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 : grdp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (47 of 51: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 37
  Gene deletion: b4382 b0238 b0125 b1241 b0351 b3831 b4069 b4384 b3708 b4152 b3115 b1849 b2296 b1612 b1611 b2883 b4122 b1779 b0477 b2797 b3117 b1814 b4471 b3616 b3589 b0261 b4138 b4123 b0621 b2406 b0114 b2366 b2492 b0904 b1533 b1206 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.374659 (mmol/gDw/h)
  Minimum Production Rate : 0.560981 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 994.937220
  EX_o2_e : 282.210615
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.577668
  EX_pi_e : 1.483361
  EX_so4_e : 0.094347
  EX_k_e : 0.073131
  EX_mg2_e : 0.003250
  EX_ca2_e : 0.001950
  EX_cl_e : 0.001950
  EX_cu2_e : 0.000266
  EX_mn2_e : 0.000259
  EX_zn2_e : 0.000128
  EX_ni2_e : 0.000121

Product: (mmol/gDw/h)
  EX_fe3_e : 999.993983
  EX_h2o_e : 547.954487
  EX_co2_e : 34.661695
  EX_ac_e : 0.862461
  Auxiliary production reaction : 0.560981
  EX_succ_e : 0.390692
  EX_ura_e : 0.265689
  DM_5drib_c : 0.000084
  DM_4crsol_c : 0.000084

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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