Comprehensive two-dimensional gas chromatography coupled with time of flight mass spectrometry featuring tandem ionization: Challenges and opportunities for accurate fingerprinting studies.

Comprehensive two-dimensional gas chromatography Fused data streams Tandem ionization Template matching UT fingerprinting

Journal

Journal of chromatography. A
ISSN: 1873-3778
Titre abrégé: J Chromatogr A
Pays: Netherlands
ID NLM: 9318488

Informations de publication

Date de publication:
19 Jul 2019
Historique:
received: 27 12 2018
revised: 14 03 2019
accepted: 15 03 2019
pubmed: 30 3 2019
medline: 5 6 2019
entrez: 30 3 2019
Statut: ppublish

Résumé

The capture of volatile patterns from food is a fingerprinting that opens access to a high level of information related to functional variables (origin, processing, shelf-life etc.) and their impact on sample composition and quality. When the focus is on food volatilome, comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry (GC×GC-TOF MS) is undoubtedly the most effective technique to obtain a highly representative fingerprinting. A recently patented ion source, featuring variable-energy EI, when operated at low energies (10 eV, 12 eV, 14 eV), claims enhanced intensity of structure-indicating ions while minimizing the inherent loss of sensitivity due to low EI energies. The spectral acquisition is done by multiplexing between two ionization energies and generates tandem data streams in a single run. This study explores the potentials of combined untargeted/targeted (UT) fingerprinting with tandem signals to study the complex volatile metabolome of high quality cocoa. The quality of the spectra at 70 eV is confirmed by similarity match factors above a fixed threshold (950) while spectral differences between hard (70 eV) and soft (12 eV, 14 eV) ionization are computed in terms of spectral similarity and signal-to-noise ratio (SNR). Tandem signals are then processed independently and after fusion in a single stream (summed signal) by the UT fingerprinting work-flow; signal characteristics (SNR, detectable 2D peaks, spectral peak intensities) are then computed and adopted to define the best strategy to discriminate and classify samples. Classification performance, on processed cocoa from four different origins, is validated by cross-comparing results between single ionization channels and fused data streams and considering both targeted and untargeted features. Classification results indicate the potential for superior performances of UT fingerprinting with fused data streams (summed signals), while signal characteristics at low ionization energies not only offer additional elements to better discriminate and/or identify isomeric analytes but also to achieve wider dynamic range of exploration.

Identifiants

pubmed: 30922719
pii: S0021-9673(19)30278-X
doi: 10.1016/j.chroma.2019.03.025
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

132-141

Informations de copyright

Copyright © 2019 Elsevier B.V. All rights reserved.

Auteurs

Chiara Cordero (C)

Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Turin, Italy. Electronic address: chiara.cordero@unito.it.

Alessandro Guglielmetti (A)

Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Turin, Italy.

Carlo Bicchi (C)

Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Turin, Italy.

Erica Liberto (E)

Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Turin, Italy.

Lucie Baroux (L)

Analytical Innovation, Corporate R&D Division, Firmenich SA, Geneva, Switzerland.

Philippe Merle (P)

Analytical Innovation, Corporate R&D Division, Firmenich SA, Geneva, Switzerland.

Qingping Tao (Q)

GC Image LLC, Lincoln, NE, USA.

Stephen E Reichenbach (SE)

GC Image LLC, Lincoln, NE, USA; Computer Science and Engineering Department, University of Nebraska - Lincoln, NE, USA.

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Classifications MeSH