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 : alltn_e
List of minimal gene deletion strategies (Download)

Gene deletion strategy (36 of 90: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 15
  Gene deletion: b4269 b0493 b3588 b3003 b3011 b1241 b0351 b0871 b3617 b4381 b0114 b2492 b0904 b0515 b1517   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.690908 (mmol/gDw/h)
  Minimum Production Rate : 0.002697 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 993.629774
  EX_o2_e : 273.028451
  EX_glc__D_e : 10.000000
  EX_nh4_e : 7.472538
  EX_pi_e : 0.666454
  EX_so4_e : 0.173984
  EX_k_e : 0.134860
  EX_mg2_e : 0.005994
  EX_ca2_e : 0.003596
  EX_cl_e : 0.003596
  EX_cu2_e : 0.000490
  EX_mn2_e : 0.000477
  EX_zn2_e : 0.000236
  EX_ni2_e : 0.000223
  EX_cobalt2_e : 0.000017

Product: (mmol/gDw/h)
  EX_fe3_e : 999.988903
  EX_h2o_e : 544.182154
  EX_co2_e : 25.923848
  EX_acald_e : 2.852605
  EX_alltn_e : 0.002697
  DM_mththf_c : 0.000310
  DM_5drib_c : 0.000155
  DM_4crsol_c : 0.000154

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