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 : pe181_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (52 of 71: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b1855 b2836 b2744 b1278 b3614 b0910 b4152 b2781 b1612 b1611 b4122 b1759 b4374 b0675 b2361 b2291 b4138 b4123 b0621 b2223 b3915 b2197 b3918 b1206 b4209   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.546958 (mmol/gDw/h)
  Minimum Production Rate : 0.288604 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 16.964090
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.971457
  EX_pi_e : 0.816203
  EX_so4_e : 0.137735
  EX_k_e : 0.106762
  EX_fe3_e : 0.008785
  EX_mg2_e : 0.004745
  EX_ca2_e : 0.002847
  EX_cl_e : 0.002847
  EX_cu2_e : 0.000388
  EX_mn2_e : 0.000378
  EX_zn2_e : 0.000187
  EX_ni2_e : 0.000177
  EX_cobalt2_e : 0.000014

Product: (mmol/gDw/h)
  EX_h2o_e : 40.276191
  EX_co2_e : 21.884171
  EX_h_e : 6.662330
  EX_succ_e : 0.570364
  EX_ura_e : 0.387874
  Auxiliary production reaction : 0.288604
  DM_5drib_c : 0.000123
  DM_4crsol_c : 0.000122

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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