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 : prlp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (45 of 71: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 29
  Gene deletion: b3399 b4069 b2502 b2744 b3708 b3008 b2297 b2458 b1982 b2797 b3117 b1814 b4471 b0675 b2361 b0261 b4381 b2406 b0114 b0755 b3612 b0529 b1539 b2492 b0904 b1533 b3927 b3821 b1813   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.647159 (mmol/gDw/h)
  Minimum Production Rate : 0.257201 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 28.085904
  EX_glc__D_e : 10.000000
  EX_nh4_e : 8.275270
  EX_pi_e : 1.138656
  EX_so4_e : 0.162968
  EX_k_e : 0.126321
  EX_fe2_e : 0.010394
  EX_mg2_e : 0.005614
  EX_ca2_e : 0.003368
  EX_cl_e : 0.003368
  EX_cu2_e : 0.000459
  EX_mn2_e : 0.000447
  EX_zn2_e : 0.000221
  EX_ni2_e : 0.000209
  EX_cobalt2_e : 0.000016

Product: (mmol/gDw/h)
  EX_h2o_e : 49.257395
  EX_co2_e : 28.824096
  EX_h_e : 7.609129
  EX_ac_e : 0.376767
  Auxiliary production reaction : 0.257201
  DM_5drib_c : 0.000434
  DM_4crsol_c : 0.000144

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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