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 : mnl1p_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (10 of 80: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 29
  Gene deletion: b4467 b1478 b4382 b1241 b4069 b4384 b2297 b2458 b2407 b3844 b1004 b3713 b1109 b0046 b3236 b1779 b0937 b2799 b3945 b1602 b2913 b0529 b2492 b0904 b1380 b1518 b0606 b2285 b1009   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.428838 (mmol/gDw/h)
  Minimum Production Rate : 0.953181 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 995.009029
  EX_o2_e : 284.289218
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.425499
  EX_pi_e : 1.366840
  EX_so4_e : 0.107990
  EX_k_e : 0.083706
  EX_mg2_e : 0.003720
  EX_ca2_e : 0.002232
  EX_cl_e : 0.002232
  EX_cu2_e : 0.000304
  EX_mn2_e : 0.000296
  EX_zn2_e : 0.000146
  EX_ni2_e : 0.000139
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_fe3_e : 999.993112
  EX_h2o_e : 548.293869
  EX_co2_e : 35.186556
  Auxiliary production reaction : 0.953181
  EX_ac_e : 0.249663
  EX_hxan_e : 0.198161
  EX_ade_e : 0.000289
  DM_mththf_c : 0.000192
  DM_5drib_c : 0.000096
  DM_4crsol_c : 0.000096

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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