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 : 5aizc_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (69 of 80: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 40
  Gene deletion: b3553 b1478 b1241 b4069 b4384 b3752 b3115 b1849 b2296 b2407 b3844 b1004 b3713 b1109 b0046 b3236 b0207 b3012 b1982 b1033 b0261 b0411 b2799 b1602 b4381 b3915 b0755 b3612 b0529 b2492 b0904 b1781 b3001 b1380 b0325 b2660 b1771 b0606 b2285 b1010   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.350256 (mmol/gDw/h)
  Minimum Production Rate : 1.098933 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 36.772537
  EX_glc__D_e : 10.000000
  EX_nh4_e : 7.081103
  EX_pi_e : 1.436792
  EX_so4_e : 0.088202
  EX_k_e : 0.068368
  EX_fe3_e : 0.005625
  EX_mg2_e : 0.003038
  EX_ca2_e : 0.001823
  EX_cl_e : 0.001823
  EX_cu2_e : 0.000248
  EX_mn2_e : 0.000242
  EX_zn2_e : 0.000119
  EX_ni2_e : 0.000113

Product: (mmol/gDw/h)
  EX_h2o_e : 53.364103
  EX_co2_e : 35.322630
  EX_h_e : 7.825132
  Auxiliary production reaction : 1.098933
  EX_ac_e : 0.203914
  EX_hxan_e : 0.000392
  DM_5drib_c : 0.000235
  DM_4crsol_c : 0.000078

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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