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 : glx_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (44 of 81: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b4382 b1241 b0351 b4069 b4384 b3752 b2297 b2458 b2407 b3124 b1779 b1982 b3616 b3589 b0261 b2913 b2406 b0112 b0114 b0755 b3612 b0529 b2492 b0904 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.424454 (mmol/gDw/h)
  Minimum Production Rate : 0.813738 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 24.863135
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.397994
  EX_pi_e : 0.409431
  EX_so4_e : 0.106886
  EX_k_e : 0.082850
  EX_fe2_e : 0.006817
  EX_mg2_e : 0.003682
  EX_ca2_e : 0.002209
  EX_cl_e : 0.002209
  EX_cu2_e : 0.000301
  EX_mn2_e : 0.000293
  EX_zn2_e : 0.000145
  EX_ni2_e : 0.000137
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_h2o_e : 41.451911
  EX_co2_e : 25.361299
  EX_h_e : 8.441192
  EX_ac_e : 2.099543
  DM_oxam_c : 0.813929
  DM_5drib_c : 0.813739
  Auxiliary production reaction : 0.813738
  DM_4crsol_c : 0.813549

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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