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 : dha_e
List of minimal gene deletion strategies (Download)

Gene deletion strategy (36 of 38: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 14
  Gene deletion: b0238 b0125 b3831 b2744 b2925 b2097 b1851 b2029 b0477 b1200 b2498 b2361 b2291 b1517   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.438416 (mmol/gDw/h)
  Minimum Production Rate : 9.618417 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 995.964618
  EX_o2_e : 262.211456
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.734855
  EX_pi_e : 0.422899
  EX_so4_e : 0.110402
  EX_k_e : 0.085576
  EX_mg2_e : 0.003803
  EX_ca2_e : 0.002282
  EX_cl_e : 0.002282
  EX_cu2_e : 0.000311
  EX_mn2_e : 0.000303
  EX_zn2_e : 0.000149
  EX_ni2_e : 0.000142
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_fe3_e : 999.992959
  EX_h2o_e : 524.722638
  EX_co2_e : 13.148805
  EX_dha_e : 9.618417
  EX_mththf_e : 0.000196
  DM_5drib_c : 0.000099
  DM_4crsol_c : 0.000098

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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