Fig 1.
Principle IDREAM illustration of combining EGRIN and PROM for building an integrated model of a metabolic network and its corresponding gene regulatory network.
Fig 2.
Strategy for IDREAM on integration of an EGRIN TRN with a metabolic model.
A. Comparison of three integrative models: PROM, IDREAM, IDREAM-hybrid. B. Detailed illustration of probability constraints in an IDREAM model. The direct and indirect interactions are represented using solid and dashed lines, respectively. For activators (red), we set the probability to Prob(Gene = ON|Factor = OFF) = FDR. For inhibitors (blue), we set Prob(Gene = ON|Factor = OFF) = 1-FDR. The constraints on the reaction flux were Vmax·Prob. For indirect interactions, no effects of TF knockout on flux constraints.
Fig 3.
MCCs between predicted and experimental growth changes across different media and at different thresholds for binarizing a call as “growth defect” or “no growth defect”.
Four conditions are presented in the four panels (A, B, C and D). Under each condition, we calculated the ratio of growth rates between TF knockout and wild-type. When the ratio was lower than some particular threshold, the corresponding TF is considered growth defective. By adjusting the threshold of growth ratio from 0.1 to 0.95, the MCCs between prediction and measurement were derived. A. Glucose minimal medium with ammonium. B. Galatose with ammonium medium. C. Glucose with urea medium. D. Combining the three media.
Fig 4.
ROC curves for growth defect predictions using IDREAM and PROM on Yeast6 model.
A. Threshold is 0.5 for binarizing a call as “growth defect” or “no growth defect” B. Threshold is 0.2 for binarizing a call as “growth defect” or “no growth defect”.
Fig 5.
MCCs by different integrative models using different thresholds of growth ratio determining growth defect.
Y6, Y7, and iMM904 refer to the Yeast metabolic models Yeast 6, Yeast 7, and iMM904 respectively.
Table 1.
Comparison of PROM and IDREAM predicted growth ratio with experiments under glucose minimal medium.
The ratio of mutant vs. wild-type growth rate was compared with the growth ratio for 119 TF knockouts previously measured by Sauer Lab. There were 51 TFs in common between the two integrative models, so we distinguish PROM by TF90 (the whole YEASTRACT-based model) and TF51 (the portion of the YEASTRACT-based model that overlaps with that from IDREAM).
Table 2.
Comparison of mean absolute residuals for IDREAM and PROM aggregating different yeast models.
The first column shows three different yeast metabolic models, aggregate refers to the predictions for all three models taken together. Column 2–4 show the Pearson correlation coefficient, p-value, and mean absolute residuals difference between predicted and actual growth by IDREAM and IDREAM_hybrid model. Column 5–7 show the Pearson correlation coefficient, p-value, and mean absolute residuals difference by PROM_TF51. Column 8 ‘vs.res.pVal’ represents the significance of difference in correlations between the two IDREAM models and the PROM model. P-values were calculated using a Fisher’s Z transform. IDREAM_h means the IDREAM_hybrid model.
Fig 6.
Synthetic growth defect interactions identified by IDREAM.
A. Growth defect confidence scores measured by ODELAY. Beyond the genetic interactions between OAF1 and genes encoding components of the pyruvate dehydrogenase (PDH) complex, ODELAY also validated the predicted genetic interaction between CIN5 and GRX5, but did not confirm the remaining 3 of the 9 predictions. B. ROC curve describing identification of IDREAM or control strains based on ODELAY scores.