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 : dpcoa_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (8 of 80: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 28
  Gene deletion: b2836 b3399 b2744 b3708 b3008 b0871 b0160 b3844 b1982 b2797 b3117 b1814 b4471 b4374 b0675 b2361 b2291 b0261 b0114 b0886 b1539 b2492 b0904 b2578 b1533 b3927 b4141 b1798   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.771406 (mmol/gDw/h)
  Minimum Production Rate : 0.088501 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 24.742225
  EX_glc__D_e : 10.000000
  EX_nh4_e : 8.950625
  EX_pi_e : 0.921105
  EX_so4_e : 0.282757
  EX_k_e : 0.150573
  EX_fe2_e : 0.012390
  EX_mg2_e : 0.006692
  EX_ca2_e : 0.004015
  EX_cl_e : 0.004015
  EX_cu2_e : 0.000547
  EX_mn2_e : 0.000533
  EX_zn2_e : 0.000263
  EX_ni2_e : 0.000249
  EX_cobalt2_e : 0.000019

Product: (mmol/gDw/h)
  EX_h2o_e : 48.440808
  EX_co2_e : 26.477094
  EX_h_e : 7.353487
  Auxiliary production reaction : 0.088501
  DM_5drib_c : 0.000518
  DM_4crsol_c : 0.000172

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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