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Huang S, Righetti L, Claassen FW, Krishna A, Ma M, van Beek TA, Chen B, Zuilhof H, Salentijn GI. Ultrafast, Selective, and Highly Sensitive Nonchromatographic Analysis of Fourteen Cannabinoids in Cannabis Extracts, Δ8-Tetrahydrocannabinol Synthetic Mixtures, and Edibles by Cyclic Ion Mobility Spectrometry-Mass Spectrometry. Anal Chem 2024. [PMID: 38862388 DOI: 10.1021/acs.analchem.3c05879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2024]
Abstract
The diversity of cannabinoid isomers and complexity of Cannabis products pose significant challenges for analytical methodologies. In this study, we developed a method to analyze 14 different cannabinoid isomers in diverse samples within milliseconds by leveraging the unique adduct-forming behavior of silver ions in advanced cyclic ion mobility spectrometry-mass spectrometry. The developed method achieved the separation of isomers from four groups of cannabinoids: Δ3-tetrahydrocannabinol (THC) (1), Δ8-THC (2), Δ9-THC (3), cannabidiol (CBD) (4), Δ8-iso-THC (5), and Δ(4)8-iso-THC (6) (all MW = 314); 9α-hydroxyhexahydrocannabinol (7), 9β-hydroxyhexahydrocannabinol (8), and 8-hydroxy-iso-THC (9) (all MW = 332); tetrahydrocannabinolic acid (THCA) (10) and cannabidiolic acid (CBDA) (11) (both MW = 358); Δ8-tetrahydrocannabivarin (THCV) (12), Δ8-iso-THCV (13), and Δ9-THCV (14) (all MW = 286). Moreover, experimental and theoretical traveling wave collision cross section values in nitrogen (TWCCSN2) of cannabinoid-Ag(I) species were obtained for the first time with an average error between experimental and theoretical values of 2.6%. Furthermore, a workflow for the identification of cannabinoid isomers in Cannabis and Cannabis-derived samples was established based on three identification steps (m/z and isotope pattern of Ag(I) adducts, TWCCSN2, and MS/MS fragments). Afterward, calibration curves of three major cannabinoids were established with a linear range of 1-250 ng·ml-1 for Δ8-THC (2) (R2 = 0.9999), 0.1-25 ng·ml-1 for Δ9-THC (3) (R2 = 0.9987), and 0.04-10 ng·ml-1 for CBD (4) (R2 = 0.9986) as well as very low limits of detection (0.008-0.2 ng·ml-1). Finally, relative quantification of Δ8-THC (2), Δ9-THC (3), and CBD (4) in eight complex acid-treated CBD mixtures was achieved without chromatographic separation. The results showed good correspondence (R2 = 0.999) with those obtained by gas chromatography-flame ionization detection/mass spectrometry.
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Affiliation(s)
- Si Huang
- Key Laboratory of Phytochemical R&D of Hunan Province and Key Laboratory of Chemical Biology & Traditional Chinese Medicine Research of Ministry of Education, Hunan Normal University, No.36, Lushan Road, Changsha 410081, China
- Laboratory of Organic Chemistry, Wageningen University, Stippeneng 4, Wageningen 6708 WE, The Netherlands
| | - Laura Righetti
- Laboratory of Organic Chemistry, Wageningen University, Stippeneng 4, Wageningen 6708 WE, The Netherlands
- Wageningen Food Safety Research (WFSR), Wageningen University & Research, P.O. Box 230, Wageningen 6700 AE, The Netherlands
| | - Frank W Claassen
- Laboratory of Organic Chemistry, Wageningen University, Stippeneng 4, Wageningen 6708 WE, The Netherlands
| | - Akash Krishna
- Laboratory of Organic Chemistry, Wageningen University, Stippeneng 4, Wageningen 6708 WE, The Netherlands
| | - Ming Ma
- Key Laboratory of Phytochemical R&D of Hunan Province and Key Laboratory of Chemical Biology & Traditional Chinese Medicine Research of Ministry of Education, Hunan Normal University, No.36, Lushan Road, Changsha 410081, China
| | - Teris A van Beek
- Laboratory of Organic Chemistry, Wageningen University, Stippeneng 4, Wageningen 6708 WE, The Netherlands
| | - Bo Chen
- Key Laboratory of Phytochemical R&D of Hunan Province and Key Laboratory of Chemical Biology & Traditional Chinese Medicine Research of Ministry of Education, Hunan Normal University, No.36, Lushan Road, Changsha 410081, China
| | - Han Zuilhof
- Key Laboratory of Phytochemical R&D of Hunan Province and Key Laboratory of Chemical Biology & Traditional Chinese Medicine Research of Ministry of Education, Hunan Normal University, No.36, Lushan Road, Changsha 410081, China
- Laboratory of Organic Chemistry, Wageningen University, Stippeneng 4, Wageningen 6708 WE, The Netherlands
| | - Gert Ij Salentijn
- Laboratory of Organic Chemistry, Wageningen University, Stippeneng 4, Wageningen 6708 WE, The Netherlands
- Wageningen Food Safety Research (WFSR), Wageningen University & Research, P.O. Box 230, Wageningen 6700 AE, The Netherlands
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2
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Nguyen R, Seguin RP, Ross DH, Chen P, Richardson S, Liem J, Lin YS, Xu L. Development and Application of a Multidimensional Database for the Detection of Quaternary Ammonium Compounds and Their Phase I Hepatic Metabolites in Humans. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:6236-6249. [PMID: 38534032 PMCID: PMC11008582 DOI: 10.1021/acs.est.3c10845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 03/06/2024] [Accepted: 03/08/2024] [Indexed: 03/28/2024]
Abstract
The COVID-19 pandemic has led to significantly increased human exposure to the widely used disinfectants quaternary ammonium compounds (QACs). Xenobiotic metabolism serves a critical role in the clearance of environmental molecules, yet limited data are available on the routes of QAC metabolism or metabolite levels in humans. To address this gap and to advance QAC biomonitoring capabilities, we analyzed 19 commonly used QACs and their phase I metabolites by liquid chromatography-ion mobility-tandem mass spectrometry (LC-IM-MS/MS). In vitro generation of QAC metabolites by human liver microsomes produced a series of oxidized metabolites, with metabolism generally occurring on the alkyl chain group, as supported by MS/MS fragmentation. Discernible trends were observed in the gas-phase IM behavior of QAC metabolites, which, despite their increased mass, displayed smaller collision cross-section (CCS) values than those of their respective parent compounds. We then constructed a multidimensional reference SQLite database consisting of m/z, CCS, retention time (rt), and MS/MS spectra for 19 parent QACs and 81 QAC metabolites. Using this database, we confidently identified 13 parent QACs and 35 metabolites in de-identified human fecal samples. This is the first study to integrate in vitro metabolite biosynthesis with LC-IM-MS/MS for the simultaneous monitoring of parent QACs and their metabolites in humans.
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Affiliation(s)
- Ryan Nguyen
- Department
of Medicinal Chemistry, University of Washington, Seattle, Washington 98195, United States
| | - Ryan P. Seguin
- Department
of Medicinal Chemistry, University of Washington, Seattle, Washington 98195, United States
| | - Dylan H. Ross
- Department
of Medicinal Chemistry, University of Washington, Seattle, Washington 98195, United States
| | - Pengyu Chen
- Department
of Medicinal Chemistry, University of Washington, Seattle, Washington 98195, United States
| | - Sean Richardson
- Department
of Mathematics, University of Washington, Seattle, Washington 98195, United States
| | - Jennifer Liem
- Department
of Pharmaceutics, University of Washington, Seattle, Washington 98195, United States
| | - Yvonne S. Lin
- Department
of Pharmaceutics, University of Washington, Seattle, Washington 98195, United States
| | - Libin Xu
- Department
of Medicinal Chemistry, University of Washington, Seattle, Washington 98195, United States
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3
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Stroganova I, Willenberg H, Tente T, Depraz Depland A, Bakels S, Rijs AM. Exploring the Aggregation Propensity of PHF6 Peptide Segments of the Tau Protein Using Ion Mobility Mass Spectrometry Techniques. Anal Chem 2024; 96:5115-5124. [PMID: 38517679 PMCID: PMC10993201 DOI: 10.1021/acs.analchem.3c04974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 03/06/2024] [Accepted: 03/07/2024] [Indexed: 03/24/2024]
Abstract
Peptide and protein aggregation involves the formation of oligomeric species, but the complex interplay between oligomers of different conformations and sizes complicates their structural elucidation. Using ion mobility mass spectrometry (IM-MS), we aim to reveal these early steps of aggregation for the Ac-PHF6-NH2 peptide segment from tau protein, thereby distinguishing between different oligomeric species and gaining an understanding of the aggregation pathway. An important factor that is often neglected, but which can alter the aggregation propensity of peptides, is the terminal capping groups. Here, we demonstrate the use of IM-MS to probe the early stages of aggregate formation of Ac-PHF6-NH2, Ac-PHF6, PHF6-NH2, and uncapped PHF6 peptide segments. The aggregation propensity of the four PHF6 segments is confirmed using thioflavin T fluorescence assays and transmission electron microscopy. A novel approach based on post-IM fragmentation and quadrupole selection on the TIMS-Qq-ToF (trapped ion mobility) spectrometer was developed to enhance oligomer assignment, especially for the higher-order aggregates. This approach pushes the limits of IM identification of isobaric species, whose signatures appear closer to each other with increasing oligomer size, and provides new insights into the interpretation of IM-MS data. In addition, TIMS collision cross section values are compared with traveling wave ion mobility (TWIMS) data to evaluate potential instrumental bias in the trapped ion mobility results. The two IM-MS instrumental platforms are based on different ion mobility principles and have different configurations, thereby providing us with valuable insight into the preservation of weakly bound biomolecular complexes such as peptide aggregates.
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Affiliation(s)
- Iuliia Stroganova
- Division
of Bioanalytical Chemistry, Department of Chemistry and Pharmaceutical
Sciences, Amsterdam Institute of Molecular and Life Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1105, Amsterdam 1081 HV, The Netherlands
- Centre
for Analytical Sciences Amsterdam, Amsterdam 1098 XH, The Netherlands
| | - Hannah Willenberg
- Division
of Bioanalytical Chemistry, Department of Chemistry and Pharmaceutical
Sciences, Amsterdam Institute of Molecular and Life Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1105, Amsterdam 1081 HV, The Netherlands
| | - Thaleia Tente
- Division
of Bioanalytical Chemistry, Department of Chemistry and Pharmaceutical
Sciences, Amsterdam Institute of Molecular and Life Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1105, Amsterdam 1081 HV, The Netherlands
| | - Agathe Depraz Depland
- Division
of Bioanalytical Chemistry, Department of Chemistry and Pharmaceutical
Sciences, Amsterdam Institute of Molecular and Life Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1105, Amsterdam 1081 HV, The Netherlands
- Centre
for Analytical Sciences Amsterdam, Amsterdam 1098 XH, The Netherlands
| | - Sjors Bakels
- Division
of Bioanalytical Chemistry, Department of Chemistry and Pharmaceutical
Sciences, Amsterdam Institute of Molecular and Life Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1105, Amsterdam 1081 HV, The Netherlands
- Centre
for Analytical Sciences Amsterdam, Amsterdam 1098 XH, The Netherlands
| | - Anouk M. Rijs
- Division
of Bioanalytical Chemistry, Department of Chemistry and Pharmaceutical
Sciences, Amsterdam Institute of Molecular and Life Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1105, Amsterdam 1081 HV, The Netherlands
- Centre
for Analytical Sciences Amsterdam, Amsterdam 1098 XH, The Netherlands
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4
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Sandoval MA, Calzadilla W, Vidal J, Brillas E, Salazar-González R. Contaminants of emerging concern: Occurrence, analytical techniques, and removal with electrochemical advanced oxidation processes with special emphasis in Latin America. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 345:123397. [PMID: 38272166 DOI: 10.1016/j.envpol.2024.123397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 12/02/2023] [Accepted: 01/17/2024] [Indexed: 01/27/2024]
Abstract
The occurrence of contaminants of emerging concern (CECs) in environmental systems is gradually more studied worldwide. However, in Latin America, the presence of contaminants of emerging concern, together with their environmental and toxicological impacts, has recently been gaining wide interest in the scientific community. This paper presents a critical review about the source, fate, and occurrence of distinct emerging contaminants reported during the last two decades in various countries of Latin America. In recent years, Brazil, Chile, and Colombia are the main countries that have conducted research on the presence of these pollutants in biological and aquatic compartments. Data gathered indicated that pharmaceuticals, pesticides, and personal care products are the most assessed CECs in Latin America, being the most common compounds the followings: atrazine, acenaphthene, caffeine, carbamazepine, ciprofloxacin, diclofenac, diuron, estrone, losartan, sulfamethoxazole, and trimethoprim. Most common analytical methodologies for identifying these compounds were HPLC and GC coupled with mass spectrometry with the potential to characterize and quantify complex substances in the environment at low concentrations. Most CECs' monitoring and detection were observed near to urban areas which confirm the out-of-date wastewater treatment plants and sanitization infrastructures limiting the removal of these pollutants. Therefore, the implementation of tertiary treatment should be required. In this tenor, this review also summarizes some studies of CECs removal using electrochemical advanced oxidation processes that showed satisfactory performance. Finally, challenges, recommendations, and future perspectives are discussed.
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Affiliation(s)
- Miguel A Sandoval
- Instituto Tecnológico Superior de Guanajuato, Tecnológico Nacional de México, Carretera Estatal Guanajuato-Puentecillas Km. 10.5, 36262, Guanajuato, Mexico
| | - Wendy Calzadilla
- Research Group of Analysis, Treatments, Electrochemistry, Recovery and Reuse of Water, (WATER2), Departamento de Química Inorgánica, Facultad de Química y de Farmacia, Pontificia Universidad Católica de Chile, Chile
| | - Jorge Vidal
- Departamento de Química de Los Materiales, Facultad de Química y Biología, Universidad de Santiago de Chile, Chile
| | - Enric Brillas
- Laboratori d'Electroquímica dels Materials i del Medi Ambient, Departament de Ciència de Materials i de Química Física, Facultat de Química, Universitat de Barcelona, Martí i Franquès 1-11, 08028 Barcelona, Spain
| | - Ricardo Salazar-González
- Departamento de Química de Los Materiales, Facultad de Química y Biología, Universidad de Santiago de Chile, Chile.
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5
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Wisanpitayakorn P, Sartyoungkul S, Kurilung A, Sirivatanauksorn Y, Visessanguan W, Sathirapongsasuti N, Khoomrung S. Accurate Prediction of Ion Mobility Collision Cross-Section Using Ion's Polarizability and Molecular Mass with Limited Data. J Chem Inf Model 2024; 64:1533-1542. [PMID: 38393779 PMCID: PMC10934814 DOI: 10.1021/acs.jcim.3c01491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 01/26/2024] [Accepted: 02/12/2024] [Indexed: 02/25/2024]
Abstract
The rotationally averaged collision cross-section (CCS) determined by ion mobility-mass spectrometry (IM-MS) facilitates the identification of various biomolecules. Although machine learning (ML) models have recently emerged as a highly accurate approach for predicting CCS values, they rely on large data sets from various instruments, calibrants, and setups, which can introduce additional errors. In this study, we identified and validated that ion's polarizability and mass-to-charge ratio (m/z) have the most significant predictive power for traveling-wave IM CCS values in relation to other physicochemical properties of ions. Constructed solely based on these two physicochemical properties, our CCS prediction approach demonstrated high accuracy (mean relative error of <3.0%) even when trained with limited data (15 CCS values). Given its ability to excel with limited data, our approach harbors immense potential for constructing a precisely predicted CCS database tailored to each distinct experimental setup. A Python script for CCS prediction using our approach is freely available at https://github.com/MSBSiriraj/SVR_CCSPrediction under the GNU General Public License (GPL) version 3.
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Affiliation(s)
- Pattipong Wisanpitayakorn
- Siriraj
Center of Research Excellence in Metabolomics and Systems Biology
(SiCORE-MSB), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj
Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Sitanan Sartyoungkul
- Siriraj
Center of Research Excellence in Metabolomics and Systems Biology
(SiCORE-MSB), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj
Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Alongkorn Kurilung
- Siriraj
Center of Research Excellence in Metabolomics and Systems Biology
(SiCORE-MSB), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj
Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Yongyut Sirivatanauksorn
- Siriraj
Center of Research Excellence in Metabolomics and Systems Biology
(SiCORE-MSB), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj
Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Wonnop Visessanguan
- National
Center for Genetic Engineering and Biotechnology (BIOTEC), Pathumthani 12120, Thailand
| | - Nuankanya Sathirapongsasuti
- Section
of Translational Medicine, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok 10400, Thailand
- Research
Network of NANOTEC - MU Ramathibodi on Nanomedicine, Bangkok 12120, Thailand
| | - Sakda Khoomrung
- Siriraj
Center of Research Excellence in Metabolomics and Systems Biology
(SiCORE-MSB), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Siriraj
Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
- Department
of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, 10700, Thailand
- Center
of Excellence for Innovation in Chemistry (PERCH−CIC), Faculty of Science Mahidol University, Bangkok 10400, Thailand
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6
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Marques Dos Santos M, Li C, Jia S, Thomas M, Gallard H, Croué JP, Carato P, Snyder SA. Formation of halogenated forms of bisphenol A (BPA) in water: Resolving isomers with ion mobility - mass spectrometry and the role of halogenation position in cellular toxicity. JOURNAL OF HAZARDOUS MATERIALS 2024; 465:133229. [PMID: 38232544 DOI: 10.1016/j.jhazmat.2023.133229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 12/05/2023] [Accepted: 12/09/2023] [Indexed: 01/19/2024]
Abstract
Halogenated BPA (XBPA) forms resulting from water chlorination can lead to increased toxicity and different biological effects. While previous studies have reported the occurrence of different XBPAs, analytical limitation have hindered the analysis and differentiation of the many potential isomeric forms. Using online solid-phase extraction - liquid chromatography - ion-mobility - high-resolution mass spectrometry (OSPE-LC-IM-HRMS), we demonstrated a rapid analysis method for the analysis of XBPA forms after water chlorination, with a total analysis time of less than 10 min including extraction and concentration and low detection limits (∼5-80 ng/L range). A multi in-vitro bioassay testing approach for the identified products revealed that cytotoxicity and bioenergetics impacts were largely associated with the presence of halogen atoms at positions 2 or 2' and the overall number of halogens incorporated into the BPA molecule. Different XBPA also showed distinct impacts on oxidative stress, peroxisome proliferator-activated receptor gamma - PPARγ, and inflammatory response. While increased DNA damage was observed for chlorinated water samples (4.14 ± 1.21-fold change), the additive effect of the selected 20 XBPA studied could not explain the increased DNA damage observed, indicating that additional species or synergistic effects might be at play.
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Affiliation(s)
- Mauricius Marques Dos Santos
- Nanyang Environment & Water Research Institute (NEWRI), Nanyang Technological University, CleanTech One, 1 Cleantech Loop, 637141, Singapore
| | - Caixia Li
- Nanyang Environment & Water Research Institute (NEWRI), Nanyang Technological University, CleanTech One, 1 Cleantech Loop, 637141, Singapore
| | - Shenglan Jia
- Nanyang Environment & Water Research Institute (NEWRI), Nanyang Technological University, CleanTech One, 1 Cleantech Loop, 637141, Singapore
| | - Mikael Thomas
- Institut de Chimie des Milieux et des Matériaux de Poitiers, IC2MP UMR 7285 CNRS, Université de Poitiers, France
| | - Hervé Gallard
- Institut de Chimie des Milieux et des Matériaux de Poitiers, IC2MP UMR 7285 CNRS, Université de Poitiers, France
| | - Jean-Philippe Croué
- Institut de Chimie des Milieux et des Matériaux de Poitiers, IC2MP UMR 7285 CNRS, Université de Poitiers, France
| | - Pascal Carato
- Laboratoire Ecologie & Biologie des Interactions, UMR CNRS 7267, Université de Poitiers, France; INSERM CIC1402, Université de Poitiers, IHES Research Group, Poitiers, France
| | - Shane Allen Snyder
- Nanyang Environment & Water Research Institute (NEWRI), Nanyang Technological University, CleanTech One, 1 Cleantech Loop, 637141, Singapore.
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7
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Kartowikromo KY, Olajide OE, Hamid AM. Collision cross section measurement and prediction methods in omics. JOURNAL OF MASS SPECTROMETRY : JMS 2023; 58:e4973. [PMID: 37620034 PMCID: PMC10530098 DOI: 10.1002/jms.4973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 06/26/2023] [Accepted: 07/20/2023] [Indexed: 08/26/2023]
Abstract
Omics studies such as metabolomics, lipidomics, and proteomics have become important for understanding the mechanisms in living organisms. However, the compounds detected are structurally different and contain isomers, with each structure or isomer leading to a different result in terms of the role they play in the cell or tissue in the organism. Therefore, it is important to detect, characterize, and elucidate the structures of these compounds. Liquid chromatography and mass spectrometry have been utilized for decades in the structure elucidation of key compounds. While prediction models of parameters (such as retention time and fragmentation pattern) have also been developed for these separation techniques, they have some limitations. Moreover, ion mobility has become one of the most promising techniques to give a fingerprint to these compounds by determining their collision cross section (CCS) values, which reflect their shape and size. Obtaining accurate CCS enables its use as a filter for potential analyte structures. These CCS values can be measured experimentally using calibrant-independent and calibrant-dependent approaches. Identification of compounds based on experimental CCS values in untargeted analysis typically requires CCS references from standards, which are currently limited and, if available, would require a large amount of time for experimental measurements. Therefore, researchers use theoretical tools to predict CCS values for untargeted and targeted analysis. In this review, an overview of the different methods for the experimental and theoretical estimation of CCS values is given where theoretical prediction tools include computational and machine modeling type approaches. Moreover, the limitations of the current experimental and theoretical approaches and their potential mitigation methods were discussed.
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Affiliation(s)
| | - Orobola E Olajide
- Department of Chemistry and Biochemistry, Auburn University, Auburn, Alabama, USA
| | - Ahmed M Hamid
- Department of Chemistry and Biochemistry, Auburn University, Auburn, Alabama, USA
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8
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Belova L, Poma G, Roggeman M, Jeong Y, Kim DH, Berghmans P, Peters J, Salamova A, van Nuijs ALN, Covaci A. Identification and characterization of quaternary ammonium compounds in Flemish indoor dust by ion-mobility high-resolution mass spectrometry. ENVIRONMENT INTERNATIONAL 2023; 177:108021. [PMID: 37307605 DOI: 10.1016/j.envint.2023.108021] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 05/14/2023] [Accepted: 06/01/2023] [Indexed: 06/14/2023]
Abstract
Quaternary ammonium compounds (QACs) are a class of surfactants commonly used in disinfecting and cleaning products. Their use has substantially increased during the COVID-19 pandemic leading to increasing human exposure. QACs have been associated with hypersensitivity reactions and an increased risk of asthma. This study introduces the first identification, characterization and semi-quantification of QACs in European indoor dust using ion-mobility high-resolution mass spectrometry (IM-HRMS), including the acquisition of collision cross section values (DTCCSN2) for targeted and suspect QACs. A total of 46 indoor dust samples collected in Belgium were analyzed using target and suspect screening. Targeted QACs (n = 21) were detected with detection frequencies ranging between 4.2 and 100 %, while 15 QACs showed detection frequencies > 90 %. Semi-quantified concentrations of individual QACs showed a maximum of 32.23 µg/g with a median ∑QAC concentration of 13.05 µg/g and allowed the calculation of Estimated Daily Intakes for adults and toddlers. Most abundant QACs matched the patterns reported in indoor dust collected in the United States. Suspect screening allowed the identification of 17 additional QACs. A dialkyl dimethyl ammonium compound with mixed chain lengths (C16:C18) was characterized as a major QAC homologue with a maximum semi-quantified concentration of 24.90 µg/g. The high detection frequencies and structural variabilities observed call for more European studies on potential human exposure to these compounds. For all targeted QACs, drift tube IM-HRMS derived collision cross section values (DTCCSN2) are reported. Reference DTCCSN2 values allowed the characterization of CCS-m/z trendlines for each of the targeted QAC classes. Experimental CCS-m/z ratios of suspect QACs were compared with the CCS-m/z trendlines. The alignment between the two datasets served as an additional confirmation of the assigned suspect QACs. The use of the 4bit multiplexing acquisition mode with consecutive high-resolution demultiplexing confirmed the presence of isomers for two of the suspect QACs.
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Affiliation(s)
- Lidia Belova
- Toxicological Centre, University of Antwerp, Antwerp, Belgium.
| | - Giulia Poma
- Toxicological Centre, University of Antwerp, Antwerp, Belgium
| | | | - Yunsun Jeong
- Toxicological Centre, University of Antwerp, Antwerp, Belgium; Division for Environmental Health, Korea Environment Institute (KEI), Sicheong-daero 370, Sejong 30147, Republic of Korea
| | - Da-Hye Kim
- Toxicological Centre, University of Antwerp, Antwerp, Belgium
| | - Patrick Berghmans
- Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol, Belgium
| | - Jan Peters
- Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol, Belgium
| | - Amina Salamova
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | | | - Adrian Covaci
- Toxicological Centre, University of Antwerp, Antwerp, Belgium.
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9
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Li X, Wang H, Jiang M, Ding M, Xu X, Xu B, Zou Y, Yu Y, Yang W. Collision Cross Section Prediction Based on Machine Learning. Molecules 2023; 28:molecules28104050. [PMID: 37241791 DOI: 10.3390/molecules28104050] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 05/10/2023] [Accepted: 05/10/2023] [Indexed: 05/28/2023] Open
Abstract
Ion mobility-mass spectrometry (IM-MS) is a powerful separation technique providing an additional dimension of separation to support the enhanced separation and characterization of complex components from the tissue metabolome and medicinal herbs. The integration of machine learning (ML) with IM-MS can overcome the barrier to the lack of reference standards, promoting the creation of a large number of proprietary collision cross section (CCS) databases, which help to achieve the rapid, comprehensive, and accurate characterization of the contained chemical components. In this review, advances in CCS prediction using ML in the past 2 decades are summarized. The advantages of ion mobility-mass spectrometers and the commercially available ion mobility technologies with different principles (e.g., time dispersive, confinement and selective release, and space dispersive) are introduced and compared. The general procedures involved in CCS prediction based on ML (acquisition and optimization of the independent and dependent variables, model construction and evaluation, etc.) are highlighted. In addition, quantum chemistry, molecular dynamics, and CCS theoretical calculations are also described. Finally, the applications of CCS prediction in metabolomics, natural products, foods, and the other research fields are reflected.
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Affiliation(s)
- Xiaohang Li
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Tianjin 301617, China
- Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Tianjin 301617, China
| | - Hongda Wang
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Tianjin 301617, China
- Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Tianjin 301617, China
| | - Meiting Jiang
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Tianjin 301617, China
- Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Tianjin 301617, China
| | - Mengxiang Ding
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Tianjin 301617, China
- Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Tianjin 301617, China
| | - Xiaoyan Xu
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Tianjin 301617, China
- Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Tianjin 301617, China
| | - Bei Xu
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Tianjin 301617, China
- Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Tianjin 301617, China
| | - Yadan Zou
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Tianjin 301617, China
- Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Tianjin 301617, China
| | - Yuetong Yu
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Tianjin 301617, China
| | - Wenzhi Yang
- State Key Laboratory of Component-Based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Tianjin 301617, China
- Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Tianjin 301617, China
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Bressan C, Celma A, Alechaga É, Monfort N, Ventura R, Sancho JV. Effects of structural characteristics of (un)conjugated steroid metabolites in their collision cross section value. Anal Chim Acta 2023; 1254:341128. [PMID: 37005032 DOI: 10.1016/j.aca.2023.341128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 03/17/2023] [Accepted: 03/20/2023] [Indexed: 04/03/2023]
Abstract
In this work, the collision cross section (CCS) value of 103 steroids (including unconjugated metabolites and phase II metabolites conjugated with sulfate and glucuronide groups) was determined by liquid chromatography coupled to traveling wave ion mobility spectrometry (LC-TWIMS). A time of flight (QTOF) mass analyzer was used to perform the analytes determination at high-resolution mass spectrometry. An electrospray ionization source (ESI) was used to generate [M+H]+, [M + NH4]+ and/or [M - H]- ions. High reproducibility was observed for the CCS determination in both urine and standard solutions, obtaining RSD lower than 0.3% and 0.5% in all cases respectively. CCS determination in matrix was in accordance with the CCS measured in standards solution showing deviations below 2%. In general, CCS values were directly correlated with the ion mass and allowed differentiating between glucuronides, sulfates and free steroids although differences among steroids of the same group were less significant. However, more specific information was obtained for phase II metabolites observing differences in the CCS value of isomeric pairs concerning the conjugation position or the α/β configuration, which could be useful in the structural elucidation of new steroid metabolites in the anti-doping field. Finally, the potential of IMS reducing interferences from the sample matrix was also tested for the analysis of a glucuronide metabolite of bolasterone (5β-androstan-7α,17α-dimethyl-3α,17β-diol-3-glucuronide) in urine samples.
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Affiliation(s)
- Claudia Bressan
- Catalonian Antidoping Laboratory, Doping Control Research Group, Fundació IMIM (Hospital Del Mar Medical Research Institute), Barcelona, Spain
| | - Alberto Celma
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Castelló, Spain; Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Élida Alechaga
- Catalonian Antidoping Laboratory, Doping Control Research Group, Fundació IMIM (Hospital Del Mar Medical Research Institute), Barcelona, Spain; Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
| | - Nuria Monfort
- Catalonian Antidoping Laboratory, Doping Control Research Group, Fundació IMIM (Hospital Del Mar Medical Research Institute), Barcelona, Spain
| | - Rosa Ventura
- Catalonian Antidoping Laboratory, Doping Control Research Group, Fundació IMIM (Hospital Del Mar Medical Research Institute), Barcelona, Spain.
| | - Juan Vicente Sancho
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Castelló, Spain
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11
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Lacalle-Bergeron L, Goterris-Cerisuelo R, Beltran J, Sancho JV, Navarro-Moreno C, Martinez-Garcia F, Portolés T. Untargeted metabolomics approach using UHPLC-IMS-QTOF MS for surface body samples to identify low-volatility chemosignals related to maternal care in mice. Talanta 2023; 258:124389. [PMID: 36867958 DOI: 10.1016/j.talanta.2023.124389] [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: 11/18/2022] [Revised: 02/14/2023] [Accepted: 02/19/2023] [Indexed: 02/25/2023]
Abstract
The present study is focused on the determination of low-volatile chemosignals excreted or secreted by mouse pups in their early days of life involved in maternal care induction in mice adult females. Untargeted metabolomics was employed to differentiate between samples collected with swabs from facial and anogenital area from neonatal mouse pups receiving maternal care (first two weeks of life) and the elder mouse pups in the weaning period (4th week old). The sample extracts were analysed by ultra-high pressure liquid chromatography (UHPLC) coupled to ion mobility separation (IMS) in combination with high resolution mass spectrometry (HRMS). After data processing with Progenesis QI and multivariate statistical analysis, five markers present in the first two weeks of mouse pups life and putatively involved in materno-filial chemical communication were tentatively identified: arginine, urocanic acid, erythro-sphingosine (d17:1), sphingosine (d18:1) and sphinganine. The four-dimensional data and the tools associated to the additional structural descriptor obtained by IMS separation were of great help in the compound identification. The results demonstrated the great potential of UHPLC-IMS-HRMS based untargeted metabolomics to identity putative pheromones in mammals.
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Affiliation(s)
- Leticia Lacalle-Bergeron
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water (IUPA), Universitat Jaume I, Av. Sos Baynat S/N, 12071, Castellón de la Plana, Spain
| | - Rafael Goterris-Cerisuelo
- Laboratory of Functional Neuroanatomy (Unitat Mixta NeuroFun-UV-UJI), Predepartamental Unit of Medicine, Universitat Jaume I, Av. Sos Baynat S/N, 12071, Castellón de la Plana, Spain
| | - Joaquin Beltran
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water (IUPA), Universitat Jaume I, Av. Sos Baynat S/N, 12071, Castellón de la Plana, Spain
| | - Juan Vicente Sancho
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water (IUPA), Universitat Jaume I, Av. Sos Baynat S/N, 12071, Castellón de la Plana, Spain
| | - Cinta Navarro-Moreno
- Laboratory of Functional Neuroanatomy (Unitat Mixta NeuroFun-UV-UJI), Predepartamental Unit of Medicine, Universitat Jaume I, Av. Sos Baynat S/N, 12071, Castellón de la Plana, Spain
| | - Fernando Martinez-Garcia
- Laboratory of Functional Neuroanatomy (Unitat Mixta NeuroFun-UV-UJI), Predepartamental Unit of Medicine, Universitat Jaume I, Av. Sos Baynat S/N, 12071, Castellón de la Plana, Spain
| | - Tania Portolés
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water (IUPA), Universitat Jaume I, Av. Sos Baynat S/N, 12071, Castellón de la Plana, Spain.
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12
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Collision Cross Section Prediction with Molecular Fingerprint Using Machine Learning. Molecules 2022; 27:molecules27196424. [PMID: 36234961 PMCID: PMC9572128 DOI: 10.3390/molecules27196424] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 09/16/2022] [Accepted: 09/19/2022] [Indexed: 11/16/2022] Open
Abstract
High-resolution mass spectrometry is a promising technique in non-target screening (NTS) to monitor contaminants of emerging concern in complex samples. Current chemical identification strategies in NTS experiments typically depend on spectral libraries, chemical databases, and in silico fragmentation tools. However, small molecule identification remains challenging due to the lack of orthogonal sources of information (e.g., unique fragments). Collision cross section (CCS) values measured by ion mobility spectrometry (IMS) offer an additional identification dimension to increase the confidence level. Thanks to the advances in analytical instrumentation, an increasing application of IMS hybrid with high-resolution mass spectrometry (HRMS) in NTS has been reported in the recent decades. Several CCS prediction tools have been developed. However, limited CCS prediction methods were based on a large scale of chemical classes and cross-platform CCS measurements. We successfully developed two prediction models using a random forest machine learning algorithm. One of the approaches was based on chemicals’ super classes; the other model was direct CCS prediction using molecular fingerprint. Over 13,324 CCS values from six different laboratories and PubChem using a variety of ion-mobility separation techniques were used for training and testing the models. The test accuracy for all the prediction models was over 0.85, and the median of relative residual was around 2.2%. The models can be applied to different IMS platforms to eliminate false positives in small molecule identification.
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