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 : gua_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (102 of 123: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 27
  Gene deletion: b2066 b0238 b0125 b1241 b0351 b4384 b0871 b2779 b3236 b2883 b3962 b0477 b2498 b3616 b3589 b4267 b1623 b0411 b0511 b0114 b0529 b2492 b0904 b0325 b0508 b0515 b4266   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.590823 (mmol/gDw/h)
  Minimum Production Rate : 0.280495 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 993.159322
  EX_o2_e : 283.925254
  EX_glc__D_e : 10.000000
  EX_nh4_e : 7.783309
  EX_pi_e : 0.569911
  EX_so4_e : 0.148781
  EX_k_e : 0.115324
  EX_mg2_e : 0.005125
  EX_cl_e : 0.003075
  EX_ca2_e : 0.003075
  EX_cu2_e : 0.000419
  EX_mn2_e : 0.000408
  EX_zn2_e : 0.000201
  EX_ni2_e : 0.000191
  EX_cobalt2_e : 0.000015

Product: (mmol/gDw/h)
  EX_fe3_e : 999.990511
  EX_h2o_e : 552.749167
  EX_co2_e : 34.346969
  Auxiliary production reaction : 0.280495
  DM_5drib_c : 0.000133
  DM_4crsol_c : 0.000132

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.

Last updated: 21-Sep-2023
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