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 : accoa_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (50 of 81: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 42
  Gene deletion: b2836 b3553 b3399 b1241 b0351 b4069 b2744 b3708 b2297 b2458 b2779 b2926 b0160 b3844 b0583 b0907 b1982 b2797 b3117 b1814 b4471 b3616 b3589 b1033 b4374 b0675 b2361 b2291 b0261 b3709 b3161 b0112 b2789 b3127 b0114 b2366 b2492 b0904 b1533 b1473 b4141 b1798   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.386807 (mmol/gDw/h)
  Minimum Production Rate : 0.578721 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 24.152857
  EX_glc__D_e : 10.000000
  EX_nh4_e : 8.228956
  EX_pi_e : 2.109278
  EX_so4_e : 0.676126
  EX_k_e : 0.075502
  EX_fe2_e : 0.006213
  EX_mg2_e : 0.003356
  EX_ca2_e : 0.002013
  EX_cl_e : 0.002013
  EX_cu2_e : 0.000274
  EX_mn2_e : 0.000267
  EX_zn2_e : 0.000132
  EX_ni2_e : 0.000125

Product: (mmol/gDw/h)
  EX_h2o_e : 47.346155
  EX_co2_e : 25.556381
  EX_h_e : 7.918501
  EX_ac_e : 2.627167
  Auxiliary production reaction : 0.578721
  DM_oxam_c : 0.000433
  DM_5drib_c : 0.000260
  EX_glyclt_e : 0.000173
  DM_4crsol_c : 0.000086

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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