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 : adprib_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (52 of 97: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 28
  Gene deletion: b4382 b4384 b3708 b3008 b3752 b0871 b2779 b2407 b0121 b1982 b2797 b3117 b1814 b4471 b0261 b2406 b0114 b0886 b1539 b2492 b0904 b2578 b1533 b3927 b3821 b4141 b1798 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.686445 (mmol/gDw/h)
  Minimum Production Rate : 0.157563 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 28.388494
  EX_glc__D_e : 10.000000
  EX_nh4_e : 8.201359
  EX_pi_e : 0.977275
  EX_so4_e : 0.172860
  EX_k_e : 0.133989
  EX_fe2_e : 0.011025
  EX_mg2_e : 0.005955
  EX_ca2_e : 0.003573
  EX_cl_e : 0.003573
  EX_cu2_e : 0.000487
  EX_mn2_e : 0.000474
  EX_zn2_e : 0.000234
  EX_ni2_e : 0.000222
  EX_cobalt2_e : 0.000017

Product: (mmol/gDw/h)
  EX_h2o_e : 49.792613
  EX_co2_e : 29.459625
  EX_h_e : 6.780016
  Auxiliary production reaction : 0.157563
  DM_5drib_c : 0.000461
  DM_4crsol_c : 0.000153

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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