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 : his__L_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (70 of 76: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 37
  Gene deletion: b4382 b3942 b1732 b4069 b4384 b3708 b3008 b2297 b2458 b2925 b2097 b0030 b2407 b3124 b0517 b1779 b2690 b1982 b2797 b3117 b1814 b4471 b0595 b0261 b3945 b2406 b0112 b0114 b2366 b2492 b0904 b2578 b1533 b3927 b3821 b0514 b3662   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.605739 (mmol/gDw/h)
  Minimum Production Rate : 0.764707 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 26.627028
  EX_glc__D_e : 10.000000
  EX_nh4_e : 8.845511
  EX_pi_e : 0.584299
  EX_so4_e : 0.152537
  EX_k_e : 0.118236
  EX_fe2_e : 0.009729
  EX_mg2_e : 0.005255
  EX_ca2_e : 0.003153
  EX_cl_e : 0.003153
  EX_cu2_e : 0.000429
  EX_mn2_e : 0.000419
  EX_zn2_e : 0.000207
  EX_ni2_e : 0.000196
  EX_cobalt2_e : 0.000015

Product: (mmol/gDw/h)
  EX_h2o_e : 47.756725
  EX_co2_e : 27.150973
  EX_h_e : 9.552394
  EX_ac_e : 1.682197
  Auxiliary production reaction : 0.764707
  EX_alltn_e : 0.002365
  DM_5drib_c : 0.002093
  DM_4crsol_c : 0.001822
  EX_glyc__R_e : 0.000843

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.

Last updated: 21-Sep-2023
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