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 : udpLa4o_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (80 of 83: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 41
  Gene deletion: b1241 b0351 b3831 b3614 b0910 b3752 b2221 b4152 b0871 b3115 b1849 b2296 b2925 b2097 b2926 b2781 b3236 b1612 b1611 b4122 b2690 b1759 b2210 b0411 b0614 b3945 b4138 b4123 b0621 b4381 b0755 b3612 b1539 b2492 b0904 b2197 b2835 b3918 b4042 b1206 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.383979 (mmol/gDw/h)
  Minimum Production Rate : 0.202797 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 32.152124
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.691535
  EX_pi_e : 0.775981
  EX_so4_e : 0.096694
  EX_k_e : 0.074950
  EX_fe2_e : 0.006167
  EX_mg2_e : 0.003331
  EX_ca2_e : 0.001999
  EX_cl_e : 0.001999
  EX_cu2_e : 0.000272
  EX_mn2_e : 0.000265
  EX_zn2_e : 0.000131
  EX_ni2_e : 0.000124

Product: (mmol/gDw/h)
  EX_h2o_e : 46.150344
  EX_co2_e : 31.288343
  EX_h_e : 8.584120
  EX_succ_e : 2.346709
  EX_ac_e : 0.223547
  Auxiliary production reaction : 0.202797
  EX_ura_e : 0.069501
  DM_5drib_c : 0.000086
  DM_4crsol_c : 0.000086

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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