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 : ttdca_p
List of minimal gene deletion strategies (Download)

Gene deletion strategy (104 of 109: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 33
  Gene deletion: b4467 b2242 b3831 b1278 b3614 b0910 b3752 b2297 b2458 b2781 b1004 b3713 b1109 b0046 b1612 b1611 b4122 b1759 b2210 b1415 b4138 b4123 b0621 b4381 b2406 b3731 b2492 b0904 b2197 b3028 b3918 b1206 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.119296 (mmol/gDw/h)
  Minimum Production Rate : 0.063006 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 981.313680
  EX_o2_e : 271.678946
  EX_glc__D_e : 10.000000
  EX_nh4_e : 1.520588
  EX_pi_e : 0.115074
  EX_so4_e : 0.030041
  EX_k_e : 0.023286
  EX_mg2_e : 0.001035
  EX_cl_e : 0.000621
  EX_ca2_e : 0.000621
  EX_cu2_e : 0.000085
  EX_mn2_e : 0.000082
  EX_zn2_e : 0.000041
  EX_ni2_e : 0.000039

Product: (mmol/gDw/h)
  EX_fe3_e : 999.998084
  EX_h2o_e : 530.472888
  EX_co2_e : 18.288776
  EX_succ_e : 8.611803
  Auxiliary production reaction : 0.126011
  EX_ura_e : 0.084598
  EX_ac_e : 0.069452
  EX_etha_e : 0.063006
  DM_5drib_c : 0.000027
  DM_4crsol_c : 0.000027

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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