Pathway Thermodynamics Highlights Kinetic Obstacles in Central Metabolism
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{"title"=>"Pathway Thermodynamics Highlights Kinetic Obstacles in Central Metabolism", "type"=>"journal", "authors"=>[{"first_name"=>"Elad", "last_name"=>"Noor", "scopus_author_id"=>"22835870600"}, {"first_name"=>"Arren", "last_name"=>"Bar-Even", "scopus_author_id"=>"9639181900"}, {"first_name"=>"Avi", "last_name"=>"Flamholz", "scopus_author_id"=>"55024090700"}, {"first_name"=>"Ed", "last_name"=>"Reznik", "scopus_author_id"=>"36239156300"}, {"first_name"=>"Wolfram", "last_name"=>"Liebermeister", "scopus_author_id"=>"8712747100"}, {"first_name"=>"Ron", "last_name"=>"Milo", "scopus_author_id"=>"57188697178"}], "year"=>2014, "source"=>"PLoS Computational Biology", "identifiers"=>{"isbn"=>"1553-7358 (Electronic)\\r1553-734X (Linking)", "scopus"=>"2-s2.0-84895727036", "pui"=>"372548696", "doi"=>"10.1371/journal.pcbi.1003483", "issn"=>"15537358", "pmid"=>"24586134", "sgr"=>"84895727036"}, "id"=>"dc1dbf50-cece-356d-bf04-a896184d62eb", "abstract"=>"In metabolism research, thermodynamics is usually used to determine the directionality of a reaction or the feasibility of a pathway. However, the relationship between thermodynamic potentials and fluxes is not limited to questions of directionality: thermodynamics also affects the kinetics of reactions through the flux-force relationship, which states that the logarithm of the ratio between the forward and reverse fluxes is directly proportional to the change in Gibbs energy due to a reaction (ΔrG'). Accordingly, if an enzyme catalyzes a reaction with a ΔrG' of -5.7 kJ/mol then the forward flux will be roughly ten times the reverse flux. As ΔrG' approaches equilibrium (ΔrG' = 0 kJ/mol), exponentially more enzyme counterproductively catalyzes the reverse reaction, reducing the net rate at which the reaction proceeds. Thus, the enzyme level required to achieve a given flux increases dramatically near equilibrium. Here, we develop a framework for quantifying the degree to which pathways suffer these thermodynamic limitations on flux. For each pathway, we calculate a single thermodynamically-derived metric (the Max-min Driving Force, MDF), which enables objective ranking of pathways by the degree to which their flux is constrained by low thermodynamic driving force. Our framework accounts for the effect of pH, ionic strength and metabolite concentration ranges and allows us to quantify how alterations to the pathway structure affect the pathway's thermodynamics. Applying this methodology to pathways of central metabolism sheds light on some of their features, including metabolic bypasses (e.g., fermentation pathways bypassing substrate-level phosphorylation), substrate channeling (e.g., of oxaloacetate from malate dehydrogenase to citrate synthase), and use of alternative cofactors (e.g., quinone as an electron acceptor instead of NAD). The methods presented here place another arrow in metabolic engineers' quiver, providing a simple means of evaluating the thermodynamic and kinetic quality of different pathway chemistries that produce the same molecules.", "link"=>"http://www.mendeley.com/research/pathway-thermodynamics-highlights-kinetic-obstacles-central-metabolism", "reader_count"=>238, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>12, "Researcher"=>60, "Student > Doctoral Student"=>12, "Student > Ph. D. Student"=>82, "Student > Postgraduate"=>7, "Student > Master"=>22, "Other"=>11, "Student > Bachelor"=>20, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>1, "Professor"=>7}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>12, "Researcher"=>60, "Student > Doctoral Student"=>12, "Student > Ph. D. Student"=>82, "Student > Postgraduate"=>7, "Student > Master"=>22, "Other"=>11, "Student > Bachelor"=>20, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>1, "Professor"=>7}, "reader_count_by_subject_area"=>{"Unspecified"=>8, "Agricultural and Biological Sciences"=>121, "Chemical Engineering"=>5, "Chemistry"=>3, "Computer Science"=>7, "Earth and Planetary Sciences"=>1, "Engineering"=>31, "Environmental Science"=>2, "Biochemistry, Genetics and Molecular Biology"=>44, "Mathematics"=>2, "Medicine and Dentistry"=>2, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Physics and Astronomy"=>9, "Immunology and Microbiology"=>2}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>2}, "Physics and Astronomy"=>{"Physics and Astronomy"=>9}, "Mathematics"=>{"Mathematics"=>2}, "Unspecified"=>{"Unspecified"=>8}, "Environmental Science"=>{"Environmental Science"=>2}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}, "Chemical Engineering"=>{"Chemical Engineering"=>5}, "Engineering"=>{"Engineering"=>31}, "Chemistry"=>{"Chemistry"=>3}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>121}, "Computer Science"=>{"Computer Science"=>7}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>44}}, "reader_count_by_country"=>{"Colombia"=>2, "Argentina"=>1, "United States"=>13, "United Kingdom"=>5, "India"=>2, "Canada"=>1, "Sweden"=>1, "Belgium"=>1, "Brazil"=>1, "Denmark"=>1, "Australia"=>1, "Germany"=>6, "Estonia"=>1}, "group_count"=>14}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1392158"], "description"=>"<p>Δ<sub>r</sub>G′ corresponds to the driving force of the net reaction (which depends on the concentrations of the substrates and products); ΔG<sup>‡</sup><sub>fwd</sub> to the thermodynamic barrier of the forward reaction, associated with the binding of the substrates and with the different reaction intermediates formed during catalysis; and ΔG<sup>‡</sup><sub>bwd</sub> corresponds to the thermodynamic barrier of the backward reaction, associated with the different reaction intermediates formed during catalysis and with the release of the products. All reactions are assumed to be catalyzed by the same amount of enzyme units. (A) High internal thermodynamic barrier and high thermodynamic driving force. (B) High internal thermodynamic barrier and low thermodynamic driving force. (C) Low internal thermodynamic barrier and low thermodynamic driving force. (D) Low internal thermodynamic barrier and high thermodynamic driving force.</p>", "links"=>[], "tags"=>["Biochemistry", "enzymes", "Enzyme kinetics", "metabolism", "Metabolic pathways", "Computational biology", "systems biology", "interplay", "flux", "energetic"], "article_id"=>939464, "categories"=>["Biological Sciences"], "users"=>["Elad Noor", "Arren Bar-Even", "Avi Flamholz", "Ed Reznik", "Wolfram Liebermeister", "Ron Milo"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003483.g004", "stats"=>{"downloads"=>3, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Schematic_representation_of_the_interplay_between_the_net_reaction_flux_and_the_internal_and_external_i_e_overall_or_net_energetic_profiles_/939464", "title"=>"Schematic representation of the interplay between the net reaction flux and the internal and external (i.e., overall or net) energetic profiles.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-02-20 02:43:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/1392156"], "description"=>"<p>(A) Structure of the TCA cycle. The reaction marked in red is the only one with a positive shadow price at pH 7.5. Non-cofactor metabolites shaded in green show positive shadow prices. (B) MDF as function of pH, as calculated for the TCA cycle and several of its similar variants. Solid cyan line: default metabolite concentration range used throughout this study (1 µM–10 mM). Dashed and dotted cyan lines: oxaloacetate concentration (marked as ‘OA’) is allowed to attain lower values, 100 nM and 10 nM, respectively. Solid magenta line: oxaloacetate is channeled (‘channeling’) between malate dehydrogenase and citrate synthase. Semi-dashed green line: quinone (‘MQO’) serves as the electron acceptor in malate oxidation, instead of NAD. The Flux-Force Efficacy axis, on the right, refers to the reactions that dissipate the smallest amount of Gibbs energy, and hence equal to the pathway MDF. The light grey line marks the values corresponding to pH 7.5, the pH used in (C). (C) The MDF and ATP yield per glucose of the different oxidative pathways. ‘PEP-GLX’ corresponds to the PEP-Glyoxylate pathway, which was found to operate in <i>E. coli</i> under glucose starvation <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003483#pcbi.1003483-Fischer1\" target=\"_blank\">[64]</a>. ‘<i>P. fluorescens</i>’ corresponds to the pathway used by <i>Pseudomonas fluorescens</i> under conditions of aluminum toxicity <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003483#pcbi.1003483-Singh1\" target=\"_blank\">[81]</a>. ‘OxPP’ corresponds to the oxidative pentose phosphate cycle, which can be used to fully oxidize sugars into CO<sub>2</sub>, providing NADPH for cellular activity. Reducing power was assumed to be converted to ATP via oxidative phosphorylation, where NADH or a pair of reduced ferredoxins give rise to 1.5 ATP molecules and reduced ubiquinone produces one ATP molecule. The structures of all pathways are given in <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003483#pcbi.1003483.s001\" target=\"_blank\">Figure S1</a>.</p>", "links"=>[], "tags"=>["Biochemistry", "enzymes", "Enzyme kinetics", "metabolism", "Metabolic pathways", "Computational biology", "systems biology", "oxidative"], "article_id"=>939461, "categories"=>["Biological Sciences"], "users"=>["Elad Noor", "Arren Bar-Even", "Avi Flamholz", "Ed Reznik", "Wolfram Liebermeister", "Ron Milo"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003483.g002", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_MDF_analysis_of_oxidative_pathways_/939461", "title"=>"MDF analysis of oxidative pathways.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-02-20 02:43:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/1392157"], "description"=>"<p>(A) Structure of EMP-glycolysis. (B) Structure of an EMP pathway variant in which substrate-level phosphorylation is bypassed. The reactions marked in red are those with positive shadow prices at pH 7.5. Non-cofactor metabolites shaded in green show positive shadow prices. (C) MDF as function of pH, as calculated for the EMP pathway (cyan) and for an EMP pathway variant in which substrate-level phosphorylation is bypassed (magenta). ‘SLP’ corresponds to substrate-level phosphorylation. The Flux-Force Efficacy axis, on the right, refers to the reactions that dissipate the smallest amount of Gibbs energy, and hence equal to the pathway MDF. The light grey line marks the values corresponding to pH 7.5, the pH used in (D). (D) The MDF and ATP yield per glucose of the different fermentation pathways. ‘ED’ corresponds to the Entner-Doudoroff pathway. ‘EDSP’ represents the semi-phosphorylative ED pathway, known to operate in several hyperthermophilic archaea lineages <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003483#pcbi.1003483-Verhees1\" target=\"_blank\">[84]</a>, <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003483#pcbi.1003483-Siebers1\" target=\"_blank\">[88]</a>, <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003483#pcbi.1003483-Ahmed1\" target=\"_blank\">[89]</a>. ‘EDNP’ represents the non-phosphorylative ED pathway, also known to operate in hyperthermophilic archaea <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003483#pcbi.1003483-Verhees1\" target=\"_blank\">[84]</a>, <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003483#pcbi.1003483-Siebers1\" target=\"_blank\">[88]</a>, <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003483#pcbi.1003483-Ahmed1\" target=\"_blank\">[89]</a>. ‘MGX’ corresponds to a variant of the EMP pathway in which dihydroxyacetone phosphate is converted into the toxic compound methylglyoxal when the concentration of inorganic phosphate becomes limiting <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003483#pcbi.1003483-Kalapos1\" target=\"_blank\">[85]</a>, <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003483#pcbi.1003483-Zhang1\" target=\"_blank\">[86]</a>, <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003483#pcbi.1003483-Hopper1\" target=\"_blank\">[87]</a>. ‘PKT’ represents a pathway, suggested long ago <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003483#pcbi.1003483-Schramm1\" target=\"_blank\">[103]</a>, that uses the pentose phosphate pathway in conjunction with the enzyme phosphoketolase that cleaves xylulose-phosphate to glyceraldehyde-phosphate and acetyl-phosphate <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003483#pcbi.1003483-Sonderegger1\" target=\"_blank\">[90]</a>, <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003483#pcbi.1003483-Bogorad1\" target=\"_blank\">[91]</a>. ‘EMP PFL’ corresponds to a variant of the EMP pathway that produces more ATP by using the enzyme pyruvate formate lyase and performing substrate-level phosphorylation on of acetyl-phosphate. The structures of all pathways are given in <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003483#pcbi.1003483.s002\" target=\"_blank\">Figure S2</a>.</p>", "links"=>[], "tags"=>["Biochemistry", "enzymes", "Enzyme kinetics", "metabolism", "Metabolic pathways", "Computational biology", "systems biology", "fermentation"], "article_id"=>939462, "categories"=>["Biological Sciences"], "users"=>["Elad Noor", "Arren Bar-Even", "Avi Flamholz", "Ed Reznik", "Wolfram Liebermeister", "Ron Milo"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003483.g003", "stats"=>{"downloads"=>0, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_MDF_analysis_of_fermentation_pathways_/939462", "title"=>"MDF analysis of fermentation pathways.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-02-20 02:43:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/1392155"], "description"=>"<p>(A) A functional relationship between the reaction driving force (−Δ<sub>r</sub>G′) and its Flux-Force Efficacy, as described in detail in the Methods section. (B) Schematic comparison between two pathways. Each pathway starts and ends with the same compounds, employs five enzymes and carries the same net flux. The kinetic parameters of all enzymes in both pathways, as well as enzyme and metabolite concentrations, are assumed to be identical. (C) Energetic profile of Embden-Meyerhof-Parnas glycolysis. Dashed black line corresponds to Δ<sub>r</sub>G′<sup>o</sup> values (metabolite concentrations of 1 M) of pathway reactions at pH 7.5. Red line corresponds to Δ<sub>r</sub>G′ values of pathway reactions after an optimization procedure that maximizes the driving force of the reactions having the lowest driving forces, as described in the Methods section.</p>", "links"=>[], "tags"=>["Biochemistry", "enzymes", "Enzyme kinetics", "metabolism", "Metabolic pathways", "Computational biology", "systems biology", "flux-force", "efficacy", "optimized", "driving-force"], "article_id"=>939460, "categories"=>["Biological Sciences"], "users"=>["Elad Noor", "Arren Bar-Even", "Avi Flamholz", "Ed Reznik", "Wolfram Liebermeister", "Ron Milo"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1003483.g001", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_Flux_Force_Efficacy_and_Minimum_Optimized_Driving_Force_MDF_/939460", "title"=>"The Flux-Force Efficacy and Minimum Optimized Driving-Force (MDF).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-02-20 02:43:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/1392161", "https://ndownloader.figshare.com/files/1392162", "https://ndownloader.figshare.com/files/1392163"], "description"=>"<div><p>In metabolism research, thermodynamics is usually used to determine the directionality of a reaction or the feasibility of a pathway. However, the relationship between thermodynamic potentials and fluxes is not limited to questions of directionality: thermodynamics also affects the kinetics of reactions through the flux-force relationship, which states that the logarithm of the ratio between the forward and reverse fluxes is directly proportional to the change in Gibbs energy due to a reaction (Δ<sub>r</sub>G′). Accordingly, if an enzyme catalyzes a reaction with a Δ<sub>r</sub>G′ of -5.7 kJ/mol then the forward flux will be roughly ten times the reverse flux. As Δ<sub>r</sub>G′ approaches equilibrium (Δ<sub>r</sub>G′ = 0 kJ/mol), exponentially more enzyme counterproductively catalyzes the reverse reaction, reducing the net rate at which the reaction proceeds. Thus, the enzyme level required to achieve a given flux increases dramatically near equilibrium. Here, we develop a framework for quantifying the degree to which pathways suffer these thermodynamic limitations on flux. For each pathway, we calculate a single thermodynamically-derived metric (the Max-min Driving Force, MDF), which enables objective ranking of pathways by the degree to which their flux is constrained by low thermodynamic driving force. Our framework accounts for the effect of pH, ionic strength and metabolite concentration ranges and allows us to quantify how alterations to the pathway structure affect the pathway's thermodynamics. Applying this methodology to pathways of central metabolism sheds light on some of their features, including metabolic bypasses (<i>e.g</i>., fermentation pathways bypassing substrate-level phosphorylation), substrate channeling (<i>e.g</i>., of oxaloacetate from malate dehydrogenase to citrate synthase), and use of alternative cofactors (<i>e.g</i>., quinone as an electron acceptor instead of NAD). The methods presented here place another arrow in metabolic engineers' quiver, providing a simple means of evaluating the thermodynamic and kinetic quality of different pathway chemistries that produce the same molecules.</p></div>", "links"=>[], "tags"=>["Biochemistry", "enzymes", "Enzyme kinetics", "metabolism", "Metabolic pathways", "Computational biology", "systems biology", "thermodynamics", "highlights", "kinetic", "obstacles"], "article_id"=>939466, "categories"=>["Biological Sciences"], "users"=>["Elad Noor", "Arren Bar-Even", "Avi Flamholz", "Ed Reznik", "Wolfram Liebermeister", "Ron Milo"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1003483.s001", "https://dx.doi.org/10.1371/journal.pcbi.1003483.s002", "https://dx.doi.org/10.1371/journal.pcbi.1003483.s003"], "stats"=>{"downloads"=>13, "page_views"=>75, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Pathway_Thermodynamics_Highlights_Kinetic_Obstacles_in_Central_Metabolism_/939466", "title"=>"Pathway Thermodynamics Highlights Kinetic Obstacles in Central Metabolism", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-02-20 02:43:43"}

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Relative Metric

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