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 (21 of 80: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b1241 b0351 b4069 b4384 b3752 b2297 b2458 b2407 b1982 b3616 b3589 b0261 b4381 b2406 b0112 b2975 b0114 b3603 b0509 b3125 b0529 b2492 b0904 b0508 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.429112 (mmol/gDw/h)
  Minimum Production Rate : 1.644765 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 20.476935
  EX_nh4_e : 11.213919
  EX_glc__D_e : 10.000000
  EX_pi_e : 2.058690
  EX_so4_e : 0.108059
  EX_k_e : 0.083760
  EX_fe2_e : 0.006892
  EX_mg2_e : 0.003723
  EX_ca2_e : 0.002234
  EX_cl_e : 0.002234
  EX_cu2_e : 0.000304
  EX_mn2_e : 0.000297
  EX_zn2_e : 0.000146
  EX_ni2_e : 0.000139
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_h2o_e : 45.882800
  EX_co2_e : 16.457750
  EX_h_e : 16.085054
  EX_ac_e : 2.272646
  Auxiliary production reaction : 1.644765
  DM_oxam_c : 0.000480
  DM_5drib_c : 0.000288
  DM_4crsol_c : 0.000096

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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