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 : 10fthf_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (17 of 46: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 29
  Gene deletion: b4382 b1241 b0351 b4069 b4384 b3115 b1849 b2296 b2779 b2926 b3617 b0030 b2407 b1982 b4014 b0261 b2976 b4388 b2406 b0112 b2789 b3127 b2975 b0114 b3603 b0529 b2492 b0904 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.267323 (mmol/gDw/h)
  Minimum Production Rate : 1.024636 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 25.318641
  EX_nh4_e : 10.059820
  EX_glc__D_e : 10.000000
  EX_pi_e : 0.257862
  EX_so4_e : 0.067317
  EX_k_e : 0.052180
  EX_fe2_e : 0.004293
  EX_mg2_e : 0.002319
  EX_ca2_e : 0.001391
  EX_cl_e : 0.001391
  EX_cu2_e : 0.000190
  EX_mn2_e : 0.000185
  EX_zn2_e : 0.000091
  EX_ni2_e : 0.000086

Product: (mmol/gDw/h)
  EX_h2o_e : 49.342770
  EX_co2_e : 22.814818
  EX_h_e : 14.538033
  EX_ac_e : 2.859437
  Auxiliary production reaction : 1.024636
  DM_oxam_c : 0.000299
  DM_5drib_c : 0.000179
  DM_4crsol_c : 0.000060

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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