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 : dcmp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (75 of 117: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 37
  Gene deletion: b4467 b4382 b4269 b0493 b3588 b3003 b3011 b1241 b0351 b4384 b2744 b0871 b2925 b2097 b3617 b0030 b2407 b1004 b3713 b1109 b0046 b2690 b1982 b2210 b0675 b0261 b0822 b1602 b4388 b1727 b0114 b0529 b2492 b0904 b1380 b3662 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.359656 (mmol/gDw/h)
  Minimum Production Rate : 1.169477 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 27.214219
  EX_glc__D_e : 10.000000
  EX_nh4_e : 7.392928
  EX_pi_e : 1.516403
  EX_so4_e : 0.090569
  EX_k_e : 0.070202
  EX_fe2_e : 0.005776
  EX_mg2_e : 0.003120
  EX_cl_e : 0.001872
  EX_ca2_e : 0.001872
  EX_cu2_e : 0.000255
  EX_mn2_e : 0.000249
  EX_zn2_e : 0.000123
  EX_ni2_e : 0.000116

Product: (mmol/gDw/h)
  EX_h2o_e : 47.245542
  EX_co2_e : 26.112030
  EX_h_e : 9.093509
  EX_pyr_e : 2.279691
  Auxiliary production reaction : 1.169477
  EX_acald_e : 0.880206
  DM_oxam_c : 0.000242
  EX_glyclt_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.

Last updated: 21-Sep-2023
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