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 : pe181_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (48 of 71: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b1855 b4382 b3831 b4384 b1278 b3614 b0910 b4152 b2781 b0030 b1612 b1611 b4122 b0651 b2162 b1759 b4138 b4123 b0621 b2406 b2197 b2835 b3918 b0494 b1206   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.558991 (mmol/gDw/h)
  Minimum Production Rate : 0.295228 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 16.003840
  EX_glc__D_e : 10.000000
  EX_nh4_e : 7.125103
  EX_pi_e : 0.834435
  EX_so4_e : 0.140765
  EX_k_e : 0.109111
  EX_fe2_e : 0.008978
  EX_mg2_e : 0.004849
  EX_cl_e : 0.002910
  EX_ca2_e : 0.002910
  EX_cu2_e : 0.000396
  EX_mn2_e : 0.000386
  EX_zn2_e : 0.000191
  EX_ni2_e : 0.000181
  EX_cobalt2_e : 0.000014

Product: (mmol/gDw/h)
  EX_h2o_e : 39.836836
  EX_co2_e : 21.034328
  EX_h_e : 6.799646
  EX_succ_e : 0.582912
  EX_ura_e : 0.396408
  Auxiliary production reaction : 0.295228
  DM_5drib_c : 0.000126
  DM_4crsol_c : 0.000125

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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