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 : prbamp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (43 of 47: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 40
  Gene deletion: b3553 b1478 b3399 b4382 b4269 b0493 b3588 b3003 b3011 b1241 b2502 b4384 b2744 b0871 b1004 b3713 b1109 b0046 b3236 b1779 b1982 b1033 b0675 b2361 b2291 b0261 b2799 b3945 b1602 b2913 b3915 b0114 b0529 b2492 b0904 b1380 b0606 b2285 b1010 b4209   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.491934 (mmol/gDw/h)
  Minimum Production Rate : 0.091830 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 37.427355
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.893933
  EX_pi_e : 0.658180
  EX_so4_e : 0.123880
  EX_k_e : 0.096022
  EX_fe3_e : 0.007903
  EX_mg2_e : 0.004268
  EX_ca2_e : 0.002561
  EX_cl_e : 0.002561
  EX_cu2_e : 0.000349
  EX_mn2_e : 0.000340
  EX_zn2_e : 0.000168
  EX_ni2_e : 0.000159
  EX_cobalt2_e : 0.000012

Product: (mmol/gDw/h)
  EX_h2o_e : 52.585669
  EX_co2_e : 38.188699
  EX_h_e : 5.109075
  EX_gly_e : 0.119187
  Auxiliary production reaction : 0.091829
  EX_ade_e : 0.000550
  DM_5drib_c : 0.000330
  DM_4crsol_c : 0.000110

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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