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Caratti A, Squara S, Bicchi C, Tao Q, Geschwender D, Reichenbach SE, Ferrero F, Borreani G, Cordero C. Augmented visualization by computer vision and chromatographic fingerprinting on comprehensive two-dimensional gas chromatographic patterns: Unraveling diagnostic signatures in food volatilome. J Chromatogr A 2023; 1699:464010. [PMID: 37116300 DOI: 10.1016/j.chroma.2023.464010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 04/18/2023] [Accepted: 04/20/2023] [Indexed: 04/30/2023]
Abstract
Computer Vision is an approach of Artificial Intelligence (AI) that conceptually enables "computers and systems to derive useful information from digital images" giving access to higher-level information and "take actions or make recommendations based on that information". Comprehensive two-dimensional chromatography gives access to highly detailed, accurate, yet unstructured information on the sample's chemical composition, and makes it possible to exploit the AI concepts at the data processing level (e.g., by Computer Vision) to rationalize raw data explorations. The goal is the understanding of the biological phenomena interrelated to a specific/diagnostic chemical signature. This study introduces a novel workflow for Computer Vision based on pattern recognition algorithms (i.e., combined untargeted and targeted UT fingerprinting) which includes the generation of composite Class Images for representative samples' classes, their effective re-alignment and registration against a comprehensive feature template followed by Augmented Visualization by comparative visual analysis. As an illustrative application, a sample set originated from a Research Project on artisanal butter (from raw sweet cream to ripened butter) is explored, capturing the evolution of volatile components along the production chain and the impact of different microbial cultures on the finished product volatilome. The workflow has significant advantages compared to the classical one-step pairwise comparison process given the ability to realign and pairwise compare both targeted and untargeted chromatographic features belonging to Class Images resembling chemical patterns from many different samples with intrinsic biological variability.
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Affiliation(s)
- Andrea Caratti
- Dipartimento di Scienza e Tecnologia del Farmaco, Università di Torino, Via Pietro Giuria 9, Turin I-10125, Italy
| | - Simone Squara
- Dipartimento di Scienza e Tecnologia del Farmaco, Università di Torino, Via Pietro Giuria 9, Turin I-10125, Italy
| | - Carlo Bicchi
- Dipartimento di Scienza e Tecnologia del Farmaco, Università di Torino, Via Pietro Giuria 9, Turin I-10125, Italy
| | | | | | - Stephen E Reichenbach
- GC Image LLC, Lincoln, NE, USA; Computer Science and Engineering Department, University of Nebraska - Lincoln, Lincoln, NE, USA
| | - Francesco Ferrero
- Department of Agricultural, Forestry and Food Sciences, Università di Torino, Grugliasco TO, Italy
| | - Giorgio Borreani
- Department of Agricultural, Forestry and Food Sciences, Università di Torino, Grugliasco TO, Italy
| | - Chiara Cordero
- Dipartimento di Scienza e Tecnologia del Farmaco, Università di Torino, Via Pietro Giuria 9, Turin I-10125, Italy.
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2
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Squara S, Manig F, Henle T, Hellwig M, Caratti A, Bicchi C, Reichenbach SE, Tao Q, Collino M, Cordero C. Extending the breadth of saliva metabolome fingerprinting by smart template strategies and effective pattern realignment on comprehensive two-dimensional gas chromatographic data. Anal Bioanal Chem 2023; 415:2493-2509. [PMID: 36631574 PMCID: PMC10149478 DOI: 10.1007/s00216-023-04516-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 12/16/2022] [Accepted: 01/03/2023] [Indexed: 01/13/2023]
Abstract
Comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC × GC-TOFMS) is one the most powerful analytical platforms for chemical investigations of complex biological samples. It produces large datasets that are rich in information, but highly complex, and its consistency may be affected by random systemic fluctuations and/or changes in the experimental parameters. This study details the optimization of a data processing strategy that compensates for severe 2D pattern misalignments and detector response fluctuations for saliva samples analyzed across 2 years. The strategy was trained on two batches: one with samples from healthy subjects who had undergone dietary intervention with high/low-Maillard reaction products (dataset A), and the second from healthy/unhealthy obese individuals (dataset B). The combined untargeted and targeted pattern recognition algorithm (i.e., UT fingerprinting) was tuned for key process parameters, the signal-to-noise ratio (S/N), and MS spectrum similarity thresholds, and then tested for the best transform function (global or local, affine or low-degree polynomial) for pattern realignment in the temporal domain. Reliable peak detection achieved its best performance, computed as % of false negative/positive matches, with a S/N threshold of 50 and spectral similarity direct match factor (DMF) of 700. Cross-alignment of bi-dimensional (2D) peaks in the temporal domain was fully effective with a supervised operation including multiple centroids (reference peaks) and a match-and-transform strategy using affine functions. Regarding the performance-derived response fluctuations, the most promising strategy for cross-comparative analysis and data fusion included the mass spectral total useful signal (MSTUS) approach followed by Z-score normalization on the resulting matrix.
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Affiliation(s)
- Simone Squara
- Dipartimento Di Scienza E Tecnologia del Farmaco, Università Degli Studi Di Torino, Via Pietro Giuria 9, 10125, Turin, Italy
| | - Friederike Manig
- Food Chemistry, Technische Universität Dresden, Dresden, Germany
| | - Thomas Henle
- Food Chemistry, Technische Universität Dresden, Dresden, Germany
| | - Michael Hellwig
- Special Food Chemistry, Technische Universität Dresden, Dresden, Germany
| | - Andrea Caratti
- Dipartimento Di Scienza E Tecnologia del Farmaco, Università Degli Studi Di Torino, Via Pietro Giuria 9, 10125, Turin, Italy
| | - Carlo Bicchi
- Dipartimento Di Scienza E Tecnologia del Farmaco, Università Degli Studi Di Torino, Via Pietro Giuria 9, 10125, Turin, Italy
| | - Stephen E Reichenbach
- Computer Science and Engineering Department, University of Nebraska, Lincoln, NE, USA.,GC Image LLC, Lincoln, NE, USA
| | | | - Massimo Collino
- Dipartimento Di Neuroscienze "Rita Levi Montalcini", University of Turin, Turin, Italy.
| | - Chiara Cordero
- Dipartimento Di Scienza E Tecnologia del Farmaco, Università Degli Studi Di Torino, Via Pietro Giuria 9, 10125, Turin, Italy.
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3
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Prebihalo SE, Reaser BC, Gough DV. Multidimensional Gas Chromatography: Benefits and Considerations for Current and Prospective Users. LCGC NORTH AMERICA 2022. [DOI: 10.56530/lcgc.na.zi3478f2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
Abstract
Two-dimensional gas chromatography (GC×GC) offers improved separation power for complex samples containing hundreds to thousands of analytes. However, several considerations must be made to determine whether multidimensional gas chromatography (MDGC) is the logical instrument choice to answer a particular scientific question, including, but not limited to, whether the analysis is targeted or non-targeted, the number of analytes of interest, and the presence of interferences that are coeluted, as well as any potential regulatory or industrial constraints. Currently, MDGC remains daunting for many users because of data complexity and the limited tools commercially available, which are critical for improving the accessibility of MDGC. Herein, we discuss considerations that may assist analysts, laboratory managers, regulatory agents, instrument and software vendors, and those interested in understanding the applicability of 2D-GC for the scientific question being investigated.
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Non-targeted analysis of VOCs by HS-SPME-G C/MS coupled with chemometrics as a potential tool for authentication of White Kołuda oat goose. ANNALS OF ANIMAL SCIENCE 2022. [DOI: 10.2478/aoas-2022-0060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Abstract
This study tested the possibility of using non-targeted analysis of volatile organic compounds by headspace solid-phase microextraction-gas chromatography-mass spectrometry coupled with chemometrics as a potential tool for differentiating leg meat of oat- and wheat-fed (ad libitum) White Kołuda geese. Thirty-six classification models were obtained for which the correct classification rate and classification accuracy for oatfed and wheat-fed geese were calculated based on a seven-fold cross-validation. Generally, the most advantageous method of the sample preparation was the high-temperature heat treatment version, whereas the highest correct classification rate was obtained when the chemometric analysis was carried out on the female, then male, and finally male + female variant of group comparisons (P<0.01). Furthermore, log-transformation appeared to be a slightly better data preprocessing technique in comparison to systematic ratio normalization. The obtained classification models can potentially differentiate the meat of oat-fattened from wheat-fattened White Kołuda geese.
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Shah NH, Noe MR, Agnew-Heard KA, Pithawalla YB, Gardner WP, Chakraborty S, McCutcheon N, Grisevich H, Hurst TJ, Morton MJ, Melvin MS, Miller IV JH. Non-Targeted Analysis Using Gas Chromatography-Mass Spectrometry for Evaluation of Chemical Composition of E-Vapor Products. Front Chem 2021; 9:742854. [PMID: 34660534 PMCID: PMC8511636 DOI: 10.3389/fchem.2021.742854] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 08/26/2021] [Indexed: 11/17/2022] Open
Abstract
The Premarket Tobacco Product Applications (PMTA) guidance issued by the Food and Drug Administration for electronic nicotine delivery systems (ENDSs) recommends that in addition to reporting harmful and potentially harmful constituents (HPHCs), manufacturers should evaluate these products for other chemicals that could form during use and over time. Although e-vapor product aerosols are considerably less complex than mainstream smoke from cigarettes and heated tobacco product (HTP) aerosols, there are challenges with performing a comprehensive chemical characterization. Some of these challenges include the complexity of the e-liquid chemical compositions, the variety of flavors used, and the aerosol collection efficiency of volatile and semi-volatile compounds generated from aerosols. In this study, a non-targeted analysis method was developed using gas chromatography-mass spectrometry (GC-MS) that allows evaluation of volatile and semi-volatile compounds in e-liquids and aerosols of e-vapor products. The method employed an automated data analysis workflow using Agilent MassHunter Unknowns Analysis software for mass spectral deconvolution, peak detection, and library searching and reporting. The automated process ensured data integrity and consistency of compound identification with >99% of known compounds being identified using an in-house custom mass spectral library. The custom library was created to aid in compound identifications and includes over 1,100 unique mass spectral entries, of which 600 have been confirmed from reference standard comparisons. The method validation included accuracy, precision, repeatability, limit of detection (LOD), and selectivity. The validation also demonstrated that this semi-quantitative method provides estimated concentrations with an accuracy ranging between 0.5- and 2.0-fold as compared to the actual values. The LOD threshold of 0.7 ppm was established based on instrument sensitivity and accuracy of the compounds identified. To demonstrate the application of this method, we share results from the comprehensive chemical profile of e-liquids and aerosols collected from a marketed e-vapor product. Applying the data processing workflow developed here, 46 compounds were detected in the e-liquid formulation and 55 compounds in the aerosol sample. More than 50% of compounds reported have been confirmed with reference standards. The profiling approach described in this publication is applicable to evaluating volatile and semi-volatile compounds in e-vapor products.
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Affiliation(s)
- Niti H. Shah
- Center for Research and Technology, Altria Client Services LLC, Richmond, VA, United States
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6
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Stilo F, Liberto E, Reichenbach SE, Tao Q, Bicchi C, Cordero C. Exploring the Extra-Virgin Olive Oil Volatilome by Adding Extra Dimensions to Comprehensive Two-Dimensional Gas Chromatography and Time-of-Flight Mass Spectrometry Featuring Tandem Ionization: Validation of Ripening Markers in Headspace Linearity Conditions. J AOAC Int 2021; 104:274-287. [PMID: 34020455 DOI: 10.1093/jaoacint/qsaa095] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 06/29/2020] [Accepted: 06/29/2020] [Indexed: 01/01/2023]
Abstract
BACKGROUND Comprehensive two-dimensional gas chromatography (GC×GC) combined with time-of-flight (TOF) MS is the most informative analytical approach for chemical characterization of the complex food volatilome. Key analytical features include separation power and resolution enhancement, improved sensitivity, and structured separation patterns from chemically correlated analytes. OBJECTIVE In this study, we explore the complex extra-virgin olive oil volatilome by combining headspace (HS) solid-phase microextraction (SPME), applied under HS linearity conditions to GC×GC-TOF MS and featuring hard and soft ionization in tandem. METHOD Multiple analytical dimensions are combined in a single run and evaluated in terms of chemical dimensionality, method absolute and relative sensitivity, identification reliability provided by spectral signatures acquired at 70 and 12 eV, and dynamic and linear range of response provided by soft ionization. RESULTS Method effectiveness is validated on a sample set of oils from Picual olives at different ripening stages. Ripening markers [3,4-diethyl-1,5-hexadiene (RS/SR), 3,4-diethyl-1,5-hexadiene (meso), (5Z)-3-ethyl-1,5-octadiene, (5E)-3-ethyl-1,5-octadiene, (E, Z)-3,7-decadiene and (E, E)-3,7-decadiene, (Z)-2-hexenal, (Z)-3-hexenal and (Z)-3-hexenal, (E)-2-pentenal, (Z)-2-pentenal, 1-pentanol, 1-penten-3-ol, 3-pentanone, and 1-penten-3-one] and quality indexes [(Z)-3-hexenal/nonanal, (Z)-3-hexenal/octane, (E)-2-pentenal/nonanal, and (E)-2-pentenal/octane] are confirmed for their validity in HS linearity conditions. CONCLUSIONS For the complex olive oil volatilome, the proposed approach offers concrete advantages for the validation of the informative role of existing analytes while suggesting new potential markers to be studied in larger sample sets. HIGHLIGHTS The accurate fingerprinting of volatiles by HS-SPME operating in HS linearity conditions followed by GC×GC-TOF MS featuring tandem ionization gives the opportunity to improve the quality of analytical data and reliability of results.
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Affiliation(s)
- Federico Stilo
- Università degli Studi di Torino, Dipartimento di Scienza e Tecnologia del Farmaco, Via Pietro Giuria 9, 10125, Torino, Italy
| | - Erica Liberto
- Università degli Studi di Torino, Dipartimento di Scienza e Tecnologia del Farmaco, Via Pietro Giuria 9, 10125, Torino, Italy
| | - Stephen E Reichenbach
- GC Image LLC, 201 N 8th Street Unit 420, Lincoln, NE 68508, USA.,University of Nebraska-Lincoln, Computer Science and Engineering Department, 256 Avery Hall, Lincoln, NE 68588, USA
| | - Qingping Tao
- GC Image LLC, 201 N 8th Street Unit 420, Lincoln, NE 68508, USA
| | - Carlo Bicchi
- Università degli Studi di Torino, Dipartimento di Scienza e Tecnologia del Farmaco, Via Pietro Giuria 9, 10125, Torino, Italy
| | - Chiara Cordero
- Università degli Studi di Torino, Dipartimento di Scienza e Tecnologia del Farmaco, Via Pietro Giuria 9, 10125, Torino, Italy
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7
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Favela KA, Hartnett MJ, Janssen JA, Vickers DW, Schaub AJ, Spidle HA, Pickens KS. Nontargeted Analysis of Face Masks: Comparison of Manual Curation to Automated GCxGC Processing Tools. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2021; 32:860-871. [PMID: 33395529 DOI: 10.1021/jasms.0c00318] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Masks constructed of a variety of materials are in widespread use due to the COVID-19 pandemic, and people are exposed to chemicals inherent in the masks through inhalation. This work aims to survey commonly available mask materials to provide an overview of potential exposure. A total of 19 mask materials were analyzed using a nontargeted analysis two-dimensional gas chromatography (GCxGC)-mass spectrometric (MS) workflow. Traditionally, there has been a lack of GCxGC-MS automated high-throughput screening methods, resulting in trade-offs with throughput and thoroughness. This work addresses the gap by introducing new machine learning software tools for high-throughput screening (Floodlight) and subsequent pattern analysis (Searchlight). A recursive workflow for chemical prioritization suitable for both manual curation and machine learning is introduced as a means of controlling the level of effort and equalizing sample loading while retaining key chemical signatures. Manual curation and machine learning were comparable with the mask materials clustering into three groups. The majority of the chemical signatures could be characterized by chemical class in seven categories: organophosphorus, long chain amides, polyethylene terephthalate oligomers, n-alkanes, olefins, branched alkanes and long-chain organic acids, alcohols, and aldehydes. The olefin, branched alkane, and organophosphorus components were primary contributors to clustering, with the other chemical classes having a significant degree of heterogeneity within the three clusters. Machine learning provided a means of rapidly extracting the key signatures of interest in agreement with the more traditional time-consuming and tedious manual curation process. Some identified signatures associated with plastics and flame retardants are potential toxins, warranting future study to understand the mask exposure route and potential health effects.
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Affiliation(s)
- Kristin A Favela
- Southwest Research Institute, Chemistry and Chemical Engineering, 6220 Culebra Road, San Antonio, Texas 78228, United States
| | - Michael J Hartnett
- Southwest Research Institute, Intelligent Systems, 6220 Culebra Road, San Antonio, Texas 78228, United States
| | - Jake A Janssen
- Southwest Research Institute, Intelligent Systems, 6220 Culebra Road, San Antonio, Texas 78228, United States
| | - David W Vickers
- Southwest Research Institute, Intelligent Systems, 6220 Culebra Road, San Antonio, Texas 78228, United States
| | - Andrew J Schaub
- Southwest Research Institute, Intelligent Systems, 6220 Culebra Road, San Antonio, Texas 78228, United States
| | - Heath A Spidle
- Southwest Research Institute, Intelligent Systems, 6220 Culebra Road, San Antonio, Texas 78228, United States
| | - Keith S Pickens
- Southwest Research Institute, Space Science and Engineering, 6220 Culebra Road, San Antonio, Texas 78228, United States
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8
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Gabetti E, Sgorbini B, Stilo F, Bicchi C, Rubiolo P, Chialva F, Reichenbach SE, Bongiovanni V, Cordero C, Cavallero A. Chemical fingerprinting strategies based on comprehensive two-dimensional gas chromatography combined with gas chromatography-olfactometry to capture the unique signature of Piemonte peppermint essential oil (Mentha x piperita var Italo-Mitcham). J Chromatogr A 2021; 1645:462101. [PMID: 33848659 DOI: 10.1016/j.chroma.2021.462101] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2020] [Revised: 03/18/2021] [Accepted: 03/22/2021] [Indexed: 10/21/2022]
Abstract
Accurate, reliable, and informative mapping of untargeted and targeted components across many samples is here performed by combining off-line GC-Olfactometry (GC-O) and comprehensive two-dimensional gas chromatography (GC×GC) coupled to time-of-flight mass spectrometry with variable ionization energy (TOF MS featuring Tandem Ionization™). In particular, untargeted and targeted (UT) features patterns are processed by chromatographic fingerprinting, giving differential priority to potent odorants' retention-times regions. Distinguishing peppermint essential oil (EO) from Piedmont (Italy - Mentha × piperita L. var. Italo-Mitcham - Menta di Pancalieri EO), with its unique sensory fingerprint (i.e., freshness and long-lasting sweetness), from high-quality peppermint EOs produced in other areas poses a great challenge. Chromatographic UT fingerprinting provided a great chemical dimensionality by mapping more than 350 peak-regions at 70 eV and 135 at 12 eV. From them, 95 components were identified and responses compared to available literature. Then, potent odorants, detected by GC-O using the aroma extraction dilution analysis (AEDA), were tracked over the chromatographic space and tentatively identified. With the highest flavor dilution (FD), 1,8-cineole (eucalyptus, fresh, camphoraceous); menthone (minty, herbaceous); and menthofuran (minty, musty, petroleum-like) were highlighted. Responsible for creamy and coumarinic notes were the diasteroisomers of (3,6)-dimethyl-4,5,6,7-tetrahydrobenzo[b]-furan-2(3H)-one (i.e., menthofurolactones), detected in higher relative abundance in Pancalieri EOs. By prioritizing the investigation of volatiles on higher LogFD retention regions, including 131 untargeted/targeted features, Pancalieri EOs were separately clustered from United States samples. Besides pre-targeted analytes, additional untargeted features were post-processed for identification within marker chemicals. Myrtenyl methyl ether, ethyl 3-methyl butanoate, propyl-2-methylbutanoate, and (E)-2-hexenal were putatively identified. Of the "unknown - knowns" with diagnostic roles, all metadata were collected including low energy spectra at 12 eV, which were found to be highly complementary to 70 eV spectra.
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Affiliation(s)
| | - Barbara Sgorbini
- University of Turin, Dipartimento di Scienza e Tecnologia del Farmaco Turin, Italy
| | - Federico Stilo
- University of Turin, Dipartimento di Scienza e Tecnologia del Farmaco Turin, Italy
| | - Carlo Bicchi
- University of Turin, Dipartimento di Scienza e Tecnologia del Farmaco Turin, Italy
| | - Patrizia Rubiolo
- University of Turin, Dipartimento di Scienza e Tecnologia del Farmaco Turin, Italy
| | | | - Stephen E Reichenbach
- Computer Science and Engineering Department, University of Nebraska - Lincoln, Lincoln, Nebraska, USA; GC Image, LLC, Lincoln, Nebraska, USA
| | | | - Chiara Cordero
- University of Turin, Dipartimento di Scienza e Tecnologia del Farmaco Turin, Italy.
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Stilo F, Bicchi C, Jimenez-Carvelo AM, Cuadros-Rodriguez L, Reichenbach SE, Cordero C. Chromatographic fingerprinting by comprehensive two-dimensional chromatography: Fundamentals and tools. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2020.116133] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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10
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A unique data analysis framework and open source benchmark data set for the analysis of comprehensive two-dimensional gas chromatography software. J Chromatogr A 2020; 1635:461721. [PMID: 33246680 DOI: 10.1016/j.chroma.2020.461721] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Revised: 11/05/2020] [Accepted: 11/09/2020] [Indexed: 12/28/2022]
Abstract
Comprehensive two-dimensional gas chromatography (GC × GC) is amongst the most powerful separation technologies currently existing. Since its advent in early 1990, it has become an established method which is readily available. However, one of its most challenging aspects, especially in hyphenation with mass spectrometry is the high amount of chemical information it provides for each measurement. The GC × GC community agrees that there, the highest demand for action is found. In response, the number of software packages allowing for in-depth data processing of GC × GC data has risen over the last couple of years. These packages provide sophisticated tools and algorithms allowing for more streamlined data evaluation. However, these tools/algorithms and their respective specific functionalities differ drastically within the available software packages and might result in various levels of findings if not appropriately implemented by the end users. This study focuses on two main objectives. First, to propose a data analysis framework and second to propose an open-source dataset for benchmarking software options and their specificities. Thus, allowing for an unanimous and comprehensive evaluation of GC × GC software. Thereby, the benchmark data includes a set of standard compound measurements and a set of chocolate aroma profiles. On this foundation, eight readily available GC × GC software packages were anonymously investigated for fundamental and advanced functionalities such as retention and detection device derived parameters, revealing differences in the determination of e.g. retention times and mass spectra.
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Prebihalo SE, Ochoa GS, Berrier KL, Skogerboe KJ, Cameron KL, Trump JR, Svoboda SJ, Wickiser JK, Synovec RE. Control-Normalized Fisher Ratio Analysis of Comprehensive Two-Dimensional Gas Chromatography Time-of-Flight Mass Spectrometry Data for Enhanced Biomarker Discovery in a Metabolomic Study of Orthopedic Knee-Ligament Injury. Anal Chem 2020; 92:15526-15533. [PMID: 33171046 DOI: 10.1021/acs.analchem.0c03456] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Sarah E. Prebihalo
- Department of Chemistry, University of Washington, Box 351700, Seattle, Washington 98195, United States
| | - Grant S. Ochoa
- Department of Chemistry, University of Washington, Box 351700, Seattle, Washington 98195, United States
| | - Kelsey L. Berrier
- Department of Chemistry, University of Washington, Box 351700, Seattle, Washington 98195, United States
| | - Kristen J. Skogerboe
- Department of Chemistry, Seattle University, Seattle, Washington 98122, United States
| | - Kenneth L. Cameron
- Keller Army Community Hospital, West Point, New York 10996, United States
| | - Jesse R. Trump
- Keller Army Community Hospital, West Point, New York 10996, United States
| | - Steven J. Svoboda
- Keller Army Community Hospital, West Point, New York 10996, United States
| | | | - Robert E. Synovec
- Department of Chemistry, University of Washington, Box 351700, Seattle, Washington 98195, United States
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12
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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] [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![]()
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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.
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13
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Wilde MJ, Zhao B, Cordell RL, Ibrahim W, Singapuri A, Greening NJ, Brightling CE, Siddiqui S, Monks PS, Free RC. Automating and Extending Comprehensive Two-Dimensional Gas Chromatography Data Processing by Interfacing Open-Source and Commercial Software. Anal Chem 2020; 92:13953-13960. [PMID: 32985172 PMCID: PMC7644112 DOI: 10.1021/acs.analchem.0c02844] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
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Comprehensive
two-dimensional gas chromatography (GC×GC) is
a powerful analytical tool for both nontargeted and targeted analyses.
However, there is a need for more integrated workflows for processing
and managing the resultant high-complexity datasets. End-to-end workflows
for processing GC×GC data are challenging and often require multiple
tools or software to process a single dataset. We describe a new approach,
which uses an existing underutilized interface within commercial software
to integrate free and open-source/external scripts and tools, tailoring
the workflow to the needs of the individual researcher within a single
software environment. To demonstrate the concept, the interface was
successfully used to complete a first-pass alignment on a large-scale
GC×GC metabolomics dataset. The analysis was performed by interfacing
bespoke and published external algorithms within a commercial software
environment to automatically correct the variation in retention times
captured by a routine reference standard. Variation in 1tR and 2tR was reduced on average
from 8 and 16% CV prealignment to less than 1 and 2% post alignment,
respectively. The interface enables automation and creation of new
functions and increases the interconnectivity between chemometric
tools, providing a window for integrating data-processing software
with larger informatics-based data management platforms.
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Affiliation(s)
- Michael J Wilde
- School of Chemistry, University of Leicester, University Road, Leicester LE1 7RH, U.K.,Department of Respiratory Sciences, University of Leicester, University Road, Leicester LE1 7RH, U.K
| | - Bo Zhao
- Leicester NIHR Biomedical Research Centre, Glenfield Hospital, Groby Road, Leicester LE3 9QP, U.K
| | - Rebecca L Cordell
- School of Chemistry, University of Leicester, University Road, Leicester LE1 7RH, U.K
| | - Wadah Ibrahim
- Department of Respiratory Sciences, University of Leicester, University Road, Leicester LE1 7RH, U.K.,Leicester NIHR Biomedical Research Centre, Glenfield Hospital, Groby Road, Leicester LE3 9QP, U.K
| | - Amisha Singapuri
- Department of Respiratory Sciences, University of Leicester, University Road, Leicester LE1 7RH, U.K.,Leicester NIHR Biomedical Research Centre, Glenfield Hospital, Groby Road, Leicester LE3 9QP, U.K
| | - Neil J Greening
- Department of Respiratory Sciences, University of Leicester, University Road, Leicester LE1 7RH, U.K.,Leicester NIHR Biomedical Research Centre, Glenfield Hospital, Groby Road, Leicester LE3 9QP, U.K
| | - Chris E Brightling
- Department of Respiratory Sciences, University of Leicester, University Road, Leicester LE1 7RH, U.K.,Leicester NIHR Biomedical Research Centre, Glenfield Hospital, Groby Road, Leicester LE3 9QP, U.K
| | - Salman Siddiqui
- Department of Respiratory Sciences, University of Leicester, University Road, Leicester LE1 7RH, U.K.,Leicester NIHR Biomedical Research Centre, Glenfield Hospital, Groby Road, Leicester LE3 9QP, U.K
| | - Paul S Monks
- School of Chemistry, University of Leicester, University Road, Leicester LE1 7RH, U.K
| | - Robert C Free
- Leicester NIHR Biomedical Research Centre, Glenfield Hospital, Groby Road, Leicester LE3 9QP, U.K
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14
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Stilo F, Liberto E, Spigolon N, Genova G, Rosso G, Fontana M, Reichenbach SE, Bicchi C, Cordero C. An effective chromatographic fingerprinting workflow based on comprehensive two-dimensional gas chromatography - Mass spectrometry to establish volatiles patterns discriminative of spoiled hazelnuts (Corylus avellana L.). Food Chem 2020; 340:128135. [PMID: 33011466 DOI: 10.1016/j.foodchem.2020.128135] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 09/15/2020] [Accepted: 09/16/2020] [Indexed: 12/28/2022]
Abstract
The volatile fraction of hazelnuts encrypts information about: cultivar/geographical origin, post-harvest treatments, oxidative stability and sensory quality. However, sensory features could be buried under other dominant chemical signatures posing challenges to an effective classification based on pleasant/unpleasant notes. Here a novel workflow that combines Untargeted and Targeted (UT) fingerprinting on comprehensive two-dimensional gas-chromatographic patterns is developed to discriminate spoiled hazelnuts from those of acceptable quality. By flash-profiling, six hazelnut classes are defined: Mould, Mould-rancid-solvent, Rancid, Rancid-stale, Rancid-solvent, and Uncoded KO. Chromatographic fingerprinting on composite 2D chromatograms from samples belonging to the same class (i.e., composite class-images) enabled effective selection of chemical markers: (a) octanoic acid that guides the sensory classification being positively correlated to mould; (b) ƴ-nonalactone, ƴ-hexalactone, acetone, and 1-nonanol that are decisive to classify OK and rancid samples; (c) heptanoic and hexanoic acids and ƴ-octalactone present in high relative abundance in rancid-solvent and rancid-stale samples.
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Affiliation(s)
- Federico Stilo
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Via Pietro Giuria 9, I-10125 Torino, Italy.
| | - Erica Liberto
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Via Pietro Giuria 9, I-10125 Torino, Italy.
| | - Nicola Spigolon
- Soremartec Italia Srl, Piazzale Ferrero 1, Alba (Cuneo), Italy
| | - Giuseppe Genova
- Soremartec Italia Srl, Piazzale Ferrero 1, Alba (Cuneo), Italy
| | - Ginevra Rosso
- Soremartec Italia Srl, Piazzale Ferrero 1, Alba (Cuneo), Italy
| | - Mauro Fontana
- Soremartec Italia Srl, Piazzale Ferrero 1, Alba (Cuneo), Italy
| | - Stephen E Reichenbach
- University of Nebraska-Lincoln, MS 0115, Lincoln, NE, 68588-0115, USA; GC Image LLC, PO Box 57403, Lincoln, NE 68505-7403, USA.
| | - Carlo Bicchi
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Via Pietro Giuria 9, I-10125 Torino, Italy.
| | - Chiara Cordero
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Via Pietro Giuria 9, I-10125 Torino, Italy.
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15
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Stilo F, Gabetti E, Bicchi C, Carretta A, Peroni D, Reichenbach SE, Cordero C, McCurry J. A step forward in the equivalence between thermal and differential-flow modulated comprehensive two-dimensional gas chromatography methods. J Chromatogr A 2020; 1627:461396. [DOI: 10.1016/j.chroma.2020.461396] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 07/06/2020] [Accepted: 07/07/2020] [Indexed: 12/18/2022]
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16
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Climate and Processing Effects on Tea ( Camellia sinensis L. Kuntze) Metabolome: Accurate Profiling and Fingerprinting by Comprehensive Two-Dimensional Gas Chromatography/Time-of-Flight Mass Spectrometry. Molecules 2020; 25:molecules25102447. [PMID: 32456315 PMCID: PMC7288030 DOI: 10.3390/molecules25102447] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 05/19/2020] [Accepted: 05/22/2020] [Indexed: 11/18/2022] Open
Abstract
This study applied an untargeted–targeted (UT) fingerprinting approach, based on comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOF MS), to assess the effects of rainfall and temperature (both seasonal and elevational) on the tea metabolome. By this strategy, the same compound found in multiple samples need only to be identified once, since chromatograms and mass spectral features are aligned in the data analysis process. Primary and specialized metabolites of leaves from two Chinese provinces, Yunnan (pu′erh) and Fujian (oolong), and a farm in South Carolina (USA, black tea) were studied. UT fingerprinting provided insight into plant metabolism activation/inhibition, taste and trigeminal sensations, and antioxidant properties, not easily attained by other analytical approaches. For example, pu′erh and oolong contained higher relative amounts of amino acids, organic acids, and sugars. Conversely, black tea contained less of all targeted compounds except fructose and glucose, which were more similar to oolong tea. Findings revealed compounds statistically different between spring (pre-monsoon) and summer (monsoon) in pu′erh and oolong teas as well as compounds that exhibited the greatest variability due to seasonal and elevational differences. The UT fingerprinting approach offered unique insights into how differences in growing conditions and commercial processing affect the nutritional benefits and sensory characteristics of tea beverages.
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17
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Sedentariness and Urinary Metabolite Profile in Type 2 Diabetic Patients, a Cross-Sectional Study. Metabolites 2020; 10:metabo10050205. [PMID: 32443532 PMCID: PMC7281751 DOI: 10.3390/metabo10050205] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 05/07/2020] [Accepted: 05/13/2020] [Indexed: 11/17/2022] Open
Abstract
Recent findings indicate a significant association between sedentary (SED)-time and type 2 diabetes mellitus (T2DM). The aim of this study was to investigate whether different levels of SED-time could impact on biochemical and physiological processes occurring in sedentary and physically inactive T2DM patients. In particular, patients from the “Italian Diabetes and Exercise Study (IDES)_2 trial belonging to the first and fourth quartile of SED-time were compared. Urine samples were analyzed by comprehensive two-dimensional gas chromatography (GC × GC) with parallel detection by mass spectrometry and flame ionization detection (GC × 2GC-MS/FID). This platform enables accurate profiling and fingerprinting of urinary metabolites while maximizing the overall information capacity, quantitation reliability, and response linearity. Moreover, using advanced pattern recognition, the fingerprinting process was extended to untargeted and targeted features, revealing diagnostic urinary fingerprints between groups. Quantitative metabolomics was then applied to analytes of relevance for robust comparisons. Increased levels of glycine, L-valine, L-threonine, L-phenylalanine, L-leucine, L-alanine, succinic acid, 2-ketoglutaric acid, xylitol, and ribitol were revealed in samples from less sedentary women. In conclusion, SED-time is associated with changes in urine metabolome signatures. These preliminary results suggest that reducing SED-time could be a strategy to improve the health status of a large proportion of diabetic patients.
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18
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Li X, Luo Y, Jiang X, Zhang H, Zhu F, Hu S, Hou H, Hu Q, Pang Y. Chemical Analysis and Simulated Pyrolysis of Tobacco Heating System 2.2 Compared to Conventional Cigarettes. Nicotine Tob Res 2020; 21:111-118. [PMID: 29319815 DOI: 10.1093/ntr/nty005] [Citation(s) in RCA: 71] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Accepted: 01/06/2018] [Indexed: 01/13/2023]
Abstract
Introduction Tobacco Heating System 2.2 (THS 2.2, marketed as iQOS) is a heat-not-burn (HNB) tobacco product that has been successfully introduced to global markets. Despite its expanding market, few independent and systematic researches into THS 2.2 have been carried out to date. Methods We tested a comprehensive list of total particulate matter (TPM), water, tar, nicotine, propylene glycol, glycerin, carbon monoxide, volatile organic compounds, aromatic amines, hydrogen cyanide, ammonia, N-nitrosamines, phenol, and polycyclic aromatic hydrocarbon under both ISO and HCI regimes. We also simulated pyrolysis of THS 2.2 heating sticks and made comparisons with conventional cigarette tobacco fillers using comprehensive gas chromatography-mass spectrometry (GC × GC-MS) to determine whether the specially designed ingredients help reduce harmful constituents. Results Other than some carbonyls, ammonia, and N-nitrosoanabasine (NAB), the delivered releases from THS 2.2 were at least 80% lower than those from 3R4F. Tar and nicotine remained almost the same as 3R4F. Interestingly, the normalized yield of THS 2.2 to 3R4F under the HCI regime was lower than that under the ISO regime. Conclusions THS 2.2 delivered fewer harmful constituents than the conventional cigarette 3R4F. Simulated pyrolysis results showed that the lower temperature instead of specially designed ingredients contributed to the distinct shift. In particular, if smoking machines are involved to evaluate the HNB products, smoking regimes of heat-not-burn tobacco products should be carefully chosen. Implications To our knowledge, few independent studies of HNB products have been published. In this paper, a comprehensive list of chemical releases was tested systematically and compared to those from 3R4F. Although THS 2.2 generates lower levels of harmful constituents, the nicotine and tar levels were almost identical to 3R4F.The results should be discussed carefully in the future when assessing the dual-use with other conventional cigarettes, nicotine dependence of HNB products, etc. This study also suggests that regulatory agencies should pay attention to the smoking regimes that are adopted to evaluate HNB tobacco products.
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Affiliation(s)
- Xiangyu Li
- Department of Environmental Science and Technology, School of Environment, Tsinghua University, Beijing, China
| | - Yanbo Luo
- Department of Analytical Chemistry, College of Chemistry and Molecular Sciences, Wuhan University, Wuhan, Hubei, China
| | - Xingyi Jiang
- Department of Biotechnology, School of International Education, Henan University of Technology, Zhengzhou, Henan, China
| | - Hongfei Zhang
- Department of Tobacco Chemistry, School Of Food Science and Engineering, Zhengzhou University of Light Industry, Zhengzhou, Henan, China
| | - Fengpeng Zhu
- Department of Tobacco Chemistry, School Of Food Science and Engineering, Zhengzhou University of Light Industry, Zhengzhou, Henan, China
| | - Shaodong Hu
- Department of polymer science and engineer, Sichuan University, Chengdu, Sichuan, China
| | - Hongwei Hou
- Department of Inorganic Chemistry, Chemistry, University of Science and Technology of China, Hefei, Anhui, China
| | - Qingyuan Hu
- Department of Optics, Anhui Institute of Optics and Fine Mechanics, The Chinese Academy of Sciences, Hefei, Anhui, China
| | - Yongqiang Pang
- Department of Analytical Chemistry, Chemistry, University of Science and Technology of China, Hefei, Anhui, China
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19
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20
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Di Giovanni N, Meuwis MA, Louis E, Focant JF. Untargeted Serum Metabolic Profiling by Comprehensive Two-Dimensional Gas Chromatography–High-Resolution Time-of-Flight Mass Spectrometry. J Proteome Res 2019; 19:1013-1028. [DOI: 10.1021/acs.jproteome.9b00535] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Affiliation(s)
- Nicolas Di Giovanni
- Department of Chemistry, Organic and Biological Analytical Chemistry Group, Quartier Agora, University of Liège, Allée du Six Août, B6c, B-4000 Liège (Sart Tilman), Belgium
| | - Marie-Alice Meuwis
- GIGA institute, Translational Gastroenterology and CHU de Liège, Hepato-Gastroenterology and Digestive Oncology, Quartier Hôpital, University of Liège, Avenue de l’Hôpital 13, B34-35, B-4000 Liège, Belgium
| | - Edouard Louis
- GIGA institute, Translational Gastroenterology and CHU de Liège, Hepato-Gastroenterology and Digestive Oncology, Quartier Hôpital, University of Liège, Avenue de l’Hôpital 13, B34-35, B-4000 Liège, Belgium
| | - Jean-François Focant
- Department of Chemistry, Organic and Biological Analytical Chemistry Group, Quartier Agora, University of Liège, Allée du Six Août, B6c, B-4000 Liège (Sart Tilman), Belgium
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21
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Rosso MC, Mazzucotelli M, Bicchi C, Charron M, Manini F, Menta R, Fontana M, Reichenbach SE, Cordero C. Adding extra-dimensions to hazelnuts primary metabolome fingerprinting by comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry featuring tandem ionization: Insights on the aroma potential. J Chromatogr A 2019; 1614:460739. [PMID: 31796248 DOI: 10.1016/j.chroma.2019.460739] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 11/22/2019] [Accepted: 11/25/2019] [Indexed: 12/20/2022]
Abstract
The information potential of comprehensive two-dimensional gas chromatography combined with time of flight mass spectrometry (GC × GC-TOFMS) featuring tandem hard (70 eV) and soft (12 eV) electron ionization is here applied to accurately delineate high-quality hazelnuts (Corylus avellana L.) primary metabolome fingerprints. The information provided by tandem signals for untargeted and targeted 2D-peaks is examined and exploited with pattern recognition based on template matching algorithms. EI-MS fragmentation pattern similarity, base-peak m/z values at the two examined energies (i.e., 12 and 70 eV) and response relative sensitivity are adopted to evaluate the complementary nature of signals. As challenging bench test, the hazelnut primary metabolome has a large chemical dimensionality that includes various chemical classes such as mono- and disaccharides, amino acids, low-molecular weight acids, and amines, further complicated by oximation/silylation to obtain volatile derivatives. Tandem ionization provides notable benefits including larger relative ratio of structural informing ions due to limited fragmentation at low energies (12 eV), meaningful spectral dissimilarity between 12 and 70 eV (direct match factor values range 222-783) and, for several analytes, enhanced relative sensitivity at lower energies. The complementary information provided by tandem ionization is exploited by untargeted/targeted (UT) fingerprinting on samples from different cultivars and geographical origins. The responses of 138 UT-peak-regions are explored to delineate informative patterns by univariate and multivariate statistics, providing insights on correlations between known precursors and (key)-aroma compounds and potent odorants. Strong positive correlations between non-volatile precursors and odorants are highlighted with some interesting linear trends for: 3-methylbutanal with isoleucine (R2 0.9284); 2,3-butanedione/2,3-pentanedione with monosaccharides (fructose/glucose derivatives) (R2 0.8543 and 0.8860); 2,5-dimethylpyrazine with alanine (R2 0.8822); and pyrroles (1H-pyrrole, 3-methyl-1H-pyrrole, and 1H-pyrrole-2-carboxaldehyde) with ornithine and alanine derivatives (R2 0.8604). The analytical work-flow provides a solid foundation for a new strategy for hazelnuts quality assessment because aroma potential could be derived from precursors' chemical fingerprints.
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Affiliation(s)
- Marta Cialiè Rosso
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Via Pietro Giuria 9, I-10125 Torino 6707172, Italy
| | - Maria Mazzucotelli
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Via Pietro Giuria 9, I-10125 Torino 6707172, Italy
| | - Carlo Bicchi
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Via Pietro Giuria 9, I-10125 Torino 6707172, Italy
| | | | | | - Roberto Menta
- Soremartec Italia Srl, Ferrero Group, Alba (CN), Italy
| | - Mauro Fontana
- Soremartec Italia Srl, Ferrero Group, Alba (CN), Italy
| | - Stephen E Reichenbach
- Computer Science and Engineering Department, University of Nebraska - Lincoln, NE, USA; GC Image LCC, Lincoln, NE, USA
| | - Chiara Cordero
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Via Pietro Giuria 9, I-10125 Torino 6707172, Italy.
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Morimoto J, Rosso MC, Kfoury N, Bicchi C, Cordero C, Robbat A. Untargeted/Targeted 2D Gas Chromatography/Mass Spectrometry Detection of the Total Volatile Tea Metabolome. Molecules 2019; 24:E3757. [PMID: 31635337 PMCID: PMC6832143 DOI: 10.3390/molecules24203757] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 09/04/2019] [Accepted: 10/15/2019] [Indexed: 01/26/2023] Open
Abstract
Identifying all analytes in a natural product is a daunting challenge, even if fractionated by volatility. In this study, comprehensive two-dimensional gas chromatography/mass spectrometry (GC×GC-MS) was used to investigate relative distribution of volatiles in green, pu-erh tea from leaves collected at two different elevations (1162 m and 1651 m). A total of 317 high and 280 low elevation compounds were detected, many of them known to have sensory and health beneficial properties. The samples were evaluated by two different software. The first, GC Image, used feature-based detection algorithms to identify spectral patterns and peak-regions, leading to tentative identification of 107 compounds. The software produced a composite map illustrating differences in the samples. The second, Ion Analytics, employed spectral deconvolution algorithms to detect target compounds, then subtracted their spectra from the total ion current chromatogram to reveal untargeted compounds. Compound identities were more easily assigned, since chromatogram complexities were reduced. Of the 317 compounds, for example, 34% were positively identified and 42% were tentatively identified, leaving 24% as unknowns. This study demonstrated the targeted/untargeted approach taken simplifies the analysis time for large data sets, leading to a better understanding of the chemistry behind biological phenomena.
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Affiliation(s)
- Joshua Morimoto
- Department of Chemistry, Tufts University, Medford, MA 02155, USA.
| | - Marta Cialiè Rosso
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, 10125 Turin, Italy.
| | - Nicole Kfoury
- Department of Chemistry, Tufts University, Medford, MA 02155, USA.
| | - Carlo Bicchi
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, 10125 Turin, Italy.
| | - Chiara Cordero
- Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, 10125 Turin, Italy.
| | - Albert Robbat
- Department of Chemistry, Tufts University, Medford, MA 02155, USA.
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Highly Informative Fingerprinting of Extra-Virgin Olive Oil Volatiles: The Role of High Concentration-Capacity Sampling in Combination with Comprehensive Two-Dimensional Gas Chromatography. SEPARATIONS 2019. [DOI: 10.3390/separations6030034] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
The study explores the complex volatile fraction of extra-virgin olive oil by combining high concentration-capacity headspace approaches with comprehensive two-dimensional gas chromatography, which is coupled with time of flight mass spectrometry. The static headspace techniques in this study are: (a) Solid-phase microextraction, with multi-polymer coating (SPME- Divinylbenzene/Carboxen/Polydimethylsiloxane), which is taken as the reference technique; (b) headspace sorptive extraction (HSSE) with either a single-material coating (polydimethylsiloxane—PDMS) or a dual-phase coating that combines PDMS/Carbopack and PDMS/EG (ethyleneglycol); (c) monolithic material sorptive extraction (MMSE), using octa-decyl silica combined with graphite carbon (ODS/CB); and dynamic headspace (d) with either PDMS foam, operating in partition mode, or Tenax TA™, operating in adsorption mode. The coverage of both targeted and untargeted 2D-peak-region features, which corresponds to detectable analytes, was examined, while concentration factors (CF) for a selection of informative analytes, including key-odorants and off-odors, and homolog-series relative ratios were calculated and the information capacity was discussed. The results highlighted the differences in concentration capacities, which were mainly caused by polymer-accumulation characteristics (sorptive/adsorptive materials) and its amount. The relative concentration capacity for homologues and potent odorants was also discussed, while headspace linearity and the relative distribution of analytes, as a function of different sampling amounts, was examined. This last point is of particular interest in quantitative studies where accurate data is needed to derive consistent conclusions.
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Comprehensive two-dimensional gas chromatography coupled with time of flight mass spectrometry featuring tandem ionization: Challenges and opportunities for accurate fingerprinting studies. J Chromatogr A 2019; 1597:132-141. [DOI: 10.1016/j.chroma.2019.03.025] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2018] [Revised: 03/14/2019] [Accepted: 03/15/2019] [Indexed: 12/16/2022]
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Reichenbach SE, Zini CA, Nicolli KP, Welke JE, Cordero C, Tao Q. Benchmarking machine learning methods for comprehensive chemical fingerprinting and pattern recognition. J Chromatogr A 2019; 1595:158-167. [DOI: 10.1016/j.chroma.2019.02.027] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2018] [Revised: 02/04/2019] [Accepted: 02/11/2019] [Indexed: 11/29/2022]
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26
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Stilo F, Liberto E, Reichenbach SE, Tao Q, Bicchi C, Cordero C. Untargeted and Targeted Fingerprinting of Extra Virgin Olive Oil Volatiles by Comprehensive Two-Dimensional Gas Chromatography with Mass Spectrometry: Challenges in Long-Term Studies. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2019; 67:5289-5302. [PMID: 30994349 DOI: 10.1021/acs.jafc.9b01661] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Comprehensive two-dimensional gas chromatography coupled with mass spectrometric detection (GC × GC-MS) offers an information-rich basis for effective chemical fingerprinting of food. However, GC × GC-MS yields 2D-peak patterns (i.e., sample 2D fingerprints) whose consistency may be affected by variables related to either the analytical platform or to the experimental parameters adopted for the analysis. This study focuses on the complex volatile fraction of extra-virgin olive oil and addresses 2D-peak patterns variations, including MS signal fluctuations, as they may occur in long-term studies where pedo-climatic, harvest year, or shelf life changes are studied. The 2D-pattern misalignments are forced by changing chromatographic settings and MS acquisition. All procedural steps, preceding pattern recognition by template matching, are analyzed and a rational workflow defined to accurately realign patterns and analytes metadata. Signal-to-noise ratio (SNR) detection threshold, reference spectra extraction, and similarity match factor threshold are critical to avoid false-negative matches. Distance thresholds and polynomial transform parameters are key for effective template matching. In targeted analysis (supervised workflow) with optimized parameters, method accuracy reaches 92.5% (i.e., % of true-positive matches) while for combined untargeted and targeted ( UT) fingerprinting (unsupervised workflow), accuracy reaches 97.9%. Response normalization also is examined, evidencing good performance of multiple internal standard normalization that effectively compensates for discriminations occurring during injection of highly volatile compounds. The resulting workflow is simple, effective, and time efficient.
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Affiliation(s)
- Federico Stilo
- Dipartimento di Scienza e Tecnologia del Farmaco , Università degli Studi di Torino , Turin I-10125 , Italy
| | - Erica Liberto
- Dipartimento di Scienza e Tecnologia del Farmaco , Università degli Studi di Torino , Turin I-10125 , Italy
| | - Stephen E Reichenbach
- Computer Science and Engineering Department , University of Nebraska , Lincoln , Nebraska 68588 , United States
- GC Image, LLC , Lincoln , Nebraska 68508 , United States
| | - Qingping Tao
- GC Image, LLC , Lincoln , Nebraska 68508 , United States
| | - Carlo Bicchi
- Dipartimento di Scienza e Tecnologia del Farmaco , Università degli Studi di Torino , Turin I-10125 , Italy
| | - Chiara Cordero
- Dipartimento di Scienza e Tecnologia del Farmaco , Università degli Studi di Torino , Turin I-10125 , Italy
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Cordero C, Kiefl J, Reichenbach SE, Bicchi C. Characterization of odorant patterns by comprehensive two-dimensional gas chromatography: A challenge in omic studies. Trends Analyt Chem 2019. [DOI: 10.1016/j.trac.2018.06.005] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
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28
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Titaley IA, Ogba OM, Chibwe L, Hoh E, Cheong PHY, Simonich SLM. Automating data analysis for two-dimensional gas chromatography/time-of-flight mass spectrometry non-targeted analysis of comparative samples. J Chromatogr A 2018; 1541:57-62. [PMID: 29448996 PMCID: PMC5909067 DOI: 10.1016/j.chroma.2018.02.016] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2017] [Revised: 02/03/2018] [Accepted: 02/06/2018] [Indexed: 12/19/2022]
Abstract
Non-targeted analysis of environmental samples, using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC/ToF-MS), poses significant data analysis challenges due to the large number of possible analytes. Non-targeted data analysis of complex mixtures is prone to human bias and is laborious, particularly for comparative environmental samples such as contaminated soil pre- and post-bioremediation. To address this research bottleneck, we developed OCTpy, a Python™ script that acts as a data reduction filter to automate GC × GC/ToF-MS data analysis from LECO® ChromaTOF® software and facilitates selection of analytes of interest based on peak area comparison between comparative samples. We used data from polycyclic aromatic hydrocarbon (PAH) contaminated soil, pre- and post-bioremediation, to assess the effectiveness of OCTpy in facilitating the selection of analytes that have formed or degraded following treatment. Using datasets from the soil extracts pre- and post-bioremediation, OCTpy selected, on average, 18% of the initial suggested analytes generated by the LECO® ChromaTOF® software Statistical Compare feature. Based on this list, 63-100% of the candidate analytes identified by a highly trained individual were also selected by OCTpy. This process was accomplished in several minutes per sample, whereas manual data analysis took several hours per sample. OCTpy automates the analysis of complex mixtures of comparative samples, reduces the potential for human error during heavy data handling and decreases data analysis time by at least tenfold.
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Affiliation(s)
- Ivan A Titaley
- Department of Chemistry, Oregon State University, Corvallis, OR, 97331, USA
| | - O Maduka Ogba
- Department of Chemistry, Oregon State University, Corvallis, OR, 97331, USA; Department of Chemistry, Pomona College, Claremont, CA, 91711, USA
| | - Leah Chibwe
- Department of Chemistry, Oregon State University, Corvallis, OR, 97331, USA
| | - Eunha Hoh
- Graduate School of Public Health, San Diego State University, San Diego, CA, 92182, USA
| | - Paul H-Y Cheong
- Department of Chemistry, Oregon State University, Corvallis, OR, 97331, USA.
| | - Staci L Massey Simonich
- Department of Chemistry, Oregon State University, Corvallis, OR, 97331, USA; Department of Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR, 97331, USA.
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29
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Bressanello D, Liberto E, Collino M, Chiazza F, Mastrocola R, Reichenbach SE, Bicchi C, Cordero C. Combined untargeted and targeted fingerprinting by comprehensive two-dimensional gas chromatography: revealing fructose-induced changes in mice urinary metabolic signatures. Anal Bioanal Chem 2018. [DOI: 10.1007/s00216-018-0950-9] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
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30
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Zushi Y, Hashimoto S. Direct Classification of GC × GC-Analyzed Complex Mixtures Using Non-Negative Matrix Factorization-Based Feature Extraction. Anal Chem 2018; 90:3819-3825. [DOI: 10.1021/acs.analchem.7b04313] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Affiliation(s)
- Yasuyuki Zushi
- Research Institute of Science for Safety and Sustainability, National Institute of Advanced Industrial Science and Technology, 16-1 Onogawa, Tsukuba, Ibaraki 305-8569, Japan
- Center for Environmental Measurement and Analysis, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan
| | - Shunji Hashimoto
- Center for Environmental Measurement and Analysis, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan
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31
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Rosso MC, Liberto E, Spigolon N, Fontana M, Somenzi M, Bicchi C, Cordero C. Evolution of potent odorants within the volatile metabolome of high-quality hazelnuts (Corylus avellana L.): evaluation by comprehensive two-dimensional gas chromatography coupled with mass spectrometry. Anal Bioanal Chem 2018; 410:3491-3506. [DOI: 10.1007/s00216-017-0832-6] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2017] [Revised: 11/06/2017] [Accepted: 12/14/2017] [Indexed: 11/28/2022]
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32
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Magagna F, Guglielmetti A, Liberto E, Reichenbach SE, Allegrucci E, Gobino G, Bicchi C, Cordero C. Comprehensive Chemical Fingerprinting of High-Quality Cocoa at Early Stages of Processing: Effectiveness of Combined Untargeted and Targeted Approaches for Classification and Discrimination. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2017; 65:6329-6341. [PMID: 28682071 DOI: 10.1021/acs.jafc.7b02167] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
This study investigates chemical information of volatile fractions of high-quality cocoa (Theobroma cacao L. Malvaceae) from different origins (Mexico, Ecuador, Venezuela, Columbia, Java, Trinidad, and Sao Tomè) produced for fine chocolate. This study explores the evolution of the entire pattern of volatiles in relation to cocoa processing (raw, roasted, steamed, and ground beans). Advanced chemical fingerprinting (e.g., combined untargeted and targeted fingerprinting) with comprehensive two-dimensional gas chromatography coupled with mass spectrometry allows advanced pattern recognition for classification, discrimination, and sensory-quality characterization. The entire data set is analyzed for 595 reliable two-dimensional peak regions, including 130 known analytes and 13 potent odorants. Multivariate analysis with unsupervised exploration (principal component analysis) and simple supervised discrimination methods (Fisher ratios and linear regression trees) reveal informative patterns of similarities and differences and identify characteristic compounds related to sample origin and manufacturing step.
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Affiliation(s)
- Federico Magagna
- Dipartimento di Scienza e Tecnologia del Farmaco, Università di Torino , I-10125 Turin, Italy
| | - Alessandro Guglielmetti
- Dipartimento di Scienza e Tecnologia del Farmaco, Università di Torino , I-10125 Turin, Italy
| | - Erica Liberto
- Dipartimento di Scienza e Tecnologia del Farmaco, Università di Torino , I-10125 Turin, Italy
| | - Stephen E Reichenbach
- Department of Computer Science and Engineering, University of Nebraska-Lincoln , Lincoln, Nebraska 68588-0115, United States
| | | | | | - Carlo Bicchi
- Dipartimento di Scienza e Tecnologia del Farmaco, Università di Torino , I-10125 Turin, Italy
| | - Chiara Cordero
- Dipartimento di Scienza e Tecnologia del Farmaco, Università di Torino , I-10125 Turin, Italy
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Pizzolante G, Cordero C, Tredici SM, Vergara D, Pontieri P, Del Giudice L, Capuzzo A, Rubiolo P, Kanchiswamy CN, Zebelo SA, Bicchi C, Maffei ME, Alifano P. Cultivable gut bacteria provide a pathway for adaptation of Chrysolina herbacea to Mentha aquatica volatiles. BMC PLANT BIOLOGY 2017; 17:30. [PMID: 28249605 PMCID: PMC5333409 DOI: 10.1186/s12870-017-0986-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2016] [Accepted: 01/24/2017] [Indexed: 06/06/2023]
Abstract
BACKGROUND A chemical cross-talk between plants and insects is required in order to achieve a successful co-adaptation. In response to herbivory, plants produce specific compounds, and feeding insects respond adequately7 to molecules produced by plants. Here we show the role of the gut microbial community of the mint beetle Chrysolina herbacea in the chemical cross-talk with Mentha aquatica (or watermint). RESULTS By using two-dimensional gas chromatography-mass spectrometry we first evaluated the chemical patterns of both M. aquatica leaf and frass volatiles extracted by C. herbacea males and females feeding on plants, and observed marked differences between males and females volatiles. The sex-specific chemical pattern of the frass paralleled with sex-specific distribution of cultivable gut bacteria. Indeed, all isolated gut bacteria from females belonged to either α- or γ-Proteobacteria, whilst those from males were γ-Proteobacteria or Firmicutes. We then demonstrated that five Serratia marcescens strains from females possessed antibacterial activity against bacteria from males belonging to Firmicutes suggesting competition by production of antimicrobial compounds. By in vitro experiments, we lastly showed that the microbial communities from the two sexes were associated to specific metabolic patterns with respect to their ability to biotransform M. aquatica terpenoids, and metabolize them into an array of compounds with possible pheromone activity. CONCLUSIONS Our data suggest that cultivable gut bacteria of Chrysolina herbacea males and females influence the volatile blend of herbivory induced Mentha aquatica volatiles in a sex-specific way.
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Affiliation(s)
- Graziano Pizzolante
- Department of Biological and Environmental Sciences and Technologies, University of Salento, via Monteroni 165, 73100 Lecce, Italy
| | - Chiara Cordero
- Dipartimento di Scienza e Tecnologia del Farmaco, Università di Torino, Via Pietro Giuria n°9, 10125 Torino, Italy
| | - Salvatore M. Tredici
- Department of Biological and Environmental Sciences and Technologies, University of Salento, via Monteroni 165, 73100 Lecce, Italy
| | - Davide Vergara
- Department of Biological and Environmental Sciences and Technologies, University of Salento, via Monteroni 165, 73100 Lecce, Italy
| | - Paola Pontieri
- Dipartimento di Biologia, Sezione di Igiene, Institute of Biosciences and Bioresources-UOS Portici (IBBR-UOS Portici), CNR, Portici (NA) c/o, 80134 Naples, Italy
| | - Luigi Del Giudice
- Dipartimento di Biologia, Sezione di Igiene, Institute of Biosciences and Bioresources-UOS Portici (IBBR-UOS Portici), CNR, Portici (NA) c/o, 80134 Naples, Italy
| | - Andrea Capuzzo
- Dipartimento di Scienze della Vita e Biologia dei Sistemi, Università di Torino, Via Quarello 15/A, 10135 Torino, Italy
| | - Patrizia Rubiolo
- Dipartimento di Scienza e Tecnologia del Farmaco, Università di Torino, Via Pietro Giuria n°9, 10125 Torino, Italy
| | - Chidananda N. Kanchiswamy
- Research and Innovation Centre Genomics and Biology of Fruit Crop Department, Fondazione Edmund Mach (FEM), Istituto Agrario San Michele (IASMA), Via Mach 1, 38010 San Michele all’Adige, TN Italy
| | - Simon A. Zebelo
- Department of Natural Sciences, University of Maryland Eastern Shore, 1117 Trigg Hall, Princess Anne, 21853 MD USA
| | - Carlo Bicchi
- Dipartimento di Scienza e Tecnologia del Farmaco, Università di Torino, Via Pietro Giuria n°9, 10125 Torino, Italy
| | - Massimo E. Maffei
- Dipartimento di Scienze della Vita e Biologia dei Sistemi, Università di Torino, Via Quarello 15/A, 10135 Torino, Italy
| | - Pietro Alifano
- Department of Biological and Environmental Sciences and Technologies, University of Salento, via Monteroni 165, 73100 Lecce, Italy
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34
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Couprie C, Duval L, Moreaud M, Hénon S, Tebib M, Souchon V. BARCHAN: Blob Alignment for Robust CHromatographic ANalysis. J Chromatogr A 2017; 1484:65-72. [DOI: 10.1016/j.chroma.2017.01.003] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Revised: 12/23/2016] [Accepted: 01/02/2017] [Indexed: 01/11/2023]
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35
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López P, Tienstra M, Lommen A, Mol HG. Validation of an automated screening method for persistent organic contaminants in fats and oils by GC × GC-ToFMS. Food Chem 2016; 211:645-53. [DOI: 10.1016/j.foodchem.2016.05.041] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2015] [Revised: 01/31/2016] [Accepted: 05/06/2016] [Indexed: 01/30/2023]
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36
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37
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Combined untargeted and targeted fingerprinting with comprehensive two-dimensional chromatography for volatiles and ripening indicators in olive oil. Anal Chim Acta 2016; 936:245-58. [DOI: 10.1016/j.aca.2016.07.005] [Citation(s) in RCA: 70] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2016] [Revised: 06/27/2016] [Accepted: 07/01/2016] [Indexed: 11/20/2022]
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38
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Strozier ED, Mooney DD, Friedenberg DA, Klupinski TP, Triplett CA. Use of Comprehensive Two-Dimensional Gas Chromatography with Time-of-Flight Mass Spectrometric Detection and Random Forest Pattern Recognition Techniques for Classifying Chemical Threat Agents and Detecting Chemical Attribution Signatures. Anal Chem 2016; 88:7068-75. [DOI: 10.1021/acs.analchem.6b00725] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Affiliation(s)
- Erich D. Strozier
- Battelle Memorial Institute, 505
King Avenue, Columbus, Ohio 43201, United States
| | - Douglas D. Mooney
- Battelle Memorial Institute, 505
King Avenue, Columbus, Ohio 43201, United States
- Early Moon, LLC, 1391 West
Fifth Avenue, Suite 423, Columbus, Ohio 43212, United States
| | - David A. Friedenberg
- Battelle Memorial Institute, 505
King Avenue, Columbus, Ohio 43201, United States
| | | | - Cheryl A. Triplett
- Battelle Memorial Institute, 505
King Avenue, Columbus, Ohio 43201, United States
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39
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Pleil JD, Isaacs KK. High-resolution mass spectrometry: basic principles for using exact mass and mass defect for discovery analysis of organic molecules in blood, breath, urine and environmental media. J Breath Res 2016; 10:012001. [DOI: 10.1088/1752-7155/10/1/012001] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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40
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Klupinski TP, Strozier ED, Friedenberg DA, Brinkman MC, Gordon SM, Clark PI. Identification of New and Distinctive Exposures from Little Cigars. Chem Res Toxicol 2016; 29:162-8. [PMID: 26605856 DOI: 10.1021/acs.chemrestox.5b00371] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Little cigar mainstream smoke is less well-characterized than cigarette mainstream smoke in terms of chemical composition. This study compared four popular little cigar products against four popular cigarette products to determine compounds that are either unique to or more abundant in little cigars. These compounds are categorized as new or distinctive exposures, respectively. Total particulate matter samples collected from machine-generated mainstream smoke were extracted with methylene chloride, and the extracts were analyzed using two-dimensional gas chromatography-time-of-flight mass spectrometry. The data were evaluated using novel data-processing algorithms that account for characteristics specific to the selected analytical technique and variability associated with replicate sample analyses. Among more than 25 000 components detected across the complete data set, ambrox was confirmed as a new exposure, and 3-methylbutanenitrile and 4-methylimidazole were confirmed as distinctive exposures. Concentrations of these compounds for the little cigar mainstream smoke were estimated at approximately 0.4, 0.7, and 12 μg/rod, respectively. In achieving these results, this study has demonstrated the capability of a powerful analytical approach to identify previously uncharacterized tobacco-related exposures from little cigars. The same approach could also be applied to other samples to characterize constituents associated with tobacco product classes or specific tobacco products of interest. Such analyses are critical in identifying tobacco-related exposures that may affect public health.
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Affiliation(s)
| | | | | | | | - Sydney M Gordon
- Battelle , 505 King Avenue, Columbus, Ohio 43201, United States
| | - Pamela I Clark
- School of Public Health, Department of Behavioral and Community Health, Tobacco Center of Regulatory Science, University of Maryland , College Park, Maryland 20742, United States
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41
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Potential of the reversed-inject differential flow modulator for comprehensive two-dimensional gas chromatography in the quantitative profiling and fingerprinting of essential oils of different complexity. J Chromatogr A 2015; 1417:79-95. [DOI: 10.1016/j.chroma.2015.09.027] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2015] [Revised: 09/09/2015] [Accepted: 09/09/2015] [Indexed: 12/16/2022]
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42
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Tranchida PQ, Purcaro G, Maimone M, Mondello L. Impact of comprehensive two-dimensional gas chromatography with mass spectrometry on food analysis. J Sep Sci 2015; 39:149-61. [DOI: 10.1002/jssc.201500379] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2015] [Revised: 05/28/2015] [Accepted: 07/08/2015] [Indexed: 02/06/2023]
Affiliation(s)
- Peter Q. Tranchida
- “Scienze del Farmaco e Prodotti per la Salute” Department; University of Messina; Messina Italy
| | - Giorgia Purcaro
- Chromaleonts.r.l, c/o “Scienze del Farmaco e Prodotti per la Salute” Department; University of Messina; Messina Italy
| | - Mariarosa Maimone
- “Scienze del Farmaco e Prodotti per la Salute” Department; University of Messina; Messina Italy
| | - Luigi Mondello
- “Scienze del Farmaco e Prodotti per la Salute” Department; University of Messina; Messina Italy
- Chromaleonts.r.l, c/o “Scienze del Farmaco e Prodotti per la Salute” Department; University of Messina; Messina Italy
- University Campus Bio-Medico of Rome; Roma Italy
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43
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Parsons BA, Marney LC, Siegler WC, Hoggard JC, Wright BW, Synovec RE. Tile-Based Fisher Ratio Analysis of Comprehensive Two-Dimensional Gas Chromatography Time-of-Flight Mass Spectrometry (GC × GC–TOFMS) Data Using a Null Distribution Approach. Anal Chem 2015; 87:3812-9. [DOI: 10.1021/ac504472s] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Brendon A. Parsons
- Department
of Chemistry, University of Washington, Box 351700, Seattle, Washington 98198, United States
| | - Luke C. Marney
- Department
of Chemistry, University of Washington, Box 351700, Seattle, Washington 98198, United States
| | - W. Christopher Siegler
- Department
of Chemistry, University of Washington, Box 351700, Seattle, Washington 98198, United States
| | - Jamin C. Hoggard
- Department
of Chemistry, University of Washington, Box 351700, Seattle, Washington 98198, United States
| | - Bob W. Wright
- Pacific Northwest National Laboratory, Battelle Boulevard, P.O. Box 999, Richland, Washington 99352, United States
| | - Robert E. Synovec
- Department
of Chemistry, University of Washington, Box 351700, Seattle, Washington 98198, United States
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44
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Improving the quality of biomarker candidates in untargeted metabolomics via peak table-based alignment of comprehensive two-dimensional gas chromatography-mass spectrometry data. J Chromatogr A 2015; 1394:111-7. [PMID: 25857541 DOI: 10.1016/j.chroma.2015.03.001] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2014] [Revised: 02/24/2015] [Accepted: 03/01/2015] [Indexed: 01/07/2023]
Abstract
The potential of high-resolution analytical technologies like GC×GC/TOF MS in untargeted metabolomics and biomarker discovery has been limited by the development of fully automated software that can efficiently align and extract information from multiple chromatographic data sets. In this work we report the first investigation on a peak-by-peak basis of the chromatographic factors that impact GC×GC data alignment. A representative set of 16 compounds of different chromatographic characteristics were followed through the alignment of 63 GC×GC chromatograms. We found that varying the mass spectral match parameter had a significant influence on the alignment for poorly-resolved peaks, especially those at the extremes of the detector linear range, and no influence on well-chromatographed peaks. Therefore, optimized chromatography is required for proper GC×GC data alignment. Based on these observations, a workflow is presented for the conservative selection of biomarker candidates from untargeted metabolomics analyses.
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45
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Pixel-Level Data Analysis Methods for Comprehensive Two-Dimensional Chromatography. ACTA ACUST UNITED AC 2015. [DOI: 10.1016/b978-0-444-63527-3.00010-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register]
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46
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Nicolotti L, Cordero C, Bressanello D, Cagliero C, Liberto E, Magagna F, Rubiolo P, Sgorbini B, Bicchi C. Parallel dual secondary column-dual detection: A further way of enhancing the informative potential of two-dimensional comprehensive gas chromatography. J Chromatogr A 2014; 1360:264-74. [DOI: 10.1016/j.chroma.2014.07.081] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2014] [Revised: 07/22/2014] [Accepted: 07/24/2014] [Indexed: 01/19/2023]
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47
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Urinary metabolic fingerprinting of mice with diet-induced metabolic derangements by parallel dual secondary column-dual detection two-dimensional comprehensive gas chromatography. J Chromatogr A 2014; 1361:265-76. [DOI: 10.1016/j.chroma.2014.08.015] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2014] [Revised: 07/31/2014] [Accepted: 08/04/2014] [Indexed: 12/19/2022]
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48
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Chin ST, Marriott PJ. Multidimensional gas chromatography beyond simple volatiles separation. Chem Commun (Camb) 2014; 50:8819-33. [DOI: 10.1039/c4cc02018a] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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49
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Resolution of co-eluting compounds of Cannabis Sativa in comprehensive two-dimensional gas chromatography/mass spectrometry detection with Multivariate Curve Resolution-Alternating Least Squares. Talanta 2014; 121:273-80. [DOI: 10.1016/j.talanta.2013.12.044] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2013] [Revised: 12/17/2013] [Accepted: 12/22/2013] [Indexed: 01/07/2023]
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50
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Purcaro G, Cordero C, Liberto E, Bicchi C, Conte LS. Toward a definition of blueprint of virgin olive oil by comprehensive two-dimensional gas chromatography. J Chromatogr A 2014; 1334:101-11. [DOI: 10.1016/j.chroma.2014.01.067] [Citation(s) in RCA: 63] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2013] [Revised: 01/17/2014] [Accepted: 01/24/2014] [Indexed: 02/08/2023]
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