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 : glyc_e
List of minimal gene deletion strategies (Download)

Gene deletion strategy (45 of 80: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 28
  Gene deletion: b4467 b0474 b1241 b0351 b3926 b0871 b2779 b2925 b2097 b1004 b3713 b1109 b0046 b3236 b2690 b0477 b2210 b3945 b1602 b2913 b0529 b2492 b0904 b1380 b0606 b0221 b2285 b4209   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.407367 (mmol/gDw/h)
  Minimum Production Rate : 0.109120 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 42.027399
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.399532
  EX_pi_e : 0.392949
  EX_so4_e : 0.102583
  EX_k_e : 0.079515
  EX_mg2_e : 0.003534
  EX_fe2_e : 0.003362
  EX_fe3_e : 0.003181
  EX_ca2_e : 0.002120
  EX_cl_e : 0.002120
  EX_cu2_e : 0.000289
  EX_mn2_e : 0.000281
  EX_zn2_e : 0.000139
  EX_ni2_e : 0.000132
  EX_cobalt2_e : 0.000010

Product: (mmol/gDw/h)
  EX_h2o_e : 53.598818
  EX_co2_e : 42.952084
  EX_h_e : 3.746234
  EX_glyc_e : 0.109120
  DM_5drib_c : 0.000092
  DM_4crsol_c : 0.000091

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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