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 : fmnh2_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (7 of 15: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 29
  Gene deletion: b4467 b3916 b3426 b2242 b1241 b0351 b3114 b3952 b0903 b2926 b1638 b3962 b4139 b4267 b4015 b1014 b0837 b0124 b1723 b0529 b0306 b3605 b3028 b0325 b0508 b4266 b1813 b2285 b1378   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.389405 (mmol/gDw/h)
  Minimum Production Rate : 0.384857 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 36.835178
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.744970
  EX_pi_e : 0.760479
  EX_so4_e : 0.098060
  EX_k_e : 0.076009
  EX_fe2_e : 0.006254
  EX_mg2_e : 0.003378
  EX_ca2_e : 0.002027
  EX_cl_e : 0.002027
  EX_cu2_e : 0.000276
  EX_mn2_e : 0.000269
  EX_zn2_e : 0.000133
  EX_ni2_e : 0.000126

Product: (mmol/gDw/h)
  EX_h2o_e : 52.759871
  EX_co2_e : 37.473619
  EX_h_e : 5.117698
  Auxiliary production reaction : 0.384857
  EX_glyclt_e : 0.000261
  DM_5drib_c : 0.000088
  DM_4crsol_c : 0.000087

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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