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 : dgsn_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (39 of 77: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b4384 b3708 b3008 b0871 b2925 b2097 b0030 b2407 b3236 b1982 b2797 b3117 b1814 b4471 b3946 b0825 b3665 b4381 b0452 b0114 b2366 b2492 b0904 b1533 b3927   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.778540 (mmol/gDw/h)
  Minimum Production Rate : 0.134193 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 24.957429
  EX_glc__D_e : 10.000000
  EX_nh4_e : 9.081746
  EX_pi_e : 0.750984
  EX_so4_e : 0.196052
  EX_k_e : 0.151965
  EX_fe2_e : 0.012504
  EX_mg2_e : 0.006754
  EX_ca2_e : 0.004052
  EX_cl_e : 0.004052
  EX_cu2_e : 0.000552
  EX_mn2_e : 0.000538
  EX_zn2_e : 0.000265
  EX_ni2_e : 0.000251
  EX_cobalt2_e : 0.000019

Product: (mmol/gDw/h)
  EX_h2o_e : 48.406081
  EX_co2_e : 26.198472
  EX_h_e : 7.994286
  EX_pyr_e : 0.167168
  Auxiliary production reaction : 0.134193
  EX_ade_e : 0.000524
  DM_5drib_c : 0.000175
  DM_4crsol_c : 0.000174

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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