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 : damp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (57 of 81: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b4467 b3399 b2744 b0871 b2779 b2925 b2097 b1004 b3713 b1109 b0046 b2690 b2210 b0675 b0822 b1602 b4381 b1727 b0114 b0529 b2492 b0904 b1380 b0515 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.370277 (mmol/gDw/h)
  Minimum Production Rate : 0.074578 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 43.415026
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.371852
  EX_pi_e : 0.431750
  EX_so4_e : 0.093243
  EX_k_e : 0.072275
  EX_fe2_e : 0.005947
  EX_mg2_e : 0.003212
  EX_ca2_e : 0.001927
  EX_cl_e : 0.001927
  EX_cu2_e : 0.000263
  EX_mn2_e : 0.000256
  EX_zn2_e : 0.000126
  EX_ni2_e : 0.000120

Product: (mmol/gDw/h)
  EX_h2o_e : 54.728979
  EX_co2_e : 44.056048
  EX_h_e : 3.775144
  Auxiliary production reaction : 0.074578
  DM_5drib_c : 0.000083
  DM_4crsol_c : 0.000083

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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