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How GC-MS Can Solve the Puzzle of Metabolomics

 

Metabolomics Metabolomics presents challenges for both the analytical methods used and the data reduction required to interpret the results. No single analytical technique can be used for complete characterization of the metabolome, and no metabolome has ever been completely characterized. This is where GC-MS comes in...

Despite these challenges, LECO’s GC-MS provides an established method to analyze the primary metabolome, whereas other techniques simply investigate the secondary and tertiary metabolites. One of the principal challenges in metabolomics is the detection and identification of unknowns; you need to know what else is in your sample to successfully characterize it, and our GC-MS solutions give you a clear advantage. Our solutions have the separation, accuracy, resolving power, deconvolution, and speed to characterize the most complex metabolite profiles.

With GC-MS you can:

  • Easily profile primary metabolites
  • Quickly identify components from large libraries
  • Access excellent high performance chromatography

Want to see this separation power in action? Check out our latest application notes, where non-targeted analysis, speed, and deconvolution of GC-MS are demonstrated.

 

Metabolomic Profiling of Corn and Rice Extracts

In this app note, our Pegasus® BT GC-TOFMS was used to analyze the metabolomics profile of corn and rice extracts, which can determine a number of characteristics about these crops and potential ways to improve them. The benchtop GC-TOFMS was optimized for speed and detection of a wide array of metabolites, and powerful software tools were used to acquire, peak find, and quickly annotate the rich, high quality spectral data.

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Analysis of Smoker’s and Non-Smoker’s Urine Using the Pegasus BT 4D

Our latest separation science instrument to enter our lineup, the Pegasus BT 4D, brings a second dimension of separation to your analysis to increase confidence in your analyte identification. In this app note, GCxGC TOFMS was used for the robust identification of compounds in two urine standard reference materials (smoker’s and non-smoker’s urine).

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