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 : 12ppd__R_e
List of minimal gene deletion strategies (Download)

Gene deletion strategy (74 of 81: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 30
  Gene deletion: b4467 b1241 b0351 b3926 b0871 b2925 b2097 b1004 b3713 b1109 b0046 b3236 b3946 b0825 b1493 b3517 b4014 b2976 b0726 b1602 b2975 b3603 b0509 b3125 b2492 b0904 b1380 b0508 b2660 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.471543 (mmol/gDw/h)
  Minimum Production Rate : 3.314406 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 26.381399
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.092630
  EX_pi_e : 0.454854
  EX_so4_e : 0.118744
  EX_k_e : 0.092042
  EX_fe2_e : 0.007573
  EX_mg2_e : 0.004091
  EX_ca2_e : 0.002454
  EX_cl_e : 0.002454
  EX_cu2_e : 0.000334
  EX_mn2_e : 0.000326
  EX_zn2_e : 0.000161
  EX_ni2_e : 0.000152
  EX_cobalt2_e : 0.000012

Product: (mmol/gDw/h)
  EX_h2o_e : 39.839842
  EX_co2_e : 30.702088
  EX_h_e : 4.332730
  EX_12ppd__R_e : 3.314406
  DM_5drib_c : 0.000106
  DM_4crsol_c : 0.000105

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
Contact