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 : dhpt_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (29 of 115: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b3399 b1241 b0351 b4069 b2502 b2744 b2297 b2458 b3617 b1982 b0675 b2361 b4014 b0261 b2976 b0507 b4381 b2406 b0112 b2975 b0114 b3603 b0529 b2492 b0904   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.357262 (mmol/gDw/h)
  Minimum Production Rate : 1.350670 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 22.568302
  EX_nh4_e : 11.972168
  EX_glc__D_e : 10.000000
  EX_pi_e : 0.344617
  EX_so4_e : 0.089966
  EX_k_e : 0.069735
  EX_fe2_e : 0.005738
  EX_mg2_e : 0.003099
  EX_ca2_e : 0.001860
  EX_cl_e : 0.001860
  EX_cu2_e : 0.000253
  EX_mn2_e : 0.000247
  EX_zn2_e : 0.000122
  EX_ni2_e : 0.000115

Product: (mmol/gDw/h)
  EX_h2o_e : 51.004008
  EX_co2_e : 19.939489
  EX_h_e : 15.990289
  EX_ac_e : 3.233437
  Auxiliary production reaction : 1.350670
  DM_oxam_c : 0.009748
  DM_5drib_c : 0.000240
  DM_4crsol_c : 0.000080

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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