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 : glyc__R_e
List of minimal gene deletion strategies (Download)

Gene deletion strategy (35 of 83: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 33
  Gene deletion: b3399 b4382 b1241 b0351 b4069 b2502 b4384 b2744 b3708 b3115 b1849 b2296 b2779 b2926 b1982 b2797 b3117 b1814 b4471 b3616 b3589 b0675 b2361 b2291 b0261 b2406 b0112 b0114 b1539 b2492 b0904 b1533 b3821   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.468538 (mmol/gDw/h)
  Minimum Production Rate : 0.350667 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 25.165703
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.761712
  EX_pi_e : 0.451954
  EX_so4_e : 0.117987
  EX_k_e : 0.091455
  EX_fe2_e : 0.007525
  EX_mg2_e : 0.004065
  EX_ca2_e : 0.002439
  EX_cl_e : 0.002439
  EX_cu2_e : 0.000332
  EX_mn2_e : 0.000324
  EX_zn2_e : 0.000160
  EX_ni2_e : 0.000151
  EX_cobalt2_e : 0.000012

Product: (mmol/gDw/h)
  EX_h2o_e : 42.219003
  EX_co2_e : 26.340066
  EX_h_e : 7.838981
  EX_ac_e : 1.780113
  DM_oxam_c : 0.701546
  DM_5drib_c : 0.701336
  DM_4crsol_c : 0.701126
  EX_glyc__R_e : 0.350667

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.

Last updated: 21-Sep-2023
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