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 : ppa_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (2 of 5: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 28
  Gene deletion: b4467 b1478 b1241 b0351 b4069 b3708 b2926 b1004 b3713 b1109 b0046 b3236 b4015 b0335 b2799 b3945 b1602 b2342 b3845 b3915 b0728 b0529 b1380 b2660 b0606 b2285 b1009 b4209   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.595886 (mmol/gDw/h)
  Minimum Production Rate : 0.023771 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 994.491425
  EX_o2_e : 284.184413
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.435513
  EX_pi_e : 0.574795
  EX_so4_e : 0.150056
  EX_k_e : 0.116313
  EX_mg2_e : 0.005169
  EX_ca2_e : 0.003102
  EX_cl_e : 0.003102
  EX_cu2_e : 0.000422
  EX_mn2_e : 0.000412
  EX_zn2_e : 0.000203
  EX_ni2_e : 0.000192
  EX_cobalt2_e : 0.000015

Product: (mmol/gDw/h)
  EX_fe3_e : 999.990429
  EX_h2o_e : 551.201228
  EX_co2_e : 35.470323
  Auxiliary production reaction : 0.023771
  DM_5drib_c : 0.000134
  DM_4crsol_c : 0.000133

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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