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 : dnad_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (70 of 84: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 42
  Gene deletion: b3399 b1241 b0351 b2502 b2744 b3708 b3008 b0871 b2779 b2925 b2097 b3617 b1982 b2797 b3117 b1814 b4471 b3946 b0825 b0675 b2361 b0261 b0507 b2913 b4381 b2406 b0112 b0452 b2868 b0114 b0886 b0529 b1539 b2492 b0904 b2578 b1533 b3927 b4141 b1798 b2285 b4209   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.353502 (mmol/gDw/h)
  Minimum Production Rate : 0.071842 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 30.145391
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.287378
  EX_pi_e : 0.484658
  EX_so4_e : 0.089020
  EX_k_e : 0.069001
  EX_mg2_e : 0.003067
  EX_fe2_e : 0.002919
  EX_fe3_e : 0.002760
  EX_ca2_e : 0.001840
  EX_cl_e : 0.001840
  EX_cu2_e : 0.000251
  EX_mn2_e : 0.000244
  EX_zn2_e : 0.000121
  EX_ni2_e : 0.000114

Product: (mmol/gDw/h)
  EX_h2o_e : 44.172428
  EX_co2_e : 28.006546
  EX_h_e : 8.885559
  EX_pyr_e : 5.308763
  Auxiliary production reaction : 0.071834
  EX_hxan_e : 0.009645
  DM_5drib_c : 0.000237
  DM_4crsol_c : 0.000079

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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