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 : glyc__R_e
List of minimal gene deletion strategies (Download)

Gene deletion strategy (53 of 83: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 35
  Gene deletion: b2836 b3399 b4382 b4069 b2744 b3708 b3008 b2297 b2458 b2779 b2926 b0160 b3844 b1982 b2797 b3117 b1814 b4471 b0675 b2361 b0261 b4381 b2406 b0112 b0114 b0886 b1539 b2492 b0904 b2578 b1533 b3927 b0594 b4141 b1798   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.637082 (mmol/gDw/h)
  Minimum Production Rate : 0.126572 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 27.752078
  EX_glc__D_e : 10.000000
  EX_nh4_e : 7.150959
  EX_pi_e : 0.614533
  EX_so4_e : 0.160430
  EX_k_e : 0.124354
  EX_fe2_e : 0.010232
  EX_mg2_e : 0.005527
  EX_ca2_e : 0.003316
  EX_cl_e : 0.003316
  EX_cu2_e : 0.000452
  EX_mn2_e : 0.000440
  EX_zn2_e : 0.000217
  EX_ni2_e : 0.000206
  EX_cobalt2_e : 0.000016

Product: (mmol/gDw/h)
  EX_h2o_e : 47.273042
  EX_co2_e : 29.148978
  EX_h_e : 6.892291
  EX_ac_e : 0.370900
  DM_oxam_c : 0.270528
  DM_5drib_c : 0.253572
  DM_4crsol_c : 0.253287
  EX_glyc__R_e : 0.126572

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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