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 : glyclt_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (75 of 83: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 42
  Gene deletion: b4467 b3942 b1732 b1241 b0351 b4069 b4384 b2744 b3752 b3926 b3115 b1849 b2296 b2926 b3617 b2407 b1004 b3713 b1109 b0046 b3124 b1982 b2210 b0261 b0411 b1602 b4381 b0112 b2975 b0114 b3603 b0755 b3612 b0529 b2492 b0904 b1380 b0514 b3662 b0606 b2285 b4209   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.305285 (mmol/gDw/h)
  Minimum Production Rate : 0.585071 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 33.263893
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.638709
  EX_pi_e : 0.294480
  EX_so4_e : 0.076877
  EX_k_e : 0.059590
  EX_mg2_e : 0.002648
  EX_fe2_e : 0.002520
  EX_fe3_e : 0.002384
  EX_ca2_e : 0.001589
  EX_cl_e : 0.001589
  EX_cu2_e : 0.000216
  EX_mn2_e : 0.000211
  EX_zn2_e : 0.000104
  EX_ni2_e : 0.000099

Product: (mmol/gDw/h)
  EX_h2o_e : 48.414601
  EX_co2_e : 33.330117
  EX_h_e : 7.244478
  EX_ac_e : 1.510286
  EX_hxan_e : 0.585413
  DM_5drib_c : 0.585276
  DM_4crsol_c : 0.585140
  Auxiliary production reaction : 0.585071

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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