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 : ametam_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (77 of 84: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 46
  Gene deletion: b4467 b2836 b1478 b1241 b4069 b4384 b3708 b3752 b2297 b2458 b2926 b2407 b1238 b1004 b3713 b1109 b0046 b3236 b2920 b1982 b2797 b3117 b1814 b4471 b0261 b0411 b2799 b3945 b1602 b2223 b4381 b2406 b3915 b2975 b3603 b0728 b1539 b2492 b0904 b1533 b1380 b2660 b0606 b2285 b1007 b4209   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.339480 (mmol/gDw/h)
  Minimum Production Rate : 0.461142 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 34.634121
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.434628
  EX_so4_e : 0.546614
  EX_pi_e : 0.327464
  EX_k_e : 0.066264
  EX_fe3_e : 0.005454
  EX_mg2_e : 0.002945
  EX_ca2_e : 0.001767
  EX_cl_e : 0.001767
  EX_cu2_e : 0.000241
  EX_mn2_e : 0.000235
  EX_zn2_e : 0.000116
  EX_ni2_e : 0.000110

Product: (mmol/gDw/h)
  EX_h2o_e : 50.780247
  EX_co2_e : 35.820194
  EX_h_e : 5.942151
  EX_ac_e : 1.893649
  Auxiliary production reaction : 0.461126
  EX_hxan_e : 0.000380
  DM_5drib_c : 0.000228
  DM_4crsol_c : 0.000076

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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