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 : cdigmp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (64 of 79: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 32
  Gene deletion: b3399 b4069 b2502 b2744 b3708 b3008 b3115 b1849 b2296 b2926 b1238 b3236 b1982 b2797 b3117 b1814 b4471 b2210 b0675 b2361 b4381 b0511 b0114 b2366 b2492 b0904 b1533 b3927 b3825 b0494 b0515 b1511   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.663906 (mmol/gDw/h)
  Minimum Production Rate : 0.140812 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 992.374299
  EX_o2_e : 278.583451
  EX_glc__D_e : 10.000000
  EX_nh4_e : 8.580041
  EX_pi_e : 0.922032
  EX_so4_e : 0.167185
  EX_k_e : 0.129590
  EX_mg2_e : 0.005759
  EX_ca2_e : 0.003456
  EX_cl_e : 0.003456
  EX_cu2_e : 0.000471
  EX_mn2_e : 0.000459
  EX_zn2_e : 0.000226
  EX_ni2_e : 0.000214
  EX_cobalt2_e : 0.000017

Product: (mmol/gDw/h)
  EX_fe3_e : 999.989337
  EX_h2o_e : 550.348432
  EX_co2_e : 29.156694
  EX_ac_e : 0.386517
  Auxiliary production reaction : 0.140812
  EX_xan_e : 0.000447
  DM_mththf_c : 0.000297
  DM_5drib_c : 0.000149
  DM_4crsol_c : 0.000148

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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