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 : glyclt_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (40 of 83: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 28
  Gene deletion: b4467 b1478 b3942 b1732 b1241 b0351 b3844 b1004 b3713 b1109 b0046 b3236 b3551 b1602 b0507 b4219 b1832 b1778 b2975 b3603 b0755 b3612 b0529 b1380 b1710 b2480 b0606 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.621205 (mmol/gDw/h)
  Minimum Production Rate : 0.057547 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 33.090385
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.708966
  EX_pi_e : 0.599218
  EX_so4_e : 0.156432
  EX_k_e : 0.121255
  EX_fe2_e : 0.009977
  EX_mg2_e : 0.005389
  EX_cl_e : 0.003233
  EX_ca2_e : 0.003233
  EX_cu2_e : 0.000440
  EX_mn2_e : 0.000429
  EX_zn2_e : 0.000212
  EX_ni2_e : 0.000201
  EX_cobalt2_e : 0.000016

Product: (mmol/gDw/h)
  EX_h2o_e : 50.791594
  EX_co2_e : 34.387277
  EX_h_e : 5.765431
  Auxiliary production reaction : 0.057547
  DM_5drib_c : 0.000140
  DM_4crsol_c : 0.000139

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
Contact