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 : cpmp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (37 of 38: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 41
  Gene deletion: b4467 b1478 b3399 b1241 b4069 b4384 b2744 b2297 b2458 b2407 b1004 b3713 b1109 b0046 b3236 b1638 b1779 b1982 b4139 b0675 b2361 b0261 b2799 b3945 b1602 b0507 b2913 b4381 b3915 b0452 b2975 b3603 b0529 b2492 b0904 b1300 b2954 b3029 b1380 b2285 b1009   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.417070 (mmol/gDw/h)
  Minimum Production Rate : 0.467943 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 38.226063
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.846369
  EX_pi_e : 0.870251
  EX_so4_e : 0.105027
  EX_k_e : 0.081409
  EX_fe3_e : 0.006699
  EX_mg2_e : 0.003618
  EX_ca2_e : 0.002171
  EX_cl_e : 0.002171
  EX_cu2_e : 0.000296
  EX_mn2_e : 0.000288
  EX_zn2_e : 0.000142
  EX_ni2_e : 0.000135
  EX_cobalt2_e : 0.000010

Product: (mmol/gDw/h)
  EX_h2o_e : 54.343171
  EX_co2_e : 37.712872
  EX_h_e : 5.955822
  Auxiliary production reaction : 0.467943
  EX_ac_e : 0.242812
  EX_ade_e : 0.000467
  DM_5drib_c : 0.000280
  DM_4crsol_c : 0.000093

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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