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 : btd_RR_e
List of minimal gene deletion strategies (Download)

Gene deletion strategy (5 of 16: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 14
  Gene deletion: CLJU_RS05830 CLJU_RS08100 CLJU_RS08095 CLJU_RS06265 CLJU_RS20875 CLJU_RS02035 CLJU_RS01155 CLJU_RS19980 CLJU_RS15035 CLJU_RS12480 CLJU_RS07210 CLJU_RS03475 CLJU_RS08715 CLJU_RS15865   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.128145 (mmol/gDw/h)
  Minimum Production Rate : 2.463598 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_fru_e : 5.000000
  EX_nh4_e : 0.976022
  EX_pi_e : 0.148475
  EX_k_e : 0.024499
  EX_so4_e : 0.024198
  EX_fe2_e : 0.001771
  EX_mg2_e : 0.001089
  EX_ca2_e : 0.000653
  EX_cl_e : 0.000653
  EX_fol_e : 0.000114
  EX_cu2_e : 0.000089
  EX_mn2_e : 0.000087
  EX_ribflv_e : 0.000057
  EX_zn2_e : 0.000043
  EX_ni2_e : 0.000040
  EX_cobalt2_e : 0.000032
  EX_thm_e : 0.000029

Product: (mmol/gDw/h)
  EX_co2_e : 7.943740
  EX_h2o_e : 4.631567
  EX_etoh_e : 3.308760
  EX_btd_RR_e : 2.463598
  EX_h_e : 0.712336
  DM_succ_c : 0.016204
  EX_ala__D_e : 0.003641
  DM_mththf_c : 0.000286

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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