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 : 12ppd__R_e
List of minimal gene deletion strategies (Download)

Gene deletion strategy (44 of 81: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b3553 b1241 b0351 b2925 b2097 b1004 b3713 b1109 b0046 b3236 b1779 b1525 b3946 b0825 b1033 b4015 b2661 b1602 b2913 b2223 b1727 b1380 b0606 b2285 b4209   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.578781 (mmol/gDw/h)
  Minimum Production Rate : 0.213673 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 994.672634
  EX_o2_e : 284.151556
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.250785
  EX_pi_e : 0.558296
  EX_so4_e : 0.145749
  EX_k_e : 0.112974
  EX_mg2_e : 0.005021
  EX_ca2_e : 0.003013
  EX_cl_e : 0.003013
  EX_cu2_e : 0.000410
  EX_mn2_e : 0.000400
  EX_zn2_e : 0.000197
  EX_ni2_e : 0.000187
  EX_cobalt2_e : 0.000014

Product: (mmol/gDw/h)
  EX_fe3_e : 999.990704
  EX_h2o_e : 550.668366
  EX_co2_e : 35.602683
  EX_12ppd__R_e : 0.213673
  DM_5drib_c : 0.000130
  DM_4crsol_c : 0.000129

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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