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 : 25aics_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (51 of 80: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 36
  Gene deletion: b3553 b1478 b4382 b1241 b4069 b4384 b3115 b1849 b2296 b2779 b0030 b2407 b3844 b1004 b3713 b1109 b0046 b3236 b1982 b1033 b0261 b2799 b3945 b1602 b0507 b2913 b2406 b3915 b0529 b2492 b0904 b1380 b3662 b0606 b2285 b1010   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.304294 (mmol/gDw/h)
  Minimum Production Rate : 0.954727 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 33.980017
  EX_glc__D_e : 10.000000
  EX_nh4_e : 7.106962
  EX_pi_e : 1.248251
  EX_so4_e : 0.076627
  EX_k_e : 0.059396
  EX_fe3_e : 0.004887
  EX_mg2_e : 0.002640
  EX_ca2_e : 0.001584
  EX_cl_e : 0.001584
  EX_cu2_e : 0.000216
  EX_mn2_e : 0.000210
  EX_zn2_e : 0.000104
  EX_ni2_e : 0.000098

Product: (mmol/gDw/h)
  EX_h2o_e : 50.304173
  EX_co2_e : 31.765645
  EX_h_e : 10.196249
  EX_ac_e : 1.665321
  Auxiliary production reaction : 0.954727
  EX_ade_e : 0.000341
  DM_5drib_c : 0.000204
  DM_4crsol_c : 0.000068

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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