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 : dhnpt_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (35 of 90: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b1241 b0351 b4069 b2744 b3115 b1849 b2296 b2883 b3616 b3589 b0261 b4381 b2406 b0112 b3654 b2868 b3714 b3664 b4064 b4464 b0114 b0529 b2492 b0904 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.458151 (mmol/gDw/h)
  Minimum Production Rate : 1.757092 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 23.942943
  EX_nh4_e : 13.733446
  EX_glc__D_e : 10.000000
  EX_pi_e : 0.441935
  EX_so4_e : 0.115371
  EX_k_e : 0.089428
  EX_fe2_e : 0.007358
  EX_mg2_e : 0.003974
  EX_cl_e : 0.002385
  EX_ca2_e : 0.002385
  EX_cu2_e : 0.000325
  EX_mn2_e : 0.000317
  EX_zn2_e : 0.000156
  EX_ni2_e : 0.000148
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_h2o_e : 50.197323
  EX_co2_e : 20.527916
  EX_h_e : 15.421771
  EX_ac_e : 2.426642
  Auxiliary production reaction : 1.757092
  DM_5drib_c : 0.000103
  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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