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 : ametam_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (49 of 84: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 29
  Gene deletion: b2836 b4384 b3708 b3008 b3752 b0871 b2925 b2097 b2407 b1779 b1982 b2797 b3117 b1814 b4471 b3946 b0825 b0261 b4381 b2406 b0114 b1539 b2492 b0904 b2578 b1533 b3927 b3662 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.371191 (mmol/gDw/h)
  Minimum Production Rate : 0.042587 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 29.999495
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.264757
  EX_pi_e : 0.358053
  EX_so4_e : 0.136059
  EX_k_e : 0.072454
  EX_fe2_e : 0.005963
  EX_mg2_e : 0.003220
  EX_cl_e : 0.001932
  EX_ca2_e : 0.001932
  EX_cu2_e : 0.000263
  EX_mn2_e : 0.000256
  EX_zn2_e : 0.000127
  EX_ni2_e : 0.000120

Product: (mmol/gDw/h)
  EX_h2o_e : 43.856794
  EX_co2_e : 28.167111
  EX_h_e : 8.829770
  EX_pyr_e : 5.333119
  Auxiliary production reaction : 0.042585
  DM_oxam_c : 0.000415
  DM_5drib_c : 0.000249
  DM_4crsol_c : 0.000083

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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