Monitoring peppermint washout in the breath metabolome by secondary electrospray ionization-high resolution mass spectrometry

Abstract

In this study, a secondary electrospray ionization-high resolution mass spectrometer (SESI-HRMS) system was employed to profile the real-time exhaled metabolome of ten subjects who had ingested a peppermint oil capsule. In total, six time points were sampled during the experiment. Using an untargeted way of profiling breath metabolome, 2333 m/z unique metabolite features were determined in positive mode, and 1322 in negative mode. To benchmark the performance of the SESI-HRMS setup, several additional checks were done, including determination of the technical variation, the biological variation of one subject within three days, the variation within a time point, and the variation across all samples, taking all m/z features into account. Reproducibility was good, with the median technical variation being ∼ 18% and the median variation within biological replicates being ∼ 34%. Both variations were lower than the variation across individuals. Washout profiles of compounds from the peppermint oil, including menthone, limonene, pulegone, menthol and menthofuran were determined in all subjects. Metabolites of the peppermint oil were also determined in breath, for example, cis/trans-carveol, perillic acid and menthol glucuronide. Butyric acid was found to be the major metabolite that reduce the uptake rate of limonene. Pathways related to limonene metabolism were examined, and meaningful pathways were identified from breath metabolomics data acquired by SESI using an untargeted analysis.

Non-invasive monitoring of microbiota and host metabolism using Secondary electrospray ionization-Mass spectrometry

“…SESI sources are commercially available and can be interfaced with commercial high-resolution mass spectrometers [27, 28, 56]. The data generated from SESI-MS is compatible with standard software for direct-injection MS-based metabolomics [57, 58], and online MS2 fragmentation for compound identification can be performed [59, 60]. Development is still needed for collecting and processing time-series data, since most current MS-based metabolomics datasets have low time-resolution or do not consider time-dependent changes at all.…”

Breath Biomarkers in Diagnostic Applications

“…In short, measuring the washout curves of the specified compounds in exhaled breath over a defined timeframe allow for mean washout times to be calculated for any one sampling and/or analytical approach, allowing for comparison with other datasets. The consortium of participating research laboratories currently numbers 16 from seven countries, with the initial pilot studies comprising 1200 breath samples collected from 200 participants, and with analyses performed using GC-MS [ 263 , 264 ], secondary electrospray ionisation mass spectrometry (SESI-MS) [ 264 , 265 ], as well as PTR-MS and selected ion flow tube-mass spectrometry (SIFT-MS) [ 266 ], and with the publication of datasets from other approaches, such as GC-IMS, pending. Although the comprehensive datasets from these feasibility studies have highlighted the necessity to improve and refine the experimental protocol, the approach taken represents a first concerted effort within the broader breath analysis community to establish a method to allow for quality assurance checks of breath data.…”

The Variability of Volatile Organic Compounds in Clinical Environments

“…Failure to adequately address this factor may confound breathomic biomarker discovery and breath-testing activity 10,11. Variability in breath biochemistry derives from: environmental contaminants; genetics; diet and lifestyle; diurnal changes in metabolism; endocrine cycles; medication; emotional/ psychological states; and, disease progression, see Figure 1. Environmental VOC exposure from inhalation, trans-dermal absorption or ingestion may result in elevated exhaled concentrations of VOC, and/or metabolic/catabolic products not originally in the environment 12 . Further, endogenous VOC, and disease markers may also be obscured, consequently, the VOC exposome generates a risk of false-attribution leading to breathtesting outcomes that are difficult to reproduce or translate into clinical practice.…”