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 : 2tpr3dpcoa_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (46 of 106: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 28
  Gene deletion: b3399 b4069 b2502 b2744 b3708 b3008 b3115 b1849 b2296 b2926 b1982 b2797 b3117 b1814 b4471 b0675 b2361 b0261 b1701 b1805 b4381 b2406 b0114 b2366 b2492 b0904 b1533 b3927   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.658515 (mmol/gDw/h)
  Minimum Production Rate : 0.098143 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 27.951159
  EX_glc__D_e : 10.000000
  EX_nh4_e : 7.798912
  EX_pi_e : 1.125923
  EX_so4_e : 0.263970
  EX_k_e : 0.128538
  EX_fe2_e : 0.010576
  EX_mg2_e : 0.005713
  EX_cl_e : 0.003428
  EX_ca2_e : 0.003428
  EX_cu2_e : 0.000467
  EX_mn2_e : 0.000455
  EX_zn2_e : 0.000225
  EX_ni2_e : 0.000213
  EX_cobalt2_e : 0.000016

Product: (mmol/gDw/h)
  EX_h2o_e : 49.003454
  EX_co2_e : 29.454735
  EX_h_e : 6.630368
  EX_ac_e : 0.481522
  Auxiliary production reaction : 0.098143
  DM_5drib_c : 0.000442
  DM_4crsol_c : 0.000147

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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