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 : ppgpp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (27 of 82: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b1241 b0351 b4069 b3115 b1849 b2296 b3617 b0030 b2407 b2883 b0261 b4381 b2406 b0112 b3654 b2868 b3714 b3664 b4064 b4464 b0114 b0529 b2492 b0904 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.572922 (mmol/gDw/h)
  Minimum Production Rate : 1.098631 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 23.699330
  EX_nh4_e : 11.680660
  EX_glc__D_e : 10.000000
  EX_pi_e : 4.947166
  EX_so4_e : 0.144273
  EX_k_e : 0.111830
  EX_fe2_e : 0.009202
  EX_mg2_e : 0.004970
  EX_cl_e : 0.002982
  EX_ca2_e : 0.002982
  EX_cu2_e : 0.000406
  EX_mn2_e : 0.000396
  EX_zn2_e : 0.000195
  EX_ni2_e : 0.000185
  EX_cobalt2_e : 0.000014

Product: (mmol/gDw/h)
  EX_h2o_e : 53.234806
  EX_co2_e : 21.626065
  EX_h_e : 10.496036
  EX_ac_e : 1.935909
  Auxiliary production reaction : 1.098631
  DM_5drib_c : 0.000129
  DM_4crsol_c : 0.000128

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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