1
|
Cialiè Rosso M, Stilo F, Squara S, Liberto E, Mai S, Mele C, Marzullo P, Aimaretti G, Reichenbach SE, Collino M, Bicchi C, Cordero C. Exploring extra dimensions to capture saliva metabolite fingerprints from metabolically healthy and unhealthy obese patients by comprehensive two-dimensional gas chromatography featuring Tandem Ionization mass spectrometry. Anal Bioanal Chem 2020; 413:403-418. [PMID: 33140127 PMCID: PMC7806578 DOI: 10.1007/s00216-020-03008-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 10/01/2020] [Accepted: 10/13/2020] [Indexed: 02/07/2023]
Abstract
This study examines the information potential of comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry (GC×GC-TOF MS) and variable ionization energy (i.e., Tandem Ionization™) to study changes in saliva metabolic signatures from a small group of obese individuals. The study presents a proof of concept for an effective exploitation of the complementary nature of tandem ionization data. Samples are taken from two sub-populations of severely obese (BMI > 40 kg/m2) patients, named metabolically healthy obese (MHO) and metabolically unhealthy obese (MUO). Untargeted fingerprinting, based on pattern recognition by template matching, is applied on single data streams and on fused data, obtained by combining raw signals from the two ionization energies (12 and 70 eV). Results indicate that at lower energy (i.e., 12 eV), the total signal intensity is one order of magnitude lower compared to the reference signal at 70 eV, but the ranges of variations for 2D peak responses is larger, extending the dynamic range. Fused data combine benefits from 70 eV and 12 eV resulting in more comprehensive coverage by sample fingerprints. Multivariate statistics, principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA) show quite good patient clustering, with total explained variance by the first two principal components (PCs) that increases from 54% at 70 eV to 59% at 12 eV and up to 71% for fused data. With PLS-DA, discriminant components are highlighted and putatively identified by comparing retention data and 70 eV spectral signatures. Within the most informative analytes, lactose is present in higher relative amount in saliva from MHO patients, whereas N-acetyl-D-glucosamine, urea, glucuronic acid γ-lactone, 2-deoxyribose, N-acetylneuraminic acid methyl ester, and 5-aminovaleric acid are more abundant in MUO patients. Visual feature fingerprinting is combined with pattern recognition algorithms to highlight metabolite variations between composite per-class images obtained by combining raw data from individuals belonging to different classes, i.e., MUO vs. MHO. Graphical abstract![]()
Collapse
Affiliation(s)
- Marta Cialiè Rosso
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Via Pietro Giuria 9, 10125, Torino, Italy
| | - Federico Stilo
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Via Pietro Giuria 9, 10125, Torino, Italy
| | - Simone Squara
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Via Pietro Giuria 9, 10125, Torino, Italy
| | - Erica Liberto
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Via Pietro Giuria 9, 10125, Torino, Italy
| | - Stefania Mai
- Division of General Medicine, IRCCS Istituto Auxologico Italiano Ospedale S. Giuseppe, 28824, Piancavallo, Italy
| | - Chiara Mele
- Division of General Medicine, IRCCS Istituto Auxologico Italiano Ospedale S. Giuseppe, 28824, Piancavallo, Italy.,Department of Translational Medicine, University of Piemonte Orientale, 28100, Novara, Italy
| | - Paolo Marzullo
- Division of General Medicine, IRCCS Istituto Auxologico Italiano Ospedale S. Giuseppe, 28824, Piancavallo, Italy. .,Department of Translational Medicine, University of Piemonte Orientale, 28100, Novara, Italy.
| | - Gianluca Aimaretti
- Department of Translational Medicine, University of Piemonte Orientale, 28100, Novara, Italy
| | - Stephen E Reichenbach
- Computer Science and Engineering Department, University of Nebraska, Lincoln, NE, 68588, USA.,GC Image, LLC, Lincoln, NE, 68508, USA
| | - Massimo Collino
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Via Pietro Giuria 9, 10125, Torino, Italy
| | - Carlo Bicchi
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Via Pietro Giuria 9, 10125, Torino, Italy
| | - Chiara Cordero
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Via Pietro Giuria 9, 10125, Torino, Italy.
| |
Collapse
|