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

Gene deletion strategy (106 of 116: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 46
  Gene deletion: b3399 b4382 b1241 b0351 b4069 b2744 b3708 b0910 b3115 b1849 b2296 b3617 b0160 b1779 b3962 b1982 b4139 b2797 b3117 b1814 b4471 b4267 b0675 b2361 b1415 b0261 b2799 b3945 b4381 b2406 b0112 b0452 b2975 b0114 b3603 b0509 b3125 b1539 b2492 b0904 b3035 b1533 b1380 b0508 b4266 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.324454 (mmol/gDw/h)
  Minimum Production Rate : 0.093765 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 36.371932
  EX_glc__D_e : 10.000000
  EX_nh4_e : 7.322297
  EX_pi_e : 1.265312
  EX_so4_e : 0.081704
  EX_k_e : 0.063331
  EX_fe2_e : 0.005211
  EX_mg2_e : 0.002815
  EX_ca2_e : 0.001689
  EX_cl_e : 0.001689
  EX_cu2_e : 0.000230
  EX_mn2_e : 0.000224
  EX_zn2_e : 0.000111
  EX_ni2_e : 0.000105

Product: (mmol/gDw/h)
  EX_h2o_e : 51.826981
  EX_co2_e : 34.670263
  EX_h_e : 8.519726
  EX_ac_e : 1.711439
  Auxiliary production reaction : 0.952341
  DM_oxam_c : 0.008853
  DM_5drib_c : 0.000218
  DM_4crsol_c : 0.000072

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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