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 : coa_x
List of minimal gene deletion strategies (Download)

Gene deletion strategy (13 of 19: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 23
  Gene deletion: PHATRDRAFT_20342 PHATRDRAFT_27726 PHATRDRAFT_draft870 PHATRDRAFT_23871 PHATRDRAFT_13987 PHATRDRAFT_draft877 PHATRDRAFT_54477 PHATRDRAFT_41807 Phatr3_EG02261 PHATRDRAFT_13476 PHATRDRAFT_34120 PHATRDRAFT_49339 PHATRDRAFT_29016 PHATRDRAFT_45239 PHATRDRAFT_28191 PHATRDRAFT_50742 Phatr3_EG02042 PHATRDRAFT_36906 PHATRDRAFT_50971 PHATRDRAFT_17720 PHATRDRAFT_38085 PHATRDRAFT_49505 PHATRDRAFT_49903   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.343675 (mmol/gDw/h)
  Minimum Production Rate : 0.011139 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_photon_e : 1000.000000
  EX_co2_e : 91.119453
  EX_h2o_e : 86.877338
  EX_no3_e : 1.760000
  EX_pi_e : 0.118753
  EX_so4_e : 0.072258
  EX_mg2_e : 0.006142

Product: (mmol/gDw/h)
  SK_for_c : 74.560441
  EX_h_e : 72.599198
  EX_o2_e : 60.032720
  DM_biomass_c : 0.343675
  Auxiliary production reaction : 0.011139

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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