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 : 4r5au_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (108 of 111: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 46
  Gene deletion: b4467 b2836 b4069 b4384 b2744 b3708 b3752 b3926 b2297 b2458 b2925 b2097 b2926 b2407 b1004 b3713 b1109 b0046 b3236 b2690 b1982 b2797 b3117 b1814 b4471 b4374 b2361 b2291 b0261 b0411 b3945 b1602 b0507 b2975 b0114 b3603 b2366 b0529 b2492 b0904 b1533 b3927 b1380 b2660 b3662 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.357555 (mmol/gDw/h)
  Minimum Production Rate : 0.227189 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 32.332053
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.771923
  EX_pi_e : 0.344900
  EX_so4_e : 0.090040
  EX_k_e : 0.069792
  EX_fe2_e : 0.005743
  EX_mg2_e : 0.003102
  EX_ca2_e : 0.001861
  EX_cl_e : 0.001861
  EX_cu2_e : 0.000254
  EX_mn2_e : 0.000247
  EX_zn2_e : 0.000122
  EX_ni2_e : 0.000115

Product: (mmol/gDw/h)
  EX_h2o_e : 43.675755
  EX_co2_e : 32.639785
  EX_h_e : 9.514075
  EX_ac_e : 5.318358
  Auxiliary production reaction : 0.227189
  EX_hxan_e : 0.000400
  DM_5drib_c : 0.000240
  DM_4crsol_c : 0.000080

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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