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 (32 of 115: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b3399 b1241 b0351 b4069 b4384 b2744 b2297 b2458 b3617 b0160 b1982 b3665 b0675 b2361 b0261 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 : 0.357257 (mmol/gDw/h)
  Minimum Production Rate : 1.350652 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 22.568006
  EX_nh4_e : 11.973606
  EX_glc__D_e : 10.000000
  EX_pi_e : 0.344612
  EX_so4_e : 0.089965
  EX_k_e : 0.069734
  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 : 51.006128
  EX_co2_e : 19.938828
  EX_h_e : 15.991273
  EX_ac_e : 3.233393
  Auxiliary production reaction : 1.350652
  DM_oxam_c : 0.009348
  EX_ade_e : 0.000400
  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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