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 : adpglc_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (56 of 73: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 36
  Gene deletion: b4467 b1478 b1241 b4069 b4384 b2297 b2458 b0030 b2407 b3844 b1004 b3713 b1109 b0046 b3236 b1779 b3665 b0411 b2799 b3945 b1602 b0153 b2913 b4381 b3654 b3714 b3664 b0529 b2492 b0904 b0591 b1380 b1511 b0606 b2285 b1009   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.363572 (mmol/gDw/h)
  Minimum Production Rate : 0.572304 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 993.512766
  EX_o2_e : 284.331200
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.788067
  EX_pi_e : 1.495312
  EX_so4_e : 0.091555
  EX_k_e : 0.070967
  EX_mg2_e : 0.003154
  EX_ca2_e : 0.001892
  EX_cl_e : 0.001892
  EX_cu2_e : 0.000258
  EX_mn2_e : 0.000251
  EX_zn2_e : 0.000124
  EX_ni2_e : 0.000117

Product: (mmol/gDw/h)
  EX_fe3_e : 999.994161
  EX_h2o_e : 550.681953
  EX_co2_e : 33.071685
  EX_glyclt_e : 1.212171
  Auxiliary production reaction : 0.572304
  EX_ac_e : 0.211667
  DM_mththf_c : 0.000163
  DM_5drib_c : 0.000082
  DM_4crsol_c : 0.000081

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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