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 : gdpfuc_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (43 of 74: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 29
  Gene deletion: b2836 b1241 b0351 b4069 b4384 b2744 b3708 b3752 b2297 b2458 b3617 b2407 b1982 b2797 b3117 b1814 b4471 b4374 b2361 b2291 b0261 b0411 b0112 b0114 b1539 b2492 b0904 b1533 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.542103 (mmol/gDw/h)
  Minimum Production Rate : 0.811067 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 21.522223
  EX_glc__D_e : 10.000000
  EX_nh4_e : 9.910001
  EX_pi_e : 2.145050
  EX_so4_e : 0.136512
  EX_k_e : 0.105815
  EX_fe2_e : 0.008707
  EX_mg2_e : 0.004703
  EX_ca2_e : 0.002822
  EX_cl_e : 0.002822
  EX_cu2_e : 0.000384
  EX_mn2_e : 0.000375
  EX_zn2_e : 0.000185
  EX_ni2_e : 0.000175
  EX_cobalt2_e : 0.000014

Product: (mmol/gDw/h)
  EX_h2o_e : 46.321913
  EX_co2_e : 20.651535
  EX_h_e : 9.473933
  EX_ac_e : 2.059674
  Auxiliary production reaction : 0.811067
  DM_5drib_c : 0.000364
  DM_4crsol_c : 0.000121

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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