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 : pnto__R_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (14 of 79: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 30
  Gene deletion: b4382 b1241 b0351 b4069 b4384 b3708 b3752 b3115 b1849 b2296 b3617 b2407 b2797 b3117 b1814 b4471 b3665 b0261 b2406 b0112 b3654 b3714 b3664 b0114 b2366 b2492 b0904 b1533 b3662 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.449409 (mmol/gDw/h)
  Minimum Production Rate : 1.010466 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 27.079676
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.864046
  EX_pi_e : 0.433503
  EX_so4_e : 0.113170
  EX_k_e : 0.087722
  EX_fe2_e : 0.007218
  EX_mg2_e : 0.003899
  EX_ca2_e : 0.002339
  EX_cl_e : 0.002339
  EX_cu2_e : 0.000319
  EX_mn2_e : 0.000311
  EX_zn2_e : 0.000153
  EX_ni2_e : 0.000145
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_h2o_e : 42.937774
  EX_co2_e : 29.049191
  EX_h_e : 7.855500
  EX_ac_e : 1.705218
  Auxiliary production reaction : 1.010466
  DM_5drib_c : 0.000101
  DM_4crsol_c : 0.000100

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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