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DHMRI scientists validated the use of comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-MS) for metabolite biomarker discovery. Although other laboratories have similar instrumentation, GC x GC-MS tends to be under-used. With the study, DHMRI added the capability to the services of the Analytical Sciences Laboratory (ASL), which encompasses metabolomics, NMR and proteomics.
“We compared two different methods- one is the more common ‘normal’ GC-MS method for the analysis of small molecules,” said Staff Scientist Jason Winnike. “The other is a two dimensional method that allows for much greater separation of compounds and makes the subsequent analysis easier.”
In the study, ASL scientists tested 109 human serum samples with GCxGC-MS compared to the standard approach of chromatography time-of-flight mass spectrometry (GC-MS). Using GCxGC-MS, more than two times as many metabolites were identified. In addition, the GCxGC-MS analysis identified 34 metabolites with statistically significant differences compared to 23 in the GC-MS analysis when compared to controls.
Working with Xiang Zhang, PhD, at the University of Louisville, Kentucky, a specialized software program was developed to streamline the analysis of the GCxGC-MS. “Combining the new software program and the technology that we have on our instrument allowed us to do more elaborate data analysis and data collections, which then increased the resolution and separation,” said ASL Group Leader and NMR Project Leader Kevin Knagge, PhD.
Beyond serum, the GCxGC-MS can profile metabolites in urine or tissue samples as well as plant materials. Currently, a study is underway analyzing metabolites in mouse plasma.
“The GCxGC-MS increases the number of compounds we can see, greatly improving the global profiling that we do,” Knagge said. “We want more metabolomics data for our global metabolomics profiling and for the studies our collaborators bring to us. We want to identify more compounds when we run a study, and this new methodology does that.”
The study was published in the April 2015 edition of the Journal of Proteome Research, in the paper entitled “Comparison of GC-MS and GCxGC-MS in the Analysis of Human Serum Samples for Biomarker Discovery.”