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 : dgsn_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (41 of 77: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b4384 b3708 b3008 b0871 b0030 b2407 b2797 b3117 b1814 b4471 b4381 b3654 b2868 b3714 b3664 b4064 b4464 b0114 b2366 b2492 b0904 b1533 b3927 b3821 b1517   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.791178 (mmol/gDw/h)
  Minimum Production Rate : 0.136955 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 24.808447
  EX_glc__D_e : 10.000000
  EX_nh4_e : 9.229432
  EX_pi_e : 0.763175
  EX_so4_e : 0.199234
  EX_k_e : 0.154432
  EX_fe2_e : 0.012707
  EX_mg2_e : 0.006863
  EX_ca2_e : 0.004118
  EX_cl_e : 0.004118
  EX_cu2_e : 0.000561
  EX_mn2_e : 0.000547
  EX_zn2_e : 0.000270
  EX_ni2_e : 0.000256
  EX_cobalt2_e : 0.000020

Product: (mmol/gDw/h)
  EX_h2o_e : 48.553782
  EX_co2_e : 26.154450
  EX_h_e : 7.954436
  Auxiliary production reaction : 0.136955
  DM_mththf_c : 0.000354
  DM_5drib_c : 0.000178
  DM_4crsol_c : 0.000176

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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