MetNetComp Database [1] / Minimal gene deletions

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

Model : iMM904 [2].
Target metabolite : cdp_n
List of minimal gene deletion strategies (Download)

Gene deletion strategy (160 of 174: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 28
  Gene deletion: YBR068C YMR083W YDR046C YBR069C YPL061W YGR087C YLR044C YLR134W YDR380W YKL106W YKL192C YPL148C YMR289W YCL025C YKR039W YOL020W YOL059W YIL053W YER062C YGR191W YHR208W YJR078W YJL121C YLR348C YLR146C YML120C YBR180W YFR047C   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.136315 (mmol/gDw/h)
  Minimum Production Rate : 0.098625 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_glc__D_e : 10.000000
  EX_o2_e : 2.000000
  EX_nh4_e : 1.132736
  EX_pi_e : 0.239821
  EX_so4_e : 0.010537

Product: (mmol/gDw/h)
  EX_h_e : 20.576945
  EX_h2o_e : 13.626584
  EX_succ_e : 6.748650
  EX_pyr_e : 6.019365
  EX_iamoh_e : 1.489306
  EX_2mbtoh_e : 0.285635
  Auxiliary production reaction : 0.098625
  EX_gly_e : 0.017815
  EX_for_e : 0.017812
  EX_pnto__R_e : 0.017108
  EX_pap_e : 0.007811

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.

Last updated: 27-Sep-2023
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