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 : eig3p_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (37 of 89: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 26
  Gene deletion: b3399 b4382 b1241 b0351 b4069 b4384 b2744 b2297 b2458 b2779 b3617 b2407 b3665 b0675 b2361 b2913 b0112 b3654 b3714 b3664 b0114 b0529 b2492 b0904 b1518 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.364991 (mmol/gDw/h)
  Minimum Production Rate : 1.399971 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 34.328224
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.741813
  EX_pi_e : 1.752044
  EX_so4_e : 0.091912
  EX_k_e : 0.071244
  EX_fe2_e : 0.005862
  EX_mg2_e : 0.003166
  EX_ca2_e : 0.001900
  EX_cl_e : 0.001900
  EX_cu2_e : 0.000259
  EX_mn2_e : 0.000252
  EX_zn2_e : 0.000124
  EX_ni2_e : 0.000118

Product: (mmol/gDw/h)
  EX_h2o_e : 51.045394
  EX_co2_e : 34.407137
  EX_h_e : 7.259134
  Auxiliary production reaction : 1.399971
  EX_ac_e : 1.105509
  DM_mththf_c : 0.000164
  DM_5drib_c : 0.000082
  DM_4crsol_c : 0.000081

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.

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Last updated: 21-Sep-2023
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