Data for Whole-cell modeling of E. coli colonies enables quantification of single-cell heterogeneity in the antibiotic response

Data from simulations used to generate the figures in the paper Whole-cell modeling of E. coli colonies enables quantification of single-cell heterogeneity in the antibiotic response.

To reproduce analyses, extract colony_data.zip in the data folder after cloning the vivarium-ecoli repository.

The extracted folder contains the following items:

• sim_dfs: a folder containing the CSV files that represent a subset of the raw simulation data used for downstream analyses.
• glc_10000_fluxome.csv: Each row represents a reaction in central carbon metabolism (in same order as listed in validation/ecoli/flat/toya_2010_central_carbon_fluxes.tsv). Each column represents a single time point for a single cell in a baseline glucose simulation (seed 10000). Each value is a flux (mmol/L/hr). Provided as input to ecoli/analysis/centralCarbonMetabolism.py script to reproduce fluxome validation plot.
• glc_10000_proteome_avgs.csv: Each row represents a protein monomer (in same order as sim_data.translation.monomer_data["id"] where sim_data is reconstruction/sim_data/kb/validationData.cPickle). Each column represents a cell in a baseline glucose simulation (seed 10000). Each row represents a protein monomer. Each value represents the average count of a given protein monomer for a given cell. Provided as input to ecoli/analysis/proteinCountsValidation.py script to reproduce proteome validation plot.
• glc_10000_expressome.csv: Each column represents a gene (with the exception of the final two metadata columns: "Time" and "Agent ID"). Each row represents a specific cell (agent) at a specific time in a baseline glucose simulation (seed 10000). Each value represents the number of new RNA transcripts for a given gene in a given cell at a given time. Provided as input to ecoli/analysis/antibiotics_colony/subgen_gene_plots/count_subgen.py script to calculate number of sub-generational genes among all genes and antibiotic response genes.
• glc_10000_total_mrna.json: Mapping of agent IDs for all cells in a baseline glucose simulation (seed 10000) to their average total mRNA count. Used by ecoli/analysis/antibiotics_colony/plot.py to generate Fig. 2C,D.
• jenner_2013.csv: Data extracted from Fig. 2C of 10.1073/pnas.1216691110. Used by ecoli/analysis/antibiotics_colony/plot.py to generate Fig. S6A.
• olson_2006.csv: Data extracted from Fig. 2D of 10.1128/AAC.01499-05. Used by ecoli/analysis/antibiotics_colony/plot.py to generate Fig. S6A.
• lysis_ratios.csv: Data extracted from Fig. 2 of 10.1099/00221287-31-3-339. Used by ecoli/analysis/antibiotics_colony/plot.py to generate Fig. 4N.