Integrating Flux Balance Analysis into Kinetic Models to Decipher the Dynamic Metabolism of Shewanella oneidensis MR-1
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{"title"=>"Integrating flux balance analysis into kinetic models to decipher the dynamic metabolism of shewanella oneidensis MR-1", "type"=>"journal", "authors"=>[{"first_name"=>"Xueyang", "last_name"=>"Feng", "scopus_author_id"=>"57192368750"}, {"first_name"=>"You", "last_name"=>"Xu", "scopus_author_id"=>"36634915900"}, {"first_name"=>"Yixin", "last_name"=>"Chen", "scopus_author_id"=>"55721157800"}, {"first_name"=>"Yinjie J.", "last_name"=>"Tang", "scopus_author_id"=>"8639293100"}], "year"=>2012, "source"=>"PLoS Computational Biology", "identifiers"=>{"scopus"=>"2-s2.0-84861149640", "sgr"=>"84861149640", "issn"=>"1553734X", "isbn"=>"%(", "pmid"=>"22319437", "doi"=>"10.1371/journal.pcbi.1002376", "pui"=>"364830969"}, "id"=>"8f6d056d-510a-3e37-906c-2ac8cd3fa55e", "abstract"=>"Shewanella oneidensis MR-1 sequentially utilizes lactate and its waste products (pyruvate and acetate) during batch culture. To decipher MR-1 metabolism, we integrated genome-scale flux balance analysis (FBA) into a multiple-substrate Monod model to perform the dynamic flux balance analysis (dFBA). The dFBA employed a static optimization approach (SOA) by dividing the batch time into small intervals (i.e., ∼400 mini-FBAs), then the Monod model provided time-dependent inflow/outflow fluxes to constrain the mini-FBAs to profile the pseudo-steady-state fluxes in each time interval. The mini-FBAs used a dual-objective function (a weighted combination of \"maximizing growth rate\" and \"minimizing overall flux\") to capture trade-offs between optimal growth and minimal enzyme usage. By fitting the experimental data, a bi-level optimization of dFBA revealed that the optimal weight in the dual-objective function was time-dependent: the objective function was constant in the early growth stage, while the functional weight of minimal enzyme usage increased significantly when lactate became scarce. The dFBA profiled biologically meaningful dynamic MR-1 metabolisms: 1. the oxidative TCA cycle fluxes increased initially and then decreased in the late growth stage; 2. fluxes in the pentose phosphate pathway and gluconeogenesis were stable in the exponential growth period; and 3. the glyoxylate shunt was up-regulated when acetate became the main carbon source for MR-1 growth.", "link"=>"http://www.mendeley.com/research/integrating-flux-balance-analysis-kinetic-models-decipher-dynamic-metabolism-shewanella-oneidensis-m", "reader_count"=>155, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>8, "Researcher"=>42, "Student > Doctoral Student"=>12, "Student > Ph. D. Student"=>48, "Student > Postgraduate"=>8, "Student > Master"=>18, "Other"=>2, "Student > Bachelor"=>6, "Lecturer"=>1, "Professor"=>9}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>8, "Researcher"=>42, "Student > Doctoral Student"=>12, "Student > Ph. D. Student"=>48, "Student > Postgraduate"=>8, "Student > Master"=>18, "Other"=>2, "Student > Bachelor"=>6, "Lecturer"=>1, "Professor"=>9}, "reader_count_by_subject_area"=>{"Engineering"=>36, "Unspecified"=>6, "Environmental Science"=>3, "Biochemistry, Genetics and Molecular Biology"=>6, "Mathematics"=>4, "Agricultural and Biological Sciences"=>77, "Medicine and Dentistry"=>1, "Chemical Engineering"=>9, "Social Sciences"=>1, "Computer Science"=>8, "Immunology and Microbiology"=>1, "Earth and Planetary Sciences"=>3}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>36}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Social Sciences"=>{"Social Sciences"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>3}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>77}, "Computer Science"=>{"Computer Science"=>8}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>6}, "Mathematics"=>{"Mathematics"=>4}, "Unspecified"=>{"Unspecified"=>6}, "Environmental Science"=>{"Environmental Science"=>3}, "Chemical Engineering"=>{"Chemical Engineering"=>9}}, "reader_count_by_country"=>{"Republic of Singapore"=>1, "Sweden"=>1, "United States"=>10, "Brazil"=>1, "United Kingdom"=>1, "Mexico"=>1, "Chile"=>1, "Germany"=>2, "India"=>1}, "group_count"=>8}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/686465"], "description"=>"<p>Exchange coefficients for key metabolic pathways of MR-1.</p>", "links"=>[], "tags"=>["coefficients", "metabolic", "pathways"], "article_id"=>356961, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Xueyang Feng", "You Xu", "Yixin Chen", "Yinjie J. Tang"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002376.t002", "stats"=>{"downloads"=>6, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Exchange_coefficients_for_key_metabolic_pathways_of_MR_1_/356961", "title"=>"Exchange coefficients for key metabolic pathways of MR-1.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-02 01:56:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/686189"], "description"=>"<p>The yellow filled cycles are intracellular metabolites; the blue filled cycles are substrates and extracellular metabolites (LAC: extracellular lactate, PYR: extracellular pyruvate, ACT: extracellular acetate); the dashed lines indicate inactive pathways; the green filled boxes are reactions listed in iSO783. All the abbreviations refer to iSO783 <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002376#pcbi.1002376-Schuetz1\" target=\"_blank\">[7]</a>.</p>", "links"=>[], "tags"=>["flux", "distributions", "metabolic"], "article_id"=>356680, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Xueyang Feng", "You Xu", "Yixin Chen", "Yinjie J. Tang"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002376.g004", "stats"=>{"downloads"=>1, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Dynamic_flux_distributions_unit_mmol_g_DCW_h_in_central_metabolic_pathways_/356680", "title"=>"Dynamic flux distributions (unit: mmol/g DCW/h) in central metabolic pathways.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-02 01:51:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/685937"], "description"=>"<p>The green dots are the measurements, and the blue lines are the simulated growth by the empirical Monod model.</p>", "links"=>[], "tags"=>["genetics and genomics", "Computational biology"], "article_id"=>356429, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Xueyang Feng", "You Xu", "Yixin Chen", "Yinjie J. Tang"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002376.g002", "stats"=>{"downloads"=>2, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Monod_model_for_growth_kinetics_/356429", "title"=>"Monod model for growth kinetics.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-02 01:47:09"}
  • {"files"=>["https://ndownloader.figshare.com/files/349834", "https://ndownloader.figshare.com/files/349859", "https://ndownloader.figshare.com/files/349867", "https://ndownloader.figshare.com/files/349873", "https://ndownloader.figshare.com/files/349876", "https://ndownloader.figshare.com/files/349886", "https://ndownloader.figshare.com/files/349894", "https://ndownloader.figshare.com/files/349900"], "description"=>"<div><p><em>Shewanella oneidensis</em> MR-1 sequentially utilizes lactate and its waste products (pyruvate and acetate) during batch culture. To decipher MR-1 metabolism, we integrated genome-scale flux balance analysis (FBA) into a multiple-substrate Monod model to perform the dynamic flux balance analysis (dFBA). The dFBA employed a static optimization approach (SOA) by dividing the batch time into small intervals (i.e., ∼400 mini-FBAs), then the Monod model provided time-dependent inflow/outflow fluxes to constrain the mini-FBAs to profile the pseudo-steady-state fluxes in each time interval. The mini-FBAs used a dual-objective function (a weighted combination of “maximizing growth rate” and “minimizing overall flux”) to capture trade-offs between optimal growth and minimal enzyme usage. By fitting the experimental data, a bi-level optimization of dFBA revealed that the optimal weight in the dual-objective function was time-dependent: the objective function was constant in the early growth stage, while the functional weight of minimal enzyme usage increased significantly when lactate became scarce. The dFBA profiled biologically meaningful dynamic MR-1 metabolisms: 1. the oxidative TCA cycle fluxes increased initially and then decreased in the late growth stage; 2. fluxes in the pentose phosphate pathway and gluconeogenesis were stable in the exponential growth period; and 3. the glyoxylate shunt was up-regulated when acetate became the main carbon source for MR-1 growth.</p> </div>", "links"=>[], "tags"=>["integrating", "flux", "kinetic", "models", "decipher", "metabolism", "mr-1"], "article_id"=>129167, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Xueyang Feng", "You Xu", "Yixin Chen", "Yinjie J. Tang"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1002376.s001", "https://dx.doi.org/10.1371/journal.pcbi.1002376.s002", "https://dx.doi.org/10.1371/journal.pcbi.1002376.s003", "https://dx.doi.org/10.1371/journal.pcbi.1002376.s004", "https://dx.doi.org/10.1371/journal.pcbi.1002376.s005", "https://dx.doi.org/10.1371/journal.pcbi.1002376.s006", "https://dx.doi.org/10.1371/journal.pcbi.1002376.s007", "https://dx.doi.org/10.1371/journal.pcbi.1002376.s008"], "stats"=>{"downloads"=>68, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Integrating_Flux_Balance_Analysis_into_Kinetic_Models_to_Decipher_the_Dynamic_Metabolism_of_Shewanella_oneidensis_MR_1/129167", "title"=>"Integrating Flux Balance Analysis into Kinetic Models to Decipher the Dynamic Metabolism of <em>Shewanella oneidensis</em> MR-1", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-02-02 02:32:47"}
  • {"files"=>["https://ndownloader.figshare.com/files/685819"], "description"=>"<p>Flowchart of dFBA to decipher the dynamic metabolism of <i>S. oneidensis</i> MR-1.</p>", "links"=>[], "tags"=>["dfba", "decipher", "metabolism"], "article_id"=>356306, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Xueyang Feng", "You Xu", "Yixin Chen", "Yinjie J. Tang"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002376.g001", "stats"=>{"downloads"=>1, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Flowchart_of_dFBA_to_decipher_the_dynamic_metabolism_of_S_oneidensis_MR_1_/356306", "title"=>"Flowchart of dFBA to decipher the dynamic metabolism of <i>S. oneidensis</i> MR-1.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-02 01:45:06"}
  • {"files"=>["https://ndownloader.figshare.com/files/686070"], "description"=>"<p>Blue ○: growth rate determined by the Monod model. Red ○: dFBA prediction using the objective function (maximization of growth rate). Green □: dFBA prediction using dual-objective functions (maximization of growth rate and minimization of overall flux). Yellow ◊: the weight of the dual-objective functions that predicted the measured growth rates. Note: the summation of the square of fluxes (∑<i>v<sup>2</sup></i>) was a very large number (total 774 fluxes), so the magnitude of weight <i>w</i> was small.</p>", "links"=>[], "tags"=>["rates"], "article_id"=>356564, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Xueyang Feng", "You Xu", "Yixin Chen", "Yinjie J. Tang"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002376.g003", "stats"=>{"downloads"=>0, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Prediction_of_growth_rates_h_8722_1_/356564", "title"=>"Prediction of growth rates (h<sup>−1</sup>).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-02 01:49:24"}
  • {"files"=>["https://ndownloader.figshare.com/files/686309"], "description"=>"<p>The standard error for GC-MS measurement was below 0.02. <b>A1</b>: dynamic isotopomer simulation for glutamate from dFBA without considering reaction reversibility (dFBA w/o reversibility). <b>A2</b>: dynamic isotopomer simulation for glutamate from dFBA considering reaction reversibility (dFBA w/ reversibility). Bar plot: comparison of experimentally observed isotopomer labeling to simulated isotopomer labeling patterns of glutamate (<b>A1</b>: without considering reaction reversibility; <b>A2</b>: considering reaction reversibility). <b>B</b>: The model fitting of the isotopomer labeling data of five key amino acids (Ala, Gly, Ser, Asp, and Glu) at t = 24 and 30 h.</p>", "links"=>[], "tags"=>["observed", "simulated", "isotopomer", "labeling", "patterns", "proteinogenic", "amino"], "article_id"=>356793, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Xueyang Feng", "You Xu", "Yixin Chen", "Yinjie J. Tang"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002376.g005", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Experimentally_observed_and_simulated_isotopomer_labeling_patterns_M_57_in_proteinogenic_amino_acids_/356793", "title"=>"Experimentally observed and simulated isotopomer labeling patterns [M-57]<sup>+</sup> in proteinogenic amino acids.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-02 01:53:13"}
  • {"files"=>["https://ndownloader.figshare.com/files/686435"], "description"=>"<p>Parameters estimated in the empirical Monod model.</p>", "links"=>[], "tags"=>["empirical", "monod"], "article_id"=>356927, "categories"=>["Biological Sciences", "Genetics"], "users"=>["Xueyang Feng", "You Xu", "Yixin Chen", "Yinjie J. Tang"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1002376.t001", "stats"=>{"downloads"=>3, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Parameters_estimated_in_the_empirical_Monod_model_/356927", "title"=>"Parameters estimated in the empirical Monod model.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-02 01:55:27"}

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Relative Metric

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