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 : nacglc2p_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (36 of 47: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 23
  Gene deletion: PHATRDRAFT_34010 PHATRDRAFT_800 PHATRDRAFT_48983 PHATRDRAFT_49372 PHATRDRAFT_3046 PHATRDRAFT_45017 PHATRDRAFT_14762 PHATRDRAFT_31906 PHATRDRAFT_50742 PHATRDRAFT_50097 PHATRDRAFT_54731 PHATRDRAFT_43194 PHATRDRAFT_20948 PHATRDRAFT_26515 PHATRDRAFT_13005 PHATRDRAFT_50084 Phatr3_EG02569 PHATRDRAFT_42245 PHATRDRAFT_32849 PHATRDRAFT_draft1517 PHATRDRAFT_28585 PHATRDRAFT_43697 PHATRDRAFT_28181   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.353890 (mmol/gDw/h)
  Minimum Production Rate : 0.027980 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_photon_e : 386.773464
  EX_co2_e : 30.144302
  EX_h2o_e : 25.550003
  EX_no3_e : 1.760000
  EX_pi_e : 0.143834
  EX_so4_e : 0.062936
  EX_mg2_e : 0.006324

Product: (mmol/gDw/h)
  EX_o2_e : 31.249706
  SK_for_c : 11.571255
  EX_h_e : 9.593949
  DM_biomass_c : 0.353890
  Auxiliary production reaction : 0.027980

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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