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 : imacp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (87 of 103: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 40
  Gene deletion: b3553 b1478 b1241 b4069 b2297 b2458 b2926 b3844 b1004 b3713 b1109 b0046 b3236 b0207 b3012 b1033 b0261 b0411 b2799 b1602 b0153 b2913 b4381 b3654 b3714 b3664 b4064 b4464 b0529 b2492 b0904 b1781 b3001 b0591 b1380 b0325 b1771 b0606 b2285 b1011   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.386385 (mmol/gDw/h)
  Minimum Production Rate : 1.216253 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 34.816817
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.605427
  EX_pi_e : 1.588962
  EX_so4_e : 0.097299
  EX_k_e : 0.075420
  EX_fe2_e : 0.006206
  EX_mg2_e : 0.003352
  EX_ca2_e : 0.002011
  EX_cl_e : 0.002011
  EX_cu2_e : 0.000274
  EX_mn2_e : 0.000267
  EX_zn2_e : 0.000132
  EX_ni2_e : 0.000125

Product: (mmol/gDw/h)
  EX_h2o_e : 52.534111
  EX_co2_e : 35.033243
  EX_h_e : 6.887725
  Auxiliary production reaction : 1.216253
  EX_ac_e : 0.904963
  DM_5drib_c : 0.000087
  DM_4crsol_c : 0.000086

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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