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 : nad_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (18 of 79: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b3399 b1241 b0351 b4069 b2744 b3115 b1849 b2296 b0160 b1982 b3616 b3589 b0675 b2361 b0261 b0507 b4381 b2406 b0112 b2975 b0114 b3603 b0529 b2492 b0904   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.465845 (mmol/gDw/h)
  Minimum Production Rate : 0.880591 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 20.878110
  EX_nh4_e : 11.207938
  EX_glc__D_e : 10.000000
  EX_pi_e : 2.210539
  EX_so4_e : 0.117309
  EX_k_e : 0.090930
  EX_fe2_e : 0.007482
  EX_mg2_e : 0.004041
  EX_ca2_e : 0.002425
  EX_cl_e : 0.002425
  EX_cu2_e : 0.000330
  EX_mn2_e : 0.000322
  EX_zn2_e : 0.000159
  EX_ni2_e : 0.000150
  EX_cobalt2_e : 0.000012

Product: (mmol/gDw/h)
  EX_h2o_e : 50.031020
  EX_co2_e : 19.211498
  EX_h_e : 9.402567
  EX_ac_e : 1.574409
  Auxiliary production reaction : 0.880591
  DM_oxam_c : 0.012711
  DM_5drib_c : 0.000313
  DM_4crsol_c : 0.000104

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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