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 : dgmp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (56 of 84: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b3399 b1241 b0351 b2744 b2930 b4232 b3697 b3925 b0871 b3115 b1849 b2296 b2779 b3617 b3946 b0825 b2913 b4381 b0511 b0114 b0529 b2492 b0904 b0516 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.358686 (mmol/gDw/h)
  Minimum Production Rate : 0.065084 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 30.389692
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.237707
  EX_pi_e : 0.411075
  EX_so4_e : 0.090324
  EX_k_e : 0.070013
  EX_fe2_e : 0.005761
  EX_mg2_e : 0.003112
  EX_ca2_e : 0.001867
  EX_cl_e : 0.001867
  EX_cu2_e : 0.000254
  EX_mn2_e : 0.000248
  EX_zn2_e : 0.000122
  EX_ni2_e : 0.000116

Product: (mmol/gDw/h)
  EX_h2o_e : 44.025996
  EX_co2_e : 28.240534
  EX_h_e : 9.105702
  EX_pyr_e : 5.445904
  Auxiliary production reaction : 0.065084
  EX_xan_e : 0.009627
  EX_glyc__R_e : 0.000120
  DM_5drib_c : 0.000081
  DM_4crsol_c : 0.000080

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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