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 : itp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (42 of 90: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 26
  Gene deletion: b3399 b0474 b1241 b0351 b4069 b2744 b0512 b2297 b2458 b3617 b2883 b0907 b1779 b1982 b0675 b2361 b0261 b4381 b0112 b4064 b4464 b0114 b0529 b2492 b0904 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.363630 (mmol/gDw/h)
  Minimum Production Rate : 0.687373 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 35.535026
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.716352
  EX_pi_e : 2.412878
  EX_so4_e : 0.091569
  EX_k_e : 0.070978
  EX_fe2_e : 0.005840
  EX_mg2_e : 0.003154
  EX_ca2_e : 0.001893
  EX_cl_e : 0.001893
  EX_cu2_e : 0.000258
  EX_mn2_e : 0.000251
  EX_zn2_e : 0.000124
  EX_ni2_e : 0.000117

Product: (mmol/gDw/h)
  EX_h2o_e : 53.170667
  EX_co2_e : 34.562905
  EX_h_e : 6.554373
  EX_ac_e : 1.798763
  Auxiliary production reaction : 0.687373
  EX_alltn_e : 0.009922
  DM_5drib_c : 0.000244
  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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