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 : cpmp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (21 of 38: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b3399 b4382 b1241 b0351 b4069 b2502 b4384 b2744 b3752 b2297 b2458 b2883 b1982 b3616 b3589 b1623 b2361 b2291 b0261 b0411 b0114 b0529 b2492 b0904 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.577705 (mmol/gDw/h)
  Minimum Production Rate : 1.107157 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 23.399347
  EX_nh4_e : 11.774955
  EX_glc__D_e : 10.000000
  EX_pi_e : 1.664415
  EX_so4_e : 0.145478
  EX_k_e : 0.112764
  EX_fe2_e : 0.009279
  EX_mg2_e : 0.005012
  EX_cl_e : 0.003007
  EX_ca2_e : 0.003007
  EX_cu2_e : 0.000410
  EX_mn2_e : 0.000399
  EX_zn2_e : 0.000197
  EX_ni2_e : 0.000187
  EX_cobalt2_e : 0.000014

Product: (mmol/gDw/h)
  EX_h2o_e : 49.852329
  EX_co2_e : 21.310840
  EX_h_e : 11.688890
  EX_ac_e : 1.952073
  Auxiliary production reaction : 1.107157
  DM_5drib_c : 0.000388
  DM_4crsol_c : 0.000129

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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