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 : dhpt_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (102 of 115: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 42
  Gene deletion: b3553 b1478 b3399 b1241 b4069 b2744 b2297 b2458 b2779 b0160 b1004 b3713 b1109 b0046 b3236 b1638 b3908 b1656 b1982 b4139 b1033 b4374 b0675 b2361 b2291 b0261 b2799 b3945 b1602 b3915 b0509 b3125 b0529 b2492 b0904 b2954 b3927 b1380 b2660 b1695 b2285 b1007   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.432036 (mmol/gDw/h)
  Minimum Production Rate : 0.243069 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 38.042597
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.126781
  EX_pi_e : 0.416744
  EX_so4_e : 0.108795
  EX_k_e : 0.084330
  EX_fe3_e : 0.006939
  EX_mg2_e : 0.003748
  EX_cl_e : 0.002249
  EX_ca2_e : 0.002249
  EX_cu2_e : 0.000306
  EX_mn2_e : 0.000299
  EX_zn2_e : 0.000147
  EX_ni2_e : 0.000140
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_h2o_e : 53.656860
  EX_co2_e : 38.357520
  EX_h_e : 5.932082
  EX_ac_e : 0.251525
  Auxiliary production reaction : 0.243069
  EX_ade_e : 0.000483
  DM_5drib_c : 0.000290
  DM_4crsol_c : 0.000096

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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