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 : dctp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (59 of 73: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 42
  Gene deletion: b3399 b0586 b4069 b2744 b3708 b3008 b0512 b3115 b1849 b2296 b0160 b1779 b1982 b2797 b3117 b1814 b4471 b3449 b4374 b0675 b2361 b2291 b0261 b0507 b3709 b3161 b0112 b0511 b2975 b0114 b3603 b0886 b2366 b2492 b0904 b2578 b1533 b3927 b1473 b0494 b4141 b1798   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.605484 (mmol/gDw/h)
  Minimum Production Rate : 0.769444 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 26.992172
  EX_glc__D_e : 10.000000
  EX_nh4_e : 8.850211
  EX_pi_e : 2.892384
  EX_so4_e : 0.152473
  EX_k_e : 0.118186
  EX_fe2_e : 0.009725
  EX_mg2_e : 0.005253
  EX_ca2_e : 0.003152
  EX_cl_e : 0.003152
  EX_cu2_e : 0.000429
  EX_mn2_e : 0.000418
  EX_zn2_e : 0.000206
  EX_ni2_e : 0.000196
  EX_cobalt2_e : 0.000015

Product: (mmol/gDw/h)
  EX_h2o_e : 51.202624
  EX_co2_e : 27.512945
  EX_h_e : 6.688082
  Auxiliary production reaction : 0.769444
  EX_ac_e : 0.352504
  EX_xan_e : 0.000678
  DM_5drib_c : 0.000406
  DM_4crsol_c : 0.000135

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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