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 : gsn_e
List of minimal gene deletion strategies (Download)

Gene deletion strategy (20 of 49: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b3399 b4269 b0493 b3588 b3003 b3011 b1241 b0351 b2744 b0871 b2883 b1982 b3616 b3589 b0675 b2361 b0261 b0411 b4381 b2406 b0112 b0114 b0529 b2492 b0904   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.601073 (mmol/gDw/h)
  Minimum Production Rate : 0.961245 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 23.550499
  EX_nh4_e : 11.297763
  EX_glc__D_e : 10.000000
  EX_pi_e : 0.579799
  EX_so4_e : 0.151362
  EX_k_e : 0.117325
  EX_fe2_e : 0.009654
  EX_mg2_e : 0.005214
  EX_ca2_e : 0.003129
  EX_cl_e : 0.003129
  EX_cu2_e : 0.000426
  EX_mn2_e : 0.000415
  EX_zn2_e : 0.000205
  EX_ni2_e : 0.000194
  EX_cobalt2_e : 0.000015

Product: (mmol/gDw/h)
  EX_h2o_e : 49.149037
  EX_co2_e : 22.702665
  EX_h_e : 10.329124
  EX_acald_e : 1.506128
  EX_gsn_e : 0.961245
  DM_5drib_c : 0.000403
  DM_4crsol_c : 0.000134

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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