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 : adn_e
List of minimal gene deletion strategies (Download)

Gene deletion strategy (79 of 82: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 44
  Gene deletion: b3553 b1478 b4269 b0493 b3588 b3003 b3011 b1241 b4384 b0871 b0030 b2407 b3844 b1004 b3713 b1109 b0046 b3236 b1638 b1982 b0477 b4139 b1033 b0261 b2799 b3945 b1602 b0153 b2913 b4381 b1297 b0509 b3125 b0755 b3612 b0529 b2492 b0904 b2954 b3035 b3029 b1380 b2285 b1011   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.479188 (mmol/gDw/h)
  Minimum Production Rate : 0.181858 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_fe2_e : 1000.000000
  EX_h_e : 994.678430
  EX_o2_e : 287.942274
  EX_glc__D_e : 10.000000
  EX_nh4_e : 6.086093
  EX_pi_e : 0.462228
  EX_so4_e : 0.120669
  EX_k_e : 0.093534
  EX_mg2_e : 0.004157
  EX_ca2_e : 0.002494
  EX_cl_e : 0.002494
  EX_cu2_e : 0.000340
  EX_mn2_e : 0.000331
  EX_zn2_e : 0.000163
  EX_ni2_e : 0.000155
  EX_cobalt2_e : 0.000012

Product: (mmol/gDw/h)
  EX_fe3_e : 999.992304
  EX_h2o_e : 553.165189
  EX_co2_e : 38.511343
  EX_adn_e : 0.181858
  EX_ade_e : 0.000322
  DM_5drib_c : 0.000108
  DM_4crsol_c : 0.000107

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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