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 : 2dr1p_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (28 of 40: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 27
  Gene deletion: b3942 b1732 b3708 b3008 b0871 b2925 b2097 b3236 b1779 b2797 b3117 b1814 b4471 b3946 b2210 b0825 b4381 b0511 b0114 b2366 b0529 b2492 b0904 b1533 b3927 b0516 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.368032 (mmol/gDw/h)
  Minimum Production Rate : 0.254911 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 29.806184
  EX_glc__D_e : 10.000000
  EX_nh4_e : 3.974718
  EX_pi_e : 0.609917
  EX_so4_e : 0.092678
  EX_k_e : 0.071837
  EX_fe2_e : 0.005911
  EX_mg2_e : 0.003193
  EX_cl_e : 0.001916
  EX_ca2_e : 0.001916
  EX_cu2_e : 0.000261
  EX_mn2_e : 0.000254
  EX_zn2_e : 0.000125
  EX_ni2_e : 0.000119

Product: (mmol/gDw/h)
  EX_h2o_e : 43.272731
  EX_co2_e : 28.138952
  EX_h_e : 8.541780
  EX_pyr_e : 5.160153
  Auxiliary production reaction : 0.254911
  DM_5drib_c : 0.000083
  DM_4crsol_c : 0.000082

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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