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 : uacmamu_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (68 of 74: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 37
  Gene deletion: b2836 b0474 b2518 b2744 b1278 b4152 b3115 b1849 b2296 b2779 b2925 b2097 b2926 b2781 b3236 b1612 b1611 b4122 b1759 b3946 b2210 b0825 b4374 b4161 b0675 b0507 b4138 b4123 b0621 b4381 b0529 b2492 b0904 b2197 b3918 b1206 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.368788 (mmol/gDw/h)
  Minimum Production Rate : 0.194774 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 991.159169
  EX_o2_e : 281.429678
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.700703
  EX_pi_e : 0.745282
  EX_so4_e : 0.092868
  EX_k_e : 0.071985
  EX_mg2_e : 0.003199
  EX_ca2_e : 0.001920
  EX_cl_e : 0.001920
  EX_cu2_e : 0.000261
  EX_mn2_e : 0.000255
  EX_zn2_e : 0.000126
  EX_ni2_e : 0.000119

Product: (mmol/gDw/h)
  EX_fe3_e : 999.994077
  EX_h2o_e : 544.230731
  EX_co2_e : 31.438217
  EX_ac_e : 4.151762
  EX_succ_e : 0.385762
  Auxiliary production reaction : 0.194774
  EX_ura_e : 0.066752
  DM_5drib_c : 0.000083
  DM_4crsol_c : 0.000082

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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