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_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (58 of 85: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 37
  Gene deletion: b2836 b1241 b0351 b4069 b4384 b3708 b3752 b2297 b2458 b2925 b2097 b3617 b2407 b1238 b3124 b1982 b2797 b3117 b1814 b4471 b3946 b0825 b0261 b4381 b2406 b0112 b2789 b3127 b2868 b0114 b2366 b0755 b3612 b2492 b0904 b1533 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.458524 (mmol/gDw/h)
  Minimum Production Rate : 0.144154 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 25.034150
  EX_glc__D_e : 10.000000
  EX_nh4_e : 8.384784
  EX_pi_e : 0.442295
  EX_so4_e : 0.115466
  EX_k_e : 0.089501
  EX_fe2_e : 0.007364
  EX_mg2_e : 0.003978
  EX_ca2_e : 0.002387
  EX_cl_e : 0.002387
  EX_cu2_e : 0.000325
  EX_mn2_e : 0.000317
  EX_zn2_e : 0.000156
  EX_ni2_e : 0.000148
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_h2o_e : 46.628217
  EX_co2_e : 25.596219
  EX_h_e : 9.532395
  EX_ac_e : 1.742069
  EX_ade_e : 0.686552
  DM_5drib_c : 0.686347
  DM_4crsol_c : 0.686142
  Auxiliary production reaction : 0.144154
  EX_glyclt_e : 0.000307

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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