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 : 2p4c2me_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (97 of 116: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 31
  Gene deletion: b4382 b3831 b4384 b3614 b0910 b3752 b4152 b3115 b1849 b2296 b2925 b2097 b2781 b1612 b1611 b4122 b1779 b2690 b1759 b4015 b0411 b3945 b4138 b4123 b0621 b2913 b0529 b2197 b3918 b1912 b1206   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.598108 (mmol/gDw/h)
  Minimum Production Rate : 0.315888 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 992.195853
  EX_o2_e : 276.415388
  EX_glc__D_e : 10.000000
  EX_nh4_e : 7.623701
  EX_pi_e : 1.524603
  EX_so4_e : 0.150616
  EX_k_e : 0.116747
  EX_mg2_e : 0.005189
  EX_cl_e : 0.003113
  EX_ca2_e : 0.003113
  EX_cu2_e : 0.000424
  EX_mn2_e : 0.000413
  EX_zn2_e : 0.000204
  EX_ni2_e : 0.000193
  EX_cobalt2_e : 0.000015

Product: (mmol/gDw/h)
  EX_fe3_e : 999.990394
  EX_h2o_e : 547.175443
  EX_co2_e : 27.061981
  EX_succ_e : 0.623703
  EX_ac_e : 0.519071
  Auxiliary production reaction : 0.315888
  EX_ura_e : 0.108259
  DM_5drib_c : 0.000135
  DM_4crsol_c : 0.000133

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.

Last updated: 21-Sep-2023
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