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 : pnto__R_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (26 of 79: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 32
  Gene deletion: b2836 b3399 b2744 b3708 b3008 b0871 b2925 b2097 b0160 b1982 b2797 b3117 b1814 b4471 b3946 b0825 b0595 b4374 b0675 b2361 b2291 b0261 b0114 b0886 b2366 b2492 b0904 b2578 b1533 b3927 b4141 b1798   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.764535 (mmol/gDw/h)
  Minimum Production Rate : 0.066522 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 992.828113
  EX_o2_e : 274.616122
  EX_glc__D_e : 10.000000
  EX_nh4_e : 8.692097
  EX_pi_e : 0.737475
  EX_so4_e : 0.284477
  EX_k_e : 0.149232
  EX_mg2_e : 0.006632
  EX_ca2_e : 0.003979
  EX_cl_e : 0.003979
  EX_cu2_e : 0.000542
  EX_mn2_e : 0.000528
  EX_zn2_e : 0.000261
  EX_ni2_e : 0.000247
  EX_cobalt2_e : 0.000019

Product: (mmol/gDw/h)
  EX_fe3_e : 999.987721
  EX_h2o_e : 547.415595
  EX_co2_e : 26.637964
  DM_oxam_c : 0.092807
  EX_5mtr_e : 0.091951
  EX_spmd_e : 0.091951
  Auxiliary production reaction : 0.066522
  DM_5drib_c : 0.000513
  DM_4crsol_c : 0.000170

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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