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 : glyc_e
List of minimal gene deletion strategies (Download)

Gene deletion strategy (18 of 80: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 27
  Gene deletion: b4467 b1241 b0351 b3926 b0871 b2925 b2097 b1004 b3713 b1109 b0046 b3236 b2690 b1493 b3517 b3945 b1602 b0507 b2975 b3603 b2492 b0904 b1380 b2660 b0606 b2285 b4209   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.451531 (mmol/gDw/h)
  Minimum Production Rate : 2.261517 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 995.843903
  EX_o2_e : 281.418307
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.876494
  EX_pi_e : 0.435549
  EX_so4_e : 0.113704
  EX_k_e : 0.088136
  EX_mg2_e : 0.003917
  EX_ca2_e : 0.002350
  EX_cl_e : 0.002350
  EX_cu2_e : 0.000320
  EX_mn2_e : 0.000312
  EX_zn2_e : 0.000154
  EX_ni2_e : 0.000146
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_fe3_e : 999.992748
  EX_h2o_e : 543.006171
  EX_co2_e : 33.681273
  EX_glyc_e : 2.595155
  DM_5drib_c : 0.000102
  DM_4crsol_c : 0.000101

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