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 : 2mcacn_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (3 of 3: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b1241 b0351 b2930 b4232 b3697 b3925 b0871 b3115 b1849 b2296 b1779 b2690 b0614 b3945 b4138 b4123 b0621 b0452 b0612 b0755 b3612 b1539 b0723 b1206 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.494237 (mmol/gDw/h)
  Minimum Production Rate : 1.082023 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 31.030125
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.337719
  EX_pi_e : 0.476744
  EX_so4_e : 0.124459
  EX_k_e : 0.096472
  EX_fe2_e : 0.007938
  EX_mg2_e : 0.004288
  EX_ca2_e : 0.002573
  EX_cl_e : 0.002573
  EX_cu2_e : 0.000350
  EX_mn2_e : 0.000342
  EX_zn2_e : 0.000169
  EX_ni2_e : 0.000160
  EX_cobalt2_e : 0.000012

Product: (mmol/gDw/h)
  EX_h2o_e : 47.300318
  EX_co2_e : 31.002814
  EX_h_e : 8.355748
  Auxiliary production reaction : 1.082023
  EX_ac_e : 0.568432
  DM_5drib_c : 0.000111
  DM_4crsol_c : 0.000110

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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