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 : ade_e
List of minimal gene deletion strategies (Download)

Gene deletion strategy (106 of 133: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b2066 b0474 b2518 b1241 b0351 b2744 b0910 b0871 b2925 b2097 b2926 b2781 b0099 b3617 b0160 b3946 b0825 b4381 b2868 b4064 b4464 b0114 b0529 b2492 b0904   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.624878 (mmol/gDw/h)
  Minimum Production Rate : 0.016771 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 31.220661
  EX_nh4_e : 10.343557
  EX_glc__D_e : 10.000000
  EX_pi_e : 0.602761
  EX_so4_e : 0.157357
  EX_k_e : 0.121972
  EX_fe2_e : 0.010036
  EX_mg2_e : 0.005421
  EX_ca2_e : 0.003252
  EX_cl_e : 0.003252
  EX_cu2_e : 0.000443
  EX_mn2_e : 0.000432
  EX_zn2_e : 0.000213
  EX_ni2_e : 0.000202
  EX_cobalt2_e : 0.000016

Product: (mmol/gDw/h)
  EX_h2o_e : 54.447855
  EX_co2_e : 29.878932
  EX_h_e : 9.336556
  EX_xan_e : 0.877768
  EX_ade_e : 0.016771
  DM_5drib_c : 0.000141
  DM_4crsol_c : 0.000139

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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