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{"title"=>"Efficient modeling of MS/MS data for metabolic flux analysis", "type"=>"journal", "authors"=>[{"first_name"=>"Naama", "last_name"=>"Tepper", "scopus_author_id"=>"35749142000"}, {"first_name"=>"Tomer", "last_name"=>"Shlomi", "scopus_author_id"=>"8592513400"}], "year"=>2015, "source"=>"PLoS ONE", "identifiers"=>{"pmid"=>"26230524", "sgr"=>"84941966264", "doi"=>"10.1371/journal.pone.0130213", "scopus"=>"2-s2.0-84941966264", "pui"=>"606056883", "isbn"=>"1932-6203 (Electronic) 1932-6203 (Linking)", "issn"=>"19326203"}, "id"=>"4b6d9f3e-7f6d-33b7-9eae-c2be475d98d3", "abstract"=>"Metabolic flux analysis (MFA) is a widely used method for quantifying intracellular metabolic fluxes. It works by feeding cells with isotopic labeled nutrients, measuring metabolite isoto- pic labeling, and computationally interpreting the measured labeling data to estimate flux. Tandem mass-spectrometry (MS/MS) has been shown to be useful for MFA, providing posi- tional isotopic labeling data. Specifically, MS/MS enables the measurement of a metabolite tandem mass-isotopomer distribution, representing the abundance in which certain parent and product fragments of a metabolite have different number of labeled atoms. However, a major limitation in using MFA with MS/MS data is the lack of a computationally efficient method for simulating such isotopic labeling data. Here, we describe the tandemer approach for efficiently computing metabolite tandem mass-isotopomer distributions in a metabolic network, given an estimation of metabolic fluxes. This approach can be used by MFA to find optimal metabolic fluxes, whose induced metabolite labeling patterns match tandem mass-isotopomer distributions measured by MS/MS. The tandemer approach is applied to simulate MS/MS data in a small-scale metabolic network model ofmammalian methionine metabolism and in a large-scalemetabolic network model of E. coli. It is shown to significantly improve the running time by between two to three orders of magnitude com- pared to the state-of-the-art, cumomers approach. We expect the tandemer approach to promote broader usage of MS/MS technology in metabolic flux analysis. Implementation is freely available at www.cs.technion.ac.il/~tomersh/methods.html", "link"=>"http://www.mendeley.com/research/efficient-modeling-msms-data-metabolic-flux-analysis", "reader_count"=>26, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>2, "Researcher"=>6, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>8, "Student > Postgraduate"=>1, "Student > Master"=>2, "Other"=>2, "Student > Bachelor"=>2, "Professor"=>2}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>2, "Researcher"=>6, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>8, "Student > Postgraduate"=>1, "Student > Master"=>2, "Other"=>2, "Student > Bachelor"=>2, "Professor"=>2}, "reader_count_by_subject_area"=>{"Engineering"=>3, "Unspecified"=>1, "Environmental Science"=>1, "Biochemistry, Genetics and Molecular Biology"=>7, "Agricultural and Biological Sciences"=>10, "Medicine and Dentistry"=>1, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Chemical Engineering"=>1, "Computer Science"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>3}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>10}, "Computer Science"=>{"Computer Science"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>7}, "Unspecified"=>{"Unspecified"=>1}, "Environmental Science"=>{"Environmental Science"=>1}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}, "Chemical Engineering"=>{"Chemical Engineering"=>1}}, "reader_count_by_country"=>{"Slovenia"=>1, "Russia"=>1}, "group_count"=>0}

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• http://doi.org/10.3389/fmicb.2019.01022
• http://doi.org/10.1021/acs.analchem.7b05329
• http://doi.org/10.1016/j.copbio.2016.10.010
• http://doi.org/10.3389/fmicb.2019.00031
• http://doi.org/10.1021/acs.analchem.5b03887

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Figshare

• {"files"=>["https://ndownloader.figshare.com/files/2196950"], "description"=>"<p>(a) Metabolite A and its MFP </p><p></p><p></p><p></p><p><mi>A</mi></p><p></p><p></p><p><mn>2,3</mn></p><p></p><p></p><p></p><p></p><p><mn>2,3</mn><mo>,</mo><mn>4</mn></p><p></p><p></p><p></p><p></p><p></p> with parent fragment N = {2,3,4} and product fragment K = {2,3}. (b) The tandemer distribution matrix <p></p><p></p><p></p><p><mo>[</mo><mi>A</mi><mo>]</mo></p><p></p><p></p><p><mn>2,3</mn></p><p></p><p></p><p></p><p></p><p><mn>2,3</mn><mo>,</mo><mn>4</mn></p><p></p><p></p><p></p><p></p><p></p>. The abundance of infeasible tandemers in <p></p><p></p><p></p><p><mo>[</mo><mi>A</mi><mo>]</mo></p><p></p><p></p><p><mn>2,3</mn></p><p></p><p></p><p></p><p></p><p><mn>2,3</mn><mo>,</mo><mn>4</mn></p><p></p><p></p><p></p><p></p><p></p> is, by definition, zero.<p></p>", "links"=>[], "tags"=>["Metabolic Flux Analysis Metabolic flux analysis", "network model", "mfa", "tandemer approach", "data", "metabolite", "ms"], "article_id"=>1499462, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Naama Tepper", "Tomer Shlomi"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0130213.g001", "stats"=>{"downloads"=>2, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Efficient_Modeling_of_MS_MS_Data_for_Metabolic_Flux_Analysis_Fig_1_/1499462", "title"=>"Efficient Modeling of MS/MS Data for Metabolic Flux Analysis - Fig 1", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-07-31 03:12:03"}
• {"files"=>["https://ndownloader.figshare.com/files/2196951"], "description"=>"<p>Calculating the tandemer distribution matrix of a product MFP based on tandemer distribution matrices of substrate MFPs in uni-substrate (a) and bi-substrate (b) reactions.</p>", "links"=>[], "tags"=>["Metabolic Flux Analysis Metabolic flux analysis", "network model", "mfa", "tandemer approach", "data", "metabolite", "ms"], "article_id"=>1499463, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Naama Tepper", "Tomer Shlomi"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0130213.g002", "stats"=>{"downloads"=>0, "page_views"=>16, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Calculating_the_tandemer_distribution_matrix_of_a_product_MFP_based_on_tandemer_distribution_matrices_of_substrate_MFPs_in_uni_substrate_a_and_bi_substrate_b_reactions_/1499463", "title"=>"Calculating the tandemer distribution matrix of a product MFP based on tandemer distribution matrices of substrate MFPs in uni-substrate (a) and bi-substrate (b) reactions.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-07-31 03:12:03"}
• {"files"=>["https://ndownloader.figshare.com/files/2196952"], "description"=>"<p>First, given MS/MS measurements and a metabolic model, a minimal set of MFPs is identified constructing an MFP graph. Second, MFPs are clustered and sorted and third, isotopic balance equations are formulated for each MFP cluster. Given a candidate flux vector, tandemer distributions are calculated by solving the set of isotopic balance equations.</p>", "links"=>[], "tags"=>["Metabolic Flux Analysis Metabolic flux analysis", "network model", "mfa", "tandemer approach", "data", "metabolite", "ms"], "article_id"=>1499464, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Naama Tepper", "Tomer Shlomi"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0130213.g003", "stats"=>{"downloads"=>0, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_An_outline_of_the_tandemers_approach_/1499464", "title"=>"An outline of the tandemers approach.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-07-31 03:12:03"}
• {"files"=>["https://ndownloader.figshare.com/files/2196953"], "description"=>"<p>(a) A toy metabolic network, where the labeling pattern of A that is supplied in the media is assumed to be known, and the tandemer distribution of </p><p></p><p></p><p></p><p><mo>[</mo><mi>E</mi><mo>]</mo></p><p></p><p></p><p><mn>2,3</mn></p><p></p><p></p><p></p><p></p><p><mn>1,2</mn><mo>,</mo><mn>3,4</mn></p><p></p><p></p><p></p><p></p><p></p> is to be calculated; (b) Atom mapping for network reactions; (c) An MFP graph and three strongly connected components whose numbering is determined via topological sorting.<p></p>", "links"=>[], "tags"=>["Metabolic Flux Analysis Metabolic flux analysis", "network model", "mfa", "tandemer approach", "data", "metabolite", "ms"], "article_id"=>1499465, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Naama Tepper", "Tomer Shlomi"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0130213.g004", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Efficient_Modeling_of_MS_MS_Data_for_Metabolic_Flux_Analysis_Fig_4_/1499465", "title"=>"Efficient Modeling of MS/MS Data for Metabolic Flux Analysis - Fig 4", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-07-31 03:12:03"}
• {"files"=>["https://ndownloader.figshare.com/files/2196954"], "description"=>"<p>Metabolites abbreviations: SAM: S-Adenosylmethionine; SAH: S-Adenosylhomocysteine; HCyc: L-Homocysteine; MTA: Methylthioadenosine.</p>", "links"=>[], "tags"=>["Metabolic Flux Analysis Metabolic flux analysis", "network model", "mfa", "tandemer approach", "data", "metabolite", "ms"], "article_id"=>1499466, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Naama Tepper", "Tomer Shlomi"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0130213.g005", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Methionine_metabolism_including_transmethylation_cycle_polyamine_biosynthesis_and_methionine_salvage_cycle_/1499466", "title"=>"Methionine metabolism, including transmethylation cycle, polyamine biosynthesis and methionine salvage cycle.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2015-07-31 03:12:03"}
• {"files"=>["https://ndownloader.figshare.com/files/2196955"], "description"=>"<p>Isotopomers are represented by sequences of zeroes and ones, denoting non-labeled and labeled atoms, respectively.</p><p>The distribution of isotopomers of metabolite A (shown in <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0130213#pone.0130213.g002\" target=\"_blank\">Fig 2</a>) within tandemers of A, defined with respect to </p><p></p><p></p><p></p><p><mi>A</mi></p><p></p><p></p><p><mn>2,3</mn></p><p></p><p></p><p></p><p></p><p><mn>2,3</mn><mo>,</mo><mn>4</mn></p><p></p><p></p><p></p><p></p><p></p>.<p></p>", "links"=>[], "tags"=>["Metabolic Flux Analysis Metabolic flux analysis", "network model", "mfa", "tandemer approach", "data", "metabolite", "ms"], "article_id"=>1499467, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Naama Tepper", "Tomer Shlomi"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0130213.t001", "stats"=>{"downloads"=>4, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_distribution_of_isotopomers_of_metabolite_A_shown_in_Fig_2_within_tandemers_of_A_defined_with_respect_to_A_2_3_2_3_4__/1499467", "title"=>"The distribution of isotopomers of metabolite A (shown in Fig 2) within tandemers of A, defined with respect to A2,32,3,4.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-07-31 03:12:03"}
• {"files"=>["https://ndownloader.figshare.com/files/2196956"], "description"=>"<p>Comparison of the performance of the cumomers and tandemers methods in calculating tandemer distributions on mammalian methionine and <i>E</i>. <i>coli</i> networks.</p>", "links"=>[], "tags"=>["Metabolic Flux Analysis Metabolic flux analysis", "network model", "mfa", "tandemer approach", "data", "metabolite", "ms"], "article_id"=>1499468, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Naama Tepper", "Tomer Shlomi"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0130213.t002", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_the_performance_of_the_cumomers_and_tandemers_methods_in_calculating_tandemer_distributions_on_mammalian_methionine_and_E_coli_networks_/1499468", "title"=>"Comparison of the performance of the cumomers and tandemers methods in calculating tandemer distributions on mammalian methionine and <i>E</i>. <i>coli</i> networks.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-07-31 03:12:03"}
• {"files"=>["https://ndownloader.figshare.com/files/2196957"], "description"=>"<div><p>Metabolic flux analysis (MFA) is a widely used method for quantifying intracellular metabolic fluxes. It works by feeding cells with isotopic labeled nutrients, measuring metabolite isotopic labeling, and computationally interpreting the measured labeling data to estimate flux. Tandem mass-spectrometry (MS/MS) has been shown to be useful for MFA, providing positional isotopic labeling data. Specifically, MS/MS enables the measurement of a metabolite tandem mass-isotopomer distribution, representing the abundance in which certain parent and product fragments of a metabolite have different number of labeled atoms. However, a major limitation in using MFA with MS/MS data is the lack of a computationally efficient method for simulating such isotopic labeling data. Here, we describe the tandemer approach for efficiently computing metabolite tandem mass-isotopomer distributions in a metabolic network, given an estimation of metabolic fluxes. This approach can be used by MFA to find optimal metabolic fluxes, whose induced metabolite labeling patterns match tandem mass-isotopomer distributions measured by MS/MS. The tandemer approach is applied to simulate MS/MS data in a small-scale metabolic network model of mammalian methionine metabolism and in a large-scale metabolic network model of <i>E</i>. <i>coli</i>. It is shown to significantly improve the running time by between two to three orders of magnitude compared to the state-of-the-art, cumomers approach. We expect the tandemer approach to promote broader usage of MS/MS technology in metabolic flux analysis. Implementation is freely available at <a href=\"http://www.cs.technion.ac.il/~tomersh/methods.html\" target=\"_blank\">www.cs.technion.ac.il/~tomersh/methods.html</a></p></div>", "links"=>[], "tags"=>["Metabolic Flux Analysis Metabolic flux analysis", "network model", "mfa", "tandemer approach", "data", "metabolite", "ms"], "article_id"=>1499469, "categories"=>["Biological Sciences", "Ecology"], "users"=>["Naama Tepper", "Tomer Shlomi"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0130213", "stats"=>{"downloads"=>8, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Efficient_Modeling_of_MS_MS_Data_for_Metabolic_Flux_Analysis_/1499469", "title"=>"Efficient Modeling of MS/MS Data for Metabolic Flux Analysis", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2015-07-31 03:12:03"}

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{"start_date"=>"2015-01-01T00:00:00Z", "end_date"=>"2015-12-31T00:00:00Z", "subject_areas"=>[]}

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