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 : unagamuf_p
List of minimal gene deletion strategies (Download)

Gene deletion strategy (41 of 79: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b1241 b0351 b4069 b4384 b2744 b2297 b2458 b2779 b3617 b0030 b2883 b1982 b0261 b4381 b2406 b0112 b2868 b4064 b4464 b0114 b0529 b2492 b0904 b3662 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.351189 (mmol/gDw/h)
  Minimum Production Rate : 0.168261 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 26.896522
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.299559
  EX_pi_e : 0.675281
  EX_so4_e : 0.088436
  EX_k_e : 0.068550
  EX_fe2_e : 0.005640
  EX_mg2_e : 0.003047
  EX_ca2_e : 0.001828
  EX_cl_e : 0.001828
  EX_cu2_e : 0.000249
  EX_mn2_e : 0.000243
  EX_zn2_e : 0.000120
  EX_ni2_e : 0.000113

Product: (mmol/gDw/h)
  EX_h2o_e : 44.242280
  EX_co2_e : 31.262676
  EX_h_e : 4.078979
  EX_ac_e : 0.513627
  Auxiliary production reaction : 0.168261
  EX_ade_e : 0.000393
  DM_5drib_c : 0.000236
  DM_4crsol_c : 0.000078

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