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 : pe161_p
List of minimal gene deletion strategies (Download)

Gene deletion strategy (65 of 80: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b1054 b3831 b2744 b3614 b0910 b3752 b4152 b2781 b1612 b1611 b4122 b1759 b4374 b2361 b2291 b0411 b4138 b4123 b0621 b2197 b3821 b3918 b0789 b1249 b1206   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.573767 (mmol/gDw/h)
  Minimum Production Rate : 0.303032 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 16.659098
  EX_glc__D_e : 10.000000
  EX_nh4_e : 7.313438
  EX_pi_e : 0.856491
  EX_so4_e : 0.144486
  EX_k_e : 0.111995
  EX_fe2_e : 0.009215
  EX_mg2_e : 0.004977
  EX_ca2_e : 0.002986
  EX_cl_e : 0.002986
  EX_cu2_e : 0.000407
  EX_mn2_e : 0.000396
  EX_zn2_e : 0.000196
  EX_ni2_e : 0.000185
  EX_cobalt2_e : 0.000014

Product: (mmol/gDw/h)
  EX_h2o_e : 40.515998
  EX_co2_e : 21.216490
  EX_h_e : 6.979378
  EX_succ_e : 0.598320
  EX_ura_e : 0.406886
  Auxiliary production reaction : 0.303032
  DM_5drib_c : 0.000129
  DM_4crsol_c : 0.000128

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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