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 (40 of 80: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 28
  Gene deletion: b4467 b1478 b4269 b0493 b3588 b3003 b3011 b1241 b0871 b2925 b2097 b2926 b3844 b1004 b3713 b1109 b0046 b3236 b2690 b2210 b3945 b1602 b2913 b2492 b0904 b1380 b0606 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.418830 (mmol/gDw/h)
  Minimum Production Rate : 0.418053 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 32.856094
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.523325
  EX_pi_e : 0.404006
  EX_so4_e : 0.105470
  EX_k_e : 0.081753
  EX_fe2_e : 0.006727
  EX_mg2_e : 0.003633
  EX_ca2_e : 0.002180
  EX_cl_e : 0.002180
  EX_cu2_e : 0.000297
  EX_mn2_e : 0.000289
  EX_zn2_e : 0.000143
  EX_ni2_e : 0.000135
  EX_cobalt2_e : 0.000010

Product: (mmol/gDw/h)
  EX_h2o_e : 46.104174
  EX_co2_e : 35.044039
  EX_h_e : 3.848374
  Auxiliary production reaction : 2.588308
  DM_5drib_c : 0.000094
  DM_4crsol_c : 0.000093

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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