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 : udpgal_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (182 of 192: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 28
  Gene deletion: YBR068C YMR083W YDR046C YBR069C YPL061W YDR035W YGR087C YFL053W YML070W YLR044C YLR134W YDR380W YKL106W YKL192C YPL148C YCL025C YKR039W YOL020W YOL059W YGR191W YLR231C YHR208W YBR166C YJL121C YLR348C YBR176W YML120C YFR047C   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.129578 (mmol/gDw/h)
  Minimum Production Rate : 0.150006 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_glc__D_e : 10.000000
  EX_o2_e : 2.000000
  EX_nh4_e : 1.062985
  EX_pi_e : 0.340479
  EX_so4_e : 0.010016

Product: (mmol/gDw/h)
  EX_h_e : 19.775454
  EX_h2o_e : 13.767101
  EX_succ_e : 6.542353
  EX_pyr_e : 6.000471
  EX_iamoh_e : 1.463343
  EX_2mbtoh_e : 0.305764
  Auxiliary production reaction : 0.150006
  EX_pap_e : 0.007425
  EX_gly_e : 0.000673
  EX_for_e : 0.000670

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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