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 : nac_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (70 of 78: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 34
  Gene deletion: b3553 b0474 b2518 b1241 b0351 b3831 b3752 b4152 b0871 b2297 b2458 b2925 b2097 b2926 b1004 b3713 b1109 b0046 b1612 b1611 b4122 b2690 b2210 b1033 b4161 b3945 b4138 b4123 b0621 b1380 b1206 b2285 b3893 b1474   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.408797 (mmol/gDw/h)
  Minimum Production Rate : 0.215904 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 32.986722
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.778862
  EX_pi_e : 0.394328
  EX_so4_e : 0.102943
  EX_k_e : 0.079794
  EX_fe2_e : 0.006566
  EX_mg2_e : 0.003546
  EX_ca2_e : 0.002128
  EX_cl_e : 0.002128
  EX_cu2_e : 0.000290
  EX_mn2_e : 0.000282
  EX_zn2_e : 0.000139
  EX_ni2_e : 0.000132
  EX_cobalt2_e : 0.000010

Product: (mmol/gDw/h)
  EX_h2o_e : 46.097484
  EX_co2_e : 33.426514
  EX_h_e : 8.437913
  EX_ac_e : 3.248347
  EX_succ_e : 0.426290
  Auxiliary production reaction : 0.215904
  EX_ura_e : 0.073993
  EX_for_e : 0.001003
  DM_5drib_c : 0.000092
  DM_4crsol_c : 0.000091

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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