MetNetComp Database [1] / Minimal gene deletions

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


Model : iML1515 [2].
Target metabolite : udpLa4o_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (8 of 83: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 21
  Gene deletion: b3831 b3614 b0910 b3752 b4152 b2779 b2781 b1612 b1611 b4122 b1759 b1701 b1805 b4138 b4123 b0621 b4381 b2406 b3918 b4042 b1206   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.667822 (mmol/gDw/h)
  Minimum Production Rate : 0.352707 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 992.218505
  EX_o2_e : 274.189076
  EX_glc__D_e : 10.000000
  EX_nh4_e : 8.159589
  EX_pi_e : 1.349599
  EX_so4_e : 0.168171
  EX_k_e : 0.130354
  EX_mg2_e : 0.005793
  EX_cl_e : 0.003476
  EX_ca2_e : 0.003476
  EX_cu2_e : 0.000473
  EX_mn2_e : 0.000461
  EX_zn2_e : 0.000228
  EX_ni2_e : 0.000216
  EX_cobalt2_e : 0.000017

Product: (mmol/gDw/h)
  EX_fe3_e : 999.989274
  EX_h2o_e : 546.839798
  EX_co2_e : 24.381973
  EX_succ_e : 0.696399
  Auxiliary production reaction : 0.352707
  EX_ura_e : 0.120878
  DM_5drib_c : 0.000150
  DM_4crsol_c : 0.000149

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: 21-Sep-2023
Contact