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 : atp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (48 of 72: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 29
  Gene deletion: b4069 b4384 b2744 b3708 b3008 b3752 b2297 b2458 b2883 b1982 b2797 b3117 b1814 b4471 b3449 b0261 b4381 b2239 b2406 b2868 b4064 b4464 b0114 b1539 b2492 b0904 b1533 b3927 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.748317 (mmol/gDw/h)
  Minimum Production Rate : 0.316985 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 24.435477
  EX_glc__D_e : 10.000000
  EX_nh4_e : 9.670869
  EX_pi_e : 1.672786
  EX_so4_e : 0.188441
  EX_k_e : 0.146066
  EX_fe2_e : 0.012019
  EX_mg2_e : 0.006492
  EX_cl_e : 0.003895
  EX_ca2_e : 0.003895
  EX_cu2_e : 0.000531
  EX_mn2_e : 0.000517
  EX_zn2_e : 0.000255
  EX_ni2_e : 0.000242
  EX_cobalt2_e : 0.000019

Product: (mmol/gDw/h)
  EX_h2o_e : 49.445151
  EX_co2_e : 25.238012
  EX_h_e : 8.266634
  EX_ac_e : 0.435660
  Auxiliary production reaction : 0.316985
  EX_ade_e : 0.000837
  DM_5drib_c : 0.000502
  DM_4crsol_c : 0.000167

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 (2023).
[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.

Last updated: 09-Jul-2025
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