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 : grdp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (32 of 51: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b3553 b3399 b2744 b0871 b2925 b2097 b1004 b3713 b1109 b0046 b3236 b1779 b1982 b3946 b0825 b1033 b0675 b2361 b4381 b0114 b0529 b2492 b0904 b1380 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.374832 (mmol/gDw/h)
  Minimum Production Rate : 0.038274 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 30.237600
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.107088
  EX_pi_e : 0.438113
  EX_so4_e : 0.094390
  EX_k_e : 0.073165
  EX_fe2_e : 0.006020
  EX_mg2_e : 0.003252
  EX_ca2_e : 0.001951
  EX_cl_e : 0.001951
  EX_cu2_e : 0.000266
  EX_mn2_e : 0.000259
  EX_zn2_e : 0.000128
  EX_ni2_e : 0.000121

Product: (mmol/gDw/h)
  EX_h2o_e : 43.835571
  EX_co2_e : 28.499775
  EX_h_e : 8.728533
  EX_pyr_e : 5.204830
  DM_oxam_c : 0.058936
  Auxiliary production reaction : 0.038274
  DM_5drib_c : 0.000084
  DM_4crsol_c : 0.000084

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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