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 : prfp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (49 of 78: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 30
  Gene deletion: b4382 b2066 b1241 b0351 b4069 b4384 b3708 b0910 b3752 b3115 b1849 b2296 b3617 b2407 b1779 b1982 b2797 b3117 b1814 b4471 b0261 b2406 b0112 b0114 b2366 b2492 b0904 b1533 b3662 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.365270 (mmol/gDw/h)
  Minimum Production Rate : 0.546514 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 34.619979
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.677458
  EX_pi_e : 1.445370
  EX_so4_e : 0.091982
  EX_k_e : 0.071298
  EX_fe2_e : 0.005867
  EX_mg2_e : 0.003169
  EX_ca2_e : 0.001901
  EX_cl_e : 0.001901
  EX_cu2_e : 0.000259
  EX_mn2_e : 0.000252
  EX_zn2_e : 0.000125
  EX_ni2_e : 0.000118

Product: (mmol/gDw/h)
  EX_h2o_e : 50.783729
  EX_co2_e : 34.033270
  EX_h_e : 7.476588
  EX_ac_e : 1.387770
  Auxiliary production reaction : 0.546514
  DM_5drib_c : 0.000245
  DM_4crsol_c : 0.000081

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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