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 : 2dr5p_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (2 of 75: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 17
  Gene deletion: b1241 b0351 b4069 b2297 b2458 b2779 b3617 b1612 b1611 b4122 b4381 b0114 b0529 b2492 b0904 b1511 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.430276 (mmol/gDw/h)
  Minimum Production Rate : 1.650381 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 29.739168
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.646946
  EX_pi_e : 2.065428
  EX_so4_e : 0.108352
  EX_k_e : 0.083987
  EX_fe2_e : 0.006911
  EX_mg2_e : 0.003733
  EX_ca2_e : 0.002240
  EX_cl_e : 0.002240
  EX_cu2_e : 0.000305
  EX_mn2_e : 0.000297
  EX_zn2_e : 0.000147
  EX_ni2_e : 0.000139
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_h2o_e : 44.944050
  EX_co2_e : 31.033889
  EX_h_e : 5.479740
  Auxiliary production reaction : 1.650381
  EX_ac_e : 0.628814
  EX_fum_e : 0.448689
  EX_mththf_e : 0.000193
  DM_5drib_c : 0.000097
  DM_4crsol_c : 0.000096

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