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 : imp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (76 of 81: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 38
  Gene deletion: b4467 b4269 b0493 b3588 b3003 b3011 b4384 b2744 b0871 b0030 b3844 b1004 b3713 b1109 b0046 b3236 b2883 b1779 b1982 b1602 b0153 b2913 b4381 b0590 b2868 b1727 b4064 b4464 b0114 b0529 b2492 b0904 b1380 b1771 b3662 b1517 b0606 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.467312 (mmol/gDw/h)
  Minimum Production Rate : 0.125252 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 37.458503
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.549509
  EX_pi_e : 0.576024
  EX_so4_e : 0.117678
  EX_k_e : 0.091216
  EX_fe2_e : 0.007505
  EX_mg2_e : 0.004054
  EX_cl_e : 0.002432
  EX_ca2_e : 0.002432
  EX_cu2_e : 0.000331
  EX_mn2_e : 0.000323
  EX_zn2_e : 0.000159
  EX_ni2_e : 0.000151
  EX_cobalt2_e : 0.000012

Product: (mmol/gDw/h)
  EX_h2o_e : 51.863171
  EX_co2_e : 38.141840
  EX_h_e : 5.270433
  EX_3hpp_e : 0.474005
  Auxiliary production reaction : 0.125252
  EX_ade_e : 0.000315
  DM_mththf_c : 0.000209
  DM_5drib_c : 0.000105
  DM_4crsol_c : 0.000104

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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