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 : glyc_e
List of minimal gene deletion strategies (Download)

Gene deletion strategy (17 of 80: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 27
  Gene deletion: b4467 b3942 b1732 b1241 b0351 b3926 b2930 b4232 b3697 b3925 b0871 b1004 b3713 b1109 b0046 b3236 b2690 b2210 b3945 b1602 b2913 b2492 b0904 b1380 b0606 b2285 b4209   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.438032 (mmol/gDw/h)
  Minimum Production Rate : 3.544267 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 28.680254
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.730705
  EX_pi_e : 0.422528
  EX_so4_e : 0.110305
  EX_k_e : 0.085501
  EX_mg2_e : 0.003800
  EX_fe2_e : 0.003615
  EX_fe3_e : 0.003420
  EX_ca2_e : 0.002280
  EX_cl_e : 0.002280
  EX_cu2_e : 0.000311
  EX_mn2_e : 0.000303
  EX_zn2_e : 0.000149
  EX_ni2_e : 0.000141
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_h2o_e : 39.409240
  EX_co2_e : 31.388011
  EX_h_e : 4.028230
  EX_glyc_e : 3.544267
  DM_5drib_c : 0.000099
  DM_4crsol_c : 0.000098

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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