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 : 5aizc_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (61 of 80: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 37
  Gene deletion: b3553 b4382 b4069 b4384 b2744 b2297 b2458 b2779 b0030 b2407 b3844 b1004 b3713 b1109 b0046 b3236 b1982 b1033 b0261 b0411 b2799 b3945 b1602 b2913 b3915 b1727 b0114 b0529 b1539 b2492 b0904 b3927 b1380 b3662 b0606 b2285 b1008   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.407172 (mmol/gDw/h)
  Minimum Production Rate : 0.613743 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 35.653176
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.240475
  EX_pi_e : 1.006503
  EX_so4_e : 0.102534
  EX_k_e : 0.079477
  EX_fe3_e : 0.006540
  EX_mg2_e : 0.003532
  EX_ca2_e : 0.002119
  EX_cl_e : 0.002119
  EX_cu2_e : 0.000289
  EX_mn2_e : 0.000281
  EX_zn2_e : 0.000139
  EX_ni2_e : 0.000132
  EX_cobalt2_e : 0.000010

Product: (mmol/gDw/h)
  EX_h2o_e : 50.958253
  EX_co2_e : 35.958956
  EX_h_e : 6.441643
  EX_etoh_e : 0.663765
  Auxiliary production reaction : 0.613743
  EX_ac_e : 0.237050
  EX_hxan_e : 0.000456
  DM_5drib_c : 0.000273
  DM_4crsol_c : 0.000091

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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