MetNetComp Database [1] / Minimal gene deletions

Minimal gene deletions for simulation-based growth-coupled production. You can also see maximal gene deletions.

Model : iLB1027_lipid [2].
Target metabolite : pe180204n6_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (31 of 39: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 19
  Gene deletion: PHATRDRAFT_20342 PHATRDRAFT_27726 PHATRDRAFT_30145 PHATRDRAFT_55192 PHATRDRAFT_21988 PHATRDRAFT_48983 PHATRDRAFT_draft1023 PHATRDRAFT_draft1645 PHATRDRAFT_34120 PHATRDRAFT_49339 PHATRDRAFT_13951 Phatr3_EG02361 PHATRDRAFT_54731 PHATRDRAFT_11016 PHATRDRAFT_13005 PHATRDRAFT_50084 PHATRDRAFT_21970 PHATRDRAFT_15777 PHATRDRAFT_43697   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.355399 (mmol/gDw/h)
  Minimum Production Rate : 0.020591 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_photon_e : 1000.000000
  EX_co2_e : 26.730537
  EX_h2o_e : 23.039675
  EX_no3_e : 1.760000
  EX_so4_e : 0.264133
  EX_pi_e : 0.108840
  EX_mg2_e : 0.006351

Product: (mmol/gDw/h)
  EX_o2_e : 31.721157
  SK_for_c : 6.194029
  EX_h_e : 3.828956
  EX_etoh_e : 0.882218
  DM_biomass_c : 0.355399
  DM_dmsp_c : 0.200928
  Auxiliary production reaction : 0.020591

Visualization
  1. Download JSON file.
  2. Go to Escher site [3].

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: 27-Sep-2023
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