Incoming links: Transcription factor
Contains the genes: e. Coli K-12 MG1655 gene thrL, e. Coli K-12 MG1655 gene thrA, e. Coli K-12 MG1655 gene thrB and e. Coli K-12 MG1655 gene thrC, all of which have directly linked functionality.
We can find it by searching for the species in the BioCyc promoter database. This leads to: biocyc.org/group?id=:ALL-PROMOTERS&orgid=ECOLI.
By finding the first operon by position we reach: biocyc.org/ECOLI/NEW-IMAGE?object=TU0-42486.
That page lists several components of the promoter, which we should try to understand!
Some of the transcription factors are proteins:
After the first gene in the codon, thrL, there is a rho-independent termination. By comparing:we understand that the presence of threonine or isoleucine variants, L-threonyl and L-isoleucyl, makes the rho-independent termination become more efficient, so the control loop is quite direct! Not sure why it cares about isoleucine as well though.
TODO which factor is actually specific to that DNA region?
github.com/CovertLab/WholeCellEcoliRelease is a whole cell simulation model created by Covert Lab and other collaborators.
The project is written in Python, hurray! But according to te README, it seems to be the use a code drop model with on-request access to master, very meh, asked rationale on GitHub discussion, and they confirmed as expected that it is to:Oh well.
- to prevent their publication ideas from being stolen. Who would steal publication ideas with public proof in an issue tracker without crediting original authors?
- to prevent noise from non collaborators. They do only get like 2 issues as year though, people forget that it is legal to ignore other people :-)
The project is a followup to the earlier M. genitalium whole cell model by Covert lab which modelled Mycoplasma genitalium. E. Coli has 8x more genes (500 vs 4k), but it the undisputed bacterial model organism and as such has been studied much more thoroughly. It also reproduces faster than Mycoplasma (20 minutes vs a few hours), which is a huge advantages for validation/exploratory experiments.
The project has a partial dependency on the proprietary optimization software CPLEX which is freeware, for students, not sure what it is used for exactly, from the comment in the
requirements.txt the dependency is only partial.This project makes Ciro Santilli think of the E. Coli as an optimization problem. Given such external nutrient/temperature condition, which DNA sequence makes the cell grow the fastest? Balancing metabolites feels like designing a Factorio speedrun.
There is one major thing missing thing in the current model: promoters/transcription factor interactions are not modelled due to lack/low quality of experimental data: github.com/CovertLab/WholeCellEcoliRelease/issues/21. They just have a magic direct "transcription factor to gene" relationship, encoded at reconstruction/ecoli/flat/foldChanges.tsv in terms of type "if this is present, such protein is expressed 10x more". Transcription units are not implemented at all it appears.
Everything in this section refers to version 7e4cc9e57de76752df0f4e32eca95fb653ea64e4, the code drop from November 2020, and was tested on Ubuntu 21.04 with a docker install of
docker.pkg.github.com/covertlab/wholecellecolirelease/wcm-full with image id 502c3e604265, unless otherwise noted.reconstruction/ecoli/flat/condition/nutrient/minimal.tsvcontains the nutrients in a minimal environment in which the cell survives:If we compare that to"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 NaNreconstruction/ecoli/flat/condition/nutrient/minimal_plus_amino_acids.tsv, we see that it adds the 20 amino acids on top of the minimal condition:so we guess that"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 NaNNaNin theupper moundlikely means infinite.We can try to understand the less obvious ones:ADP: TODOPI: TODOPROTON[c]: presumably a measure of pHGLC[p]: glucose, this can be seen by comparingminimal.tsvwithminimal_no_glucose.tsvAMMONIUM: 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/000000_basal.tsv
reconstruction/ecoli/flat/reconstruction/ecoli/flat/condition/timeseries/` contains sequences of conditions for each time. For example: *contains:"time (units.s)" "nutrients" 0 "minimal"which means just usingreconstruction/ecoli/flat/condition/nutrient/minimal.tsvuntil infinity. That is the default one used byrunSim.py, as can be seen from./out/manual/wildtype_000000/000000/generation_000000/000000/simOut/Environment/attributes/nutrientTimeSeriesLabelwhich contains just000000_basal. *reconstruction/ecoli/flat/reconstruction/ecoli/flat/condition/timeseries/000001_cut_glucose.tsvis more interesting and contains: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!"time (units.s)" "nutrients" 0 "minimal" 1200 "minimal_no_glucose"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.tsvcontains 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"]conditionrefers to entries inreconstruction/ecoli/flat/condition/condition_defs.tsvnutrientsrefers to entries underreconstruction/ecoli/flat/condition/nutrient/, e.g.reconstruction/ecoli/flat/condition/nutrient/minimal.tsvorreconstruction/ecoli/flat/condition/nutrient/minimal_plus_amino_acids.tsvgenotype perturbations: there aren't any in the file, but this suggests that genotype modifications can also be incorporated heredoubling 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
The key model database is located in the source code at
reconstruction/ecoli/flat.Let's try to understand some interesting looking, with a special focus on our understanding of the tiny E. Coli K-12 MG1655 operon thrLABC part of the metabolism, which we have well understood at Section "E. Coli K-12 MG1655 operon thrLABC".
We'll realize that a lot of data and IDs come from/match BioCyc quite closely.
reconstruction/ecoli/flat/compartments.tsvcontains cellular compartment information:"abbrev" "id" "n" "CCO-BAC-NUCLEOID" "j" "CCO-CELL-PROJECTION" "w" "CCO-CW-BAC-NEG" "c" "CCO-CYTOSOL" "e" "CCO-EXTRACELLULAR" "m" "CCO-MEMBRANE" "o" "CCO-OUTER-MEM" "p" "CCO-PERI-BAC" "l" "CCO-PILUS" "i" "CCO-PM-BAC-NEG"CCO: "Celular COmpartment"BAC-NUCLEOID: nucleoidCELL-PROJECTION: cell projectionCW-BAC-NEG: TODO confirm: cell wall (of a Gram-negative bacteria)CYTOSOL: cytosolEXTRACELLULAR: outside the cellMEMBRANE: cell membraneOUTER-MEM: bacterial outer membranePERI-BAC: periplasmPILUS: pilusPM-BAC-NEG: TODO: plasma membrane, but that is the same as cell membrane no?
reconstruction/ecoli/flat/promoters.tsvcontains promoter information. Simple file, sample lines:corresponds to E. Coli K-12 MG1655 promoter thrLp, which starts as position 148."position" "direction" "id" "name" 148 "+" "PM00249" "thrLp"reconstruction/ecoli/flat/proteins.tsvcontains protein information. Sample line corresponding to e. Coli K-12 MG1655 gene thrA:so we understand that:"aaCount" "name" "seq" "comments" "codingRnaSeq" "mw" "location" "rnaId" "id" "geneId" [91, 46, 38, 44, 12, 53, 30, 63, 14, 46, 89, 34, 23, 30, 29, 51, 34, 4, 20, 0, 69] "ThrA" "MRVL..." "Location information from Ecocyc dump." "AUGCGAGUGUUG..." [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 89103.51099999998, 0.0, 0.0, 0.0, 0.0] ["c"] "EG10998_RNA" "ASPKINIHOMOSERDEHYDROGI-MONOMER" "EG10998"aaCount: amino acid count, how many of each of the 20 proteinogenic amino acid are thereseq: full sequence, using the single letter abbreviation of the proteinogenic amino acidsmw; molecular weight? The 11 components appear to be given atreconstruction/ecoli/flat/scripts/unifyBulkFiles.py:so they simply classify the weight? Presumably this exists for complexes that have multiple classes?molecular_weight_keys = [ '23srRNA', '16srRNA', '5srRNA', 'tRNA', 'mRNA', 'miscRNA', 'protein', 'metabolite', 'water', 'DNA', 'RNA' # nonspecific RNA ]23srRNA,16srRNA,5srRNAare the three structural RNAs present in the ribosome: 23S ribosomal RNA, 16S ribosomal RNA, 5S ribosomal RNA, all others are obvious:- tRNA
- mRNA
- protein. This is the seventh class, and this enzyme only contains mass in this class as expected.
- metabolite
- water
- DNA
- RNA: TODO
rnavsmiscRNA
location: cell compartment where the protein is present,cdefined atreconstruction/ecoli/flat/compartments.tsvas cytoplasm, as expected for something that will make an amino acid
reconstruction/ecoli/flat/rnas.tsv: TODO vstranscriptionUnits.tsv. Sample lines:"halfLife" "name" "seq" "type" "modifiedForms" "monomerId" "comments" "mw" "location" "ntCount" "id" "geneId" "microarray expression" 174.0 "ThrA [RNA]" "AUGCGAGUGUUG..." "mRNA" [] "ASPKINIHOMOSERDEHYDROGI-MONOMER" "" [0.0, 0.0, 0.0, 0.0, 790935.00399999996, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] ["c"] [553, 615, 692, 603] "EG10998_RNA" "EG10998" 0.0005264904halfLife: half-lifemw: molecular weight, same as inreconstruction/ecoli/flat/proteins.tsv. This molecule only have weight in themRNAclass, as expected, as it just codes for a proteinlocation: same as inreconstruction/ecoli/flat/proteins.tsvntCount: nucleotide count for each of the ATGCmicroarray expression: presumably refers to DNA microarray for gene expression profiling, but what measure exactly?
reconstruction/ecoli/flat/sequence.fasta: FASTA DNA sequence, first two lines:>E. coli K-12 MG1655 U00096.2 (1 to 4639675 = 4639675 bp) AGCTTTTCATTCTGACTGCAACGGGCAATATGTCTCTGTGTGGATTAAAAAAAGAGTGTCTGATAGCAGCTTCTGreconstruction/ecoli/flat/transcriptionUnits.tsv: transcription units. We can observe for example the two different transcription units of the E. Coli K-12 MG1655 operon thrLABC in the lines:"expression_rate" "direction" "right" "terminator_id" "name" "promoter_id" "degradation_rate" "id" "gene_id" "left" 0.0 "f" 310 ["TERM0-1059"] "thrL" "PM00249" 0.198905992329492 "TU0-42486" ["EG11277"] 148 657.057317358791 "f" 5022 ["TERM_WC-2174"] "thrLABC" "PM00249" 0.231049060186648 "TU00178" ["EG10998", "EG10999", "EG11000", "EG11277"] 148promoter_id: matches promoter id inreconstruction/ecoli/flat/promoters.tsvgene_id: matches id inreconstruction/ecoli/flat/genes.tsvid: matches exactly those used in BioCyc, which is quite nice, might be more or less standardized:
reconstruction/ecoli/flat/genes.tsv"length" "name" "seq" "rnaId" "coordinate" "direction" "symbol" "type" "id" "monomerId" 66 "thr operon leader peptide" "ATGAAACGCATT..." "EG11277_RNA" 189 "+" "thrL" "mRNA" "EG11277" "EG11277-MONOMER" 2463 "ThrA" "ATGCGAGTGTTG" "EG10998_RNA" 336 "+" "thrA" "mRNA" "EG10998" "ASPKINIHOMOSERDEHYDROGI-MONOMER"reconstruction/ecoli/flat/metabolites.tsvcontains metabolite information. Sample lines:In the case of the enzyme thrA, one of the two reactions it catalyzes is "L-aspartate 4-semialdehyde" into "Homoserine"."id" "mw7.2" "location" "HOMO-SER" 119.12 ["n", "j", "w", "c", "e", "m", "o", "p", "l", "i"] "L-ASPARTATE-SEMIALDEHYDE" 117.104 ["n", "j", "w", "c", "e", "m", "o", "p", "l", "i"]Starting from the enzyme page: biocyc.org/gene?orgid=ECOLI&id=EG10998 we reach the reaction page: biocyc.org/ECOLI/NEW-IMAGE?type=REACTION&object=HOMOSERDEHYDROG-RXN which has reaction IDHOMOSERDEHYDROG-RXN, and that page which clarifies the IDs:so these are the compounds that we care about.- biocyc.org/compound?orgid=ECOLI&id=L-ASPARTATE-SEMIALDEHYDE: "L-aspartate 4-semialdehyde" has ID
L-ASPARTATE-SEMIALDEHYDE - biocyc.org/compound?orgid=ECOLI&id=HOMO-SER: "Homoserine" has ID
HOMO-SER
- biocyc.org/compound?orgid=ECOLI&id=L-ASPARTATE-SEMIALDEHYDE: "L-aspartate 4-semialdehyde" has ID
reconstruction/ecoli/flat/reactions.tsvcontains chemical reaction information. Sample lines:"reaction id" "stoichiometry" "is reversible" "catalyzed by" "HOMOSERDEHYDROG-RXN-HOMO-SER/NAD//L-ASPARTATE-SEMIALDEHYDE/NADH/PROTON.51." {"NADH[c]": -1, "PROTON[c]": -1, "HOMO-SER[c]": 1, "L-ASPARTATE-SEMIALDEHYDE[c]": -1, "NAD[c]": 1} false ["ASPKINIIHOMOSERDEHYDROGII-CPLX", "ASPKINIHOMOSERDEHYDROGI-CPLX"] "HOMOSERDEHYDROG-RXN-HOMO-SER/NADP//L-ASPARTATE-SEMIALDEHYDE/NADPH/PROTON.53." {"NADPH[c]": -1, "NADP[c]": 1, "PROTON[c]": -1, "L-ASPARTATE-SEMIALDEHYDE[c]": -1, "HOMO-SER[c]": 1 false ["ASPKINIIHOMOSERDEHYDROGII-CPLX", "ASPKINIHOMOSERDEHYDROGI-CPLX"]catalized by: here we seeASPKINIHOMOSERDEHYDROGI-CPLX, which we can guess is a protein complex made out ofASPKINIHOMOSERDEHYDROGI-MONOMER, which is the ID for thethrAwe care about! This is confirmed incomplexationReactions.tsv.
reconstruction/ecoli/flat/complexationReactions.tsvcontains information about chemical reactions that produce protein complexes:The"process" "stoichiometry" "id" "dir" "complexation" [ { "molecule": "ASPKINIHOMOSERDEHYDROGI-CPLX", "coeff": 1, "type": "proteincomplex", "location": "c", "form": "mature" }, { "molecule": "ASPKINIHOMOSERDEHYDROGI-MONOMER", "coeff": -4, "type": "proteinmonomer", "location": "c", "form": "mature" } ] "ASPKINIHOMOSERDEHYDROGI-CPLX_RXN" 1coeffis how many monomers need to get together for form the final complex. This can be seen from the Summary section of ecocyc.org/gene?orgid=ECOLI&id=ASPKINIHOMOSERDEHYDROGI-MONOMER:Fantastic literature summary! Can't find that in database form there however.Aspartate kinase I / homoserine dehydrogenase I comprises a dimer of ThrA dimers. Although the dimeric form is catalytically active, the binding equilibrium dramatically favors the tetrameric form. The aspartate kinase and homoserine dehydrogenase activities of each ThrA monomer are catalyzed by independent domains connected by a linker region.
reconstruction/ecoli/flat/proteinComplexes.tsvcontains protein complex information:"name" "comments" "mw" "location" "reactionId" "id" "aspartate kinase / homoserine dehydrogenase" "" [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 356414.04399999994, 0.0, 0.0, 0.0, 0.0] ["c"] "ASPKINIHOMOSERDEHYDROGI-CPLX_RXN" "ASPKINIHOMOSERDEHYDROGI-CPLX"reconstruction/ecoli/flat/protein_half_lives.tsvcontains the half-life of proteins. Very few proteins are listed however for some reason.reconstruction/ecoli/flat/tfIds.csv: transcription factors information:"TF" "geneId" "oneComponentId" "twoComponentId" "nonMetaboliteBindingId" "activeId" "notes" "arcA" "EG10061" "PHOSPHO-ARCA" "PHOSPHO-ARCA" "fnr" "EG10325" "FNR-4FE-4S-CPLX" "FNR-4FE-4S-CPLX" "dksA" "EG10230"