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 : ppa_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (3 of 5: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 29
  Gene deletion: b4467 b1478 b1241 b0351 b4069 b3708 b3844 b1004 b3713 b1109 b0046 b3236 b1779 b0937 b4015 b1701 b1805 b0335 b2799 b3945 b1602 b2913 b0728 b0529 b1380 b0606 b0221 b2285 b1011   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.578050 (mmol/gDw/h)
  Minimum Production Rate : 0.025910 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 34.949463
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.242886
  EX_pi_e : 0.557590
  EX_so4_e : 0.145564
  EX_k_e : 0.112831
  EX_fe2_e : 0.009284
  EX_mg2_e : 0.005015
  EX_ca2_e : 0.003009
  EX_cl_e : 0.003009
  EX_cu2_e : 0.000410
  EX_mn2_e : 0.000399
  EX_zn2_e : 0.000197
  EX_ni2_e : 0.000187
  EX_cobalt2_e : 0.000014

Product: (mmol/gDw/h)
  EX_h2o_e : 51.460680
  EX_co2_e : 36.195988
  EX_h_e : 5.337261
  Auxiliary production reaction : 0.025910
  DM_5drib_c : 0.000130
  DM_4crsol_c : 0.000129

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