF-[Formula: see text]B activation. Thus, a cell-type and condition-specific signaling network can provide functional insight into signaling cascades. Furthermore, we demonstrate the energy dependence of TLR signaling pathways in monocytes.", "link"=>"http://www.mendeley.com/research/contextualization-procedure-modeling-monocyte-specific-tlr-signaling", "reader_count"=>27, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>2, "Researcher"=>10, "Student > Ph. D. Student"=>10, "Student > Master"=>1, "Student > Bachelor"=>3, "Professor"=>1}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>2, "Researcher"=>10, "Student > Ph. D. Student"=>10, "Student > Master"=>1, "Student > Bachelor"=>3, "Professor"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>4, "Unspecified"=>1, "Biochemistry, Genetics and Molecular Biology"=>4, "Agricultural and Biological Sciences"=>12, "Medicine and Dentistry"=>2, "Computer Science"=>3, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>4}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>2}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>12}, "Computer Science"=>{"Computer Science"=>3}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>4}, "Unspecified"=>{"Unspecified"=>1}}, "reader_count_by_country"=>{"Austria"=>1, "United States"=>1, "United Kingdom"=>1}, "group_count"=>3}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/529128"], "description"=>"<p><b>A.</b> The procedure for the generation of the monocyte specific model was divided into two parts. First, a suitable cutoff was defined for mapping the gene expression data. Therefore, preliminary monocyte models were generated for two cutoffs (p and p). Both cutoffs led to high numbers of blocked reactions and dead-end nodes in the networks. We identified the set of genes only absent in the more stringent cutoff and validated expression of the gene products using the Human Protein Atlas immunohistochemical data of two monocytic leukemia cell lines (THP-1 and U-937) and chose the cutoff, which represented monocyte protein expression the best. The second part of the procedure concerned the assurance of monocyte specific network functionality. Input and output capabilities of the monocyte model were curated according to cell-type specific literature evidence. <b>B.</b> Statistic of the number of deleted genes, reactions constrained during the data mapping, blocked reactions, and dead-end nodes in the preliminary monocyte models, the curated monocyte model (ihsMonoTLR), and the LPS stimulation specific monocyte model (ihsMonoTLR_LPS). <b>C.</b> Graph illustrating the detection probability of the genes absent in the stringent and present in the moderate cutoff. Genes are colored according to whether they were expressed (red), they were not expressed (blue), no data was available (pale), or data among cell lines was discriminating (purple). In many cases, no data was available, or the proteins were expressed in the cell lines. Only in few cases, the genes were not expressed in any of the cell lines. Also, absent gene expression was distributes across the entire range of the thresholds, such that no intermediate cutoff could be established. As a result, the monocyte model was based on the more moderate cutoff.</p>", "links"=>[], "tags"=>["cutoff", "monocyte"], "article_id"=>199629, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Maike K. Aurich", "Ines Thiele"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0049978.g002", "stats"=>{"downloads"=>0, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Definition_of_cutoff_for_initial_monocyte_draft_model_/199629", "title"=>"Definition of cutoff for initial monocyte draft-model.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-12-06 02:40:29"}
  • {"files"=>["https://ndownloader.figshare.com/files/529725"], "description"=>"<p>Fluxes are given in ().</p>", "links"=>[], "tags"=>["flux", "reactions", "tlr", "signaling"], "article_id"=>200222, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Maike K. Aurich", "Ines Thiele"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0049978.t003", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Maximum_possible_flux_values_for_output_reactions_in_the_different_TLR_signaling_models_/200222", "title"=>"Maximum possible flux values for output reactions in the different TLR signaling models.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-12-06 00:03:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/284950", "https://ndownloader.figshare.com/files/285040", "https://ndownloader.figshare.com/files/285087", "https://ndownloader.figshare.com/files/285235"], "description"=>"<div><p>Innate immunity is the first line of defense against invasion of pathogens. Toll-like receptor (TLR) signaling is involved in a variety of human diseases extending far beyond immune system–related diseases, affecting a number of different tissues and cell-types. Computational models often do not account for cell-type specific differences in signaling networks. Investigation of these differences and its phenotypic implications could increase understanding of cell signaling and processes such as inflammation. The wealth of knowledge for TLR signaling has been recently summarized in a stoichiometric signaling network applicable for constraint-based modeling and analysis (COBRA). COBRA methods have been applied to investigate tissue-specific metabolism using omics data integration. Comparable approaches have not been conducted using signaling networks. In this study, we present ihsTLRv2, an updated TLR signaling network accounting for the association of 314 genes with 558 network reactions. We present a mapping procedure for transcriptomic data onto signaling networks and demonstrate the generation of a monocyte-specific TLR network. The generated monocyte network is characterized through expression of a specific set of isozymes rather than reduction of pathway contents. While further tailoring the network to a specific stimulation condition, we observed that the quantitative changes in gene expression due to LPS stimulation affected the tightly connected set of genes. Differential expression influenced about one third of the entire TLR signaling network, in particular, NF-B activation. Thus, a cell-type and condition-specific signaling network can provide functional insight into signaling cascades. Furthermore, we demonstrate the energy dependence of TLR signaling pathways in monocytes.</p> </div>", "links"=>[], "tags"=>["contextualization", "modeling", "monocyte", "tlr", "signaling"], "article_id"=>116169, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Maike K. Aurich", "Ines Thiele"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0049978.s001", "https://dx.doi.org/10.1371/journal.pone.0049978.s002", "https://dx.doi.org/10.1371/journal.pone.0049978.s003", "https://dx.doi.org/10.1371/journal.pone.0049978.s004"], "stats"=>{"downloads"=>23, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Contextualization_Procedure_and_Modeling_of_Monocyte_Specific_TLR_Signaling__/116169", "title"=>"Contextualization Procedure and Modeling of Monocyte Specific TLR Signaling", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-12-06 01:42:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/529661"], "description"=>"*<p>Metabolite transporter did not have a chemical compound as the genes were only added to the transport reaction.</p>", "links"=>[], "tags"=>["absent"], "article_id"=>200163, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Maike K. Aurich", "Ines Thiele"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0049978.t004", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Distribution_of_absent_genes_/200163", "title"=>"Distribution of absent genes.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-12-06 00:02:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/529357"], "description"=>"<p>We extracted a sub-network from LPS stimulation specific monocyte model (ihsMonoTLR_LPS) consisting of all reactions associated with the 28 up-regulated genes, which included 19% of the reactions and 39% of the chemical compounds of ihsMonoTLR_LPS. The visualization revealed a comprehensively connected network. Details can be viewed using the file provided in the supporting information (<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049978#pone.0049978.s004\" target=\"_blank\">File S4</a>). Network illustration was generated using software Paint4Net <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049978#pone.0049978-Kostromins1\" target=\"_blank\">[65]</a>.</p>", "links"=>[], "tags"=>["resulting", "up-regulated", "genes", "lps", "stimulation", "monocyte"], "article_id"=>199855, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Maike K. Aurich", "Ines Thiele"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0049978.g004", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Network_resulting_from_mapping_of_the_up_regulated_genes_onto_the_LPS_stimulation_specific_monocyte_model_/199855", "title"=>"Network resulting from mapping of the up-regulated genes onto the LPS stimulation specific monocyte model.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-12-06 02:44:15"}
  • {"files"=>["https://ndownloader.figshare.com/files/529039"], "description"=>"<p>The workflow describes the process of generating cell-type specific, and subsequently cell and condition specific models of TLR signaling in four steps. (1) In the first step, Homo sapiens genes and gene-reaction associations were added to the model. Further, reactions and chemical compounds connected to the signaling of TLR11 were deleted and exchange reactions added. (2) Transcriptomic data was mapped to the model leading to preliminary monocyte specific models of TLR signaling using different cutoffs during the mapping process. (3) The most suitable preliminary model was chosen based on comparison with cell-type specific proteomic data (HPA) and literature evidence. Manual curation was essential to ensure monocyte specific input-output capabilities of the final monocyte model ihsMonoTLR. (4) Transcriptomic data derived from LPS stimulated monocytes was mapped to the ihsMonoTLR to tailor the model condition specific. Statistics on the network sizes at each stage reveal how network size remains comparable while gene contents reduced with increasing modeling resolution.</p>", "links"=>[], "tags"=>["ihstlrv1", "driven", "monocyte", "lps", "stimulated"], "article_id"=>199530, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Maike K. Aurich", "Ines Thiele"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0049978.g001", "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Workflow_leading_from_ihsTLRv1_to_a_data_driven_monocyte_and_LPS_stimulated_monocyte_model_/199530", "title"=>"Workflow leading from ihsTLRv1 to a data driven monocyte and LPS stimulated monocyte model.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-12-06 02:38:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/529747"], "description"=>"<p>Redundant genes comprise of all genes, which are associated with chemical compounds having isoforms.</p>", "links"=>[], "tags"=>["generic", "tlr"], "article_id"=>200247, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Maike K. Aurich", "Ines Thiele"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0049978.t002", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Statistics_of_the_gene_extension_of_the_generic_human_TLR_model_/200247", "title"=>"Statistics of the gene extension of the generic human TLR model.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-12-06 00:04:07"}
  • {"files"=>["https://ndownloader.figshare.com/files/529574"], "description"=>"<p>The sub-network that was extracted from ihsMonoTLR_LPS based on the three down-regulated genes comprised of 26 metabolites and eleven reactions. Illustration of the sub-network revealed three separated modules confirming that the impact of down-regulation, based on involvement, was rather small. Network illustration was generated using software Paint4Net <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049978#pone.0049978-Kostromins1\" target=\"_blank\">[65]</a>.</p>", "links"=>[], "tags"=>["modules", "resulting", "down-regulated", "genes", "lps", "stimulation", "monocyte", "tlr"], "article_id"=>200069, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Maike K. Aurich", "Ines Thiele"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0049978.g006", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Network_modules_resulting_from_mapping_of_the_down_regulated_genes_onto_the_LPS_stimulation_specific_monocyte_TLR_model_/200069", "title"=>"Network modules resulting from mapping of the down-regulated genes onto the LPS stimulation specific monocyte TLR model.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-12-06 00:01:09"}
  • {"files"=>["https://ndownloader.figshare.com/files/529226"], "description"=>"<p>hMonoTLR_LPS was used for the sensitivity analysis. The network contains nine output reactions for six distinct outputs ROS, IRF3, IRF7, CRE, AP-1, and NF-B. ROS,CRE, AP-1, and NF-B could be produced by all receptor inputs. Energy dependencies of output production did not differ among input receptors. IRF3 was only produced after stimulation of TLR4. IRF7 was only produced when TLR4 and either TLR7, TLR8 or TLR9 were stimulated together. In case of IRF7, we stimulated the network via TLR4 and TLR8.</p>", "links"=>[], "tags"=>["genetics and genomics", "Computational biology"], "article_id"=>199734, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Maike K. Aurich", "Ines Thiele"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0049978.g003", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sensitivity_analysis_/199734", "title"=>"Sensitivity analysis.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-12-06 02:42:14"}
  • {"files"=>["https://ndownloader.figshare.com/files/529490"], "description"=>"<p>We report the connectivity as a ratio of compound and (chemical compounds) in the respective model (ihsMonoTLR_LPS subnetwork and ihsMonoTLR_LPS).</p>", "links"=>[], "tags"=>["connectivity", "lps", "stimulation", "up-regulated"], "article_id"=>199987, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Maike K. Aurich", "Ines Thiele"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0049978.g005", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_chemical_compound_connectivity_in_the_LPS_stimulation_specific_versus_the_up_regulated_sub_network_/199987", "title"=>"Comparison of (chemical compound) connectivity in the LPS stimulation specific versus the up-regulated sub-network.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-12-06 02:46:27"}
  • {"files"=>["https://ndownloader.figshare.com/files/529697"], "description"=>"*<p>IRF7 can only be produced after stimulation of combinations of TLR receptors, TLR3 or TLR4 combined with either TLR7, TLR8 or TLR9.</p>", "links"=>[], "tags"=>["outputs", "covered", "generic", "monocyte", "tlr", "signaling"], "article_id"=>200193, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Maike K. Aurich", "Ines Thiele"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0049978.t001", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Inputs_and_outputs_covered_by_generic_ihsTLRv2_and_monocyte_specific_hMonoTLR_amp_hMonoTLR_LPS_TLR_signaling_models_/200193", "title"=>"Inputs and outputs covered by generic (ihsTLRv2) and monocyte specific (hMonoTLR & hMonoTLR_LPS) TLR signaling models.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-12-06 00:03:13"}

PMC Usage Stats | Further Information

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Relative Metric

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