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 : seramp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (40 of 80: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b3399 b4069 b2744 b3708 b3008 b2297 b2458 b0160 b1982 b2797 b3117 b1814 b4471 b2440 b4374 b0675 b2361 b2291 b0261 b0114 b1539 b2492 b0904 b1533 b3927   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.761275 (mmol/gDw/h)
  Minimum Production Rate : 0.193688 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 24.305287
  EX_glc__D_e : 10.000000
  EX_nh4_e : 9.383836
  EX_pi_e : 0.928019
  EX_so4_e : 0.191704
  EX_k_e : 0.148596
  EX_fe2_e : 0.012227
  EX_mg2_e : 0.006604
  EX_ca2_e : 0.003962
  EX_cl_e : 0.003962
  EX_cu2_e : 0.000540
  EX_mn2_e : 0.000526
  EX_zn2_e : 0.000260
  EX_ni2_e : 0.000246
  EX_cobalt2_e : 0.000019

Product: (mmol/gDw/h)
  EX_h2o_e : 48.163605
  EX_co2_e : 25.348799
  EX_h_e : 8.212856
  EX_ac_e : 0.443204
  Auxiliary production reaction : 0.193688
  DM_5drib_c : 0.000171
  DM_4crsol_c : 0.000170

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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