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 : u23ga_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (59 of 81: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b4382 b0474 b2518 b4384 b2744 b1278 b4152 b2779 b2781 b1612 b1611 b4122 b1759 b4374 b4161 b0675 b4138 b4123 b0621 b2406 b2197 b3821 b3918 b1206 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.449492 (mmol/gDw/h)
  Minimum Production Rate : 0.237397 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 26.283928
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.729382
  EX_pi_e : 0.908376
  EX_so4_e : 0.113191
  EX_k_e : 0.087738
  EX_fe2_e : 0.007219
  EX_mg2_e : 0.003899
  EX_ca2_e : 0.002340
  EX_cl_e : 0.002340
  EX_cu2_e : 0.000319
  EX_mn2_e : 0.000311
  EX_zn2_e : 0.000153
  EX_ni2_e : 0.000145
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_h2o_e : 44.736141
  EX_co2_e : 29.142021
  EX_h_e : 5.467678
  EX_succ_e : 0.468726
  Auxiliary production reaction : 0.237397
  EX_ura_e : 0.081359
  DM_5drib_c : 0.000101
  DM_4crsol_c : 0.000100

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.

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Last updated: 21-Sep-2023
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