MetNetComp Database / Minimal gene deletions

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

Model : iHN637 [2].
Target metabolite : glyc3p_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (3 of 54: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 9
  Gene deletion: CLJU_RS06265 CLJU_RS09865 CLJU_RS09915 CLJU_RS03525 CLJU_RS07210 CLJU_RS03475 CLJU_RS18495 CLJU_RS01595 CLJU_RS18530   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.100197 (mmol/gDw/h)
  Minimum Production Rate : 0.016993 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_fru_e : 5.000000
  EX_nh4_e : 0.841945
  EX_pi_e : 0.133086
  EX_so4_e : 0.100562
  EX_k_e : 0.019155
  EX_fe2_e : 0.001385
  EX_mg2_e : 0.000851
  EX_ca2_e : 0.000511
  EX_cl_e : 0.000511
  EX_fol_e : 0.000089
  EX_cu2_e : 0.000070
  EX_mn2_e : 0.000068
  EX_ribflv_e : 0.000045
  EX_zn2_e : 0.000033
  EX_ni2_e : 0.000032
  EX_cobalt2_e : 0.000025
  EX_thm_e : 0.000022

Product: (mmol/gDw/h)
  EX_co2_e : 8.957532
  EX_etoh_e : 8.009120
  EX_h2o_e : 3.030160
  EX_h_e : 0.572622
  EX_ac_e : 0.100137
  EX_met__L_e : 0.081642
  Auxiliary production reaction : 0.016993
  DM_succ_c : 0.012670
  EX_glyc_e : 0.002304
  DM_mththf_c : 0.000223

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] Orth, J. D., Fleming, R. M., Palsson, B. Ø. (2010). Reconstruction and use of microbial metabolic networks: the core Escherichia coli metabolic model as an educational guide. EcoSal plus, 4(1).
[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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