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 : nadhx__S_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (30 of 81: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 28
  Gene deletion: b1855 b3553 b1478 b1241 b0351 b3708 b2779 b1004 b3713 b1109 b0046 b3236 b2920 b1033 b2799 b3945 b1602 b0507 b3915 b0452 b0728 b0529 b1380 b2660 b0606 b2285 b1007 b4209   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.590607 (mmol/gDw/h)
  Minimum Production Rate : 0.023560 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 34.059685
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.543429
  EX_pi_e : 0.616824
  EX_so4_e : 0.148727
  EX_k_e : 0.115282
  EX_fe3_e : 0.009486
  EX_mg2_e : 0.005124
  EX_ca2_e : 0.003074
  EX_cl_e : 0.003074
  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 : 51.302728
  EX_co2_e : 35.263523
  EX_h_e : 5.554021
  Auxiliary production reaction : 0.023560
  DM_5drib_c : 0.000133
  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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