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 (60 of 90: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 29
  Gene deletion: b3399 b2744 b3708 b3008 b0871 b2779 b0160 b1982 b2797 b3117 b1814 b4471 b0675 b2361 b0261 b4381 b2406 b0452 b0114 b0529 b1539 b2492 b0904 b2578 b1533 b3927 b3447 b0221 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.494380 (mmol/gDw/h)
  Minimum Production Rate : 0.100542 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 37.890934
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.754918
  EX_pi_e : 0.778507
  EX_so4_e : 0.124495
  EX_k_e : 0.096500
  EX_fe2_e : 0.007940
  EX_mg2_e : 0.004289
  EX_ca2_e : 0.002573
  EX_cl_e : 0.002573
  EX_cu2_e : 0.000351
  EX_mn2_e : 0.000342
  EX_zn2_e : 0.000169
  EX_ni2_e : 0.000160
  EX_cobalt2_e : 0.000012

Product: (mmol/gDw/h)
  EX_h2o_e : 53.063703
  EX_co2_e : 38.674473
  EX_h_e : 4.770623
  Auxiliary production reaction : 0.100542
  DM_oxam_c : 0.013489
  DM_5drib_c : 0.000332
  DM_4crsol_c : 0.000110

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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