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 : sbt6p_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (42 of 83: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 36
  Gene deletion: b4467 b1478 b3399 b4269 b0493 b3588 b3003 b3011 b1241 b2744 b0871 b2779 b0160 b3844 b1004 b3713 b1109 b0046 b3236 b4374 b2361 b2291 b2799 b3945 b1602 b0507 b2913 b3915 b0529 b2492 b0904 b1380 b1518 b0606 b2285 b1007   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.444843 (mmol/gDw/h)
  Minimum Production Rate : 0.898856 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 995.307814
  EX_o2_e : 284.647754
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.401914
  EX_pi_e : 1.327955
  EX_so4_e : 0.112020
  EX_k_e : 0.086830
  EX_mg2_e : 0.003859
  EX_ca2_e : 0.002315
  EX_cl_e : 0.002315
  EX_cu2_e : 0.000315
  EX_mn2_e : 0.000307
  EX_zn2_e : 0.000152
  EX_ni2_e : 0.000144
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_fe3_e : 999.992855
  EX_h2o_e : 548.688247
  EX_co2_e : 35.749450
  Auxiliary production reaction : 0.898856
  EX_ade_e : 0.119529
  DM_mththf_c : 0.000199
  DM_5drib_c : 0.000100
  DM_4crsol_c : 0.000099

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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