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 : mththf_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (33 of 41: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 27
  Gene deletion: b1241 b0351 b4069 b4384 b2744 b3708 b3115 b1849 b2296 b3617 b0030 b2407 b1982 b2797 b3117 b1814 b4471 b4374 b2361 b2291 b0114 b2366 b2492 b0904 b1533 b1601 b1517   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.619272 (mmol/gDw/h)
  Minimum Production Rate : 0.926965 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 23.917975
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.688085
  EX_pi_e : 0.597353
  EX_so4_e : 0.155945
  EX_k_e : 0.120878
  EX_fe2_e : 0.009946
  EX_mg2_e : 0.005372
  EX_ca2_e : 0.003223
  EX_cl_e : 0.003223
  EX_cu2_e : 0.000439
  EX_mn2_e : 0.000428
  EX_zn2_e : 0.000211
  EX_ni2_e : 0.000200
  EX_cobalt2_e : 0.000015

Product: (mmol/gDw/h)
  EX_h2o_e : 41.592914
  EX_co2_e : 25.239653
  EX_h_e : 8.043054
  EX_ac_e : 2.352936
  DM_mththf_c : 0.926965
  DM_5drib_c : 0.000416
  DM_4crsol_c : 0.000138

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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