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 : q8_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (61 of 83: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 29
  Gene deletion: b3553 b1478 b1241 b0351 b4069 b3708 b2926 b3844 b1004 b3713 b1109 b0046 b3236 b1033 b0335 b2799 b3945 b1602 b0507 b3915 b0452 b0728 b0529 b1380 b2660 b3546 b0606 b2285 b1011   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.609077 (mmol/gDw/h)
  Minimum Production Rate : 0.002801 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 33.514491
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.577976
  EX_pi_e : 0.587519
  EX_so4_e : 0.153378
  EX_k_e : 0.118888
  EX_fe3_e : 0.009782
  EX_mg2_e : 0.005284
  EX_ca2_e : 0.003170
  EX_cl_e : 0.003170
  EX_cu2_e : 0.000432
  EX_mn2_e : 0.000421
  EX_zn2_e : 0.000208
  EX_ni2_e : 0.000197
  EX_cobalt2_e : 0.000015

Product: (mmol/gDw/h)
  EX_h2o_e : 50.975694
  EX_co2_e : 34.862939
  EX_h_e : 5.606222
  Auxiliary production reaction : 0.002801
  DM_5drib_c : 0.000137
  DM_4crsol_c : 0.000136

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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