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 : dgdp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (22 of 41: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 26
  Gene deletion: b3399 b2744 b3708 b3008 b0871 b2925 b2097 b2926 b3236 b2690 b2797 b3117 b1814 b4471 b2210 b2440 b3945 b4381 b2868 b0114 b1539 b2492 b0904 b1533 b3927 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.376704 (mmol/gDw/h)
  Minimum Production Rate : 0.057837 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 30.157663
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.396979
  EX_pi_e : 0.479044
  EX_so4_e : 0.094862
  EX_k_e : 0.073530
  EX_fe2_e : 0.006050
  EX_mg2_e : 0.003268
  EX_ca2_e : 0.001961
  EX_cl_e : 0.001961
  EX_cu2_e : 0.000267
  EX_mn2_e : 0.000260
  EX_zn2_e : 0.000128
  EX_ni2_e : 0.000122

Product: (mmol/gDw/h)
  EX_h2o_e : 44.200287
  EX_co2_e : 28.162796
  EX_h_e : 8.981277
  EX_pyr_e : 5.249198
  Auxiliary production reaction : 0.057837
  EX_xan_e : 0.009857
  DM_5drib_c : 0.000085
  DM_4crsol_c : 0.000084

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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