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 : ahdt_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (16 of 83: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b3399 b1241 b0351 b4069 b2744 b2297 b2458 b3617 b0160 b1982 b4374 b0675 b2361 b2291 b0261 b0112 b2975 b0114 b3603 b0509 b3125 b0529 b2492 b0904 b0508   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.457223 (mmol/gDw/h)
  Minimum Production Rate : 1.752513 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 24.021590
  EX_nh4_e : 13.701052
  EX_glc__D_e : 10.000000
  EX_pi_e : 5.698580
  EX_so4_e : 0.115138
  EX_k_e : 0.089247
  EX_fe2_e : 0.007343
  EX_mg2_e : 0.003966
  EX_ca2_e : 0.002380
  EX_cl_e : 0.002380
  EX_cu2_e : 0.000324
  EX_mn2_e : 0.000316
  EX_zn2_e : 0.000156
  EX_ni2_e : 0.000148
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_h2o_e : 55.473067
  EX_co2_e : 20.615366
  EX_h_e : 11.881240
  EX_ac_e : 2.421526
  Auxiliary production reaction : 1.752513
  DM_oxam_c : 0.000512
  DM_5drib_c : 0.000307
  DM_4crsol_c : 0.000102

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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