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 : nadphx__S_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (64 of 78: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 41
  Gene deletion: b4467 b4269 b0493 b3588 b3003 b3011 b1241 b0351 b4384 b0871 b2779 b3617 b0030 b2407 b3844 b1004 b3713 b1109 b0046 b3236 b0937 b1982 b0261 b3945 b1602 b0507 b4381 b2406 b1727 b2975 b0114 b3603 b0529 b2492 b0904 b1380 b2660 b3662 b0606 b2285 b1011   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.350462 (mmol/gDw/h)
  Minimum Production Rate : 0.235907 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 33.634633
  EX_glc__D_e : 10.000000
  EX_nh4_e : 7.605440
  EX_pi_e : 1.540176
  EX_so4_e : 0.088253
  EX_k_e : 0.068408
  EX_fe2_e : 0.005629
  EX_mg2_e : 0.003040
  EX_ca2_e : 0.001824
  EX_cl_e : 0.001824
  EX_cu2_e : 0.000248
  EX_mn2_e : 0.000242
  EX_zn2_e : 0.000120
  EX_ni2_e : 0.000113

Product: (mmol/gDw/h)
  EX_h2o_e : 52.341932
  EX_co2_e : 33.751473
  EX_h_e : 6.239252
  EX_etoh_e : 0.709471
  Auxiliary production reaction : 0.400706
  EX_his__L_e : 0.337857
  EX_ade_e : 0.000392
  DM_5drib_c : 0.000235
  DM_4crsol_c : 0.000078

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.

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Last updated: 21-Sep-2023
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