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 : cpmp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (38 of 38: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 46
  Gene deletion: b3553 b1478 b4269 b0493 b3588 b3003 b3011 b1241 b4384 b2744 b3752 b0871 b2779 b2925 b2097 b2407 b1004 b3713 b1109 b0046 b3236 b1638 b2690 b1982 b4139 b1033 b4374 b2361 b2291 b0261 b2799 b3945 b1602 b2342 b3845 b2406 b0114 b0529 b2492 b0904 b3927 b3029 b1380 b2660 b3662 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.346897 (mmol/gDw/h)
  Minimum Production Rate : 0.092771 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 30.356731
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.210316
  EX_pi_e : 0.427390
  EX_so4_e : 0.087356
  EX_k_e : 0.067712
  EX_fe3_e : 0.005572
  EX_mg2_e : 0.003009
  EX_ca2_e : 0.001806
  EX_cl_e : 0.001806
  EX_cu2_e : 0.000246
  EX_mn2_e : 0.000240
  EX_zn2_e : 0.000118
  EX_ni2_e : 0.000112

Product: (mmol/gDw/h)
  EX_h2o_e : 43.776523
  EX_co2_e : 28.134890
  EX_h_e : 9.130115
  EX_pyr_e : 5.370568
  EX_3hpp_e : 0.195460
  Auxiliary production reaction : 0.092771
  DM_5drib_c : 0.000233
  DM_4crsol_c : 0.000077

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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