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 : cxsam_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (2 of 5: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b4382 b4069 b4384 b3708 b3008 b3752 b3115 b1849 b2296 b2407 b1982 b2797 b3117 b1814 b4471 b0261 b2406 b0114 b1539 b2492 b0904 b1533 b3927 b3821 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.737941 (mmol/gDw/h)
  Minimum Production Rate : 0.136715 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 23.807071
  EX_glc__D_e : 10.000000
  EX_nh4_e : 9.044179
  EX_pi_e : 0.711822
  EX_so4_e : 0.322543
  EX_k_e : 0.144041
  EX_fe2_e : 0.011852
  EX_mg2_e : 0.006402
  EX_ca2_e : 0.003841
  EX_cl_e : 0.003841
  EX_cu2_e : 0.000523
  EX_mn2_e : 0.000510
  EX_zn2_e : 0.000252
  EX_ni2_e : 0.000238
  EX_cobalt2_e : 0.000018

Product: (mmol/gDw/h)
  EX_h2o_e : 47.164285
  EX_co2_e : 25.118204
  EX_h_e : 8.147880
  EX_ac_e : 0.566333
  EX_acser_e : 0.254196
  Auxiliary production reaction : 0.136715
  DM_5drib_c : 0.000495
  DM_4crsol_c : 0.000165

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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