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 (50 of 83: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 32
  Gene deletion: b4467 b2836 b4269 b0493 b3588 b3003 b3011 b0474 b2518 b3926 b0871 b2779 b1004 b3713 b1109 b0046 b3236 b1638 b1779 b4139 b1602 b2913 b3915 b2975 b3603 b0529 b2492 b0904 b3029 b1380 b1771 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.489116 (mmol/gDw/h)
  Minimum Production Rate : 0.210300 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 38.562836
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.282411
  EX_pi_e : 0.471804
  EX_so4_e : 0.123169
  EX_k_e : 0.095472
  EX_fe3_e : 0.007856
  EX_mg2_e : 0.004243
  EX_ca2_e : 0.002546
  EX_cl_e : 0.002546
  EX_cu2_e : 0.000347
  EX_mn2_e : 0.000338
  EX_zn2_e : 0.000167
  EX_ni2_e : 0.000158
  EX_cobalt2_e : 0.000012

Product: (mmol/gDw/h)
  EX_h2o_e : 52.415707
  EX_co2_e : 39.503433
  EX_h_e : 4.712349
  Auxiliary production reaction : 0.210300
  DM_5drib_c : 0.000110
  DM_4crsol_c : 0.000109

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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