Presentation Profile

A wide array of analytical instrumentation exist to perform quantitative and qualitative analysis on complex mixtures. The choice of chemical analysis tool, in conjunction with appropriate sample preparation, allows the lens to be focused on a particular sample dimension. Loosely, different sample dimensions can be equated to different classes of analytes contained in a sample. While, we ultimately will likely use very different strategies to characterize e.g. fatty acids vs. proteins in a biological sample, there is potentially value in monitoring each of these analyte classes for correlations with physiological changes that may results as part of a disease or some other abnormality. In fact, if one were trying to classify samples that were normal vs. abnormal, it could be argued that, while the monitoring of one sample dimension might be more diagnostic than another, monitoring and combining data from multiple sample dimensions would like provide additional information to aid the classification. This concept of chemical multi-fingerprinting (CMF) could ultimately help draw lines between different sample

classifications, where they were previously difficult to discern. We are currently working to define useful strategies for the combination of multiple analytical techniques for CMF of various sample types. This includes the development of highly featured targeted and non-targeted methods using: Headspace – solid phase microextraction (Arrow) – gas chromatography with parallel vacuum ultraviolet spectroscopy and tandem mass spectrometry detection (HS-SPME-GC-VUV/MS); liquid chromatography – triple quadrupole and quadrupole – time-of-flight – mass spectrometry (LC-QQQ-MS and LC-QTOF-MS); and on-line supercritical fluid extraction – supercritical fluid chromatography – mass spectrometry (SFE-SFC- MS) with fraction collection capabilities. Generally, the strategy is to use untargeted analytical strategies in order to identify the most powerful discriminating features in a particular sample dimension; then, a targeted method can be developed for routine measurement and screening. While a full workflow is still being delineated, data exhibiting the potential power of a CMF strategy has been collected for some complex systems, such as for differentiating craft beers and for classifying pathogenic bacteria exposed to different stressors.