Fig. 3: Application of METIS for optimization of a LacI gene circuit.
From: A versatile active learning workflow for optimization of genetic and metabolic networks
a LacI gene circuits characterized by dynamic range (DR) and fold-change (FC) of the output (Gfp fluorescence) between 0 and 10 mM IPTG. b Active learning by varying components of E. coli TXTL, 4 lacI circuit plasmids as alternatives, T7 RNA polymerase and a T7-lacI plasmid. c The objective function (FC × DR) and fold change (FC) values, average of triplicates (n = 3 independent experiments) in 10 rounds of active learning. The gray lines show the median. d The distribution yield values within the range of each factor. e Feature importance percentages showing the effect of each factor on the objective function. f Titration of PT7-LacI plasmid and T7 RNA polymerase with the optimal composition (from active learning that achieved with pTHS circuit). The heatmaps show FC × DR (left) and FC (right) values (average of triplicates, n = 3 independent experiments) of the titration. g Fluorescence values (average of triplicates, n = 3 independent experiments) of the similar titration as in f but instead of the pTHS circuit, a Gfp expressing plasmid was used). h Titration of LacI plasmids with constitutive/T7 promoter in combination with a Gfp plasmid with constitutive/T7 promoter. i The RT-qPCR results of the relative level of LacI and Gfp mRNAs after 10 h. Relative log2 resource share between LacI and Gfp mRNA in each sample is reported to account for RNA purification efficiency variability. In h and i bars are the average of triplicates (n = 3 independent experiments) and error bars are standard deviation. j Usage of the METIS module, K most informative combinations for further LacI circuit optimization. k Objective function FC × DR and FC (average of triplicates, n = 3 independent experiments) of 20 most informative combinations with purified LacI (Day 0) followed by Day 1 experiments suggested by METIS. The gray lines show the median. The Google Colab Python notebook and all active learning data (combinations and yields) in this figure are available at https://github.com/amirpandi/METIS. Source data for f–i are provided as a Source Data file.
