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 : eig3p_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (43 of 89: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 28
  Gene deletion: b3399 b4269 b0493 b3588 b3003 b3011 b1241 b0351 b2502 b4384 b2744 b3752 b0871 b3617 b2883 b1982 b1623 b4374 b2361 b2291 b0261 b0411 b0112 b0114 b0529 b2492 b0904 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.590395 (mmol/gDw/h)
  Minimum Production Rate : 1.919232 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 22.650493
  EX_nh4_e : 10.214674
  EX_glc__D_e : 10.000000
  EX_pi_e : 2.488730
  EX_so4_e : 0.148673
  EX_k_e : 0.115241
  EX_fe2_e : 0.009482
  EX_mg2_e : 0.005122
  EX_ca2_e : 0.003073
  EX_cl_e : 0.003073
  EX_cu2_e : 0.000419
  EX_mn2_e : 0.000408
  EX_zn2_e : 0.000201
  EX_ni2_e : 0.000191
  EX_cobalt2_e : 0.000015

Product: (mmol/gDw/h)
  EX_h2o_e : 48.397645
  EX_co2_e : 23.210800
  EX_h_e : 9.263244
  Auxiliary production reaction : 1.919232
  EX_acald_e : 0.519755
  DM_5drib_c : 0.000396
  DM_4crsol_c : 0.000132

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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