E. Coli Whole Cell Model by Covert Lab / Condition Updated 2025-07-16
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  • reconstruction/ecoli/flat/condition/nutrient/minimal.tsv contains the nutrients in a minimal environment in which the cell survives:
    "molecule id" "lower bound (units.mmol / units.g / units.h)" "upper bound (units.mmol / units.g / units.h)"
"ADP[c]" 3.15 3.15
"PI[c]" 3.15 3.15
"PROTON[c]" 3.15 3.15
"GLC[p]" NaN 20
"OXYGEN-MOLECULE[p]" NaN NaN
"AMMONIUM[c]" NaN NaN
"PI[p]" NaN NaN
"K+[p]" NaN NaN
"SULFATE[p]" NaN NaN
"FE+2[p]" NaN NaN
"CA+2[p]" NaN NaN
"CL-[p]" NaN NaN
"CO+2[p]" NaN NaN
"MG+2[p]" NaN NaN
"MN+2[p]" NaN NaN
"NI+2[p]" NaN NaN
"ZN+2[p]" NaN NaN
"WATER[p]" NaN NaN
"CARBON-DIOXIDE[p]" NaN NaN
"CPD0-1958[p]" NaN NaN
"L-SELENOCYSTEINE[c]" NaN NaN
"GLC-D-LACTONE[c]" NaN NaN
"CYTOSINE[c]" NaN NaN
    If we compare that to reconstruction/ecoli/flat/condition/nutrient/minimal_plus_amino_acids.tsv, we see that it adds the 20 amino acids on top of the minimal condition:
    "L-ALPHA-ALANINE[p]" NaN NaN
"ARG[p]" NaN NaN
"ASN[p]" NaN NaN
"L-ASPARTATE[p]" NaN NaN
"CYS[p]" NaN NaN
"GLT[p]" NaN NaN
"GLN[p]" NaN NaN
"GLY[p]" NaN NaN
"HIS[p]" NaN NaN
"ILE[p]" NaN NaN
"LEU[p]" NaN NaN
"LYS[p]" NaN NaN
"MET[p]" NaN NaN
"PHE[p]" NaN NaN
"PRO[p]" NaN NaN
"SER[p]" NaN NaN
"THR[p]" NaN NaN
"TRP[p]" NaN NaN
"TYR[p]" NaN NaN
"L-SELENOCYSTEINE[c]" NaN NaN
"VAL[p]" NaN NaN
    so we guess that NaN in the upper mound likely means infinite.
    We can try to understand the less obvious ones:
    • ADP: TODO
    • PI: TODO
    • PROTON[c]: presumably a measure of pH
    • GLC[p]: glucose, this can be seen by comparing minimal.tsv with minimal_no_glucose.tsv
    • AMMONIUM: ammonium. This appears to be the primary source of nitrogen atoms for producing amino acids.
    • CYTOSINE[c]: hmmm, why is external cytosine needed? Weird.
  • reconstruction/ecoli/flat/reconstruction/ecoli/flat/condition/timeseries/ contains sequences of conditions for each time. For example:
    • reconstruction/ecoli/flat/reconstruction/ecoli/flat/condition/timeseries/000000_basal.tsv contains:
      "time (units.s)" "nutrients"
0 "minimal"
      which means just using reconstruction/ecoli/flat/condition/nutrient/minimal.tsv until infinity. That is the default one used by runSim.py, as can be seen from ./out/manual/wildtype_000000/000000/generation_000000/000000/simOut/Environment/attributes/nutrientTimeSeriesLabel which contains just 000000_basal.
    • reconstruction/ecoli/flat/reconstruction/ecoli/flat/condition/timeseries/000001_cut_glucose.tsv is more interesting and contains:
      "time (units.s)" "nutrients"
0 "minimal"
1200 "minimal_no_glucose"
      so we see that this will shift the conditions half-way to a condition that will eventually kill the bacteria because it will run out of glucose and thus energy!
    Timeseries can be selected with --variant nutrientTimeSeries X Y, see also: run variants.
    We can use that variant with:
    VARIANT="condition" FIRST_VARIANT_INDEX=1 LAST_VARIANT_INDEX=1 python runscripts/manual/runSim.py
  • reconstruction/ecoli/flat/condition/condition_defs.tsv contains lines of form:
    "condition" "nutrients"                "genotype perturbations" "doubling time (units.min)" "active TFs"
"basal"     "minimal"                  {}                       44.0                        []
"no_oxygen" "minimal_minus_oxygen"     {}                       100.0                       []
"with_aa"   "minimal_plus_amino_acids" {}                       25.0                        ["CPLX-125", "MONOMER0-162", "CPLX0-7671", "CPLX0-228", "MONOMER0-155"]
    • condition refers to entries in reconstruction/ecoli/flat/condition/condition_defs.tsv
    • nutrients refers to entries under reconstruction/ecoli/flat/condition/nutrient/, e.g. reconstruction/ecoli/flat/condition/nutrient/minimal.tsv or reconstruction/ecoli/flat/condition/nutrient/minimal_plus_amino_acids.tsv
    • genotype perturbations: there aren't any in the file, but this suggests that genotype modifications can also be incorporated here
    • doubling time: TODO experimental data? Because this should be a simulation output, right? Or do they cheat and fix doubling by time?
    • active TFs: this suggests that they are cheating transcription factors here, as those would ideally be functions of other more basic inputs
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E. Coli Whole Cell Model by Covert Lab / Output overview Updated 2025-07-16
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Run output is placed under out/:
Some of the output data is stored as .cpickle files. To observe those files, you need the original Python classes, and therefore you have to be inside Docker, from the host it won't work.
We can list all the plots that have been produced under out/ with
find -name '*.png'
Plots are also available in SVG and PDF formats, e.g.:
  • PNG: ./out/manual/plotOut/low_res_plots/massFractionSummary.png
  • SVG: ./out/manual/plotOut/svg_plots/massFractionSummary.svg The SVGs write text as polygons, see also: SVG fonts.
  • PDF: ./out/manual/plotOut/massFractionSummary.pdf
The output directory has a hierarchical structure of type:
./out/manual/wildtype_000000/000000/generation_000000/000000/
where:
  • wildtype_000000: variant conditions. wildtype is a human readable label, and 000000 is an index amongst the possible wildtype conditions. For example, we can have different simulations with different nutrients, or different DNA sequences. An example of this is shown at run variants.
  • 000000: initial random seed for the initial cell, likely fed to NumPy's np.random.seed
  • genereation_000000: this will increase with generations if we simulate multiple cells, which is supported by the model
  • 000000: this will presumably contain the cell index within a generation
We also understand that some of the top level directories contain summaries over all cells, e.g. the massFractionSummary.pdf plot exists at several levels of the hierarchy:
./out/manual/plotOut/massFractionSummary.pdf
./out/manual/wildtype_000000/plotOut/massFractionSummary.pdf
./out/manual/wildtype_000000/000000/plotOut/massFractionSummary.pdf
./out/manual/wildtype_000000/000000/generation_000000/000000/plotOut/massFractionSummary.pdf
Each of thoes four levels of plotOut is generated by a different one of the analysis scripts:
  • ./out/manual/plotOut: generated by python runscripts/manual/analysisVariant.py. Contains comparisons of different variant conditions. We confirm this by looking at the results of run variants.
  • ./out/manual/wildtype_000000/plotOut: generated by python runscripts/manual/analysisCohort.py --variant_index 0. TODO not sure how to differentiate between two different labels e.g. wildtype_000000 and somethingElse_000000. If -v is not given, a it just picks the first one alphabetically. TODO not sure how to automatically generate all of those plots without inspecting the directories.
  • ./out/manual/wildtype_000000/000000/plotOut: generated by python runscripts/manual/analysisMultigen.py --variant_index 0 --seed 0
  • ./out/manual/wildtype_000000/000000/generation_000000/000000/plotOut: generated by python runscripts/manual/analysisSingle.py --variant_index 0 --seed 0 --generation 0 --daughter 0. Contains information about a single specific cell.
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