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 : 10fthf_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (7 of 46: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b3399 b1241 b0351 b4069 b2502 b2744 b2297 b2458 b3617 b1982 b0675 b2361 b4014 b0261 b2976 b0507 b4381 b2406 b0112 b2975 b0114 b3603 b0529 b2492 b0904   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.313938 (mmol/gDw/h)
  Minimum Production Rate : 1.186878 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 20.579700
  EX_nh4_e : 11.707218
  EX_glc__D_e : 10.000000
  EX_pi_e : 0.302826
  EX_so4_e : 0.079056
  EX_k_e : 0.061278
  EX_fe2_e : 0.005042
  EX_mg2_e : 0.002723
  EX_ca2_e : 0.001634
  EX_cl_e : 0.001634
  EX_cu2_e : 0.000223
  EX_mn2_e : 0.000217
  EX_zn2_e : 0.000107
  EX_ni2_e : 0.000101

Product: (mmol/gDw/h)
  EX_h2o_e : 48.534290
  EX_co2_e : 17.676236
  EX_h_e : 16.424952
  EX_ac_e : 2.841327
  Auxiliary production reaction : 1.186878
  DM_oxam_c : 0.008566
  DM_5drib_c : 0.000211
  DM_4crsol_c : 0.000070

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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