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 : 14dhncoa_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (50 of 84: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 41
  Gene deletion: b4382 b4069 b4384 b3708 b3008 b2297 b2458 b0030 b2407 b3236 b1982 b2797 b3117 b1814 b4471 b3665 b0261 b0507 b3709 b2406 b3161 b0112 b2975 b0114 b3603 b0886 b1539 b2492 b0904 b3035 b2578 b1533 b3927 b3825 b2965 b0693 b1473 b0494 b4141 b1798 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.668593 (mmol/gDw/h)
  Minimum Production Rate : 0.212411 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 22.914164
  EX_glc__D_e : 10.000000
  EX_nh4_e : 8.711363
  EX_pi_e : 1.282161
  EX_so4_e : 0.380776
  EX_k_e : 0.130505
  EX_fe2_e : 0.010738
  EX_mg2_e : 0.005800
  EX_ca2_e : 0.003480
  EX_cl_e : 0.003480
  EX_cu2_e : 0.000474
  EX_mn2_e : 0.000462
  EX_zn2_e : 0.000228
  EX_ni2_e : 0.000216
  EX_cobalt2_e : 0.000017

Product: (mmol/gDw/h)
  EX_h2o_e : 47.949906
  EX_co2_e : 24.551645
  EX_h_e : 7.385928
  EX_ac_e : 0.601656
  Auxiliary production reaction : 0.212411
  EX_ade_e : 0.000748
  DM_5drib_c : 0.000449
  DM_4crsol_c : 0.000149

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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