Develop algorithms for gene deletion strategies for growth-coupled production

src/design/TrimGdel/GRPRchecker.m

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+function [GR ,PR] = GRPRchecker(model, targetMet, gvalue)
+% GRPRchecker calculates the maximum GR and the minimu PR 
+% under the GR maximization when a constraint-based model, a target
+% metabolite, and a gene deletion stratety are given.
+%
+% USAGE:
+%
+%    function [GR, PR]  
+%        = GRPRchecker(model, targetMet, givenGvalue)
+%
+% INPUTS:
+%    model:     COBRA model structure containing the following required fields to perform gDel_minRN.
+%
+%        *.rxns:       Rxns in the model
+%        *.mets:       Metabolites in the model
+%        *.genes:      Genes in the model
+%        *.grRules:    Gene-protein-reaction relations in the model
+%        *.S:          Stoichiometric matrix (sparse)
+%        *.b:          RHS of Sv = b (usually zeros)
+%        *.c:          Objective coefficients
+%        *.lb:         Lower bounds for fluxes
+%        *.ub:         Upper bounds for fluxes
+%        *.rev:        Reversibility of fluxes
+%
+%    targetMet:    target metabolites    (e.g.,  'btn_c')
+%    gvalue:       The first column is the list of genes in the original model.
+%                  The second column contains a 0/1 vector indicating which genes should be deleted.
+%                      0: indicates genes to be deleted.
+%                      1: indecates genes to be remained.
+%
+% OUTPUTS:
+%    GR:    the growth rate obained when the gene deletion strategy is
+%           applied and the growth rate is maximized.
+%    PR:    the minimum target metabolite production rate obained 
+%           when the gene deletion strategy is applied and the growth rate is maximized.
+% 
+% .. Author:    - Takeyuki Tamura, Mar 06, 2025
+%
+
+
+[model, targetRID, extype] = modelSetting(model, targetMet);
+
+m = size(model.mets, 1);
+n = size(model.rxns, 1);
+g = size(model.genes, 1);
+gid = find(model.c);
+pid = targetRID;
+
+
+model2 = model;
+[grRules0] = calculateGR(model, gvalue);
+lb2 = model.lb;
+ub2 = model.ub;
+
+for i=1:n
+    if grRules0{i, 4} == 0
+        lb2(i) = 0;
+        ub2(i) = 0;
+    end
+end
+
+gm.A = sparse(model.S);
+gm.obj = -model.c;
+gm.modelsense = 'Min';
+gm.sense = repmat('=', 1, size(model.S, 1));
+gm.lb = lb2;
+gm.ub = ub2;
+opt0 = gurobi(gm);
+
+[opt0.x(gid) opt0.x(pid)]
+
+GR0 = -opt0.objval;
+lb2(gid) = GR0;
+ub2(gid) = GR0;
+model2.c(gid) = 0;
+model2.c(pid) = 1;
+
+gm2.A = sparse(model.S);
+gm2.obj = model2.c;
+gm2.modelsense = 'Min';
+gm2.sense = repmat('=', 1, size(model.S, 1));
+gm2.lb = lb2;
+gm2.ub = ub2;
+opt1 = gurobi(gm2);
+
+GR = GR0
+PR = opt1.x(pid)
+[GR PR]
+
+return;
+end
+

src/design/TrimGdel/TrimGdel.m

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+function [gvalue, GR, PR, size1, size2, size3, success] = TrimGdel(model, targetMet, maxLoop, PRLB, GRLB)
+% TrimGdel appropriately considers GPR rules and determines 
+% a minimal gene deletion strategies to achieve growth-coupled production 
+% for a given target metabolite and a genome-scale model.
+% even in the worst-case analysis (ensures the weak-growth-coupled production).
+%
+% Gurobi is required for this version. 
+% The CPLEX version is available on https://github.com/MetNetComp/TrimGdel
+%
+% USAGE:
+%
+%    function [gvalue, GR, PR, size1, size2, size3, success] 
+%                      = TrimGdel(model, targetMet, maxLoop, PRLB, GRLB)
+%
+% INPUTS:
+%    model:    COBRA model structure containing the following required fields to perform gDel_minRN.
+%
+%        *.rxns:       Rxns in the model
+%        *.mets:       Metabolites in the model
+%        *.genes:      Genes in the model
+%        *.grRules:    Gene-protein-reaction relations in the model
+%        *.S:          Stoichiometric matrix (sparse)
+%        *.b:          RHS of Sv = b (usually zeros)
+%        *.c:          Objective coefficients
+%        *.lb:         Lower bounds for fluxes
+%        *.ub:         Upper bounds for fluxes
+%        *.rev:        Reversibility of fluxes
+%
+%    targetMet:    target metabolites    (e.g.,  'btn_c')
+%    maxLoop:      the maximum number of iterations in gDel_minRN
+%    PRLB:         the minimum required production rates of the target metabolites
+%                  when gDel-minRN searches the gene deletion
+%                  strategy candidates. 
+%                  (But it is not ensured to achieve this minimum required value
+%                  when GR is maximized withoug PRLB.)
+%    GRLB:         the minimum required growth rate 
+%                  when gDel-minRN searches the gene deletion
+%                  strategy candidates. 
+%
+% OUTPUTS:
+%    gvalue:     a small gene deletion strategy (obtained by TrimGdel).
+%                The first column is the list of genes.
+%                The second column is a 0/1 vector indicating which genes should be deleted.
+%                    0: indicates genes to be deleted.
+%                    1: indecates genes to be remained.
+%    GR:         the maximum growth rate when the obtained gene deletion
+%                strategy represented by gvalue is applied.
+%    PR:         the minimum production rate of the target metabolite under 
+%                the maximization of the growth rate when the obtained gene deletion
+%                strategy represented by gvalue is applied.
+%    size1:      the number of gene deletions after Step1.
+%    size2:      the number of gene deletions after Step2.
+%    size3:      the number of gene deletions after Step3.
+%    success:    indicates whether TrimGdel obained an appropriate gene
+%                deletion strategy. (1:success, 0:failure)
+%
+% NOTE:
+%
+%    T. Tamura, "Trimming Gene Deletion Strategies for Growth-Coupled 
+%    Production in Constraint-Based Metabolic Networks: TrimGdel," 
+%    in IEEE/ACM Transactions on Computational Biology and Bioinformatics,
+%    vol. 20, no. 2, pp. 1540-1549, 2023.
+%
+%    Comprehensive computational results are accumulated in MetNetComp
+%    database.
+%    https://metnetcomp.github.io/database1/indexFiles/index.html
+%
+%    T. Tamura, "MetNetComp: Database for Minimal and Maximal Gene-Deletion Strategies 
+%    for Growth-Coupled Production of Genome-Scale Metabolic Networks," 
+%    in IEEE/ACM Transactions on Computational Biology and Bioinformatics, 
+%    vol. 20, no. 6, pp. 3748-3758, 2023, 
+% 
+% .. Author:    - Takeyuki Tamura, Mar 06, 2025
+%
+
+[gvalue gr pr it success] = gDel_minRN(model, targetMet, maxLoop, PRLB, GRLB) % Step 1
+if success
+    [gvalue, GR, PR, size1, size2, size3] = step2and3(model, targetMet, gvalue) % Step 2 and 3
+else
+    gvalue = [];
+    GR = 0;
+    PR = 0;
+    size1 = 0;
+    size2 = 0;
+    size3 = 0;
+end
+
+end
+

src/design/TrimGdel/calculateGR.m

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+function [grRules] = calculateGR(model, gvalue)
+% calculateGR is a function of gDel_minRN that reads
+% a COBRA model and a 0-1 assignment for genes and outputs whether
+% each reaction is repressed or not.
+%
+% USAGE:
+%
+%    function [grRules] = calculateGR(model, gvalue)
+%
+% INPUTS:
+%    model:    COBRA model structure containing the following required fields to perform gDel_minRN.
+%
+%        *.rxns:       Rxns in the model
+%        *.mets:       Metabolites in the model
+%        *.genes:      Genes in the model
+%        *.grRules:    Gene-protein-reaction relations in the model
+%        *.S:          Stoichiometric matrix (sparse)
+%        *.b:          RHS of Sv = b (usually zeros)
+%        *.c:          Objective coefficients
+%        *.lb:         Lower bounds for fluxes
+%        *.ub:         Upper bounds for fluxes
+%        *.rev:        Reversibility of fluxes
+%
+%    gvalue:    The first column is the list of genes in the original model.
+%               The second column contains a 0/1 vector indicating which genes should be deleted.
+%                   0: indicates genes to be deleted.
+%                   1: indecates genes to be remained.
+%
+% OUTPUT:
+%    grRules:    The first column is the list of GPR-rules. If a reaction does
+%                not have a GPR-rule, it is represented as 1.
+%                In the second columun, each gene is converted to 0 or 1 based
+%                on the given 0-1 assignment, with AND converted to * and OR
+%                converted to +.
+%                The third comumn contains the calculation results from the
+%                second column.
+%                The fourth column is 0 if the third column is 0 and 1 if it is
+%                greater. If it is 0, the reaction is repressed; if it is 1, it
+%                is not repressed.
+% 
+% .. Author:    - Takeyuki Tamura, Mar 06, 2025
+%
+
+grRules = cell(size(model.rxns));
+for i=1:size(model.grRules, 1)
+    grRules{i, 1} = model.grRules{i,1};
+end
+for i = 1:size(model.rxns, 1)
+    if isempty(grRules{i, 1})==1
+        grRules{i,1} = '1';
+    end
+end
+grRules(:, 2) = strrep(grRules, 'or', '+');
+grRules(:,2) = strrep(grRules(:,2), 'and', '*');
+
+[xname2, index] = sortrows(gvalue(:,1), 'descend');
+for i=1:size(index, 1)
+   sorted_gvalue(i, 1) = gvalue{index(i, 1), 2}; 
+end
+for i = 1:size(model.genes, 1)
+    grRules(:, 2) = strrep(grRules(:, 2), xname2{i, 1},num2str(sorted_gvalue(i, 1)));
+end
+for i = 1:size(grRules, 1)
+    %i
+    if isempty(grRules{i, 2}) == 0
+        grRules{i, 3} = eval(grRules{i, 2});
+        if grRules{i, 3} > 0.9
+            grRules{i, 4} = 1;
+        else
+            grRules{i, 4} = 0;
+        end
+    else
+       grRules{i, 4} = -1; 
+    end
+end
+end
+

src/design/TrimGdel/example1.m

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+function [] = example1()
+% example1 calculates the gene deletion strategy for growth coupling
+% for succinate in e_coli_core.
+%
+% USAGE:
+%
+%     function [] = example1()
+%
+% .. Author:    - Takeyuki Tamura, Mar 05, 2025
+%
+
+
+load('e_coli_core.mat');
+model = e_coli_core;
+
+[gvalue, GR, PR, size1, size2, size3, success] = TrimGdel(model, 'succ_e', 10, 0.1, 0.1)
+
+end
+

src/design/TrimGdel/example2.m

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+function [outputArg1, outputArg2] = example2()
+% example2 calculates the gene deletion strategy for growth coupling
+% for biotin in iML1515.
+% 
+% USAGE:
+%
+%     function [] = example2()
+%
+% .. Author:    - Takeyuki Tamura, Mar 06, 2025
+%
+
+load('iML1515.mat');
+model = iML1515;
+[gvalue, GR, PR, size1, size2, size3, success] = TrimGdel(model, 'btn_c', 10, 0.1, 0.1)
+
+end
+

src/design/TrimGdel/example3.m

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+function [outputArg1, outputArg2] = example3()
+% example3 calculates the gene deletion strategy for growth coupling
+% for riboflavin in iML1515.
+% 
+% USAGE:
+%
+%     function [] = example3()
+% 
+% .. Author:    - Takeyuki Tamura, Mar 06, 2025
+%
+
+load('iML1515.mat');
+model = iML1515;
+
+[gvalue, GR, PR, size1, size2, size3, success] = TrimGdel(model, 'ribflv_c', 10, 0.1, 0.1)
+
+end
+

src/design/TrimGdel/example4.m

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+function [outputArg1, outputArg2] = exampl4()
+% example4 calculates the gene deletion strategy for growth coupling
+% for pantothenate in iML1515.
+% 
+% USAGE:
+%
+%     function [] = example4()
+%
+% .. Author:    - Takeyuki Tamura, Mar 06, 2025
+%
+
+load('iML1515.mat');
+model = iML1515;
+
+[gvalue, GR, PR, size1, size2, size3, success] = TrimGdel(model, 'pnto__R_c', 10, 0.1, 0.1)
+
+end
+

src/design/TrimGdel/example5.m

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+function [outputArg1, outputArg2] = example5()
+% example5 calculates the gene deletion strategy for growth coupling
+% for succinate in iMM904.
+% 
+% USAGE:
+%
+%     function [] = example5()
+%
+% .. Author:    - Takeyuki Tamura, Mar 06, 2025
+%
+
+load('iMM904.mat');
+model = iMM904;
+
+[gvalue, GR, PR, size1, size2, size3, success] = TrimGdel(model, 'succ_e', 10, 0.1, 0.1)
+
+end
+