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 : duri_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (37 of 50: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 38
  Gene deletion: b4382 b3942 b1732 b1241 b0351 b4069 b4384 b2744 b1479 b3115 b1849 b2296 b3617 b2407 b3844 b3236 b0907 b2463 b2210 b3551 b4219 b1832 b1778 b3654 b2868 b3714 b3664 b4064 b4464 b0114 b0529 b2492 b0904 b1710 b2480 b1511 b3662 b0606   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.488456 (mmol/gDw/h)
  Minimum Production Rate : 1.873536 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 19.437883
  EX_glc__D_e : 10.000000
  EX_nh4_e : 9.022351
  EX_pi_e : 0.471167
  EX_so4_e : 0.123003
  EX_k_e : 0.095343
  EX_fe2_e : 0.007845
  EX_mg2_e : 0.004237
  EX_ca2_e : 0.002542
  EX_cl_e : 0.002542
  EX_cu2_e : 0.000346
  EX_mn2_e : 0.000338
  EX_zn2_e : 0.000167
  EX_ni2_e : 0.000158
  EX_cobalt2_e : 0.000012

Product: (mmol/gDw/h)
  EX_h2o_e : 43.254149
  EX_co2_e : 18.099270
  EX_h_e : 10.729674
  Auxiliary production reaction : 1.873536
  EX_ac_e : 1.479576
  EX_fum_e : 0.507451
  DM_mththf_c : 0.000219
  DM_5drib_c : 0.000110
  DM_4crsol_c : 0.000109

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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