MetNetComp Database [1] / Minimal gene deletions Minimal gene deletions for simulation-based growth-coupled production. You can also see maximal gene deletions.

Model : iML1515 [2].
Target metabolite : 12ppd__S_e
List of minimal gene deletion strategies (Download)

Gene deletion strategy (41 of 92: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 30
  Gene deletion: b4467 b1241 b0351 b2930 b4232 b3697 b3925 b0871 b2926 b1004 b3713 b1109 b0046 b3236 b3946 b0825 b3945 b1602 b2913 b4381 b3915 b1727 b2975 b3603 b2492 b0904 b1380 b0606 b2285 b4209   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.480045 (mmol/gDw/h)
  Minimum Production Rate : 1.118740 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 34.026561
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.184450
  EX_pi_e : 0.463055
  EX_so4_e : 0.120885
  EX_k_e : 0.093702
  EX_fe3_e : 0.007710
  EX_mg2_e : 0.004164
  EX_ca2_e : 0.002499
  EX_cl_e : 0.002499
  EX_cu2_e : 0.000340
  EX_mn2_e : 0.000332
  EX_zn2_e : 0.000164
  EX_ni2_e : 0.000155
  EX_cobalt2_e : 0.000012

Product: (mmol/gDw/h)
  EX_h2o_e : 47.725733
  EX_co2_e : 36.363772
  EX_h_e : 4.418559
  EX_12ppd__S_e : 1.310856
  DM_5drib_c : 0.000108
  DM_4crsol_c : 0.000107

Visualization
  1. Download JSON file.
  2. Go to Escher site [3].
  3. Select "Data > Load reaction data" and apply the downloaded file.

References
[1] Tamura, T. MetNetComp: Database for minimal and maximal gene deletion strategies for growth-coupled production of genome-scale metabolic networks, IEEE/ACM Transactions on Computational Biology and Bioinformatics, in press.
[2] Norsigian, C. J., Pusarla, N., McConn, J. L., Yurkovich, J. T., Dräger, A., Palsson, B. O., & King, Z. (2020). BiGG Models 2020: multi-strain genome-scale models and expansion across the phylogenetic tree. Nucleic acids research, 48(D1), D402-D406.
[3] King, Z. A., Dräger, A., Ebrahim, A., Sonnenschein, N., Lewis, N. E., & Palsson, B. O. (2015). Escher: a web application for building, sharing, and embedding data-rich visualizations of biological pathways. PLoS computational biology, 11(8), e1004321.

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Last updated: 21-Sep-2023
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