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 : amet_c
List of minimal gene deletion strategies (Download)

Gene deletion strategy (43 of 83: See next) for growth-coupled production (at least stoichioemetrically feasible)
  Gene deletion size : 28
  Gene deletion: b3399 b2744 b3708 b3008 b0871 b0160 b1238 b2920 b1982 b2797 b3117 b1814 b4471 b0675 b2361 b0261 b4381 b0452 b0114 b0728 b0886 b2366 b2492 b0904 b2578 b1533 b3927 b3825   (List of alternative genes)
  Computed by: RandTrimGdel [1] (Step 1, Step 2)

When growth rate is maximized,
  Growth Rate : 0.751397 (mmol/gDw/h)
  Minimum Production Rate : 0.149716 (mmol/gDw/h)

Substrate: (mmol/gDw/h)
  EX_o2_e : 25.307528
  EX_glc__D_e : 10.000000
  EX_nh4_e : 9.013320
  EX_pi_e : 0.724802
  EX_so4_e : 0.338933
  EX_k_e : 0.146667
  EX_fe2_e : 0.012068
  EX_mg2_e : 0.006518
  EX_ca2_e : 0.003911
  EX_cl_e : 0.003911
  EX_cu2_e : 0.000533
  EX_mn2_e : 0.000519
  EX_zn2_e : 0.000256
  EX_ni2_e : 0.000243
  EX_cobalt2_e : 0.000019

Product: (mmol/gDw/h)
  EX_h2o_e : 48.849533
  EX_co2_e : 26.911192
  EX_h_e : 7.353283
  Auxiliary production reaction : 0.149716
  DM_5drib_c : 0.000504
  DM_4crsol_c : 0.000168

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.

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Last updated: 21-Sep-2023
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