MetNetComp Database [1] / Minimal gene deletions Minimal gene deletions for simulation-based growth-coupled production. You can also see maximal gene deletions.

Model : STM_v1_0 [2].
Target metabolite : pa161_p
List of minimal gene deletion strategies (Download)

Gene deletion strategy (17 of 110: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: STM3646 STM1749 STM2463 STM2285 STM3526 STM4326 STM1885 STM2952 STM0840 STM0842 STM2947 STM3709 STM1135 STM4183 STM0491 STM0369 STM1448 STM4484 STM2317 STM3179 STM1480 STM4126 STM4578 STM1124 STM3708   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.238989 (mmol/gDw/h)
  Minimum Production Rate : 0.016422 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 18.500000
  EX_glc__D_e : 5.000000
  EX_nh4_e : 2.633693
  EX_pi_e : 0.228364
  EX_k_e : 0.042444
  EX_so4_e : 0.029152
  EX_mg2_e : 0.001887
  EX_fe2_e : 0.001752
  EX_ca2_e : 0.001132
  EX_cl_e : 0.001132
  EX_cu2_e : 0.000755
  EX_mn2_e : 0.000755
  EX_mobd_e : 0.000755
  EX_zn2_e : 0.000755
  EX_cobalt2_e : 0.000755

Product: (mmol/gDw/h)
  EX_h2o_e : 25.615259
  EX_co2_e : 18.961045
  EX_h_e : 2.026059
  EX_acald_e : 0.609716
  Auxiliary production reaction : 0.016422
  DM_hmfurn_c : 0.000107

Visualization
  1. Download JSON file.
  2. Go to Escher site [3].

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: 27-Sep-2023
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