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 : q8h2_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (63 of 86: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b3708 b3008 b0871 b2925 b2097 b1612 b1611 b4122 b1779 b2690 b2797 b3117 b1814 b4471 b3945 b4381 b0452 b2868 b0114 b2366 b2492 b0904 b1533 b3927 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.365637 (mmol/gDw/h)
  Minimum Production Rate : 0.018077 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 29.893769
  EX_glc__D_e : 10.000000
  EX_nh4_e : 3.948846
  EX_pi_e : 0.352695
  EX_so4_e : 0.092075
  EX_k_e : 0.071370
  EX_fe2_e : 0.005872
  EX_mg2_e : 0.003172
  EX_cl_e : 0.001903
  EX_ca2_e : 0.001903
  EX_cu2_e : 0.000259
  EX_mn2_e : 0.000253
  EX_zn2_e : 0.000125
  EX_ni2_e : 0.000118

Product: (mmol/gDw/h)
  EX_h2o_e : 43.613200
  EX_co2_e : 28.203802
  EX_h_e : 8.914714
  EX_pyr_e : 4.792532
  EX_fum_e : 0.381283
  Auxiliary production reaction : 0.018077
  DM_5drib_c : 0.000082
  DM_4crsol_c : 0.000082

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.

Last updated: 21-Sep-2023
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