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 : duri_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (19 of 50: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b1478 b2066 b1241 b0351 b0910 b0871 b2779 b2925 b2097 b3617 b3236 b2690 b2498 b2210 b0675 b0822 b2913 b4381 b0511 b0114 b0529 b2492 b0904 b0516 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.361221 (mmol/gDw/h)
  Minimum Production Rate : 0.055930 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 30.379541
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.326790
  EX_pi_e : 0.348436
  EX_so4_e : 0.090963
  EX_k_e : 0.070508
  EX_fe2_e : 0.005802
  EX_mg2_e : 0.003134
  EX_ca2_e : 0.001880
  EX_cl_e : 0.001880
  EX_cu2_e : 0.000256
  EX_mn2_e : 0.000250
  EX_zn2_e : 0.000123
  EX_ni2_e : 0.000117

Product: (mmol/gDw/h)
  EX_h2o_e : 44.123197
  EX_co2_e : 28.175374
  EX_h_e : 9.112200
  EX_pyr_e : 5.367402
  EX_xan_e : 0.078443
  Auxiliary production reaction : 0.055930
  EX_glyc__R_e : 0.000121
  DM_5drib_c : 0.000081
  DM_4crsol_c : 0.000081

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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