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 : pant__R_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (66 of 93: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 27
  Gene deletion: b3553 b1478 b4382 b1241 b4384 b2930 b4232 b3697 b3925 b0871 b2407 b1004 b3713 b1109 b0046 b1779 b2690 b2210 b1033 b0675 b0822 b1602 b0114 b2492 b0904 b1380 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.386527 (mmol/gDw/h)
  Minimum Production Rate : 0.311664 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 996.130561
  EX_o2_e : 291.126772
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.174462
  EX_pi_e : 0.372847
  EX_so4_e : 0.097335
  EX_k_e : 0.075447
  EX_mg2_e : 0.003353
  EX_cl_e : 0.002012
  EX_ca2_e : 0.002012
  EX_cu2_e : 0.000274
  EX_mn2_e : 0.000267
  EX_zn2_e : 0.000132
  EX_ni2_e : 0.000125

Product: (mmol/gDw/h)
  EX_fe3_e : 999.993792
  EX_h2o_e : 552.468859
  EX_co2_e : 42.264845
  Auxiliary production reaction : 0.311664
  DM_5drib_c : 0.000087
  DM_4crsol_c : 0.000086

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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