MetNetComp Database [1] / Minimal gene deletions

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

Model : iPC815 [2].
Target metabolite : apg120_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (30 of 34: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 27
  Gene deletion: YPO3371 YPO1384 YPO4078 YPO3825 YPO3937 YPO2157 YPO0918 YPO3428 YPO0459 YPO0348 YPO0253 YPO3992 YPO0347 YPO3202 YPO1965 YPO0670 YPO2303 YPO3914 YPO2295 YPO3358 YPO2559 YPO1851 YPO3418 YPO2370 YPO1133 YPO2836 YPO2567   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.090358 (mmol/gDw/h)
  Minimum Production Rate : 0.064114 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_h_e : 8.676808
  EX_cit_e : 7.400000
  EX_o2_e : 3.153950
  EX_gly_e : 2.200000
  EX_cys__L_e : 1.000000
  EX_glc__D_e : 0.196016
  EX_pi_e : 0.141063
  EX_phe__L_e : 0.017168
  EX_met__L_e : 0.012650
  EX_tyr__L_e : 0.011746

Product: (mmol/gDw/h)
  EX_co2_e : 13.420367
  EX_succ_e : 7.400000
  EX_h2o_e : 4.858031
  EX_nh4_e : 1.637880
  EX_h2s_e : 0.993399
  EX_pro__L_e : 0.497246
  EX_ac_e : 0.492623
  EX_glyald_e : 0.064590
  Auxiliary production reaction : 0.064114
  EX_glyc3p_e : 0.002973

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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