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 : dgmp_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (58 of 84: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 25
  Gene deletion: b4467 b3399 b2744 b0871 b2925 b2097 b2926 b1004 b3713 b1109 b0046 b3236 b0517 b2690 b0505 b3945 b1602 b4381 b0511 b0114 b0529 b2492 b0904 b1380 b2285   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.373568 (mmol/gDw/h)
  Minimum Production Rate : 0.060223 (mmol/gDw/h)

 Substrate: (mmol/gDw/h)
  EX_o2_e : 30.215908
  EX_glc__D_e : 10.000000
  EX_nh4_e : 4.415715
  EX_pi_e : 0.420569
  EX_so4_e : 0.094072
  EX_k_e : 0.072918
  EX_fe2_e : 0.006000
  EX_mg2_e : 0.003241
  EX_ca2_e : 0.001944
  EX_cl_e : 0.001944
  EX_cu2_e : 0.000265
  EX_mn2_e : 0.000258
  EX_zn2_e : 0.000127
  EX_ni2_e : 0.000121

Product: (mmol/gDw/h)
  EX_h2o_e : 44.202657
  EX_co2_e : 28.170096
  EX_h_e : 9.078471
  EX_pyr_e : 5.264767
  Auxiliary production reaction : 0.060223
  EX_xan_e : 0.020024
  DM_5drib_c : 0.000084
  DM_4crsol_c : 0.000083

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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