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 : unagamuf_p
List of minimal gene deletion strategies (Download)

Gene deletion strategy (42 of 79: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 26
  Gene deletion: b3399 b1241 b0351 b4069 b2502 b2744 b3115 b1849 b2296 b3617 b1623 b3665 b4374 b0675 b2361 b2291 b0411 b0112 b3654 b3714 b3664 b0114 b0529 b2492 b0904 b1517   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.460008 (mmol/gDw/h)
  Minimum Production Rate : 0.220553 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 16.625974
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.629710
  EX_pi_e : 0.884833
  EX_so4_e : 0.115839
  EX_k_e : 0.089790
  EX_fe2_e : 0.007388
  EX_mg2_e : 0.003991
  EX_ca2_e : 0.002394
  EX_cl_e : 0.002394
  EX_cu2_e : 0.000326
  EX_mn2_e : 0.000318
  EX_zn2_e : 0.000157
  EX_ni2_e : 0.000149
  EX_cobalt2_e : 0.000012

Product: (mmol/gDw/h)
  EX_h2o_e : 39.349242
  EX_co2_e : 22.349529
  EX_h_e : 5.340111
  EX_ac_e : 0.672265
  Auxiliary production reaction : 0.220553
  DM_mththf_c : 0.000206
  DM_5drib_c : 0.000104
  DM_4crsol_c : 0.000103

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.

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Last updated: 21-Sep-2023
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