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 : coa_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (9 of 83: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 29
  Gene deletion: b3399 b1241 b0351 b4069 b2502 b2744 b3708 b2297 b2458 b3617 b1238 b1982 b2797 b3117 b1814 b4471 b0675 b2361 b0261 b4381 b2406 b0112 b0452 b2868 b0114 b2366 b2492 b0904 b1533   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.518678 (mmol/gDw/h)
  Minimum Production Rate : 0.517333 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 20.726234
  EX_glc__D_e : 10.000000
  EX_nh4_e : 9.225917
  EX_pi_e : 2.052320
  EX_so4_e : 0.647947
  EX_k_e : 0.101242
  EX_fe2_e : 0.008330
  EX_mg2_e : 0.004500
  EX_ca2_e : 0.002700
  EX_cl_e : 0.002700
  EX_cu2_e : 0.000368
  EX_mn2_e : 0.000358
  EX_zn2_e : 0.000177
  EX_ni2_e : 0.000168
  EX_cobalt2_e : 0.000013

Product: (mmol/gDw/h)
  EX_h2o_e : 45.881100
  EX_co2_e : 22.349102
  EX_h_e : 9.067464
  EX_ac_e : 2.746738
  Auxiliary production reaction : 0.517333
  EX_ade_e : 0.000580
  DM_5drib_c : 0.000348
  DM_4crsol_c : 0.000116

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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