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 : trp__L_e
List of minimal gene deletion strategies (Download)

Gene deletion strategy (63 of 80: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 49
  Gene deletion: b4467 b1478 b1241 b4069 b4384 b3708 b3752 b2297 b2458 b2779 b2407 b3844 b1238 b1004 b3713 b1109 b0046 b3124 b3236 b1982 b2797 b3117 b1814 b4471 b2440 b0261 b2799 b3945 b1602 b0153 b4381 b2406 b2975 b3603 b0584 b2366 b2492 b0904 b1533 b1380 b0494 b2660 b0514 b4141 b1798 b3662 b0606 b2285 b1009   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.395066 (mmol/gDw/h)
  Minimum Production Rate : 0.600995 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 34.167849
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.470884
  EX_pi_e : 0.381083
  EX_so4_e : 0.099486
  EX_k_e : 0.077114
  EX_fe2_e : 0.006345
  EX_mg2_e : 0.003427
  EX_ca2_e : 0.002056
  EX_cl_e : 0.002056
  EX_cu2_e : 0.000280
  EX_mn2_e : 0.000273
  EX_zn2_e : 0.000135
  EX_ni2_e : 0.000128

Product: (mmol/gDw/h)
  EX_h2o_e : 50.555404
  EX_co2_e : 35.310410
  EX_h_e : 5.764174
  EX_ac_e : 0.929945
  EX_trp__L_e : 0.600995
  EX_ade_e : 0.000442
  DM_5drib_c : 0.000265
  DM_4crsol_c : 0.000088

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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