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 : dgdp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (19 of 41: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b4069 b4384 b3708 b3752 b2297 b2458 b2926 b2407 b2797 b3117 b1814 b4471 b2440 b3665 b4381 b3654 b3714 b3664 b0114 b1539 b2492 b0904 b1533 b3927 b1518   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.680459 (mmol/gDw/h)
  Minimum Production Rate : 0.216828 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 28.198150
  EX_glc__D_e : 10.000000
  EX_nh4_e : 8.433033
  EX_pi_e : 1.090030
  EX_so4_e : 0.171353
  EX_k_e : 0.132821
  EX_fe2_e : 0.010929
  EX_mg2_e : 0.005903
  EX_cl_e : 0.003542
  EX_ca2_e : 0.003542
  EX_cu2_e : 0.000482
  EX_mn2_e : 0.000470
  EX_zn2_e : 0.000232
  EX_ni2_e : 0.000220
  EX_cobalt2_e : 0.000017

Product: (mmol/gDw/h)
  EX_h2o_e : 49.895983
  EX_co2_e : 29.108194
  EX_h_e : 7.515789
  EX_ac_e : 0.396153
  Auxiliary production reaction : 0.216828
  DM_mththf_c : 0.000305
  DM_5drib_c : 0.000153
  DM_4crsol_c : 0.000152

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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