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 : ade_e
List of minimal gene deletion strategies (Download)

Gene deletion strategy (109 of 133: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b4467 b4069 b3926 b2297 b2458 b3844 b1004 b3713 b1109 b0046 b3236 b0261 b1602 b4381 b2868 b4064 b4464 b0114 b0529 b2492 b0904 b1380 b2660 b0606 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.473785 (mmol/gDw/h)
  Minimum Production Rate : 0.219178 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 38.442638
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.212727
  EX_pi_e : 0.457016
  EX_so4_e : 0.119308
  EX_k_e : 0.092479
  EX_fe2_e : 0.007609
  EX_mg2_e : 0.004110
  EX_ca2_e : 0.002466
  EX_cl_e : 0.002466
  EX_cu2_e : 0.000336
  EX_mn2_e : 0.000327
  EX_zn2_e : 0.000162
  EX_ni2_e : 0.000153
  EX_cobalt2_e : 0.000012

Product: (mmol/gDw/h)
  EX_h2o_e : 53.608888
  EX_co2_e : 38.905758
  EX_h_e : 5.725046
  EX_ac_e : 0.275831
  EX_ade_e : 0.219178
  DM_5drib_c : 0.000107
  DM_4crsol_c : 0.000106

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
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