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Omics Forecasting: Predictive Calculations Permit the Rapid Interpretation of High-Resolution Mass Spectral Data from Complex Mixtures.

Jonathan R CaveEvan ParkerCarlito B LebrillaAndrew L Waterhouse
Published in: Journal of agricultural and food chemistry (2019)
For some complex mixtures, chromatographic techniques are insufficient to separate the large numbers of compounds present. In addition, these mixtures often contain compounds with similar or identical molecular masses and shared fragmentation transitions. Advancements in mass spectrometry have provided more and more detailed molecular profiles with significant increases in resolution. This has led to a capacity to distinguish a very large number of compounds in complex mixtures, providing overwhelming data sets. The approach of calculating molecular formulas from a mass list has become more and more problematic as the number of signals has increased exponentially, to the point that it has become impossible to manually interpret the thousands of mass signals. The current approach is to calculate a list of possible formulas that fall within a specific mass error of the observed signal. Then, one must look for possible structures that can be derived from each entry on the list of formulas. However, an alternative approach is to anticipate the possible structures of a particular set of compounds, such as red wine pigments, and then compare the ion signals against a predicted list. To that end, starting with known wine pigment types, we have generated a set of expected wine pigment variants based on known derivatives of condensed tannin oligomers, anthocyanins, and fermentation products. After the ability to distinguish compounds by mass spectrometry was accounted for, over 1 million results were generated consisting of known and anticipated wine pigments. A comparison with a small sample of wine phenolic fractions show a large number of matches, suggesting that this approach may be helpful.
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