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 : ddca_p
List of minimal gene deletion strategies (Download)

Gene deletion strategy (76 of 76: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 42
  Gene deletion: b4467 b2836 b2242 b3846 b2341 b0474 b2518 b3831 b2744 b1278 b3752 b0963 b2781 b3617 b1004 b3713 b1109 b0046 b3236 b1612 b1611 b4122 b1759 b3616 b3589 b4374 b4161 b2361 b2291 b4014 b2976 b0411 b4138 b4123 b0621 b2197 b3028 b3918 b1206 b2285 b3893 b1474   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.493544 (mmol/gDw/h)
  Minimum Production Rate : 0.521325 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 27.150237
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.030219
  EX_pi_e : 0.476075
  EX_so4_e : 0.124284
  EX_k_e : 0.096336
  EX_fe2_e : 0.007927
  EX_mg2_e : 0.004281
  EX_ca2_e : 0.002569
  EX_cl_e : 0.002569
  EX_cu2_e : 0.000350
  EX_mn2_e : 0.000341
  EX_zn2_e : 0.000168
  EX_ni2_e : 0.000159
  EX_cobalt2_e : 0.000012

Product: (mmol/gDw/h)
  EX_h2o_e : 45.325530
  EX_co2_e : 30.027770
  EX_h_e : 6.785517
  Auxiliary production reaction : 0.521325
  EX_succ_e : 0.514663
  EX_ura_e : 0.349995
  DM_5drib_c : 0.000111
  DM_4crsol_c : 0.000110

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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