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 : glyc_e
List of minimal gene deletion strategies (Download)

Gene deletion strategy (19 of 80: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 27
  Gene deletion: b4467 b0474 b2518 b1241 b0351 b3926 b0871 b2925 b2097 b3844 b1004 b3713 b1109 b0046 b3236 b1779 b3946 b0825 b4015 b1602 b2913 b2492 b0904 b1380 b1771 b0606 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.443231 (mmol/gDw/h)
  Minimum Production Rate : 2.079115 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 33.584629
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.786859
  EX_pi_e : 0.427543
  EX_so4_e : 0.111614
  EX_k_e : 0.086516
  EX_fe2_e : 0.007119
  EX_mg2_e : 0.003845
  EX_ca2_e : 0.002307
  EX_cl_e : 0.002307
  EX_cu2_e : 0.000314
  EX_mn2_e : 0.000306
  EX_zn2_e : 0.000151
  EX_ni2_e : 0.000143
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_h2o_e : 45.195446
  EX_co2_e : 35.570051
  EX_h_e : 4.072585
  EX_glyc_e : 2.079115
  DM_5drib_c : 0.000100
  DM_4crsol_c : 0.000099

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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