Merge pull request #40 from SysBioChalmers/devel

v1.2.2

ComplementaryData/Lopes2019/exp_pFBA_exchFluxes.tsv

@@ -0,0 +1,25 @@
+reaction	reactionName	A120	A100	A80	A60	G120	G100	G80	G60	X120	X100	X80	X60
+r_1634	acetate exchange	-0.512667	-3.172305	-4.343820	-4.020462	-0.000000	-0.000000	-0.000000	-0.000000	-0.000000	-0.000000	-0.000000	-0.000000
+r_1654	ammonium exchange	-0.030923	-0.247279	-0.389617	-0.452686	-1.507276	-0.993742	-0.936494	-5.786349	-0.002223	-0.036967	-9.244457	-9.478203
+r_1672	carbon dioxide exchange	0.258000	3.215537	4.652600	3.503269	0.807700	2.311900	1.869300	3.000400	0.039452	0.394382	2.488000	3.088000
+r_1718	D-xylose exchange	-0.000000	-0.000000	-0.000000	-0.000000	-0.000000	-0.000000	-0.000000	-0.000000	-0.017241	-0.164336	-2.594055	-3.453143
+r_1761	ethanol exchange	0.000000	0.000000	0.000000	0.000000	0.000000	0.136508	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000
+r_1793	formate exchange	0.006539	0.000000	0.000000	0.000000	0.000000	0.000000	0.202581	0.000000	0.000000	0.000000	0.012118	0.012554
+r_1808	glycerol exchange	-0.000000	-0.000000	-0.000000	-0.000000	-1.003376	-5.226696	-6.285165	-13.274739	-0.000000	-0.000000	-0.000000	-0.000000
+r_1815	glyoxylate exchange	0.186315	0.000000	0.000000	0.000000	0.001652	0.000000	0.207868	0.000000	0.000000	0.000000	0.000000	0.000000
+r_1832	H+ exchange	-0.301951	-3.039587	-4.146997	-3.802682	1.105225	0.410663	2.027415	7.103974	-0.000245	-0.002014	8.956486	9.017361
+r_1861	iron(2+) exchange	-0.000000	-0.000000	-0.000000	-0.000000	-0.000000	-0.000000	-0.000000	-0.000000	-0.000000	-0.000000	-0.000000	-0.000000
+r_1865	isoamylol exchange	0.000000	0.043541	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000
+r_1873	L-alanine exchange	0.000000	0.000000	0.000000	0.000000	0.000000	0.175717	0.000000	4.079272	0.000000	0.000000	0.000000	0.000000
+r_1989	oxaloacetate(2-) exchange	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.499306	0.000000	0.000000	0.000000	0.000000	0.000000
+r_1992	oxygen exchange	-0.353445	-2.290040	-3.913066	-2.872298	-1.695843	-3.572956	-5.437861	-9.819611	-0.028052	-0.305925	-6.127170	-6.371272
+r_2005	phosphate exchange	-0.002299	-0.016636	-0.022741	-0.024849	-0.008556	-0.047134	-0.047384	-0.060969	-0.000245	-0.002014	-0.014598	-0.023036
+r_2033	pyruvate exchange	0.000000	0.000000	0.000000	0.000000	0.000000	1.435312	1.926621	4.411282	0.000000	0.000000	0.000000	0.000000
+r_2060	sulphate exchange	-0.000632	-0.519094	-0.007948	-0.009278	-0.002533	-0.016531	-0.018965	-0.034167	-0.000046	-0.000746	-0.005541	-0.008913
+r_2061	sulphite exchange	0.000000	0.514020	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000
+r_2091	urea exchange	0.000000	0.000000	0.000000	0.000000	0.691837	0.000000	0.000000	0.000000	0.000000	0.000000	4.485542	4.520198
+r_2100	water exchange	0.587434	4.270393	6.017051	5.279056	3.743349	11.968339	14.318412	29.461122	0.046558	0.484276	11.788595	12.588360
+r_2104	xylitol exchange	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.000000	0.001395	0.016699	0.687846	1.109349
+r_2111	growth	0.007818	0.062000	0.086000	0.101764	0.031000	0.162000	0.178000	0.233000	0.000800	0.007000	0.053900	0.090000
+EXC_OUT_s_3717	protein exchange (OUT)	0.000126	0.000981	0.001593	0.001480	0.001228	0.006778	0.006608	0.007255	0.000000	0.000000	0.000000	0.000000
+r_4046	non-growth associated maintenance reaction	0.000002	0.023711	5.820578	0.000034	3.240072	6.293890	13.820184	33.490490	0.105586	1.237592	8.291982	7.669704

ComplementaryData/Lopes2019/theor_maxLipid_exchFluxes.tsv

@@ -0,0 +1,12 @@
+reaction	acetate	glycerol	xylose	xylose (no PK-PTA)
+acetate exchange	-5.000000e-01	0	0	0
+ammonium exchange	-1.446275e-03	-1.999921e-03	-1.780501e-03	-1.709859e-03
+carbon dioxide exchange	5.032288e-01	3.130608e-01	3.884278e-01	4.126924e-01
+D-xylose exchange	0	0	-2.000000e-01	-2.000000e-01
+glycerol exchange	0	-3.333333e-01	0	0
+H+ exchange	-4.895723e-01	-1.238315e-01	1.283747e-02	1.232813e-02
+oxygen exchange	-3.075425e-01	-2.091307e-01	-1.475195e-01	-1.813422e-01
+phosphate exchange	-1.678881e-03	-2.321571e-03	-2.066861e-03	-1.984857e-03
+water exchange	5.529470e-01	7.151447e-01	4.496356e-01	4.714716e-01
+lipid backbone exchange	6.035038e-02	8.345300e-02	7.429701e-02	7.134922e-02
+lipid chain exchange	6.028702e-02	8.336538e-02	7.421900e-02	7.127431e-02

ComplementaryData/data/biomassCuration.csv

@@ -1,4 +1,4 @@
-metabolite,metID,pseudoreaction,coeff
+metabolite,metID,pseudoreaction,coeff
 dAMP,s_0584,DNA,-0.0023
 dCMP,s_0589,DNA,-0.0037
 dGMP,s_0615,DNA,-0.0037

ComplementaryData/data/fluxData_Lopes2019.csv

@@ -0,0 +1,13 @@
+,growth,acetate,glycerol,xylose,co2,o2,xylitol,ammonium,protExch,lipidsRatio,proteinRatio
+A120,0.009,0.512667333,,,0.258,-2.446423378,,0.011897343,0.000125786,0.534,0.233423761
+A100,0.062,3.172305443,,,4.243,-2.290039723,,0.102895526,0.000980834,0.4,0.238080093
+A80,0.086,4.343820155,,,5.749,-4.576271055,,0.189400418,0.001593176,0.378,0.278774698
+A60,0.114,4.020461624,,,5.12,-3.811746902,,0.241149653,0.001480052,0.272,0.277617088
+G120,0.031,,1.003375652,,0.8077,-4.03836813,,0.051908645,0.001227674,0.439,0.213697615
+G100,0.162,,5.226696569,,2.3119,-3.572956103,,0.419473453,0.006777971,0.523,0.294960672
+G80,0.178,,6.285164983,,1.8693,-5.437861108,,0.464773989,0.006607892,0.39,0.31817701
+G60,0.233,,13.2747394,,3.0004,-9.819610125,,1.304989817,0.007254707,0.366,0.488763919
+X120,0.0008,,,0.017240889,0.103,-2.163,0.001395384,0.000733333,0,0.6,0.1551
+X100,0.007,,,0.164335802,0.615,-2.321,0.01669892,0.008555556,3.367E-09,0.5,0.355409519
+X80,0.0539,,,2.594055279,2.488,-10.343,0.687846423,0.18528125,2.16139E-08,0.412,0.339935599
+X60,0.09,,,3.453142849,3.088,-9.067,1.109348557,0.452844198,0,0.334,0.324461679

ComplementaryScripts/Lopes2019/analyzeLopes.m

@@ -0,0 +1,177 @@
+clear;clc;if ~exist('scripts') | ~endsWith(scripts,'ComplementaryScripts'); run('../../init_rhtoGEM.m'); end
+%% Generate condition-specific models by modifying biomass composition and
+% constraining with measured fluxes
+model   = importModel([root '\ModelFiles\xml\rhto.xml']);
+
+%% Readjust some reactions
+model = setParam(model,'lb','r_4046',0); % NGAM set to zero, maximized later on
+
+% Add protein excretion reation.
+model           = addExchangeRxns(model,'out','s_3717');
+lipidPos        = find(contains(model.rxnNames,{'lipid backbone pseudoreaction','lipid chain pseudoreaction'}));
+[scaleLp,~]     = find(model.S(:,lipidPos)<0);
+ngamIdx = getIndexes(model,'r_4046','rxns');
+[~,allExIdx] = getExchangeRxns(model,'both');
+allExIdx = [allExIdx; getIndexes(model,'r_4046','rxns')]; % Include NGAM
+
+%% Load experimental data
+expDat      = readLopesData();
+cd([scripts '/experimental/'])
+
+%% Make condition specific models, set rates and adjust biomass equation
+clear out
+for i=1:length(expDat.sample)
+    models{i} = model;
+    %% Set exchange fluxes
+    models{i} = setParam(models{i},'eq',{'r_1634','r_1808','r_1718','r_1714'},[-expDat.rates(i,2:4),0]);
+    %% Scale lipids in biomass to fit measured total lipid content
+    fL = 1.01;
+    while abs(fL-1) > 0
+        fL0 = fL;
+        models{i}.S(scaleLp,lipidPos) = full(models{i}.S(scaleLp,lipidPos))*fL;
+        [~,~,~,~,~,L]   = sumBioMass(models{i});
+        fL              = expDat.lipids(i)/L;
+    end
+    %% Scale protein & other biomass components
+    [models{i},GAMpol]  = changeOtherComp(models{i},expDat,i);
+    models{i}           = setGAM(models{i},GAMpol);
+    %% Protein excretion
+    if ~(expDat.rates(i,9) == 0)
+        [~,P]  = sumBioMass(models{i}); % Weight of protein pseudometabolite
+        pIdx   = getIndexes(models{i},'EXC_OUT_s_3717','rxns');
+        models{i}.S(find(models{1}.S(:,pIdx)),pIdx) = -1/P; % Make flux represent 1 g/gDCW/h
+        models{i} = setParam(models{i},'eq','EXC_OUT_s_3717',expDat.rates(i,9));
+    end
+    %% Xylitol excretion, and limit gas exchanges
+    models{i} = setParam(models{i},'eq','r_2104',expDat.rates(i,7)); % Xylitol    
+    models{i} = setParam(models{i},'ub','r_1672',expDat.rates(i,5)); % CO2
+    models{i} = setParam(models{i},'lb','r_1992',expDat.rates(i,6)); % O2
+    models{i} = setParam(models{i},'ub','r_1654',-expDat.rates(i,8)); % Ammonium    
+    % Growth rate
+    sol(1,i)=solveLP(models{i},1);
+    sol(1,i)=solveLP(models{i},1);
+    out(:,i)=sol(1,i).x;
+    disp(['Growth rate in sample ' num2str(i) ': ' num2str(-sol(1,i).f)]);
+end
+
+%% Compare simulated growth with measured growth. Set the lower value as
+% lower bound and then maximize NGAM
+for i=1:length(models)
+   sim = sol(1,i).x(getIndexes(models{i},'r_2111','rxns'));
+   exp = expDat.rates(i,1);
+   models{i} = setParam(models{i},'lb','r_2111',min([sim,exp]));
+   models{i} = setParam(models{i},'obj','r_4046',1);
+   sol(1,i) = solveLP(models{i},1);
+   fba(:,i)=sol(1,i).x;
+end
+%% Attempt to fix CO2 and O2 close to measured value
+for i=1:length(models)
+    disp(['Model: ' num2str(i)])
+    models{i} = setParam(models{i},'obj','r_1672',1);
+    tmp2 = solveLP(models{i});
+    models{i} = setParam(models{i},'lb', 'r_1672', 0.999*-tmp2.f);
+    models{i} = setParam(models{i},'obj','r_1992',-1);
+    tmp2 = solveLP(models{i});
+    models{i} = setParam(models{i},'ub', 'r_1992', 0.999*tmp2.f);
+    models{i} = setParam(models{i},'obj','r_4046',1);
+    tmp2 = solveLP(models{i});
+    fba(:,i)=tmp2.x;
+    disp(num2str(-tmp2.f))
+end
+
+%% Random sampling
+% Fix measured exchange fluxes around 5% of the value from FBA
+exIdx = getIndexes(model,{'r_1634','r_1808','r_1718','r_1714',...
+    'EXC_OUT_s_3717','r_2104','r_1672','r_1992','r_1654','r_2111','r_4046'},'rxns');
+
+nsamples = 5000;%
+%load([root '/scrap/randsampl.mat'], 'goodRxns*')
+for i=1:numel(models)
+    % Fix measured exchange fluxes + NGAM around 5% of the value from FBA.
+    fluxes = sol(1,i).x(exIdx);
+    models{i} = setParam(models{i},'var',exIdx,fluxes,5);
+    if i==1
+        [~, goodRxns1] = randomSampling(models{i},1,true,true,true);
+    elseif i==5
+        [~, goodRxns5] = randomSampling(models{i},1,true,true,true);
+    elseif i==9
+        [~, goodRxns9] = randomSampling(models{i},1,true,true,true);
+    end
+    if i<5
+        rs{i} = randomSampling(models{i},nsamples,true,true,true,goodRxns1);
+    elseif i<9
+        rs{i} = randomSampling(models{i},nsamples,true,true,true,goodRxns5);
+    else
+        rs{i} = randomSampling(models{i},nsamples,true,true,true,goodRxns9);
+    end
+end
+
+for i=1:length(rs)
+    fluxMean(:,i) = full(mean(rs{i},2));
+    fluxSD(:,i) = full(std(rs{i},0,2));
+end
+
+save([root '/scrap/randsampl.mat'], 'fba', 'rs', 'fluxMean', 'models', 'goodRxns*','fluxSD')
+
+%% Write files
+%FBA results, only exchange fluxes. For internal fluxes, refer to mean from
+%random sampling.
+out = [models{1}.rxns models{1}.rxnNames num2cell(fba)];
+out = out(allExIdx,:);
+rmIdx = find(sum(cell2mat(out(:,3:end)),2) == 0);
+out(rmIdx,:) =[];
+fid = fopen([data '/Lopes2019/exp_pFBA_exchFluxes.tsv'],'w');
+fprintf(fid,['%s' repmat('\t%s',1,13) '\n'],["reaction" "reactionName" string(expDat.sample')]);
+for j=1:size(out,1)
+    fprintf(fid,['%s\t%s' repmat('\t%f',1,12) '\n'],out{j,:});
+end
+fclose(fid);
+
+%% Write file with all mean fluxes
+clear out;for i=1:numel(models); out(:,i) = fluxMean(:,i); end
+clear out2;for i=1:numel(models); out2(:,i) = fluxSD(:,i); end
+
+out = [models{1}.rxns models{1}.rxnNames num2cell(out) num2cell(out2)];
+fid = fopen([data '/Lopes2019/exp_randSampl_allFluxes.tsv'],'w');
+fprintf(fid,['%s' repmat('\t%s',1,25) '\n'],["rxnID" "reactionName" ...
+    strcat('mean_',string(expDat.sample')) strcat('std_',string(expDat.sample'))]);
+for j=1:length(out)
+    fprintf(fid,['%s\t%s' repmat('\t%d',1,24) '\n'],out{j,:});
+end
+fclose(fid);
+
+% Write exchange fluxes only
+out = out(allExIdx,:);
+rmIdx = find(sum(cell2mat(out(:,3:end)),2) == 0);
+out(rmIdx,:) =[];
+fid = fopen([data '/Lopes2019/exp_randSampl_exchFluxes.tsv'],'w');
+fprintf(fid,['%s' repmat('\t%s',1,25) '\n'],["rxnID" "reactionName" ...
+    strcat('mean_',string(expDat.sample')) strcat('std_',string(expDat.sample'))]);
+for j=1:length(out)
+    fprintf(fid,['%s\t%s' repmat('\t%d',1,24) '\n'],out{j,:});
+end
+fclose(fid);
+
+%% NADH and NADPH reactions
+for i={'NADPH','NADH'}
+    [fluxes, rxnIdx] = getMetProduction(models{1},i,fluxMean,true);
+    clear out
+    out.rxns    = models{1}.rxns(rxnIdx);
+    out.rxnNames= models{1}.rxnNames(rxnIdx);
+    out.rxnEqns = constructEquations(models{1},rxnIdx);
+    out.fluxes  = num2cell(fluxes);
+    out = [out.rxns out.rxnNames out.rxnEqns out.fluxes];
+    fid = fopen([data '/Lopes2019/exp_randSampl_' i{1} '_productionFluxes.tsv'],'w');
+    fprintf(fid,['%s' repmat('\t%s',1,14) '\n'],["rxnID" "rxnName" ...
+        "rxnEqn" string(expDat.sample')]);
+    for j=1:length(out)
+        fprintf(fid,['%s\t%s\t%s' repmat('\t%f',1,12) '\n'],out{j,:});
+    end
+    fclose(fid);
+end
+
+%% Export models
+for i=1:numel(models)
+    fn = ['rhto_' expDat.sample{i} '.xml'];
+    exportModel(models{i},[data '/Lopes2019/' fn]);
+end

ComplementaryScripts/Lopes2019/readLopesData.m

@@ -0,0 +1,12 @@
+function data = readLopesData()
+fid = fopen('../../ComplementaryData/data/fluxData_Lopes2019.csv');
+types = textscan(fid,repmat('%s',[1,12]),1,'Delimiter',',');
+dat = textscan(fid,['%s' repmat(' %f32 ',[1,11])],'Delimiter',',','HeaderLines',1);
+fclose(fid);
+data.types      = horzcat(types{2:end});
+data.sample     = dat{1};
+data.rates      = cat(2,dat{[2:10]});
+data.rates(isnan(data.rates)) = 0;
+data.lipids     = dat{11};
+data.protein    = dat{12};
+end

ComplementaryScripts/Lopes2019/theoretical_maxLipids.m

@@ -0,0 +1,60 @@
+clear;clc;if ~exist('scripts') | ~endsWith(scripts,'ComplementaryScripts'); run('../../init_rhtoGEM.m'); end
+%% Theoretical simulations
+% Take rhtoGEM model as it is
+cd([scripts '/experimental/']);
+model = importModel([root '\ModelFiles\xml\rhto.xml']);
+model.rev(getIndexes(model,{'r_1634','r_1718','r_1808'},'rxns')) = 1;
+
+% Allow excretion of lipid chains and backbones. This allows for optimizing
+% production of lipid pseudometabolite
+chainExIdx  = getIndexes(model,'r_4064','rxns');
+backbExIdx  = getIndexes(model,'r_4062','rxns');
+tmp = setParam(model,'ub',[chainExIdx,backbExIdx],1000);
+tmp = setParam(tmp,'obj','r_4062',1); % Maximize lipid pseudometabolite production
+tmp = setParam(tmp,'eq','r_4046',0); % Set NGAM to 0
+
+% Get optimal solutions for each carbon source
+tmp = setParam(tmp,'lb',{'r_1634','r_1808','r_1718','r_1714'},[-1/2,0,0,0]);
+solAce = solveLP(tmp,1);
+
+tmp = setParam(tmp,'lb',{'r_1634','r_1808','r_1718','r_1714'},[0,-1/3,0,0]);
+solGly = solveLP(tmp,1);
+
+tmp = setParam(tmp,'lb',{'r_1634','r_1808','r_1718','r_1714'},[0,0,-1/5,0]);
+solXyl = solveLP(tmp,1);
+
+rxnIdx = find(ismember(model.rxnNames,'phosphoketolase'));
+tmp = setParam(tmp,'eq',rxnIdx,0); % Disable phosphoketolase
+solXylnoPK = solveLP(tmp,1);
+
+% Print maximum lipid yields
+fprintf(['Lipid pseudometabolite produced per C from each carbon source:\n' ...
+    'Acetate: ' num2str(-solAce.f) ' Glycerol: ' num2str(-solGly.f) ...
+    ' Xylose: ' num2str(-solXyl.f) ' Xylose (no PK-PTA): ' num2str(-solXylnoPK.f) '\n'])
+
+% Write file with all fluxes
+out = [solAce.x, solGly.x, solXyl.x solXylnoPK.x];
+out = [model.rxnNames num2cell(out)];
+fid = fopen([data '/Lopes2019/theor_maxLipid_allFluxes.tsv'],'w');
+fprintf(fid,'%s\t%s\t%s\t%s\t%s\n',["reaction" "Acetate" "Glycerol" "Xylose" ...
+    "Xylose (no PK-PTA)"]);
+for j=1:length(out)
+    fprintf(fid,'%s\t%d\t%d\t%d\t%d\n',out{j,:});
+end
+fclose(fid);
+
+%% Write file with exchange fluxes
+[~,idx] = getExchangeRxns(model,'both');
+out = out(idx,:);
+
+% Remove exchange reactions not carrying flux
+rmIdx = sum(cell2mat(out(:,2:end)),2) == 0;
+out = out(~rmIdx,:);
+
+fid = fopen([data '/Lopes2019/theor_maxLipid_exchFluxes.tsv'],'w');
+fprintf(fid,['%s' repmat('\t%s',1,4) '\n'],["reaction" "acetate" ...
+    "glycerol" "xylose" "xylose (no PK-PTA)"]);
+for j=1:length(out)
+    fprintf(fid,['%s' repmat('\t%d',1,4) '\n'],out{j,:});
+end
+fclose(fid);

ComplementaryScripts/experimental/getMetProduction.m

@@ -0,0 +1,18 @@
+function [fluxes, rxnIdx] = getMetProduction(model,metName,solVector,nonZero)
+% Which fluxes produce/consume a metabolite (excluding transport
+% reactions).
+% nonZero   only include non zero fluxes, default false
+
+metLoc      = find(ismember(model.metNames,metName));
+subS        = full(model.S(metLoc,:));
+[~,rxnIdx]  = find(subS);
+coeff       = sum(subS(:,rxnIdx),1);
+
+fluxes = solVector(rxnIdx,:) .* transpose(coeff);
+
+if nonZero
+    nonZero     = sum(fluxes,2)~=0;
+    fluxes      = fluxes(nonZero,:);
+    rxnIdx      = rxnIdx(nonZero);
+end
+end

ComplementaryScripts/validation/geneEssentiality.m

@@ -37,4 +37,4 @@
 FN = length(intersect(exp_non,dat_ess));
 
 disp(sprintf(['TP: ' num2str(TP) '\nTN: ' num2str(TN) '\nFP: ' num2str(FP)...
-    '\nFN: ' num2str(FN) '\nAccuracy: ' num2str(TN/(TN+FP))]));
+    '\nFN: ' num2str(FN) '\nSpecificity: ' num2str(TN/(TN+FP))]));

README.md

@@ -15,15 +15,18 @@ _Rhodotorula toruloides_ (syn. _Rhodosporidium toruloides_) is a basidiomycetous
 **GEM category:** Species; **Utilisation:** experimental data reconstruction; **Field:** metabolic-network reconstruction; **Type of model:** reconstruction, curated; **Model source:** [yeast-GEM](https://github.com/SysBioChalmers/yeast-GEM) & [iYali](https://github.com/SysBioChalmers/Yarrowia_lipolytica_W29-GEM); **Omic source:** genomics; **Taxonomy:** _Rhodotorula toruloides_; **Metabolic system:** general metabolism; **Bioreactor**; **Strain:** NP11; **Condition:** minimal medium;
 
 - Reference:  
-> Tiukova IA _et al_. (2019) "Genome-scale model of _Rhodotorula toruloides_ metabolism" bioRxiv doi:[10.1101/528489](https://doi.org/10.1101/528489)
+> Tiukova IA, Prigent S, Nielsen J, Sandgren M & Kerkhoven EJ (2019) "Genome-scale model of _Rhodotorula toruloides_ metabolism" _Biotechnol Bioeng_. doi:[10.1002/bit.27162](https://onlinelibrary.wiley.com/doi/full/10.1002/bit.27162)
 
-- Last update: 2019-07-24
+
+> Lopes HJS _et al_. "C/N ratio and carbon source-dependent lipid production profiling in _Rhodotorula toruloides_" _Under review_
+
+- Last update: 2019-10-21
 
 - Main model descriptors:
 
 | Taxonomy | Template Model | Reactions | Metabolites | Genes |
 | ------------- |:-------------:|:-------------:|:-------------:|:-----:|
-| _Rhodotorula toruloides_|	[yeast-GEM](https://github.com/SysBioChalmers/yeast-GEM) & [iYali](https://github.com/SysBioChalmers/Yarrowia_lipolytica_W29-GEM) | 2731 | 2277 | 852 |
+| _Rhodotorula toruloides_|	[yeast-GEM](https://github.com/SysBioChalmers/yeast-GEM) & [iYali](https://github.com/SysBioChalmers/Yarrowia_lipolytica_W29-GEM) | 2729 | 2277 | 859 |
 
 A [Memote](https://memote.readthedocs.io/en/latest/) snapshot report of the most recent release is available [here](https://SysBioChalmers.github.io/rhto-GEM).
 
@@ -57,6 +60,7 @@ The model is available in `.xml`, `.txt`, `.yml`, `.mat` and `.xlsx` (the last 2
 
 * `newCommit.m`: prepares files from a modified model for a new GitHub commit in a development branch.
 * `newCommit.m`: prepares files from a modified model for a new GitHub release in the master branch.
+* `Lopes2019`: folder with scripts related to Lopes _et al_. (2019)
 * `analysis`: folder with scripts performing analyses on rhto-GEM.
 * `curation`: folder with additional curation scripts, after the initial reconstruction
 * `experimental`: folder with scripts that modify _rhto-GEM_ to incorporate experimental data.
@@ -65,6 +69,7 @@ The model is available in `.xml`, `.txt`, `.yml`, `.mat` and `.xlsx` (the last 2
 
 ### Complementary data
 
+* `Lopes2019`: folder with data related to Lopes _et al_. (2019)
 * `data`: experimentally measured data.
 * `genome`: protein fasta files of _R. toruloides_, _S. cerevisiae_ and _Y. lipolytica_, as used for identifying orthologs.
 * `meneco`: input and output files for meneco, as run for `r4_gapfilling`.