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 : 2agpg141_p
List of minimal gene deletion strategies (Download)

Gene deletion strategy (51 of 53: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 36
  Gene deletion: b2242 b3553 b2744 b3614 b0910 b2781 b1004 b3713 b1109 b0046 b3236 b1612 b1611 b4122 b1759 b1033 b4374 b0675 b1415 b4014 b2976 b4138 b4123 b0621 b4381 b2406 b2197 b2835 b3028 b3918 b4042 b0494 b1206 b2285 b3893 b1474   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.512526 (mmol/gDw/h)
  Minimum Production Rate : 0.270688 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 993.757336
  EX_o2_e : 277.914896
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.262149
  EX_pi_e : 0.765073
  EX_so4_e : 0.129064
  EX_k_e : 0.100041
  EX_mg2_e : 0.004446
  EX_ca2_e : 0.002668
  EX_cl_e : 0.002668
  EX_cu2_e : 0.000363
  EX_mn2_e : 0.000354
  EX_zn2_e : 0.000175
  EX_ni2_e : 0.000166
  EX_cobalt2_e : 0.000013

Product: (mmol/gDw/h)
  EX_fe3_e : 999.991768
  EX_h2o_e : 546.381144
  EX_co2_e : 29.957753
  EX_succ_e : 0.534458
  EX_ura_e : 0.363457
  Auxiliary production reaction : 0.270688
  DM_5drib_c : 0.000115
  DM_4crsol_c : 0.000114

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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