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 : 6hmhptpp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (42 of 95: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 26
  Gene deletion: b4384 b3708 b3008 b0871 b0030 b2407 b1982 b2797 b3117 b1814 b4471 b0261 b4381 b2406 b0114 b0886 b2366 b2492 b0904 b2578 b1533 b3927 b3821 b4141 b1798 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.784569 (mmol/gDw/h)
  Minimum Production Rate : 0.180086 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 25.310455
  EX_glc__D_e : 10.000000
  EX_nh4_e : 9.373708
  EX_pi_e : 1.116972
  EX_so4_e : 0.197570
  EX_k_e : 0.153142
  EX_fe2_e : 0.012601
  EX_mg2_e : 0.006806
  EX_ca2_e : 0.004084
  EX_cl_e : 0.004084
  EX_cu2_e : 0.000556
  EX_mn2_e : 0.000542
  EX_zn2_e : 0.000268
  EX_ni2_e : 0.000253
  EX_cobalt2_e : 0.000020

Product: (mmol/gDw/h)
  EX_h2o_e : 49.414029
  EX_co2_e : 26.534700
  EX_h_e : 7.929277
  Auxiliary production reaction : 0.180086
  DM_5drib_c : 0.000526
  DM_4crsol_c : 0.000175

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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