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 : pg181_p
List of minimal gene deletion strategies (Download)

Gene deletion strategy (70 of 71: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 36
  Gene deletion: b2836 b2242 b3553 b4382 b0474 b2518 b3831 b4384 b1278 b3752 b2781 b1004 b3713 b1109 b0046 b1612 b1611 b4122 b1759 b2210 b1033 b4161 b1415 b4138 b4123 b0621 b2406 b2197 b3028 b3918 b0494 b1206 b3546 b2285 b3893 b1474   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.443479 (mmol/gDw/h)
  Minimum Production Rate : 0.234221 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 994.598341
  EX_o2_e : 274.859404
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.418518
  EX_pi_e : 0.662003
  EX_so4_e : 0.111677
  EX_k_e : 0.086564
  EX_mg2_e : 0.003847
  EX_ca2_e : 0.002308
  EX_cl_e : 0.002308
  EX_cu2_e : 0.000314
  EX_mn2_e : 0.000306
  EX_zn2_e : 0.000151
  EX_ni2_e : 0.000143
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_fe3_e : 999.992877
  EX_h2o_e : 543.531440
  EX_co2_e : 28.852150
  EX_succ_e : 0.462456
  EX_ura_e : 0.314492
  Auxiliary production reaction : 0.234221
  DM_5drib_c : 0.000100
  DM_4crsol_c : 0.000099

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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