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 (28 of 73: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b3399 b1241 b0351 b4069 b2744 b2297 b2458 b0160 b3616 b3589 b1623 b3665 b0675 b2361 b0261 b4381 b2406 b0112 b3654 b3714 b3664 b0114 b0529 b2492 b0904   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.514944 (mmol/gDw/h)
  Minimum Production Rate : 0.973978 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 21.136330
  EX_nh4_e : 10.431236
  EX_glc__D_e : 10.000000
  EX_pi_e : 2.444673
  EX_so4_e : 0.129673
  EX_k_e : 0.100513
  EX_fe2_e : 0.008271
  EX_mg2_e : 0.004467
  EX_cl_e : 0.002680
  EX_ca2_e : 0.002680
  EX_cu2_e : 0.000365
  EX_mn2_e : 0.000356
  EX_zn2_e : 0.000176
  EX_ni2_e : 0.000166
  EX_cobalt2_e : 0.000013

Product: (mmol/gDw/h)
  EX_h2o_e : 47.034212
  EX_co2_e : 19.800286
  EX_h_e : 9.393441
  EX_ac_e : 1.740000
  Auxiliary production reaction : 0.973978
  DM_5drib_c : 0.000116
  DM_4crsol_c : 0.000115

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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