Integrating ion mobility spectrometry into MS-based exposome measurements Perspective
Figure 1. The ‘omes’ measured in exposome studies. The genome and transcriptome are comprised of DNA and RNA, respectively, which are polymers of four defined nucleotides. Similarly, proteins are polymers composed of 20 defined amino acids. In contrast, the metabolome and related small molecule ‘omes’ are comprised of molecules with much greater chemical diversity.
have been optimized to provide accurate identifica- tion and quantification with high sensitivity (i.e., true positive rate) and specificity (i.e., true negative rate) in select matrices [35]. Select examples of targeted analy- sis include a multipanel LC-MS assay to assess expo- sure to pesticides, veterinary drugs and parabens [36], GC-MS analysis of flame retardants after flow-through air sampling [37] and the measurement of estrogens in wastewater samples using GC-MS [38]. The assays used for targeted analysis can be as simple as a glucose colo- rimetric [39] kit to determine the degree of hypergly- cemia [40] associated with the response to exposure to streptozotocin [41], or certain drugs [42], to as complex as chromatography coupled with MS to quantify oxy- genated polycyclic aromatic hydrocarbons [43]. Regard- less of the degree of complexity of the assay, targeted analysis is rooted in the fundamentals of basic ana- lytical chemistry: an analyte is selected for quantifi- cation in a given matrix; experiments are performed to optimize the detection of the analyte by the chosen measurement platform, based on analyses of authen- tic chemical standards; if necessary, experiments are performed to optimize the extraction of the chosen analyte from a given matrix, again using authentic chemical standards and with determination of extrac- tion efficiency; finally, an approach for appropriate
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quantitative data analysis is established, usually based on calibration curves constructed through analyses of authentic chemical standards in the matrix of interest and, ideally using stable isotope-labeled internal stan- dards. The benefits of targeted analysis include the accurate, quantification of the analyte(s) of interest, based on the optimization of all aspects of the analysis method; low limits of quantification (e.g., sufficient to quantify pM levels of chemicals in blood [44]), again due to the optimization of the method parameters; and usually absolute confidence in the identity of the analyte. Caveats of
targeted approaches include the
narrow snapshot of chemistry measured; the level of effort required to fully optimize and validate the ana- lytical pipeline [43,45], and the relatively low analysis t hroughput, depending on the specifics of the method.
Untargeted analysis In contrast to targeted analysis, untargeted analysis does not focus on a specific analyte but instead seeks to comprehensively measure all analytes in a sample. Untargeted analysis of small molecules is increas- ingly popular in metabolomics and environmental studies [46–57]. For general metabolomics studies, NMR spectroscopy [58] and MS [59] have been the primary analytical techniques employed. NMR is
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