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 : ade_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (54 of 78: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b4382 b1241 b0351 b4384 b2930 b4232 b3697 b3925 b0871 b2297 b2458 b0030 b2407 b2690 b3616 b3589 b3665 b3945 b3654 b3714 b3664 b0114 b0529 b2492 b0904   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.755862 (mmol/gDw/h)
  Minimum Production Rate : 0.202987 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 25.502896
  EX_glc__D_e : 10.000000
  EX_nh4_e : 9.178180
  EX_pi_e : 0.729109
  EX_so4_e : 0.190341
  EX_k_e : 0.147539
  EX_fe2_e : 0.012140
  EX_mg2_e : 0.006557
  EX_ca2_e : 0.003934
  EX_cl_e : 0.003934
  EX_cu2_e : 0.000536
  EX_mn2_e : 0.000522
  EX_zn2_e : 0.000258
  EX_ni2_e : 0.000244
  EX_cobalt2_e : 0.000019

Product: (mmol/gDw/h)
  EX_h2o_e : 48.868938
  EX_co2_e : 26.338066
  EX_h_e : 8.500873
  EX_pyr_e : 0.540777
  Auxiliary production reaction : 0.202987
  DM_5drib_c : 0.000170
  DM_4crsol_c : 0.000169

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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