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 : acetol_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (11 of 80: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b4467 b1478 b1241 b4069 b2297 b2458 b1004 b3713 b1109 b0046 b3236 b1779 b4015 b3945 b1602 b3915 b0452 b2492 b0904 b1380 b2660 b0606 b2285 b1010 b4209   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.495661 (mmol/gDw/h)
  Minimum Production Rate : 0.167530 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 36.228361
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.353094
  EX_pi_e : 0.478117
  EX_so4_e : 0.124817
  EX_k_e : 0.096750
  EX_fe3_e : 0.007961
  EX_mg2_e : 0.004300
  EX_ca2_e : 0.002580
  EX_cl_e : 0.002580
  EX_cu2_e : 0.000351
  EX_mn2_e : 0.000343
  EX_zn2_e : 0.000169
  EX_ni2_e : 0.000160
  EX_cobalt2_e : 0.000012

Product: (mmol/gDw/h)
  EX_h2o_e : 50.628888
  EX_co2_e : 37.543840
  EX_h_e : 4.850856
  Auxiliary production reaction : 0.511477
  EX_ac_e : 0.288567
  DM_5drib_c : 0.000112
  DM_4crsol_c : 0.000111

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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