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 (166 of 192: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 28
  Gene deletion: YDL168W YMR303C YBR068C YDR046C YBR069C YPL061W YDR035W YGR087C YFL053W YML070W YLR044C YLR134W YDR380W YDL080C YKL192C YHR002W YCL025C YKR039W YOL020W YOL059W YGR191W YLR231C YBR166C YJL121C YLR348C YLR017W YML120C YHR074W   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.107104 (mmol/gDw/h)
  Minimum Production Rate : 0.121890 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_glc__D_e : 10.000000
  EX_o2_e : 2.000000
  EX_nh4_e : 1.122961
  EX_pi_e : 0.277229
  EX_so4_e : 0.008279

Product: (mmol/gDw/h)
  EX_h_e : 22.051451
  EX_h2o_e : 13.323758
  EX_succ_e : 6.932025
  EX_3c3hmp_e : 3.431904
  EX_pyr_e : 0.504500
  EX_gly_e : 0.249091
  EX_etoh_e : 0.248535
  Auxiliary production reaction : 0.121890
  EX_pap_e : 0.006137
  EX_for_e : 0.000554

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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