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 : succoa_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (8 of 28: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 32
  Gene deletion: b4382 b1241 b0351 b4069 b4384 b3708 b3115 b1849 b2296 b3617 b0030 b2407 b1982 b2797 b3117 b1814 b4471 b0261 b2406 b0112 b2975 b0114 b3603 b0509 b3125 b1539 b2492 b0904 b1533 b3821 b0508 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.504220 (mmol/gDw/h)
  Minimum Production Rate : 0.502939 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 20.060769
  EX_glc__D_e : 10.000000
  EX_nh4_e : 8.966667
  EX_pi_e : 1.995190
  EX_so4_e : 0.629912
  EX_k_e : 0.098420
  EX_fe2_e : 0.008098
  EX_mg2_e : 0.004374
  EX_ca2_e : 0.002624
  EX_cl_e : 0.002624
  EX_cu2_e : 0.000357
  EX_mn2_e : 0.000348
  EX_zn2_e : 0.000172
  EX_ni2_e : 0.000163
  EX_cobalt2_e : 0.000013

Product: (mmol/gDw/h)
  EX_h2o_e : 45.265415
  EX_co2_e : 21.387520
  EX_h_e : 9.316281
  EX_ac_e : 2.670425
  Auxiliary production reaction : 0.502939
  DM_oxam_c : 0.000564
  DM_5drib_c : 0.000338
  DM_4crsol_c : 0.000112

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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