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 : trp__L_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (18 of 116: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 37
  Gene deletion: b3553 b3399 b1241 b0351 b4069 b2502 b2744 b3708 b2297 b2458 b0583 b1982 b2797 b3117 b1814 b4471 b3616 b3589 b1033 b4374 b0675 b2361 b2291 b0261 b0507 b3709 b3161 b0112 b0114 b1539 b2492 b0904 b1533 b3821 b1473 b4141 b1798   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.467594 (mmol/gDw/h)
  Minimum Production Rate : 1.399220 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 18.764361
  EX_glc__D_e : 10.000000
  EX_nh4_e : 7.848942
  EX_pi_e : 0.451044
  EX_so4_e : 0.117750
  EX_k_e : 0.091271
  EX_fe2_e : 0.007510
  EX_mg2_e : 0.004056
  EX_ca2_e : 0.002434
  EX_cl_e : 0.002434
  EX_cu2_e : 0.000332
  EX_mn2_e : 0.000323
  EX_zn2_e : 0.000159
  EX_ni2_e : 0.000151
  EX_cobalt2_e : 0.000012

Product: (mmol/gDw/h)
  EX_h2o_e : 44.003669
  EX_co2_e : 20.460990
  EX_h_e : 9.572381
  EX_ac_e : 2.476139
  Auxiliary production reaction : 1.399220
  DM_oxam_c : 0.000523
  DM_5drib_c : 0.000314
  EX_glyclt_e : 0.000313
  DM_4crsol_c : 0.000104

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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