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 : ap4a_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (66 of 70: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 41
  Gene deletion: b4467 b1478 b3399 b1241 b0351 b2744 b3708 b3008 b0871 b3844 b1004 b3713 b1109 b0046 b3236 b1779 b1982 b2797 b3117 b1814 b4471 b0675 b2361 b0261 b2799 b3945 b1602 b2913 b4381 b3915 b2366 b0529 b2492 b0904 b3927 b3821 b1380 b0606 b0221 b2285 b1007   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.501055 (mmol/gDw/h)
  Minimum Production Rate : 0.009569 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 38.181020
  EX_glc__D_e : 10.000000
  EX_nh4_e : 5.561722
  EX_pi_e : 0.521595
  EX_so4_e : 0.126176
  EX_k_e : 0.097802
  EX_fe3_e : 0.008047
  EX_mg2_e : 0.004347
  EX_ca2_e : 0.002608
  EX_cl_e : 0.002608
  EX_cu2_e : 0.000355
  EX_mn2_e : 0.000346
  EX_zn2_e : 0.000171
  EX_ni2_e : 0.000162
  EX_cobalt2_e : 0.000013

Product: (mmol/gDw/h)
  EX_h2o_e : 52.778308
  EX_co2_e : 39.169462
  EX_h_e : 4.725881
  EX_hxan_e : 0.013671
  Auxiliary production reaction : 0.009569
  EX_glyclt_e : 0.001844
  DM_5drib_c : 0.000336
  DM_4crsol_c : 0.000112

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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