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 : hxan_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (56 of 74: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 27
  Gene deletion: b3399 b1241 b0351 b2502 b2744 b0871 b2779 b2925 b2097 b2690 b3616 b3589 b4374 b0675 b2361 b2291 b3945 b3654 b2868 b3714 b3664 b4064 b4464 b0114 b0529 b2492 b0904   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.685739 (mmol/gDw/h)
  Minimum Production Rate : 0.836077 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 990.343838
  EX_o2_e : 278.297248
  EX_nh4_e : 10.750227
  EX_glc__D_e : 10.000000
  EX_pi_e : 0.661468
  EX_so4_e : 0.172683
  EX_k_e : 0.133851
  EX_mg2_e : 0.005949
  EX_ca2_e : 0.003569
  EX_cl_e : 0.003569
  EX_cu2_e : 0.000486
  EX_mn2_e : 0.000474
  EX_zn2_e : 0.000234
  EX_ni2_e : 0.000221
  EX_cobalt2_e : 0.000017

Product: (mmol/gDw/h)
  EX_fe3_e : 999.988986
  EX_h2o_e : 553.300838
  EX_co2_e : 27.673191
  Auxiliary production reaction : 0.836077
  DM_5drib_c : 0.000154
  DM_4crsol_c : 0.000153

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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