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 : gtp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (38 of 70: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b2836 b3399 b4069 b2502 b2744 b3708 b3008 b2297 b2458 b1238 b1982 b2797 b3117 b1814 b4471 b0675 b2361 b0261 b4381 b0114 b1539 b2492 b0904 b1533 b3927   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.744721 (mmol/gDw/h)
  Minimum Production Rate : 0.315402 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 24.766623
  EX_glc__D_e : 10.000000
  EX_nh4_e : 9.619927
  EX_pi_e : 1.664567
  EX_so4_e : 0.187536
  EX_k_e : 0.145364
  EX_fe2_e : 0.011961
  EX_mg2_e : 0.006460
  EX_ca2_e : 0.003876
  EX_cl_e : 0.003876
  EX_cu2_e : 0.000528
  EX_mn2_e : 0.000515
  EX_zn2_e : 0.000254
  EX_ni2_e : 0.000241
  EX_cobalt2_e : 0.000019

Product: (mmol/gDw/h)
  EX_h2o_e : 49.491467
  EX_co2_e : 25.409834
  EX_h_e : 8.222560
  EX_ac_e : 0.433566
  Auxiliary production reaction : 0.315402
  DM_5drib_c : 0.000500
  DM_4crsol_c : 0.000166

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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