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 : dmlz_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (159 of 163: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 26
  Gene deletion: YKL106W YCR032W YCR010C YBR085W YMR056C YBL030C YHR002W YJL060W YAR035W YER024W YPL262W YIL155C YIL053W YER062C YMR189W YMR250W YHR208W YMR267W YJL121C YKL141W YDR178W YPL188W YJR049C YEL041W YOR377W YGR177C   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.198514 (mmol/gDw/h)
  Minimum Production Rate : 0.001749 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_glc__D_e : 10.000000
  EX_nh4_e : 1.252364
  EX_o2_e : 0.091246
  EX_pi_e : 0.061996
  EX_so4_e : 0.015345

Product: (mmol/gDw/h)
  EX_co2_e : 17.228673
  EX_etoh_e : 16.908531
  EX_h2o_e : 3.033133
  EX_h_e : 1.661729
  EX_2hb_e : 0.269293
  EX_fum_e : 0.077103
  EX_for_e : 0.029438
  EX_spmd_e : 0.024913
  EX_succ_e : 0.021956
  EX_pap_e : 0.011375
  EX_gly_e : 0.002779
  Auxiliary production reaction : 0.001749

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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