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 : adn_e
List of minimal gene deletion strategies (Download)

Gene deletion strategy (37 of 82: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b4382 b4384 b2744 b3708 b3008 b3752 b0871 b2926 b2407 b1982 b2797 b3117 b1814 b4471 b2440 b0261 b0114 b0529 b1539 b2492 b0904 b1533 b3927 b3662 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.498379 (mmol/gDw/h)
  Minimum Production Rate : 0.114396 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 37.621081
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.954432
  EX_pi_e : 0.480740
  EX_so4_e : 0.125502
  EX_k_e : 0.097280
  EX_fe2_e : 0.008004
  EX_mg2_e : 0.004323
  EX_ca2_e : 0.002594
  EX_cl_e : 0.002594
  EX_cu2_e : 0.000353
  EX_mn2_e : 0.000344
  EX_zn2_e : 0.000170
  EX_ni2_e : 0.000161
  EX_cobalt2_e : 0.000012

Product: (mmol/gDw/h)
  EX_h2o_e : 52.817924
  EX_co2_e : 38.398754
  EX_h_e : 5.151285
  EX_adn_e : 0.114396
  DM_5drib_c : 0.000334
  DM_4crsol_c : 0.000111

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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