Hierarchical cluster analysis of technical replicates to identify interferents in untargeted mass spectrometry metabolomics.

Hierarchical cluster analysis of technical replicates to identify interferents in untargeted mass spectrometry metabolomics.
Anal Chim Acta. 2018 Aug 27;1021:69-77
Authors: Caesar LK, Kvalheim OM, Cech NB
Abstract
Mass spectral data sets often contain experimental artefacts, and data filtering prior to statistical analysis is crucial to extract reliable information. This is particularly true in untargeted metabolomics analyses, where the analyte(s) of interest are not known a priori. It is often assumed that chemical interferents (i.e. solvent contaminants such as plasticizers) are consistent across samples, and can be removed by background subtraction from blank injections. On the contrary, it is shown here that chemical contaminants may vary in abundance across each injection, potentially leading to their misidentification as relevant sample components. With this metabolomics study, we demonstrate the effectiveness of hierarchical cluster analysis (HCA) of replicate injections (technical replicates) as a methodology to identify chemical interferents and reduce their contaminating contribution to metabolomics models. Pools of metabolites with varying complexity were prepared from the botanical Angelica keiskei Koidzumi and spiked with known metabolites. Each set of pools was analyzed in triplicate and at multiple concentrations using ultraperformance liquid chromatography coupled to mass spectrometry (UPLC-MS). Before filtering, HCA...

Source: Analytica Chimica Acta - April 25, 2018 Category: Chemistry Authors: Caesar LK, Kvalheim OM, Cech NB Tags: Anal Chim Acta Source Type: research