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 : dadp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (53 of 95: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b3399 b1241 b0351 b2744 b2930 b4232 b3697 b3925 b0871 b2297 b2458 b3617 b0160 b1779 b2690 b4374 b2361 b2291 b3945 b2868 b0114 b0529 b2492 b0904 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.358144 (mmol/gDw/h)
  Minimum Production Rate : 0.072014 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 30.344134
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.228958
  EX_pi_e : 0.489495
  EX_so4_e : 0.090188
  EX_k_e : 0.069907
  EX_fe2_e : 0.005752
  EX_mg2_e : 0.003107
  EX_ca2_e : 0.001864
  EX_cl_e : 0.001864
  EX_cu2_e : 0.000254
  EX_mn2_e : 0.000247
  EX_zn2_e : 0.000122
  EX_ni2_e : 0.000116

Product: (mmol/gDw/h)
  EX_h2o_e : 44.082672
  EX_co2_e : 28.240851
  EX_h_e : 9.025669
  EX_pyr_e : 5.445880
  Auxiliary production reaction : 0.072014
  EX_hxan_e : 0.000241
  DM_5drib_c : 0.000081
  DM_4crsol_c : 0.000080

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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