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 : 5caiz_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (25 of 79: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b3399 b1241 b0351 b4069 b2502 b4384 b2744 b2297 b2458 b2926 b3617 b3236 b1982 b2210 b3665 b4374 b0675 b2361 b2291 b0261 b0112 b0114 b0529 b2492 b0904   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.427137 (mmol/gDw/h)
  Minimum Production Rate : 1.637193 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 25.570092
  EX_glc__D_e : 10.000000
  EX_nh4_e : 9.527009
  EX_pi_e : 2.049212
  EX_so4_e : 0.107562
  EX_k_e : 0.083374
  EX_fe2_e : 0.006860
  EX_mg2_e : 0.003705
  EX_cl_e : 0.002223
  EX_ca2_e : 0.002223
  EX_cu2_e : 0.000303
  EX_mn2_e : 0.000295
  EX_zn2_e : 0.000146
  EX_ni2_e : 0.000138
  EX_cobalt2_e : 0.000011

Product: (mmol/gDw/h)
  EX_h2o_e : 47.587950
  EX_co2_e : 23.206126
  EX_h_e : 12.737761
  EX_ac_e : 2.261897
  Auxiliary production reaction : 1.637193
  EX_ade_e : 0.000478
  DM_5drib_c : 0.000287
  DM_4crsol_c : 0.000095

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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