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 : imacp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (28 of 103: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b3399 b4382 b1241 b0351 b4069 b2502 b4384 b2744 b3115 b1849 b2296 b2926 b3617 b1982 b3665 b0675 b2361 b2291 b0112 b0114 b0529 b2492 b0904 b1511 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.379749 (mmol/gDw/h)
  Minimum Production Rate : 1.456068 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 34.482315
  EX_glc__D_e : 10.000000
  EX_nh4_e : 7.014676
  EX_pi_e : 1.822377
  EX_so4_e : 0.095629
  EX_k_e : 0.074124
  EX_fe2_e : 0.006099
  EX_mg2_e : 0.003294
  EX_cl_e : 0.001977
  EX_ca2_e : 0.001977
  EX_cu2_e : 0.000269
  EX_mn2_e : 0.000262
  EX_zn2_e : 0.000129
  EX_ni2_e : 0.000123

Product: (mmol/gDw/h)
  EX_h2o_e : 53.331133
  EX_co2_e : 34.564035
  EX_h_e : 6.957932
  Auxiliary production reaction : 1.456068
  EX_ac_e : 0.555229
  EX_ade_e : 0.000256
  DM_mththf_c : 0.000170
  DM_5drib_c : 0.000085
  DM_4crsol_c : 0.000085

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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