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 : didp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (48 of 87: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b4382 b4069 b4384 b3708 b3752 b3115 b1849 b2296 b2779 b2407 b1982 b2797 b3117 b1814 b4471 b2239 b3453 b0114 b2366 b2492 b0904 b1533 b3927 b3825 b1511   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.679332 (mmol/gDw/h)
  Minimum Production Rate : 0.216126 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 28.145324
  EX_glc__D_e : 10.000000
  EX_nh4_e : 8.201228
  EX_pi_e : 1.087539
  EX_so4_e : 0.171069
  EX_k_e : 0.132601
  EX_fe2_e : 0.010911
  EX_mg2_e : 0.005893
  EX_cl_e : 0.003536
  EX_ca2_e : 0.003536
  EX_cu2_e : 0.000482
  EX_mn2_e : 0.000469
  EX_zn2_e : 0.000232
  EX_ni2_e : 0.000219
  EX_cobalt2_e : 0.000017

Product: (mmol/gDw/h)
  EX_h2o_e : 49.695561
  EX_co2_e : 29.162780
  EX_h_e : 7.285845
  EX_ac_e : 0.395497
  Auxiliary production reaction : 0.216126
  DM_mththf_c : 0.000304
  DM_5drib_c : 0.000153
  DM_4crsol_c : 0.000151

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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