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 : 25aics_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (52 of 80: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 36
  Gene deletion: b3553 b1478 b1241 b4069 b4384 b3752 b2297 b2458 b2779 b2926 b2407 b3844 b1004 b3713 b1109 b0046 b3236 b0937 b1982 b1033 b0261 b2799 b3945 b1602 b4381 b2406 b0529 b1539 b2492 b0904 b1380 b2660 b3662 b0606 b2285 b1008   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.314348 (mmol/gDw/h)
  Minimum Production Rate : 0.249709 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 33.332588
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.366076
  EX_pi_e : 0.552931
  EX_so4_e : 0.079159
  EX_k_e : 0.061359
  EX_fe2_e : 0.005049
  EX_mg2_e : 0.002727
  EX_ca2_e : 0.001636
  EX_cl_e : 0.001636
  EX_cu2_e : 0.000223
  EX_mn2_e : 0.000217
  EX_zn2_e : 0.000107
  EX_ni2_e : 0.000102

Product: (mmol/gDw/h)
  EX_h2o_e : 49.970845
  EX_co2_e : 33.007115
  EX_h_e : 7.591585
  EX_ac_e : 1.232668
  EX_hxan_e : 0.493076
  DM_5drib_c : 0.492936
  DM_4crsol_c : 0.492795
  Auxiliary production reaction : 0.249709

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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