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 : succoa_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (15 of 28: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 35
  Gene deletion: b3399 b0586 b4069 b2502 b2744 b3708 b3008 b2297 b2458 b1982 b2797 b3117 b1814 b4471 b4374 b0675 b2361 b2291 b0261 b3709 b3161 b0112 b2868 b0114 b1539 b2492 b0904 b2578 b1533 b3927 b3821 b1473 b3447 b4141 b1798   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.713432 (mmol/gDw/h)
  Minimum Production Rate : 0.181325 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 23.373535
  EX_glc__D_e : 10.000000
  EX_nh4_e : 8.978271
  EX_pi_e : 1.232155
  EX_so4_e : 0.360981
  EX_k_e : 0.139257
  EX_fe2_e : 0.011458
  EX_mg2_e : 0.006189
  EX_ca2_e : 0.003713
  EX_cl_e : 0.003713
  EX_cu2_e : 0.000506
  EX_mn2_e : 0.000493
  EX_zn2_e : 0.000243
  EX_ni2_e : 0.000230
  EX_cobalt2_e : 0.000018

Product: (mmol/gDw/h)
  EX_h2o_e : 47.640411
  EX_co2_e : 24.984840
  EX_h_e : 7.881264
  EX_ac_e : 0.596675
  Auxiliary production reaction : 0.181325
  EX_ade_e : 0.000798
  DM_5drib_c : 0.000479
  DM_4crsol_c : 0.000159

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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