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 : grdp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (31 of 51: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b1241 b0351 b4069 b2930 b4232 b3697 b3925 b2297 b2458 b2926 b3124 b0517 b2690 b3616 b3589 b3945 b4381 b0114 b0755 b3612 b0529 b2492 b0904 b1517 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.361900 (mmol/gDw/h)
  Minimum Production Rate : 0.127040 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 32.669430
  EX_glc__D_e : 10.000000
  EX_nh4_e : 3.908487
  EX_pi_e : 0.603172
  EX_so4_e : 0.091134
  EX_k_e : 0.070640
  EX_fe2_e : 0.005812
  EX_mg2_e : 0.003139
  EX_cl_e : 0.001884
  EX_ca2_e : 0.001884
  EX_cu2_e : 0.000257
  EX_mn2_e : 0.000250
  EX_zn2_e : 0.000123
  EX_ni2_e : 0.000117

Product: (mmol/gDw/h)
  EX_h2o_e : 43.887788
  EX_co2_e : 33.949893
  EX_h_e : 8.160523
  EX_ac_e : 4.962284
  Auxiliary production reaction : 0.127040
  DM_mththf_c : 0.000162
  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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