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 (17 of 80: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 26
  Gene deletion: b4467 b1478 b1241 b0351 b0871 b2779 b1004 b3713 b1109 b0046 b3236 b0261 b3945 b1602 b2913 b4381 b3915 b0452 b0529 b2492 b0904 b1380 b0606 b2285 b1010 b4209   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.502958 (mmol/gDw/h)
  Minimum Production Rate : 0.132650 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 37.816259
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.431906
  EX_pi_e : 0.485157
  EX_so4_e : 0.126655
  EX_k_e : 0.098174
  EX_fe3_e : 0.008078
  EX_mg2_e : 0.004363
  EX_ca2_e : 0.002618
  EX_cl_e : 0.002618
  EX_cu2_e : 0.000357
  EX_mn2_e : 0.000348
  EX_zn2_e : 0.000172
  EX_ni2_e : 0.000162
  EX_cobalt2_e : 0.000013

Product: (mmol/gDw/h)
  EX_h2o_e : 52.235623
  EX_co2_e : 38.957926
  EX_h_e : 4.629459
  Auxiliary production reaction : 0.132650
  DM_5drib_c : 0.000113
  DM_4crsol_c : 0.000112

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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