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 : ditp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (76 of 82: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 38
  Gene deletion: b4467 b1478 b1241 b4069 b4384 b2297 b2458 b2925 b2097 b2407 b1004 b3713 b1109 b0046 b3236 b1779 b2690 b0207 b3012 b2799 b1602 b2913 b4381 b3915 b0529 b2492 b0904 b1781 b3001 b1380 b0325 b1695 b1771 b1511 b0606 b2285 b1007 b4209   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.378199 (mmol/gDw/h)
  Minimum Production Rate : 0.344951 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 33.414249
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.465601
  EX_pi_e : 1.399668
  EX_so4_e : 0.095238
  EX_k_e : 0.073822
  EX_fe3_e : 0.006074
  EX_mg2_e : 0.003281
  EX_ca2_e : 0.001969
  EX_cl_e : 0.001969
  EX_cu2_e : 0.000268
  EX_mn2_e : 0.000261
  EX_zn2_e : 0.000129
  EX_ni2_e : 0.000122

Product: (mmol/gDw/h)
  EX_h2o_e : 45.652615
  EX_co2_e : 31.181536
  EX_h_e : 9.094037
  EX_glyclt_e : 4.701557
  Auxiliary production reaction : 0.344951
  EX_ac_e : 0.220182
  EX_ade_e : 0.000255
  DM_mththf_c : 0.000169
  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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