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 : udp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (73 of 76: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 38
  Gene deletion: b4269 b0493 b3588 b3003 b3011 b0474 b2518 b1241 b0351 b3831 b3752 b2930 b4232 b3697 b3925 b4152 b2297 b2458 b2781 b1612 b1611 b4122 b2690 b1759 b4161 b0411 b3945 b4138 b4123 b0621 b2913 b0755 b3612 b3918 b0789 b1249 b1206 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.456039 (mmol/gDw/h)
  Minimum Production Rate : 0.240855 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 30.872513
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.571984
  EX_pi_e : 0.921608
  EX_so4_e : 0.114840
  EX_k_e : 0.089016
  EX_fe2_e : 0.007324
  EX_mg2_e : 0.003956
  EX_cl_e : 0.002374
  EX_ca2_e : 0.002374
  EX_cu2_e : 0.000323
  EX_mn2_e : 0.000315
  EX_zn2_e : 0.000156
  EX_ni2_e : 0.000147
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_h2o_e : 46.727509
  EX_co2_e : 30.376011
  EX_h_e : 8.800115
  EX_succ_e : 1.969200
  EX_ac_e : 0.265500
  Auxiliary production reaction : 0.240855
  EX_ura_e : 0.082544
  DM_5drib_c : 0.000103
  DM_4crsol_c : 0.000102

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
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