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 : dhpt_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (35 of 115: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b1241 b0351 b4069 b4384 b3752 b2297 b2458 b2407 b1982 b3616 b3589 b4014 b0261 b2976 b0507 b4381 b2406 b0112 b2975 b0114 b3603 b0529 b2492 b0904 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.354920 (mmol/gDw/h)
  Minimum Production Rate : 1.360391 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 22.548969
  EX_nh4_e : 11.995853
  EX_glc__D_e : 10.000000
  EX_pi_e : 0.342358
  EX_so4_e : 0.089376
  EX_k_e : 0.069278
  EX_fe2_e : 0.005700
  EX_mg2_e : 0.003079
  EX_ca2_e : 0.001847
  EX_cl_e : 0.001847
  EX_cu2_e : 0.000252
  EX_mn2_e : 0.000245
  EX_zn2_e : 0.000121
  EX_ni2_e : 0.000115

Product: (mmol/gDw/h)
  EX_h2o_e : 51.044398
  EX_co2_e : 19.904883
  EX_h_e : 16.024785
  EX_ac_e : 3.240104
  Auxiliary production reaction : 1.360391
  DM_oxam_c : 0.000397
  DM_5drib_c : 0.000238
  DM_4crsol_c : 0.000079

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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