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 : ahcys_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (15 of 80: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 29
  Gene deletion: b4069 b4384 b2744 b3708 b3008 b2297 b2458 b0030 b2407 b1779 b2687 b1982 b2797 b3117 b1814 b4471 b4374 b2361 b2291 b2406 b0114 b2366 b2492 b0904 b2578 b1533 b3927 b3821 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.650393 (mmol/gDw/h)
  Minimum Production Rate : 0.206920 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 27.950234
  EX_glc__D_e : 10.000000
  EX_nh4_e : 8.265713
  EX_pi_e : 0.627373
  EX_so4_e : 0.370702
  EX_k_e : 0.126952
  EX_fe2_e : 0.010446
  EX_mg2_e : 0.005642
  EX_ca2_e : 0.003385
  EX_cl_e : 0.003385
  EX_cu2_e : 0.000461
  EX_mn2_e : 0.000449
  EX_zn2_e : 0.000222
  EX_ni2_e : 0.000210
  EX_cobalt2_e : 0.000016

Product: (mmol/gDw/h)
  EX_h2o_e : 49.306841
  EX_co2_e : 29.234872
  EX_h_e : 7.389323
  EX_ac_e : 0.585570
  Auxiliary production reaction : 0.206920
  DM_5drib_c : 0.000436
  DM_4crsol_c : 0.000145

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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