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 : gsn_e
List of minimal gene deletion strategies (Download)

Gene deletion strategy (49 of 49: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 49
  Gene deletion: b3553 b3942 b1732 b1241 b0351 b4069 b1479 b2297 b2458 b3617 b0030 b2407 b3844 b3236 b2883 b2463 b3962 b0104 b2210 b4267 b1033 b3551 b1014 b0261 b3945 b2913 b4219 b1832 b1778 b4381 b2406 b0112 b2868 b4064 b4464 b0114 b0755 b3612 b0529 b0306 b1539 b3605 b2492 b0904 b1380 b0325 b1710 b2480 b4266   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.361185 (mmol/gDw/h)
  Minimum Production Rate : 0.582029 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 36.480392
  EX_glc__D_e : 10.000000
  EX_nh4_e : 7.363806
  EX_pi_e : 0.348402
  EX_so4_e : 0.090954
  EX_k_e : 0.070501
  EX_fe2_e : 0.005801
  EX_mg2_e : 0.003133
  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 : 52.274644
  EX_co2_e : 35.228639
  EX_h_e : 8.568339
  EX_ac_e : 1.786589
  EX_gsn_e : 0.582029
  EX_ade_e : 0.110578
  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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