Supplementary File:
Supplementary Table A1. The list of metabolites which can impose an increase in the optimum flux of biomass production, as the result of making their exchange flux negative. For each metabolite, the relative amount of increase in the flux biomass production is calculated, using FBA (more information in the first section of Material and methods). We chose the first metabolite in the list (phosphatidylserine) for supplementation of the medium in vitro. After designing the experiments, we used the same procedure to test another phospholipid (phosphatidylethanolamine) which is the third metabolite in the list. Other metabolites may need different solvents and therefore, these metabolites can be tested in future work.
Fold of increase in biomass flux / Metabolite1.37 / Phosphatidylserine
1.26 / Hexadecanoate (n-C16:0)
1.22 / Phosphatidylethanolamine
1.21 / Tetradecanoate (n-C14:0)
1.15 / ADP
1.11 / ATP
1.09 / Octanoate (n-C8:0)
1.08 / CMP
1.05 / Tetracosapentaenoic acid, n-3
1.04 / Tetracosahexaenoic acid, n-3
1.04 / Tetracosapentaenoic acid, n-6
1.04 / GTP
1.04 / Lignoceric acid
1.03 / Hexacosanoate (n-C26:0)
1.03 / UTP
1.02 / Tetracosatetraenoic acid n-6
1.02 / Nervonic acid
1.02 / l-Arabinose
Supplementary Table A.2.As we mentioned in the manuscript, MTA uses the amount of activity of reactions in the first state of the cell and a list of reaction which have to be up- or down-regulated in the second state. The output of MTA algorithm includes a score for each of the reactions of the metabolic model. A higher score for a reaction suggests that its knock-down is more important for transforming from the stemness state to differentiated state. The stem cell model, iMSC1255, has 2288 reactions. We sorted the output list of MTA according to the scores and represented the top 10 high-score reactions in Table 2. We also noted that the literature about stem cell differentiation is mainly focused on the reactions of central carbon metabolism, trying to establish a correlation between metabolic changes and stem cell differentiation. Therefore, we also listed the scores of central carbon metabolism reactions, i.e., glycolysis and TCA cycle, in Supplementary table A.2. The top ranking reaction in this list, i.e., citrate synthase, is only 32nd, which ranks far below the high-score reactions of Table 2. The average rank of central carbon metabolism reactions is about 412. Therefore, one may suggest that for differentiation, alterations of certain reactions like mitochondrial transport reactions, may have a much important role compared to the reactions of central carbon metabolism.
Name of the reactions / Score of the reactions based on MTA / Rank of the reactionsglucose exchange / 57.9839 / 108
hexokinase / -2139.59 / 526
glucose-6-phosphate isomerize / -4531.69 / 555
phosphofructokinase / -7120.38 / 605
transaldolase / -4238.41 / 550
fructose-bisphosphate aldolase / -7120.38 / 604
glyceraldehyde-3-phosphate dehydrogenase / -682.475 / 446
phosphoglycerate kinase / -10641.2 / 669
phosphoglycerate mutase / -1895.14 / 520
enolase / -1895.14 / 519
pyruvate kinase / -3002.8 / 532
lactate dehydrogenase / 35.92986 / 194
pyruvate mitochondrial transport / -20.8512 / 240
pyruvate dehydrogenase / 63.5295 / 67
pyruvate carboxylase / 21.69115 / 206
malate dehydrogenase / 42.10982 / 189
fumarase, mitochondrial / 60.59096 / 68
succinate dehydrogenase / 59.09935 / 69
succinate coA ligase / -12.0788 / 231
2-oxoglutarate dehydrogenase / -58.7698 / 278
isocitrate dehydrogenase / -10544.8 / 668
aconitate hydratase / -3811.13 / 543
citrate synthase / 162.6781 / 32
oxygen exchange / 66.74729 / 66
oxygen transport / 57.9839 / 145
superoxide dismutase / -394520 / 1075
catalase / -714537 / 1106
cytochrome c oxidase / -141416 / 936
ATP synthase / 47.38415 / 187
lactate transport / 36.64185 / 193
glutamine exchange / -10390.3 / 667
Tuning the concentrations of medium components
We need a plot of the concentrations of the medium componentsin different exchange fluxes. The exchange fluxes of amino acids in two different medium concentrations were measured in(Higuera et al. 2012).We assumed that a linear relation exists between concentrations and fluxes. Additionally, we need an estimation of exchange fluxes of amino acids, while the biomass production flux is maintained in its optimum value. Thus, we enumerate 2523 series of flux distributions of iMSC1255, using enumerateOptimalSolutions function of COBRA Toolbox. The mean of exchange fluxes for each reaction was calculated and found on the plot (Supplementary Figure A.1). The corresponding concentrations were proposed as new medium compositions (Supplementary Table A.3). We hope that this new medium composition can improve the experimental cell proliferation.
Supplementary Figure A.1. The plots of concentrations of amino acids are drawn against exchange fluxes, using two data series measured in(Higuera et al. 2012). The first data series were measured in batchcell culture (shown with ) and the other is measured in continuous cell culture (shown with ). The mean of each exchange flux in the optimal flux distributions is located on the plot (shown with ). The corresponding concentration for each amino acidis proposed for a new design of cell culture medium.
Supplementary Table A.3.The list of the concentrations of amino acids in our new medium design, in millimolar (mM). In order to have a comparison between our proposed media and the routine cell culture media, we have mentioned the concentrations of amino acids in α-MEM (Simonsen and Levinson 1983) and RPMI(Mössinger 1991) in the table. The concentrations of most of the amino acidsin our proposed medium are comparable tothe concentrations in α-MEM and RPMI. In future work, our medium can be tested in vitro in order to validate its positive impact on increasing cell proliferation.
Concentrations in α-MEM (mM) / Concentrations in RPMI (mM) / Concentrations in our proposed medium (mM) / Amino acid0.498 / 1.149 / 0.414 / l-Arginine
0.333 / 0.379 / 0.165 / l-Asparagine
0.225 / 0.150 / 0.196 / l-Aspartate
0.200 / 0.097 / 0.122 / l-Histidine
0.400 / 0.382 / 0.265 / l-Isoleucine
0.397 / 0.382 / 0.261 / l-Leucine
0.101 / 0.101 / 0.057 / l-Methionine
0.348 / 0.174 / 0.195 / l-Proline
- / - / 0.028 / l-Ornithine
0.198 / 0.111 / 0.145 / l-Tyrosine
0.393 / 0.171 / 0.238 / l-Valine
2.000 / 2.055 / 3.605 / l-Glutamine
0.281 / - / 0.185 / l-Alanine
0.510 / 0.136 / 0.405 / l-Glutamate
0.667 / 0.133 / 0.295 / Glycine
0.399 / 0.219 / 0.233 / l-Lysine
0.194 / 0.091 / 0.138 / l-Phenylalanine
0.238 / 0.286 / 0.211 / l-Serine
0.403 / 0.168 / 0.271 / l-Threonine
0.568 / - / 0.097 / l-Cysteine