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 : 2dhp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (90 of 109: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 28
  Gene deletion: b4467 b1478 b1241 b0351 b0871 b2925 b2097 b2926 b3844 b1004 b3713 b1109 b0046 b3236 b2690 b2799 b3945 b1602 b2913 b4381 b2975 b3603 b2492 b0904 b1380 b0606 b2285 b1011   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.425103 (mmol/gDw/h)
  Minimum Production Rate : 1.181034 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 33.967593
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.591072
  EX_pi_e : 0.410056
  EX_so4_e : 0.107049
  EX_k_e : 0.082977
  EX_fe2_e : 0.006828
  EX_mg2_e : 0.003688
  EX_cl_e : 0.002213
  EX_ca2_e : 0.002213
  EX_cu2_e : 0.000301
  EX_mn2_e : 0.000294
  EX_zn2_e : 0.000145
  EX_ni2_e : 0.000137
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_h2o_e : 47.872105
  EX_co2_e : 35.465288
  EX_h_e : 5.087046
  Auxiliary production reaction : 1.181034
  DM_5drib_c : 0.000096
  DM_4crsol_c : 0.000095

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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