MetNetComp Database [1] / Minimal gene deletions

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

Model : STM_v1_0 [2].
Target metabolite : pa161_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (1 of 113: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 21
  Gene deletion: STM3646 STM4108 STM2285 STM3526 STM4326 STM1511 STM1884 STM0321 STM3529 STM1135 STM1448 STM3069 STM4184 STM4484 STM2317 STM3179 STM4569 STM1480 STM4126 STM2338 STM2466   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.256236 (mmol/gDw/h)
  Minimum Production Rate : 0.028332 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 18.500000
  EX_glc__D_e : 5.000000
  EX_nh4_e : 2.823752
  EX_pi_e : 0.255568
  EX_k_e : 0.045507
  EX_so4_e : 0.031256
  EX_mg2_e : 0.002023
  EX_fe2_e : 0.001878
  EX_ca2_e : 0.001214
  EX_cl_e : 0.001214
  EX_cobalt2_e : 0.000809
  EX_cu2_e : 0.000809
  EX_mn2_e : 0.000809
  EX_mobd_e : 0.000809
  EX_zn2_e : 0.000809

Product: (mmol/gDw/h)
  EX_h2o_e : 25.989551
  EX_co2_e : 18.812240
  EX_h_e : 2.314129
  EX_ac_e : 0.141860
  Auxiliary production reaction : 0.028332
  EX_glyald_e : 0.000178
  DM_hmfurn_c : 0.000114

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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