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 : air_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (23 of 84: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b1241 b0351 b4069 b4384 b2744 b2297 b2458 b2779 b0030 b2883 b1982 b3616 b3589 b0261 b4381 b2406 b0112 b2868 b4064 b4464 b0114 b0529 b2492 b0904 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.452394 (mmol/gDw/h)
  Minimum Production Rate : 1.734003 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 23.534192
  EX_nh4_e : 10.090358
  EX_glc__D_e : 10.000000
  EX_pi_e : 2.170385
  EX_so4_e : 0.113922
  EX_k_e : 0.088304
  EX_fe2_e : 0.007266
  EX_mg2_e : 0.003925
  EX_ca2_e : 0.002355
  EX_cl_e : 0.002355
  EX_cu2_e : 0.000321
  EX_mn2_e : 0.000313
  EX_zn2_e : 0.000154
  EX_ni2_e : 0.000146
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_h2o_e : 46.854004
  EX_co2_e : 22.764443
  EX_h_e : 11.756964
  EX_ac_e : 2.395646
  Auxiliary production reaction : 1.734003
  EX_ade_e : 0.000506
  DM_5drib_c : 0.000304
  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