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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,89 @@ | ||
| % keep biomass at fixed value? | ||
| changeCobraSolver('ibm_cplex', 'all',0); | ||
| load(fullfile('model','iRi1574.mat')); | ||
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| % find minimum uptake of palmitate at optimal biomass | ||
| minFlux = fluxVariability(model,'rxnNameList', 'r1007_e0'); | ||
| model.ub(findRxnIDs(model,'r1007_e0')) = minFlux; | ||
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| % find optimal growth rate | ||
| bio_idx = find(model.c); | ||
| sol = optimizeCbModel(model); | ||
| mu_opt = sol.f; | ||
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| carbonSources = { | ||
| 'm0564[e0]' % D-glucose | ||
| 'm0588[e0]' % D-fructose | ||
| 'm0047[e0]' % raffinose | ||
| 'm1282[e0]' % melibiose | ||
| 'm0366[e0]' % D-xylose (Sugiura et al., PNAS Vol. 117, 2020) | ||
| 'm0028[e0]' % acetate (Pfeffer et al., Plant Physiol. Vol. 120, 1999) | ||
| 'm1331[e0]' % myristate (Sugiura et al., PNAS Vol. 117, 2020) | ||
| 'm0129[e0]' % glycine | ||
| 'm1335[e0]' % gycerol (Bago et al., Plant Physiol. Vol. 131, 2003) | ||
| 'm0239[c0]' % trehalose | ||
| }; | ||
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| oldUptake = { | ||
| 'r1533_e0' % D-Glucose | ||
| 'r1534_e0' % D-Fructose | ||
| 'r1006_e0' % myo-Inositol | ||
| 'r1002_e0' % Glycine | ||
| 'r1633_e0' % Myristate | ||
| }; | ||
| cSourceNames = regexprep(model.metNames(findMetIDs(model, carbonSources)),'_','-'); | ||
| % remove all carbon sources | ||
| model = removeRxns(model,oldUptake,'metFlag',false); | ||
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| % add sink reaction for cytosolic ATP | ||
| model = addSinkReactions(model,'m0464[c0]',0,1000); | ||
| model.c(:) = 0; | ||
| model.c(end) = 1; | ||
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| mu_perc = [50 0]; | ||
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| atp_production = zeros(numel(carbonSources),numel(mu_perc)); | ||
| carbon_source_upt = zeros(numel(carbonSources),numel(mu_perc)); | ||
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| for i=1:numel(carbonSources) | ||
| for j=1:numel(mu_perc) | ||
| tmpModel = addExchangeRxn(model,carbonSources(i)); | ||
| tmpModel.lb(bio_idx) = mu_perc(j)*mu_opt/100; | ||
| s = optimizeCbModel(tmpModel); | ||
| if s.stat == 1 | ||
| atp_production(i,j) = s.f; | ||
| carbon_source_upt(i,j) = abs(s.x(end)); | ||
| end | ||
| end | ||
| end | ||
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| colors = [[142,153,204];[236,176,80]]/255; | ||
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| labels = categorical(cSourceNames); | ||
| labels = reordercats(labels,cSourceNames); | ||
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| subplot(1,2,1) | ||
| b=bar(labels,atp_production'); | ||
| ylabel('ATP production [mmol/gDW/h]','FontSize',14) | ||
| set(gca,'LineWidth',1.3,'FontSize',14) | ||
| l=legend(strsplit(strtrim(sprintf('%d%% ',100-mu_perc))),'LineWidth',1,... | ||
| 'FontSize',10,'NumColumns',2,'Location','northwest','Box','off'); | ||
| title(l,'Allowed growth reduction') | ||
| b(1).FaceColor = colors(1,:); | ||
| b(2).FaceColor = colors(2,:); | ||
| text(-0.2,1.01,'A','units','normalized','fontweight','bold','fontsize',14) | ||
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| subplot(1,2,2) | ||
| b=bar(labels,atp_production' ./ carbon_source_upt'); | ||
| ylabel('ATP yield','FontSize',14) | ||
| set(gca,'LineWidth',1.3, 'FontSize',14) | ||
| l=legend(strsplit(strtrim(sprintf('%d%% ',100-mu_perc))),'LineWidth',1,... | ||
| 'FontSize',10,'NumColumns',2,'Location','northwest','Box','off'); | ||
| title(l,'Allowed growth reduction') | ||
| b(1).FaceColor = colors(1,:); | ||
| b(2).FaceColor = colors(2,:); | ||
| text(-0.2,1.01,'B','units','normalized','fontweight','bold','fontsize',14) | ||
|
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| print(fullfile('results','figures','atp-production.png'),'-painters','-dpng') |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,87 +1,87 @@ | ||
| % calculate growth rates from hyphae dry weights, dry weight of parent | ||
| % spores and growth duration | ||
| % DW(t) = DW(0) * exp(mu * t) | ||
| % <==> mu = ln( DW(t) / DW(0) ) / t | ||
| topDir = ''; | ||
|
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||
| % read growth predictions with FBA and eMOMENT with different carbon sources and | ||
| % concentration as in Hildebrandt et al. 2006 | ||
| mu_emoment = readtable([topDir, 'results\carbon-sources\growth.csv'],... | ||
| 'ReadVariableNames', false, 'ReadRowNames', true); | ||
| carbonSourceNames = mu_emoment.Properties.RowNames; | ||
| concentrations = [10 100 1000]; | ||
| mu_emoment = table2array(mu_emoment); | ||
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| mu_fba = readtable([topDir, 'results\carbon-sources\growth-fba.csv'],... | ||
| 'ReadVariableNames', false, 'ReadRowNames', true); | ||
| mu_fba = table2array(mu_fba); | ||
|
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| % Total protein from Table 2 in Hildebrandt et al. 2006 (10.1111/j.1574-6968.2005.00027.x) | ||
| p_tot = [ | ||
| 91 95 96; | ||
| 88 98 89; | ||
| 102 103 106; | ||
| 83 86 75; | ||
| ]/1000; | ||
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| % Final hyphal dry weight from Table 2 in Hildebrandt et al. 2006 (10.1111/j.1574-6968.2005.00027.x) | ||
| DW_t = [ | ||
| 3.4 3.6 3.3; | ||
| 3.2 3.3 3.1; | ||
| 3.7 4 4.5; | ||
| 3.3 3.5 3 | ||
| ]; | ||
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| % Number of parent spores from Hildebrandt et al. 2006: started experiment from 1000 spores | ||
| n_spores = 1000; | ||
| % spore dry weight (Sugiura et al. 2020, 10.1073/pnas.2006948117) (Fig S1) | ||
| weight_per_spore = .3E-6; | ||
| DW_0 = weight_per_spore*n_spores; | ||
| % Growth duration from Hildebrandt et al. 2006: 2.5 month (transform to | ||
| % hours) | ||
| t = 2.5 * 30 * 24; | ||
| % calculate growth rate | ||
| mu = log(DW_t / DW_0) / t; | ||
|
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| % calculate correlations: | ||
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| [rho,pval] = corr(reshape(mu,numel(mu),1),reshape(mu_emoment,numel(mu_emoment),1),... | ||
| 'type', 'Spearman'); | ||
| fprintf('Spearman correlation calculated growth rate vs eMOMENT growth rate: %.2g (p=%.2g)\n',... | ||
| rho, pval) | ||
| [rho,pval] = corr(reshape(mu,numel(mu),1),reshape(mu_emoment,numel(mu_emoment),1)); | ||
| fprintf('Pearson correlation calculated growth rate vs eMOMENT growth rate: %.2g (p=%.2g)\n\n',... | ||
| rho, pval) | ||
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| [rho, pval] = corr(reshape(mu,numel(mu),1),reshape(mu_fba,numel(mu_fba),1),... | ||
| 'type', 'Spearman'); | ||
| fprintf('Spearman correlation calculated growth rate vs FBA growth rate: %.2g (p=%.2g)\n',... | ||
| rho, pval) | ||
| [rho, pval] = corr(reshape(mu,numel(mu),1),reshape(mu_fba,numel(mu_fba),1)); | ||
| fprintf('Pearson correlation calculated growth rate vs FBA growth rate: %.2g (p=%.2g)\n\n',... | ||
| rho, pval) | ||
|
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| [rho, pval] = corr(reshape(mu_fba,numel(mu_fba),1),reshape(mu_emoment,numel(mu_emoment),1),... | ||
| 'type', 'Spearman'); | ||
| fprintf('Spearman correlation FBA growth rate vs eMOMENT growth rate: %.2g (p=%.2g)\n',... | ||
| rho, pval) | ||
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| [rho, pval] = corr(reshape(mu_fba,numel(mu_fba),1),reshape(mu_emoment,numel(mu_emoment),1)); | ||
| fprintf('Pearson correlation FBA growth rate vs eMOMENT growth rate: %.2g (p=%.2g)\n\n',... | ||
| rho, pval) | ||
|
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||
| [rho, pval] = corr(reshape(mu_emoment,numel(mu_emoment),1),reshape(p_tot,numel(p_tot),1),... | ||
| 'type', 'Spearman'); | ||
| fprintf('Spearman correlation eMOMENT growth rate vs measured protein content: %.2g (p=%.2g)\n',... | ||
| rho, pval) | ||
| [rho, pval] = corr(reshape(mu_emoment,numel(mu_emoment),1),reshape(p_tot,numel(p_tot),1)); | ||
| fprintf('Pearson correlation eMOMENT growth rate vs measured protein content: %.2g (p=%.2g)\n\n',... | ||
| rho, pval) | ||
|
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||
| [rho, pval] = corr(reshape(mu_fba,numel(mu_fba),1),reshape(p_tot,numel(p_tot),1),... | ||
| 'type', 'Spearman'); | ||
| fprintf('Spearman correlation FBA growth rate vs measured protein content: %.2g (p=%.2g)\n',... | ||
| rho, pval) | ||
| [rho, pval] = corr(reshape(mu_fba,numel(mu_fba),1),reshape(p_tot,numel(p_tot),1)); | ||
| fprintf('Pearson correlation FBA growth rate vs measured protein content: %.2g (p=%.2g)\n\n',... | ||
| % calculate growth rates from hyphae dry weights, dry weight of parent | ||
| % spores and growth duration | ||
| % DW(t) = DW(0) * exp(mu * t) | ||
| % <==> mu = ln( DW(t) / DW(0) ) / t | ||
| topDir = ''; | ||
|
|
||
| % read growth predictions with FBA and eMOMENT with different carbon sources and | ||
| % concentration as in Hildebrandt et al. 2006 | ||
| mu_emoment = readtable([topDir, 'results\carbon-sources\growth.csv'],... | ||
| 'ReadVariableNames', false, 'ReadRowNames', true); | ||
| carbonSourceNames = mu_emoment.Properties.RowNames; | ||
| concentrations = [10 100 1000]; | ||
| mu_emoment = table2array(mu_emoment); | ||
|
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||
| mu_fba = readtable([topDir, 'results\carbon-sources\growth-fba.csv'],... | ||
| 'ReadVariableNames', false, 'ReadRowNames', true); | ||
| mu_fba = table2array(mu_fba); | ||
|
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||
| % Total protein from Table 2 in Hildebrandt et al. 2006 (10.1111/j.1574-6968.2005.00027.x) | ||
| p_tot = [ | ||
| 91 95 96; | ||
| 88 98 89; | ||
| 102 103 106; | ||
| 83 86 75; | ||
| ]/1000; | ||
|
|
||
| % Final hyphal dry weight from Table 2 in Hildebrandt et al. 2006 (10.1111/j.1574-6968.2005.00027.x) | ||
| DW_t = [ | ||
| 3.4 3.6 3.3; | ||
| 3.2 3.3 3.1; | ||
| 3.7 4 4.5; | ||
| 3.3 3.5 3 | ||
| ]; | ||
|
|
||
| % Number of parent spores from Hildebrandt et al. 2006: started experiment from 1000 spores | ||
| n_spores = 1000; | ||
| % spore dry weight (Sugiura et al. 2020, 10.1073/pnas.2006948117) (Fig S1) | ||
| weight_per_spore = .3E-6; | ||
| DW_0 = weight_per_spore*n_spores; | ||
| % Growth duration from Hildebrandt et al. 2006: 2.5 month (transform to | ||
| % hours) | ||
| t = 2.5 * 30 * 24; | ||
| % calculate growth rate | ||
| mu = log(DW_t / DW_0) / t; | ||
|
|
||
| % calculate correlations: | ||
|
|
||
| [rho,pval] = corr(reshape(mu,numel(mu),1),reshape(mu_emoment,numel(mu_emoment),1),... | ||
| 'type', 'Spearman'); | ||
| fprintf('Spearman correlation calculated growth rate vs eMOMENT growth rate: %.2g (p=%.2g)\n',... | ||
| rho, pval) | ||
| [rho,pval] = corr(reshape(mu,numel(mu),1),reshape(mu_emoment,numel(mu_emoment),1)); | ||
| fprintf('Pearson correlation calculated growth rate vs eMOMENT growth rate: %.2g (p=%.2g)\n\n',... | ||
| rho, pval) | ||
|
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||
| [rho, pval] = corr(reshape(mu,numel(mu),1),reshape(mu_fba,numel(mu_fba),1),... | ||
| 'type', 'Spearman'); | ||
| fprintf('Spearman correlation calculated growth rate vs FBA growth rate: %.2g (p=%.2g)\n',... | ||
| rho, pval) | ||
| [rho, pval] = corr(reshape(mu,numel(mu),1),reshape(mu_fba,numel(mu_fba),1)); | ||
| fprintf('Pearson correlation calculated growth rate vs FBA growth rate: %.2g (p=%.2g)\n\n',... | ||
| rho, pval) | ||
|
|
||
| [rho, pval] = corr(reshape(mu_fba,numel(mu_fba),1),reshape(mu_emoment,numel(mu_emoment),1),... | ||
| 'type', 'Spearman'); | ||
| fprintf('Spearman correlation FBA growth rate vs eMOMENT growth rate: %.2g (p=%.2g)\n',... | ||
| rho, pval) | ||
|
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||
| [rho, pval] = corr(reshape(mu_fba,numel(mu_fba),1),reshape(mu_emoment,numel(mu_emoment),1)); | ||
| fprintf('Pearson correlation FBA growth rate vs eMOMENT growth rate: %.2g (p=%.2g)\n\n',... | ||
| rho, pval) | ||
|
|
||
| [rho, pval] = corr(reshape(mu_emoment,numel(mu_emoment),1),reshape(p_tot,numel(p_tot),1),... | ||
| 'type', 'Spearman'); | ||
| fprintf('Spearman correlation eMOMENT growth rate vs measured protein content: %.2g (p=%.2g)\n',... | ||
| rho, pval) | ||
| [rho, pval] = corr(reshape(mu_emoment,numel(mu_emoment),1),reshape(p_tot,numel(p_tot),1)); | ||
| fprintf('Pearson correlation eMOMENT growth rate vs measured protein content: %.2g (p=%.2g)\n\n',... | ||
| rho, pval) | ||
|
|
||
| [rho, pval] = corr(reshape(mu_fba,numel(mu_fba),1),reshape(p_tot,numel(p_tot),1),... | ||
| 'type', 'Spearman'); | ||
| fprintf('Spearman correlation FBA growth rate vs measured protein content: %.2g (p=%.2g)\n',... | ||
| rho, pval) | ||
| [rho, pval] = corr(reshape(mu_fba,numel(mu_fba),1),reshape(p_tot,numel(p_tot),1)); | ||
| fprintf('Pearson correlation FBA growth rate vs measured protein content: %.2g (p=%.2g)\n\n',... | ||
| rho, pval) |
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