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SONG Y, QI Z, CAI Z. [Application of multiomics mass spectrometry in the research of chemical exposome]. Se Pu 2024; 42:120-130. [PMID: 38374592 PMCID: PMC10877483 DOI: 10.3724/sp.j.1123.2023.10001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Indexed: 02/21/2024] Open
Abstract
Environmental factors, such as environmental pollutants, behaviors, and lifestyles, are the leading causes of chronic noncommunicable diseases. Estimates indicate that approximately 50% of all deaths worldwide can be attributed to environmental factors. The exposome is defined as the totality of human environmental (i.e., all nongenetic) exposures from conception, including general external exposure (e.g., climate, education, and urban environment), specific external exposure (e.g., pollution, physical activity, and diet), and internal exposure (e.g., metabolic factors, oxidative stress, inflammation, and protein modification). As a new paradigm, this concept aims to comprehensively understand the link between human health and environmental factors. Therefore, a comprehensive measurement of the exposome, including accurate and reliable measurements of exposure to the external environment and a wide range of biological responses to the internal environment, is of great significance. The measurement of the general external exposome depends on advances in environmental sensors, personal-sensing technologies, and geographical information systems. The determination of exogenous chemicals to which individuals are exposed and endogenous chemicals that are produced or modified by external stressors relies on improvements in methodology and the development of instrumental approaches, including colorimetric, chromatographic, spectral, and mass-spectrometric methods. This article reviews the research strategies for chemical exposomes and summarizes existing exposome-measurement methods, focusing on mass spectrometry (MS)-based methods. The top-down and bottom-up approaches are commonly used in exposome studies. The bottom-up approach focuses on the identification of chemicals in the external environment (e.g., soil, water, diet, and air), whereas the top-down approach focuses on the evaluation of endogenous chemicals and biological processes in biological samples (e.g., blood, urine, and serum). Low- and high-resolution MS (LRMS and HRMS, respectively) have become the most popular methods for the direct measurement of exogenous and endogenous chemicals owing to their superior sensitivity, specificity, and dynamic range. LRMS has been widely applied in the targeted analysis of expected chemicals, whereas HRMS is a promising technique for the suspect and unknown screening of unexpected chemicals. The development of MS-based multiomics, including proteomics, metabolomics, epigenomics, and spatial omics, provides new opportunities to understand the effects of environmental exposure on human health. Metabolomics involves the sum of all low-molecular-weight metabolites in a living system. Nontargeted metabolomics can measure both endogenous and exogenous chemicals, which would directly link exposure to biological effects, internal dose, and disease pathobiology, whereas proteomics could play an important role in predicting potential adverse health outcomes and uncovering molecular mechanisms. MS imaging (MSI) is an emerging technique that provides unlabeled in-depth measurements of endogenous and exogenous molecules directly from tissue and cell sections without changing their spatial information. MSI-based spatial omics, which has been widely applied in biomarker discovery for clinical diagnosis, as well as drug and pollutant monitoring, is expected to become an effective method for exposome measurement. Integrating these response measurements from metabolomics, proteomics, spatial omics, and epigenomics will enable the generation of new hypotheses to discover the etiology of diseases caused by chemical exposure. Finally, we highlight the major challenges in achieving chemical exposome measurements.
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Muller HB, Scholl G, Far J, De Pauw E, Eppe G. Sliding Windows in Ion Mobility (SWIM): A New Approach to Increase the Resolving Power in Trapped Ion Mobility-Mass Spectrometry Hyphenated with Chromatography. Anal Chem 2023; 95:17586-17594. [PMID: 37976440 DOI: 10.1021/acs.analchem.3c03039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2023]
Abstract
Over the past decade, the separation efficiency achieved by linear IMS instruments has increased substantially, with state-of-the-art IM technologies, such as the trapped ion mobility (TIMS), the cyclic traveling wave ion mobility (cTWIMS), and the structure for lossless ion manipulation (SLIM) platforms commonly demonstrating resolving powers in excess of 200. However, for complex sample analysis that require front end separation, the achievement of such high resolving power in TIMS is significantly hampered, since the ion mobility range must be broad enough to analyze all the classes of compounds of interest, whereas the IM analysis time must be short enough to cope with the time scale of the preseparation technique employed. In this paper, we introduce the concept of sliding windows in ion mobility (SWIM) for chromatography hyphenated TIMS applications that bypasses the need to use a wide and fixed IM range by using instead narrow and mobile ion mobility windows that adapt to the analytes' ion mobility during chromatographic separation. GC-TIMS-MS analysis of a mixture of 174 standards from several halogenated persistent organic pollutant (POP) classes, including chlorinated and brominated dioxins, biphenyls, and PBDEs, demonstrated that the average IM resolving power could be increased up to 40% when the SWIM mode was used, thereby greatly increasing the method selectivity for the analysis of complex samples.
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Affiliation(s)
- Hugo B Muller
- Mass Spectrometry Laboratory, University of Liège, Liège 4000, Belgium
| | - Georges Scholl
- Mass Spectrometry Laboratory, University of Liège, Liège 4000, Belgium
| | - Johann Far
- Mass Spectrometry Laboratory, University of Liège, Liège 4000, Belgium
| | - Edwin De Pauw
- Mass Spectrometry Laboratory, University of Liège, Liège 4000, Belgium
| | - Gauthier Eppe
- Mass Spectrometry Laboratory, University of Liège, Liège 4000, Belgium
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Riboni N, Bianchi F, Mattarozzi M, Caldara M, Gullì M, Graziano S, Maestri E, Marmiroli N, Careri M. Ultra-high Performance Liquid Chromatography-Ion Mobility-High-Resolution Mass Spectrometry to Evaluate the Metabolomic Response of Durum Wheat to Sustainable Treatments. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2023; 71:15407-15416. [PMID: 37796632 PMCID: PMC10591464 DOI: 10.1021/acs.jafc.3c04532] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 09/07/2023] [Accepted: 09/22/2023] [Indexed: 10/07/2023]
Abstract
Sustainable agriculture aims at achieving a healthy food production while reducing the use of fertilizers and greenhouse gas emissions using biostimulants and soil amendments. Untargeted metabolomics by ultra-high performance liquid chromatography-ion mobility-high-resolution mass spectrometry, operating in a high-definition MSE mode, was applied to investigate the metabolome of durum wheat in response to sustainable treatments, i.e., the addition of biochar, commercial plant growth promoting microbes, and their combination. Partial least squares-discriminant analysis provided a good discrimination among treatments with sensitivity, specificity, and a non-error rate close to 1. A total of 88 and 45 discriminant compounds having biological, nutritional, and technological implications were tentatively identified in samples grown in 2020 and 2021. The addition of biochar-biostimulants produced the highest up-regulation of lipids and flavonoids, with the glycolipid desaturation being the most impacted pathway, whereas carbohydrates were mostly down-regulated. The findings achieved suggest the safe use of the combined biochar-biostimulant treatment for sustainable wheat cultivation.
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Affiliation(s)
- Nicolò Riboni
- Department
of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area delle Scienze 11/A-17/A, 43124 Parma, Italy
| | - Federica Bianchi
- Department
of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area delle Scienze 11/A-17/A, 43124 Parma, Italy
- Center
for Energy and Environment (CIDEA), Centro Santa Elisabetta, University of Parma, Parco Area delle Scienze 95, 43124 Parma, Italy
| | - Monica Mattarozzi
- Department
of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area delle Scienze 11/A-17/A, 43124 Parma, Italy
- Interdepartmental
Center SITEIA.PARMA, University of Parma, Parco Area delle Scienze 181/A, 43124 Parma, Italy
| | - Marina Caldara
- Department
of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area delle Scienze 11/A-17/A, 43124 Parma, Italy
| | - Mariolina Gullì
- Department
of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area delle Scienze 11/A-17/A, 43124 Parma, Italy
- Interdepartmental
Center SITEIA.PARMA, University of Parma, Parco Area delle Scienze 181/A, 43124 Parma, Italy
| | - Sara Graziano
- Interdepartmental
Center SITEIA.PARMA, University of Parma, Parco Area delle Scienze 181/A, 43124 Parma, Italy
| | - Elena Maestri
- Department
of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area delle Scienze 11/A-17/A, 43124 Parma, Italy
- Interdepartmental
Center SITEIA.PARMA, University of Parma, Parco Area delle Scienze 181/A, 43124 Parma, Italy
| | - Nelson Marmiroli
- Department
of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area delle Scienze 11/A-17/A, 43124 Parma, Italy
- Centro
Santa Elisabetta, National Interuniversity
Center for Environmental Sciences (CINSA), Parco Area delle Scienze 95, 43124 Parma, Italy
| | - Maria Careri
- Department
of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area delle Scienze 11/A-17/A, 43124 Parma, Italy
- Interdepartmental
Center SITEIA.PARMA, University of Parma, Parco Area delle Scienze 181/A, 43124 Parma, Italy
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4
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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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Christofi E, Barran P. Ion Mobility Mass Spectrometry (IM-MS) for Structural Biology: Insights Gained by Measuring Mass, Charge, and Collision Cross Section. Chem Rev 2023; 123:2902-2949. [PMID: 36827511 PMCID: PMC10037255 DOI: 10.1021/acs.chemrev.2c00600] [Citation(s) in RCA: 38] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/26/2023]
Abstract
The investigation of macromolecular biomolecules with ion mobility mass spectrometry (IM-MS) techniques has provided substantial insights into the field of structural biology over the past two decades. An IM-MS workflow applied to a given target analyte provides mass, charge, and conformation, and all three of these can be used to discern structural information. While mass and charge are determined in mass spectrometry (MS), it is the addition of ion mobility that enables the separation of isomeric and isobaric ions and the direct elucidation of conformation, which has reaped huge benefits for structural biology. In this review, where we focus on the analysis of proteins and their complexes, we outline the typical features of an IM-MS experiment from the preparation of samples, the creation of ions, and their separation in different mobility and mass spectrometers. We describe the interpretation of ion mobility data in terms of protein conformation and how the data can be compared with data from other sources with the use of computational tools. The benefit of coupling mobility analysis to activation via collisions with gas or surfaces or photons photoactivation is detailed with reference to recent examples. And finally, we focus on insights afforded by IM-MS experiments when applied to the study of conformationally dynamic and intrinsically disordered proteins.
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Affiliation(s)
- Emilia Christofi
- Michael Barber Centre for Collaborative Mass Spectrometry, Manchester Institute of Biotechnology, University of Manchester, Princess Street, Manchester M1 7DN, United Kingdom
| | - Perdita Barran
- Michael Barber Centre for Collaborative Mass Spectrometry, Manchester Institute of Biotechnology, University of Manchester, Princess Street, Manchester M1 7DN, United Kingdom
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Belova L, Celma A, Van Haesendonck G, Lemière F, Sancho JV, Covaci A, van Nuijs ALN, Bijlsma L. Revealing the differences in collision cross section values of small organic molecules acquired by different instrumental designs and prediction models. Anal Chim Acta 2022; 1229:340361. [PMID: 36156233 DOI: 10.1016/j.aca.2022.340361] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 08/31/2022] [Accepted: 09/02/2022] [Indexed: 11/17/2022]
Abstract
The number of open access databases containing experimental and predicted collision cross section (CCS) values is rising and leads to their increased use for compound identification. However, the reproducibility of reference values with different instrumental designs and the comparison between predicted and experimental CCS values is still under evaluation. This study compared experimental CCS values of 56 small molecules (Contaminants of Emerging Concern) acquired by both drift tube (DT) and travelling wave (TW) ion mobility mass spectrometry (IM-MS). The TWIM-MS included two instrumental designs (Synapt G2 and VION). The experimental TWCCSN2 values obtained by the TWIM-MS systems showed absolute percent errors (APEs) < 2% in comparison to experimental DTIMS data, indicating a good correlation between the datasets. Furthermore, TWCCSN2 values of [M - H]- ions presented the lowest APEs. An influence of the compound class on APEs was observed. The applicability of prediction models based on artificial neural networks (ANN) and multivariate adaptive regression splines (MARS), both built using TWIM-MS data, was investigated for the first time for the prediction of DTCCSN2 values. For [M+H]+ and [M - H]- ions, the 95th percentile confidence intervals of observed APEs were comparable to values reported for both models indicating a good applicability for DTIMS predictions. For the prediction of DTCCSN2 values of [M+Na]+ ions, the MARS based model provided the best results with 73.9% of the ions showing APEs below the threshold reported for [M+Na]+. Finally, recommendations for database transfer and applications of prediction models for future DTIMS studies are made.
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Affiliation(s)
- Lidia Belova
- Toxicological Centre, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Belgium.
| | - Alberto Celma
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Avinguda de Vicent Sos Baynat, 12006, Castelló, Spain
| | - Glenn Van Haesendonck
- Biomolecular & Analytical Mass Spectrometry (BAMS) Group, University of Antwerp, Groenenborgerlaan 171, 2020, Antwerp, Belgium
| | - Filip Lemière
- Biomolecular & Analytical Mass Spectrometry (BAMS) Group, University of Antwerp, Groenenborgerlaan 171, 2020, Antwerp, Belgium
| | - Juan Vicente Sancho
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Avinguda de Vicent Sos Baynat, 12006, Castelló, Spain
| | - Adrian Covaci
- Toxicological Centre, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Belgium
| | | | - Lubertus Bijlsma
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Avinguda de Vicent Sos Baynat, 12006, Castelló, Spain.
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7
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Paglia G, Smith AJ, Astarita G. Ion mobility mass spectrometry in the omics era: Challenges and opportunities for metabolomics and lipidomics. MASS SPECTROMETRY REVIEWS 2022; 41:722-765. [PMID: 33522625 DOI: 10.1002/mas.21686] [Citation(s) in RCA: 84] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 01/17/2021] [Accepted: 01/17/2021] [Indexed: 06/12/2023]
Abstract
Researchers worldwide are taking advantage of novel, commercially available, technologies, such as ion mobility mass spectrometry (IM-MS), for metabolomics and lipidomics applications in a variety of fields including life, biomedical, and food sciences. IM-MS provides three main technical advantages over traditional LC-MS workflows. Firstly, in addition to mass, IM-MS allows collision cross-section values to be measured for metabolites and lipids, a physicochemical identifier related to the chemical shape of an analyte that increases the confidence of identification. Second, IM-MS increases peak capacity and the signal-to-noise, improving fingerprinting as well as quantification, and better defining the spatial localization of metabolites and lipids in biological and food samples. Third, IM-MS can be coupled with various fragmentation modes, adding new tools to improve structural characterization and molecular annotation. Here, we review the state-of-the-art in IM-MS technologies and approaches utilized to support metabolomics and lipidomics applications and we assess the challenges and opportunities in this growing field.
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Affiliation(s)
- Giuseppe Paglia
- School of Medicine and Surgery, University of Milano-Bicocca, Vedano al Lambro (MB), Italy
| | - Andrew J Smith
- School of Medicine and Surgery, University of Milano-Bicocca, Vedano al Lambro (MB), Italy
| | - Giuseppe Astarita
- Department of Biochemistry and Molecular & Cellular Biology, Georgetown University, Washington, District of Columbia, USA
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Delvaux A, Rathahao-Paris E, Alves S. Different ion mobility-mass spectrometry coupling techniques to promote metabolomics. MASS SPECTROMETRY REVIEWS 2022; 41:695-721. [PMID: 33492707 DOI: 10.1002/mas.21685] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Metabolomics has become increasingly popular in recent years for many applications ranging from clinical diagnosis, human health to biotechnological questioning. Despite technological advances, metabolomic studies are still currently limited by the difficulty of identifying all metabolites, a class of compounds with great chemical diversity. Although lengthy chromatographic analyses are often used to obtain comprehensive data, many isobar and isomer metabolites still remain unresolved, which is a critical point for the compound identification. Currently, ion mobility spectrometry is being explored in metabolomics as a way to improve metabolome coverage, analysis throughput and isomer separation. In this review, all the steps of a typical workflow for untargeted metabolomics are discussed considering the use of an ion mobility instrument. An overview of metabolomics is first presented followed by a brief description of ion mobility instrumentation. The ion mobility potential for complex mixture analysis is discussed regarding its coupling with a mass spectrometer alone, providing gas-phase separation before mass analysis as well as its combination with different separation platforms (conventional hyphenation but also multidimensional ion mobility couplings), offering multidimensional separation. Various instrumental and analytical conditions for improving the ion mobility separation are also described. Finally, data mining, including software packages and visualization approaches, as well as the construction of ion mobility databases for the metabolite identification are examined.
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Affiliation(s)
- Aurélie Delvaux
- Faculté des Sciences et de l'Ingénierie, Institut Parisien de Chimie Moléculaire (IPCM), Sorbonne Université, Paris, 75005, France
| | - Estelle Rathahao-Paris
- Faculté des Sciences et de l'Ingénierie, Institut Parisien de Chimie Moléculaire (IPCM), Sorbonne Université, Paris, 75005, France
- Département Médicaments et Technologies pour la Santé (DMTS), SPI, Université Paris-Saclay, CEA, INRAE, Gif-sur-Yvette, 91191, France
| | - Sandra Alves
- Faculté des Sciences et de l'Ingénierie, Institut Parisien de Chimie Moléculaire (IPCM), Sorbonne Université, Paris, 75005, France
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Stecker MM, Peltier MR, Reiss AB. The role of massive demographic databases in intractable illnesses: Denomics for dementia. AIMS Public Health 2022; 9:618-629. [PMID: 36330282 PMCID: PMC9581740 DOI: 10.3934/publichealth.2022043] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 08/10/2022] [Accepted: 08/14/2022] [Indexed: 07/26/2023] Open
Abstract
Despite intensive research, effective treatments for many common and devastating diseases are lacking. For example, huge efforts and billions of dollars have been invested in Alzheimer's disease (AD), which affects over 50 million people worldwide. However, there is still no effective drug that can slow or cure AD. This relates, in part, to the absence of an animal model or cellular system that incorporates all the relevant features of the disease. Therefore, large scale studies on human populations and tissues will be key to better understanding dementia and developing methods to prevent or treat it. This is especially difficult because the dementia phenotype can result from many different processes and is likely to be affected by multiple personal and environmental variables. We hypothesize that analyzing massive volumes of demographic data that are currently available and combining this with genomic, proteomic, and metabolomic profiles of AD patients and their families, new insights into pathophysiology and treatment of AD may arise. While this requires much coordination and cooperation among large institutions, the potential for advancement would be life-changing for millions of people. In many ways this represents the next step in the information revolution started by the Human Genome Project.
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Affiliation(s)
| | - Morgan R. Peltier
- Department of Psychiatry, Hackensack Meridian Health, Neptune City, NJ 07753, USA
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Costalunga R, Tshepelevitsh S, Sepman H, Kull M, Kruve A. Sodium adduct formation with graph-based machine learning can aid structural elucidation in non-targeted LC/ESI/HRMS. Anal Chim Acta 2022; 1204:339402. [PMID: 35397906 DOI: 10.1016/j.aca.2021.339402] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 12/07/2021] [Accepted: 12/23/2021] [Indexed: 11/01/2022]
Abstract
Non-targeted screening with LC/ESI/HRMS aims to identify the structure of the detected compounds using their retention time, exact mass, and fragmentation pattern. Challenges remain in differentiating between isomeric compounds. One untapped possibility to facilitate identification of isomers relies on different ionic species formed in electrospray. In positive ESI mode, both protonated molecules and adducts can be formed; however, not all isomeric structures form the same ionic species. The complicated mechanism of adduct formation has hindered the use of this molecular characteristic in the structural elucidation in non-targeted screening. Here, we have studied the adduct formation for 94 small molecules with ion mobility spectra and compared collision cross-sections of the respective ions. Based on the results we developed a fast support vector machine classifier with polynomial kernels for accurately predicting the sodium adduct formation in ESI/HRMS. The model is trained on five independent data sets from different laboratories and uses the graph-based connectivity of functional groups and PubChem fingerprints to predict the sodium adduct formation in ESI/HRMS. The validation of the model showed an accuracy of 74.7% (balanced accuracy 70.0%) on a dataset from an independent laboratory, which was not used in the training of the model. Lastly, we applied the classification algorithm to the SusDat database by NORMAN network to evaluate the proportion of isomeric compounds that could be distinguished based on predicted sodium adduct formation. It was observed that sodium adduct formation probability can provide additional selectivity for about one quarter of the exact masses and, therefore, shows practical utility for structural assignment in non-targeted screening.
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Affiliation(s)
- Riccardo Costalunga
- Department of Materials and Environmental Chemistry, Stockholm University, Svante Arrhenius väg 16, 106 91, Stockholm, Sweden; Department of Food and Drug, University of Parma, via Università, 12, I 43121, Parma, Italy
| | - Sofja Tshepelevitsh
- Institute of Chemistry, University of Tartu, Ravila 14a, Tartu, 50411, Estonia
| | - Helen Sepman
- Department of Materials and Environmental Chemistry, Stockholm University, Svante Arrhenius väg 16, 106 91, Stockholm, Sweden
| | - Meelis Kull
- Institute of Computer Science, University of Tartu, Narva mnt 18, 51009, Tartu, Estonia
| | - Anneli Kruve
- Department of Materials and Environmental Chemistry, Stockholm University, Svante Arrhenius väg 16, 106 91, Stockholm, Sweden.
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11
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Colby SM, Chang CH, Bade JL, Nunez JR, Blumer MR, Orton DJ, Bloodsworth KJ, Nakayasu ES, Smith RD, Ibrahim YM, Renslow RS, Metz TO. DEIMoS: An Open-Source Tool for Processing High-Dimensional Mass Spectrometry Data. Anal Chem 2022; 94:6130-6138. [PMID: 35430813 PMCID: PMC9047447 DOI: 10.1021/acs.analchem.1c05017] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 04/05/2022] [Indexed: 01/06/2023]
Abstract
We present DEIMoS: Data Extraction for Integrated Multidimensional Spectrometry, a Python application programming interface (API) and command-line tool for high-dimensional mass spectrometry data analysis workflows that offers ease of development and access to efficient algorithmic implementations. Functionality includes feature detection, feature alignment, collision cross section (CCS) calibration, isotope detection, and MS/MS spectral deconvolution, with the output comprising detected features aligned across study samples and characterized by mass, CCS, tandem mass spectra, and isotopic signature. Notably, DEIMoS operates on N-dimensional data, largely agnostic to acquisition instrumentation; algorithm implementations simultaneously utilize all dimensions to (i) offer greater separation between features, thus improving detection sensitivity, (ii) increase alignment/feature matching confidence among data sets, and (iii) mitigate convolution artifacts in tandem mass spectra. We demonstrate DEIMoS with LC-IMS-MS/MS metabolomics data to illustrate the advantages of a multidimensional approach in each data processing step.
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Affiliation(s)
- Sean M. Colby
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352 United States
| | - Christine H. Chang
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352 United States
| | - Jessica L. Bade
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352 United States
| | - Jamie R. Nunez
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352 United States
| | - Madison R. Blumer
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352 United States
| | - Daniel J. Orton
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352 United States
| | - Kent J. Bloodsworth
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352 United States
| | - Ernesto S. Nakayasu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352 United States
| | - Richard D. Smith
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352 United States
| | - Yehia M. Ibrahim
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352 United States
| | - Ryan S. Renslow
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352 United States
| | - Thomas O. Metz
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352 United States
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12
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David A, Chaker J, Price EJ, Bessonneau V, Chetwynd AJ, Vitale CM, Klánová J, Walker DI, Antignac JP, Barouki R, Miller GW. Towards a comprehensive characterisation of the human internal chemical exposome: Challenges and perspectives. ENVIRONMENT INTERNATIONAL 2021; 156:106630. [PMID: 34004450 DOI: 10.1016/j.envint.2021.106630] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Revised: 04/15/2021] [Accepted: 05/03/2021] [Indexed: 05/18/2023]
Abstract
The holistic characterisation of the human internal chemical exposome using high-resolution mass spectrometry (HRMS) would be a step forward to investigate the environmental ætiology of chronic diseases with an unprecedented precision. HRMS-based methods are currently operational to reproducibly profile thousands of endogenous metabolites as well as externally-derived chemicals and their biotransformation products in a large number of biological samples from human cohorts. These approaches provide a solid ground for the discovery of unrecognised biomarkers of exposure and metabolic effects associated with many chronic diseases. Nevertheless, some limitations remain and have to be overcome so that chemical exposomics can provide unbiased detection of chemical exposures affecting disease susceptibility in epidemiological studies. Some of these limitations include (i) the lack of versatility of analytical techniques to capture the wide diversity of chemicals; (ii) the lack of analytical sensitivity that prevents the detection of exogenous (and endogenous) chemicals occurring at (ultra) trace levels from restricted sample amounts, and (iii) the lack of automation of the annotation/identification process. In this article, we discuss a number of technological and methodological limitations hindering applications of HRMS-based methods and propose initial steps to push towards a more comprehensive characterisation of the internal chemical exposome. We also discuss other challenges including the need for harmonisation and the difficulty inherent in assessing the dynamic nature of the internal chemical exposome, as well as the need for establishing a strong international collaboration, high level networking, and sustainable research infrastructure. A great amount of research, technological development and innovative bio-informatics tools are still needed to profile and characterise the "invisible" (not profiled), "hidden" (not detected) and "dark" (not annotated) components of the internal chemical exposome and concerted efforts across numerous research fields are paramount.
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Affiliation(s)
- Arthur David
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35000 Rennes, France.
| | - Jade Chaker
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35000 Rennes, France
| | - Elliott J Price
- Faculty of Sports Studies, Masaryk University, Brno, Czech Republic; RECETOX Centre, Masaryk University, Brno, Czech Republic
| | - Vincent Bessonneau
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, F-35000 Rennes, France
| | - Andrew J Chetwynd
- School of Geography Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
| | | | - Jana Klánová
- RECETOX Centre, Masaryk University, Brno, Czech Republic
| | - Douglas I Walker
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | | | - Robert Barouki
- Unité UMR-S 1124 Inserm-Université Paris Descartes "Toxicologie Pharmacologie et Signalisation Cellulaire", Paris, France
| | - Gary W Miller
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
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13
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Tinte MM, Chele KH, van der Hooft JJJ, Tugizimana F. Metabolomics-Guided Elucidation of Plant Abiotic Stress Responses in the 4IR Era: An Overview. Metabolites 2021; 11:445. [PMID: 34357339 PMCID: PMC8305945 DOI: 10.3390/metabo11070445] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 06/30/2021] [Accepted: 07/03/2021] [Indexed: 12/27/2022] Open
Abstract
Plants are constantly challenged by changing environmental conditions that include abiotic stresses. These are limiting their development and productivity and are subsequently threatening our food security, especially when considering the pressure of the increasing global population. Thus, there is an urgent need for the next generation of crops with high productivity and resilience to climate change. The dawn of a new era characterized by the emergence of fourth industrial revolution (4IR) technologies has redefined the ideological boundaries of research and applications in plant sciences. Recent technological advances and machine learning (ML)-based computational tools and omics data analysis approaches are allowing scientists to derive comprehensive metabolic descriptions and models for the target plant species under specific conditions. Such accurate metabolic descriptions are imperatively essential for devising a roadmap for the next generation of crops that are resilient to environmental deterioration. By synthesizing the recent literature and collating data on metabolomics studies on plant responses to abiotic stresses, in the context of the 4IR era, we point out the opportunities and challenges offered by omics science, analytical intelligence, computational tools and big data analytics. Specifically, we highlight technological advancements in (plant) metabolomics workflows and the use of machine learning and computational tools to decipher the dynamics in the chemical space that define plant responses to abiotic stress conditions.
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Affiliation(s)
- Morena M. Tinte
- Department of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg 2006, South Africa; (M.M.T.); (K.H.C.)
| | - Kekeletso H. Chele
- Department of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg 2006, South Africa; (M.M.T.); (K.H.C.)
| | | | - Fidele Tugizimana
- Department of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg 2006, South Africa; (M.M.T.); (K.H.C.)
- International Research and Development Division, Omnia Group, Ltd., Johannesburg 2021, South Africa
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14
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Borges R, Colby SM, Das S, Edison AS, Fiehn O, Kind T, Lee J, Merrill AT, Merz KM, Metz TO, Nunez JR, Tantillo DJ, Wang LP, Wang S, Renslow RS. Quantum Chemistry Calculations for Metabolomics. Chem Rev 2021; 121:5633-5670. [PMID: 33979149 PMCID: PMC8161423 DOI: 10.1021/acs.chemrev.0c00901] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Indexed: 02/07/2023]
Abstract
A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials ("standards"), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building reference libraries, i.e., in silico libraries for "standards-free" identification. In this review, we cover the major roadblocks currently facing metabolomics and discuss applications where quantum chemistry calculations offer a solution. Several successful examples for nuclear magnetic resonance spectroscopy, ion mobility spectrometry, infrared spectroscopy, and mass spectrometry methods are reviewed. Finally, we consider current best practices, sources of error, and provide an outlook for quantum chemistry calculations in metabolomics studies. We expect this review will inspire researchers in the field of small-molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples.
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Affiliation(s)
- Ricardo
M. Borges
- Walter
Mors Institute of Research on Natural Products, Federal University of Rio de Janeiro, Rio de Janeiro 21941-901, Brazil
| | - Sean M. Colby
- Biological
Science Division, Pacific Northwest National
Laboratory, Richland, Washington 99352, United States
| | - Susanta Das
- Department
of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
| | - Arthur S. Edison
- Departments
of Genetics and Biochemistry and Molecular Biology, Complex Carbohydrate
Research Center and Institute of Bioinformatics, University of Georgia, Athens, Georgia 30602, United States
| | - Oliver Fiehn
- West
Coast Metabolomics Center for Compound Identification, UC Davis Genome
Center, University of California, Davis, California 95616, United States
| | - Tobias Kind
- West
Coast Metabolomics Center for Compound Identification, UC Davis Genome
Center, University of California, Davis, California 95616, United States
| | - Jesi Lee
- West
Coast Metabolomics Center for Compound Identification, UC Davis Genome
Center, University of California, Davis, California 95616, United States
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Amy T. Merrill
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Kenneth M. Merz
- Department
of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
| | - Thomas O. Metz
- Biological
Science Division, Pacific Northwest National
Laboratory, Richland, Washington 99352, United States
| | - Jamie R. Nunez
- Biological
Science Division, Pacific Northwest National
Laboratory, Richland, Washington 99352, United States
| | - Dean J. Tantillo
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Lee-Ping Wang
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Shunyang Wang
- West
Coast Metabolomics Center for Compound Identification, UC Davis Genome
Center, University of California, Davis, California 95616, United States
- Department
of Chemistry, University of California, Davis, California 95616, United States
| | - Ryan S. Renslow
- Biological
Science Division, Pacific Northwest National
Laboratory, Richland, Washington 99352, United States
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15
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Belova L, Caballero-Casero N, van Nuijs ALN, Covaci A. Ion Mobility-High-Resolution Mass Spectrometry (IM-HRMS) for the Analysis of Contaminants of Emerging Concern (CECs): Database Compilation and Application to Urine Samples. Anal Chem 2021; 93:6428-6436. [PMID: 33845572 DOI: 10.1021/acs.analchem.1c00142] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Ion mobility mass spectrometry (IM-MS)-derived collision cross section (CCS) values can serve as a valuable additional identification parameter within the analysis of compounds of emerging concern (CEC) in human matrices. This study introduces the first comprehensive database of DTCCSN2 values of 148 CECs and their metabolites including bisphenols, alternative plasticizers (AP), organophosphate flame retardants (OP), perfluoroalkyl chemicals (PFAS), and others. A total of 311 ions were included in the database, whereby the DTCCSN2 values for 113 compounds are reported for the first time. For 105 compounds, more than one ion is reported. Moreover, the DTCCSN2 values of several isomeric CECs and their metabolites are reported to allow a distinction between isomers. Comprehensive quality assurance guidelines were implemented in the workflow of acquiring DTCCSN2 values to ensure reproducible experimental conditions. The reliability and reproducibility of the complied database were investigated by analyzing pooled human urine spiked with 30 AP and OP metabolites at two concentration levels. For all investigated metabolites, the DTCCSN2 values measured in urine showed a percent error of <1% in comparison to database values. DTCCSN2 values of OP metabolites showed an average percent error of 0.12% (50 ng/mL in urine) and 0.15% (20 ng/mL in urine). For AP metabolites, these values were 0.10 and 0.09%, respectively. These results show that the provided database can be of great value for enhanced identification of CECs in environmental and human matrices, which can advance future suspect screening studies on CECs.
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Affiliation(s)
- Lidia Belova
- Toxicological Centre, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
| | | | | | - Adrian Covaci
- Toxicological Centre, University of Antwerp, Universiteitsplein 1, 2610 Antwerp, Belgium
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16
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Roman-Hubers AT, McDonald TJ, Baker ES, Chiu WA, Rusyn I. A Comparative Analysis of Analytical Techniques for Rapid Oil Spill Identification. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2021; 40:1034-1049. [PMID: 33315271 PMCID: PMC8104454 DOI: 10.1002/etc.4961] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2020] [Revised: 11/20/2020] [Accepted: 12/09/2020] [Indexed: 05/25/2023]
Abstract
The complex chemical composition of crude oils presents many challenges for rapid chemical characterization in the case of a spill. A number of approaches are currently used to "fingerprint" petroleum-derived samples. Gas chromatography coupled with mass spectrometry (GC-MS) is the most common, albeit not very rapid, technique; however, with GC-MS alone, it is difficult to resolve the complex substances in crude oils. The present study examined the potential application of ion mobility spectrometry-mass spectrometry (IMS-MS) coupled with chem-informatic analyses as an alternative high-throughput method for the chemical characterization of crude oils. We analyzed 19 crude oil samples from on- and offshore locations in the Gulf of Mexico region in the United States using both GC-MS (biomarkers, gasoline range hydrocarbons, and n-alkanes) and IMS-MS (untargeted analysis). Hierarchical clustering, principal component analysis, and nearest neighbor-based classification were used to examine sample similarity and geographical groupings. We found that direct-injection IMS-MS performed either equally or better than GC-MS in the classification of the origins of crude oils. In addition, IMS-MS greatly increased the sample analysis throughput (minutes vs hours per sample). Finally, a tabletop science-to-practice exercise, utilizing both the GC-MS and IMS-MS data, was conducted with emergency response experts from regulatory agencies and the oil industry. This activity showed that the stakeholders found the IMS-MS data to be highly informative for rapid chemical fingerprinting of complex substances in general and specifically advantageous for accurate and confident source-grouping of crude oils. Collectively, the present study shows the utility of IMS-MS as a technique for rapid fingerprinting of complex samples and demonstrates its advantages over traditional GC-MS-based analyses when used for decision-making in emergency situations. Environ Toxicol Chem 2021;40:1034-1049. © 2020 SETAC.
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Affiliation(s)
- Alina T. Roman-Hubers
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, Texas, USA
- Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, Texas, USA
| | - Thomas J. McDonald
- Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, Texas, USA
- Department of Environmental & Occupational Health, Texas A&M University, College Station, Texas, USA
| | - Erin S. Baker
- Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, Texas, USA
- Department of Chemistry, North Carolina State University, Raleigh, North Carolina, USA
| | - Weihsueh A. Chiu
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, Texas, USA
- Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, Texas, USA
| | - Ivan Rusyn
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, Texas, USA
- Interdisciplinary Faculty of Toxicology, Texas A&M University, College Station, Texas, USA
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17
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Hyötyläinen T. Analytical challenges in human exposome analysis with focus on environmental analysis combined with metabolomics. J Sep Sci 2021; 44:1769-1787. [PMID: 33650238 DOI: 10.1002/jssc.202001263] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 02/23/2021] [Accepted: 02/23/2021] [Indexed: 12/19/2022]
Abstract
Environmental factors, such as chemical exposures, are likely to play a crucial role in the development of several human chronic diseases. However, how the specific exposures contribute to the onset and progress of various diseases is still poorly understood. In part, this is because comprehensive characterization of the chemical exposome is a highly challenging task, both due to its complex dynamic nature as well as due to the analytical challenges. Herein, the analytical challenges in the field of exposome research are reviewed, with specific emphasis on the sampling, sample preparation, and analysis, as well as challenges in the compound identification. The primary focus is on the human chemical exposome, that is, exposures to mixtures of environmental chemicals and its impact on human metabolome. In order to highlight the recent progress in the exposome research in relation to human health and disease, selected examples of human exposome studies are presented.
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Affiliation(s)
- Tuulia Hyötyläinen
- MTM Research Centre, School of Science and Technology, Örebro University, Örebro, Sweden
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18
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Data processing strategies for non-targeted analysis of foods using liquid chromatography/high-resolution mass spectrometry. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2021.116188] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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19
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Conant CR, Attah IK, Garimella SVB, Nagy G, Bilbao A, Smith RD, Ibrahim YM. Evaluation of Waveform Profiles for Traveling Wave Ion Mobility Separations in Structures for Lossless Ion Manipulations. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2021; 32:225-236. [PMID: 33126794 PMCID: PMC8170696 DOI: 10.1021/jasms.0c00282] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Structures for lossless ion manipulations (SLIM) have recently enabled a powerful implementation of traveling wave ion mobility spectrometry (TWIMS) for ultrahigh resolution separations; however, experimental parameters have not been optimized, and potential significant gains may be feasible. Most TWIMS separations have utilized square-shaped waveforms applied by time-dependent voltage stepping across repeating sets of electrodes, but alternative waveforms may provide further improvements to resolution. Here, we characterize five waveforms (including square and sine) in terms of their transmission efficiency, IMS resolution, and resolving power, and explore the effects of TW amplitude and speed on the performance of each. We found, consistent with previous work, separations were generally improved with higher TW amplitudes, moderately improved by lower speeds (limited by ion "surfing" with the waves), and found decreases in signal intensity at the extremes of operating conditions. The triangle and asymmetric "ramp forward" shaped profiles were found to provide modestly greater resolution and resolving power, an observation we tentatively attribute to their relatively uniform fields and minimal low-field regions.
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Affiliation(s)
- Christopher R Conant
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Isaac K Attah
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Sandilya V B Garimella
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Gabe Nagy
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Aivett Bilbao
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Richard D Smith
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Yehia M Ibrahim
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
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20
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An assessment of quality assurance/quality control efforts in high resolution mass spectrometry non-target workflows for analysis of environmental samples. Trends Analyt Chem 2020. [DOI: 10.1016/j.trac.2020.116063] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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21
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Celma A, Sancho JV, Schymanski EL, Fabregat-Safont D, Ibáñez M, Goshawk J, Barknowitz G, Hernández F, Bijlsma L. Improving Target and Suspect Screening High-Resolution Mass Spectrometry Workflows in Environmental Analysis by Ion Mobility Separation. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2020; 54:15120-15131. [PMID: 33207875 DOI: 10.1021/acs.est.0c05713] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Currently, the most powerful approach to monitor organic micropollutants (OMPs) in environmental samples is the combination of target, suspect, and nontarget screening strategies using high-resolution mass spectrometry (HRMS). However, the high complexity of sample matrices and the huge number of OMPs potentially present in samples at low concentrations pose an analytical challenge. Ion mobility separation (IMS) combined with HRMS instruments (IMS-HRMS) introduces an additional analytical dimension, providing extra information, which facilitates the identification of OMPs. The collision cross-section (CCS) value provided by IMS is unaffected by the matrix or chromatographic separation. Consequently, the creation of CCS databases and the inclusion of ion mobility within identification criteria are of high interest for an enhanced and robust screening strategy. In this work, a CCS library for IMS-HRMS, which is online and freely available, was developed for 556 OMPs in both positive and negative ionization modes using electrospray ionization. The inclusion of ion mobility data in widely adopted confidence levels for identification in environmental reporting is discussed. Illustrative examples of OMPs found in environmental samples are presented to highlight the potential of IMS-HRMS and to demonstrate the additional value of CCS data in various screening strategies.
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Affiliation(s)
- Alberto Celma
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Avda. Sos Baynat s/n, E-12071 Castellón, Spain
| | - Juan V Sancho
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Avda. Sos Baynat s/n, E-12071 Castellón, Spain
| | - Emma L Schymanski
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 6, Avenue du Swing, L-4367 Belvaux, Luxembourg
| | - David Fabregat-Safont
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Avda. Sos Baynat s/n, E-12071 Castellón, Spain
| | - María Ibáñez
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Avda. Sos Baynat s/n, E-12071 Castellón, Spain
| | - Jeff Goshawk
- Waters Corporation, Stamford Avenue, Altrincham Road, Wilmslow, Cheshire SK9 4AX, U.K
| | - Gitte Barknowitz
- Waters Corporation, Stamford Avenue, Altrincham Road, Wilmslow, Cheshire SK9 4AX, U.K
| | - Félix Hernández
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Avda. Sos Baynat s/n, E-12071 Castellón, Spain
| | - Lubertus Bijlsma
- Environmental and Public Health Analytical Chemistry, Research Institute for Pesticides and Water, University Jaume I, Avda. Sos Baynat s/n, E-12071 Castellón, Spain
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22
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Mass spectrometry-based metabolomics for an in-depth questioning of human health. Adv Clin Chem 2020; 99:147-191. [PMID: 32951636 DOI: 10.1016/bs.acc.2020.02.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
Today, metabolomics is becoming an indispensable tool to get a more comprehensive analysis of complex living systems, providing insights on multiple aspects of physiology. Although its application in large scale population-based studies is very challenging due to the processing of large sample sets as well as the complexity of data information, its potential to characterize human health is well recognized. Technological advances in metabolomics pave the way for the efficient biomarker discovery of disease etiology, diagnosis and prognosis. Here, different steps of the metabolomics workflow, particularly mass spectrometry-based approaches, are discussed to demonstrate the potential of metabolomics to address biological questioning in human health. First an overview of metabolomics is provided with its interest in human health studies. Analytical development and advances in mass spectrometry instrumentation and computational tools are discussed regarding their application limits. Advancing metabolomics for applicability in human health and large-scale studies is presented and discussed in conclusion.
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23
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Couvillion SP, Agrawal N, Colby SM, Brandvold KR, Metz TO. Who Is Metabolizing What? Discovering Novel Biomolecules in the Microbiome and the Organisms Who Make Them. Front Cell Infect Microbiol 2020; 10:388. [PMID: 32850487 PMCID: PMC7410922 DOI: 10.3389/fcimb.2020.00388] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 06/25/2020] [Indexed: 12/14/2022] Open
Abstract
Even as the field of microbiome research has made huge strides in mapping microbial community composition in a variety of environments and organisms, explaining the phenotypic influences on the host by microbial taxa-both known and unknown-and their specific functions still remain major challenges. A pressing need is the ability to assign specific functions in terms of enzymes and small molecules to specific taxa or groups of taxa in the community. This knowledge will be crucial for advancing personalized therapies based on the targeted modulation of microbes or metabolites that have predictable outcomes to benefit the human host. This perspective article advocates for the combined use of standards-free metabolomics and activity-based protein profiling strategies to address this gap in functional knowledge in microbiome research via the identification of novel biomolecules and the attribution of their production to specific microbial taxa.
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Affiliation(s)
- Sneha P. Couvillion
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States
| | - Neha Agrawal
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States
| | - Sean M. Colby
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States
| | - Kristoffer R. Brandvold
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States
- Elson S. Floyd College of Medicine, Washington State University, Spokane, WA, United States
| | - Thomas O. Metz
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States
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24
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Kaufmann A, Butcher P, Maden K, Walker S, Widmer M. Does the ion mobility resolving power as provided by commercially available ion mobility quadrupole time-of-flight mass spectrometry instruments permit the unambiguous identification of small molecules in complex matrices? Anal Chim Acta 2020; 1107:113-126. [DOI: 10.1016/j.aca.2020.02.032] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 02/10/2020] [Accepted: 02/14/2020] [Indexed: 12/17/2022]
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25
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Graton J, Hernández-Mesa M, Normand S, Dervilly G, Le Questel JY, Le Bizec B. Characterization of Steroids through Collision Cross Sections: Contribution of Quantum Chemistry Calculations. Anal Chem 2020; 92:6034-6042. [DOI: 10.1021/acs.analchem.0c00357] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Affiliation(s)
- Jérôme Graton
- CNRS, CEISAM, UMR 6230, Université de Nantes, Nantes F-44000, France
| | - Maykel Hernández-Mesa
- Laboratoire d’Etude des Résidus et Contaminants dans les Aliments (LABERCA), INRAE, Oniris, Nantes F-44307, France
| | - Samuel Normand
- CNRS, CEISAM, UMR 6230, Université de Nantes, Nantes F-44000, France
| | - Gaud Dervilly
- Laboratoire d’Etude des Résidus et Contaminants dans les Aliments (LABERCA), INRAE, Oniris, Nantes F-44307, France
| | | | - Bruno Le Bizec
- Laboratoire d’Etude des Résidus et Contaminants dans les Aliments (LABERCA), INRAE, Oniris, Nantes F-44307, France
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26
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Hernández-Mesa M, D'Atri V, Barknowitz G, Fanuel M, Pezzatti J, Dreolin N, Ropartz D, Monteau F, Vigneau E, Rudaz S, Stead S, Rogniaux H, Guillarme D, Dervilly G, Le Bizec B. Interlaboratory and Interplatform Study of Steroids Collision Cross Section by Traveling Wave Ion Mobility Spectrometry. Anal Chem 2020; 92:5013-5022. [PMID: 32167758 DOI: 10.1021/acs.analchem.9b05247] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Collision cross section (CCS) databases based on single-laboratory measurements must be cross-validated to extend their use in peak annotation. This work addresses the validation of the first comprehensive TWCCSN2 database for steroids. First, its long-term robustness was evaluated (i.e., a year and a half after database generation; Synapt G2-S instrument; bias within ±1.0% for 157 ions, 95.7% of the total ions). It was further cross-validated by three external laboratories, including two different TWIMS platforms (i.e., Synapt G2-Si and two Vion IMS QToF; bias within the threshold of ±2.0% for 98.8, 79.9, and 94.0% of the total ions detected by each instrument, respectively). Finally, a cross-laboratory TWCCSN2 database was built for 87 steroids (142 ions). The cross-laboratory database consists of average TWCCSN2 values obtained by the four TWIMS instruments in triplicate measurements. In general, lower deviations were observed between TWCCSN2 measurements and reference values when the cross-laboratory database was applied as a reference instead of the single-laboratory database. Relative standard deviations below 1.5% were observed for interlaboratory measurements (<1.0% for 85.2% of ions) and bias between average values and TWCCSN2 measurements was within the range of ±1.5% for 96.8% of all cases. In the context of this interlaboratory study, this threshold was also suitable for TWCCSN2 measurements of steroid metabolites in calf urine. Greater deviations were observed for steroid sulfates in complex urine samples of adult bovines, showing a slight matrix effect. The implementation of a scoring system for the application of the CCS descriptor in peak annotation is also discussed.
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Affiliation(s)
| | - Valentina D'Atri
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, CMU-Rue Michel Servet 1, 1211 Geneva 4, Switzerland
| | - Gitte Barknowitz
- Waters Corporation, Stamford Avenue, Altrincham Road, Wilmslow SK9 4AX, U.K
| | - Mathieu Fanuel
- INRAE, UR1268 Biopolymers Interactions Assemblies (BIA), Rue de la Géraudière B.P. 71627, F-44316 Nantes, France
| | - Julian Pezzatti
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, CMU-Rue Michel Servet 1, 1211 Geneva 4, Switzerland
| | - Nicola Dreolin
- Waters Corporation, Stamford Avenue, Altrincham Road, Wilmslow SK9 4AX, U.K
| | - David Ropartz
- INRAE, UR1268 Biopolymers Interactions Assemblies (BIA), Rue de la Géraudière B.P. 71627, F-44316 Nantes, France
| | | | | | - Serge Rudaz
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, CMU-Rue Michel Servet 1, 1211 Geneva 4, Switzerland
| | - Sara Stead
- Waters Corporation, Stamford Avenue, Altrincham Road, Wilmslow SK9 4AX, U.K
| | - Hélène Rogniaux
- INRAE, UR1268 Biopolymers Interactions Assemblies (BIA), Rue de la Géraudière B.P. 71627, F-44316 Nantes, France
| | - Davy Guillarme
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, CMU-Rue Michel Servet 1, 1211 Geneva 4, Switzerland
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Abstract
This chapter describes the developments in drift-tube ion mobility-mass spectrometry (DTIM-MS) that have driven application development in 'omics analyses. Harnessing the additional, orthogonal separation that DTIM provides increased confidence in compound identifications as the mass spectral complexity can be reduced and mobility-derived parameters (most prominently the collision cross section, CCS) used to support identity confirmation goals for a variety of 'omics application areas. Presented within this contribution is a methodology for improving the transmission and maintaining accurate determination of drift time-derived CCS (DTCCS) for low molecular weight compounds for a typical nontargeted 'omics (metabolomics) workflow using liquid chromatography in combination with DTIM-MS.
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Affiliation(s)
- Tim J Causon
- Institute of Analytical Chemistry, University of Natural Resources and Life Sciences (BOKU), Vienna, Austria.
| | | | - Stephan Hann
- Institute of Analytical Chemistry, University of Natural Resources and Life Sciences (BOKU), Vienna, Austria
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28
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Nuñez JR, Colby SM, Thomas DG, Tfaily MM, Tolic N, Ulrich EM, Sobus JR, Metz TO, Teeguarden JG, Renslow RS. Evaluation of In Silico Multifeature Libraries for Providing Evidence for the Presence of Small Molecules in Synthetic Blinded Samples. J Chem Inf Model 2019; 59:4052-4060. [PMID: 31430141 DOI: 10.1021/acs.jcim.9b00444] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The current gold standard for unambiguous molecular identification in metabolomics analysis is comparing two or more orthogonal properties from the analysis of authentic reference materials (standards) to experimental data acquired in the same laboratory with the same analytical methods. This represents a significant limitation for comprehensive chemical identification of small molecules in complex samples. The process is time consuming and costly, and the majority of molecules are not yet represented by standards. Thus, there is a need to assemble evidence for the presence of small molecules in complex samples through the use of libraries containing calculated chemical properties. To address this need, we developed a Multi-Attribute Matching Engine (MAME) and a library derived in part from our in silico chemical library engine (ISiCLE). Here, we describe an initial evaluation of these methods in a blinded analysis of synthetic chemical mixtures as part of the U.S. Environmental Protection Agency's (EPA) Non-Targeted Analysis Collaborative Trial (ENTACT, Phase 1). For molecules in all mixtures, the initial blinded false negative rate (FNR), false discovery rate (FDR), and accuracy were 57%, 77%, and 91%, respectively. For high evidence scores, the FDR was 35%. After unblinding of the sample compositions, we optimized the scoring parameters to better exploit the available evidence and increased the accuracy for molecules suspected as present. The final FNR, FDR, and accuracy were 67%, 53%, and 96%, respectively. For high evidence scores, the FDR was 10%. This study demonstrates that multiattribute matching methods in conjunction with in silico libraries may one day enable reduced reliance on experimentally derived libraries for building evidence for the presence of molecules in complex samples.
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Affiliation(s)
- Jamie R Nuñez
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Sean M Colby
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Dennis G Thomas
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Malak M Tfaily
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States.,Department of Environmental Science , University of Arizona , Tucson 85712 , United States
| | - Nikola Tolic
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Elin M Ulrich
- U.S. Environmental Protection Agency, Office of Research and Development , National Exposure Research Laboratory , Research Triangle Park , North Carolina 27711 , United States
| | - Jon R Sobus
- U.S. Environmental Protection Agency, Office of Research and Development , National Exposure Research Laboratory , Research Triangle Park , North Carolina 27711 , United States
| | - Thomas O Metz
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Justin G Teeguarden
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States.,Department of Environmental and Molecular Toxicology , Oregon State University , Corvallis , Oregon 97331 , United States
| | - Ryan S Renslow
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
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29
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Xue J, Lai Y, Liu CW, Ru H. Towards Mass Spectrometry-Based Chemical Exposome: Current Approaches, Challenges, and Future Directions. TOXICS 2019; 7:toxics7030041. [PMID: 31426576 PMCID: PMC6789759 DOI: 10.3390/toxics7030041] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Revised: 08/12/2019] [Accepted: 08/14/2019] [Indexed: 12/13/2022]
Abstract
The proposal of the “exposome” concept represents a shift of the research paradigm in studying exposure-disease relationships from an isolated and partial way to a systematic and agnostic approach. Nevertheless, exposome implementation is facing a variety of challenges including measurement techniques and data analysis. Here we focus on the chemical exposome, which refers to the mixtures of chemical pollutants people are exposed to from embryo onwards. We review the current chemical exposome measurement approaches with a focus on those based on the mass spectrometry. We further explore the strategies in implementing the concept of chemical exposome and discuss the available chemical exposome studies. Early progresses in the chemical exposome research are outlined, and major challenges are highlighted. In conclusion, efforts towards chemical exposome have only uncovered the tip of the iceberg, and further advancement in measurement techniques, computational tools, high-throughput data analysis, and standardization may allow more exciting discoveries concerning the role of exposome in human health and disease.
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Affiliation(s)
- Jingchuan Xue
- Center for Environmental Health and Susceptibility, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Yunjia Lai
- Center for Environmental Health and Susceptibility, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Chih-Wei Liu
- Center for Environmental Health and Susceptibility, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Hongyu Ru
- Department of Population Health and Pathobiology, North Carolina State University, Raleigh, NC 27607, USA.
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31
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Nakayasu ES, Qian WJ, Evans-Molina C, Mirmira RG, Eizirik DL, Metz TO. The role of proteomics in assessing beta-cell dysfunction and death in type 1 diabetes. Expert Rev Proteomics 2019; 16:569-582. [PMID: 31232620 PMCID: PMC6628911 DOI: 10.1080/14789450.2019.1634548] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Accepted: 06/18/2019] [Indexed: 12/17/2022]
Abstract
Introduction: Type 1 diabetes (T1D) is characterized by autoimmune-induced dysfunction and destruction of the pancreatic beta cells. Unfortunately, this process is poorly understood, and the current best treatment for type 1 diabetes is the administration of exogenous insulin. To better understand these mechanisms and to develop new therapies, there is an urgent need for biomarkers that can reliably predict disease stage. Areas covered: Mass spectrometry (MS)-based proteomics and complementary techniques play an important role in understanding the autoimmune response, inflammation and beta-cell death. MS is also a leading technology for the identification of biomarkers. This, and the technical difficulties and new technologies that provide opportunities to characterize small amounts of sample in great depth and to analyze large sample cohorts will be discussed in this review. Expert opinion: Understanding disease mechanisms and the discovery of disease-associated biomarkers are highly interconnected goals. Ideal biomarkers would be molecules specific to the different stages of the disease process that are released from beta cells to the bloodstream. However, such molecules are likely to be present in trace amounts in the blood due to the small number of pancreatic beta cells in the human body and the heterogeneity of the target organ and disease process.
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Affiliation(s)
- Ernesto S. Nakayasu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Wei-Jun Qian
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Carmella Evans-Molina
- Center for Diabetes and Metabolic Diseases, Herman B. Wells Center for Pediatric Research, Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Raghavendra G. Mirmira
- Center for Diabetes and Metabolic Diseases, Herman B. Wells Center for Pediatric Research, Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Decio L. Eizirik
- ULB Center for Diabetes Research, Medical Faculty, Université Libre de Bruxelles, Brussels, Belgium
| | - Thomas O. Metz
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
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32
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Ho SM, Lewis JD, Mayer EA, Bernstein CN, Plevy SE, Chuang E, Rappaport SM, Croitoru K, Korzenik JR, Krischer J, Hyams JS, Judson R, Kellis M, Jerrett M, Miller GW, Grant ML, Shtraizent N, Honig G, Hurtado-Lorenzo A, Wu GD. Challenges in IBD Research: Environmental Triggers. Inflamm Bowel Dis 2019; 25:S13-S23. [PMID: 31095702 PMCID: PMC6787673 DOI: 10.1093/ibd/izz076] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Indexed: 02/07/2023]
Abstract
Environmental triggers is part of five focus areas of the Challenges in IBD research document, which also includes preclinical human IBD mechanisms, novel technologies, precision medicine and pragmatic clinical research. The Challenges in IBD research document provides a comprehensive overview of current gaps in inflammatory bowel diseases (IBD) research and delivers actionable approaches to address them. It is the result of a multidisciplinary input from scientists, clinicians, patients, and funders, and represents a valuable resource for patient centric research prioritization. In particular, the environmental triggers section is focused on the main research gaps in elucidating causality of environmental factors in IBD. Research gaps were identified in: 1) epidemiology of exposures; 2) identification of signatures of biological response to exposures; and 3) mechanisms of how environmental exposures drive IBD. To address these gaps, the implementation of longitudinal prospective studies to determine disease evolution and identify sub-clinical changes in response to exposures is proposed. This can help define critical windows of vulnerability and risk prediction. In addition, systems biology analysis and in silico modeling were proposed as approaches to integrate the IBD exposome for the identification of biological signatures of response to exposures, and to develop prediction models of the effects of environmental factors in driving disease activity and response to therapy. This research could lead to identification of biomarkers of exposures and new modalities for therapeutic intervention. Finally, hypothesis-driven mechanistic studies to understand gene-environment interactions and to validate causality of priority factors should be performed to determine how environment influences clinical outcomes.
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Affiliation(s)
| | - James D Lewis
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Emeran A Mayer
- University of California Los Angeles, Los Angeles, California
| | | | | | | | | | | | | | | | - Jeffrey S Hyams
- Connecticut Children’s Medical Center, Hartford, Connecticut
| | - Richard Judson
- United States Environmental Protection Agency, Washington, District of Columbia
| | - Manolis Kellis
- Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Michael Jerrett
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | | | - Melanie L Grant
- Children’s National Health System, Washington, District of Columbia
| | | | - Gerard Honig
- Crohn’s & Colitis Foundation, New York, New York
| | - Andrés Hurtado-Lorenzo
- Crohn’s & Colitis Foundation, New York, New York,Address correspondence to: Andrés Hurtado-Lorenzo, PhD, 733 3rd Ave Suite 510, New York, NY USA 10017 ()
| | - Gary D Wu
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
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33
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Morris CB, May JC, Leaptrot KL, McLean JA. Evaluating Separation Selectivity and Collision Cross Section Measurement Reproducibility in Helium, Nitrogen, Argon, and Carbon Dioxide Drift Gases for Drift Tube Ion Mobility-Mass Spectrometry. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2019; 30:1059-1068. [PMID: 30887459 PMCID: PMC6520154 DOI: 10.1007/s13361-019-02151-4] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 02/05/2019] [Accepted: 02/06/2019] [Indexed: 05/04/2023]
Abstract
Previous ion mobility (IM) studies have demonstrated that varying the drift gas composition can be used to enhance chemical selectivity and resolution, yet there are few drift gas studies aimed at achieving quantitatively reproducible mobility measurements. Here, we critically evaluate the conditions necessary to achieve reproducible collision cross section (CCS) measurements in pure drift gases (helium, nitrogen, argon, and carbon dioxide) using a commercial uniform field drift tube instrument. Optimal experimental parameters are assessed based on the convergence of CCS measurements to reproducible values which are compared with literature values. A suite of calibration standards with diverse masses, biological classes, and charge states are examined to assess chemical selectivity and resolution achievable in each drift gas. Results indicate nitrogen and argon perform similarly and are sufficient for most applications where high resolving power and high peak capacity are desired. Carbon dioxide exhibits more selectivity for resolving structurally heterogeneous compounds, which may be preferable in specific analyte pair separations. Helium demonstrated modest separation capabilities but has utility for comparison to theoretical values and previously published work. In drift gases other than nitrogen, pressure differentials up to 230 mTorr between the drift tube and upstream chamber were optimal for improving correlation to literature values, while in nitrogen, the recommended pressure differential of 150 mTorr was found appropriate. We present recommended experimental parameters as well as gas-specific CCS measurements for structurally homogeneous sets of analytes which are suitable for use by other laboratories as standards for purposes of instrument calibration and overall assessment of IM separation performance.
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Affiliation(s)
- Caleb B Morris
- Center for Innovative Technology, Department of Chemistry, Vanderbilt Institute of Chemical Biology, Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville, TN, USA
| | - Jody C May
- Center for Innovative Technology, Department of Chemistry, Vanderbilt Institute of Chemical Biology, Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville, TN, USA
| | - Katrina L Leaptrot
- Center for Innovative Technology, Department of Chemistry, Vanderbilt Institute of Chemical Biology, Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville, TN, USA
| | - John A McLean
- Center for Innovative Technology, Department of Chemistry, Vanderbilt Institute of Chemical Biology, Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville, TN, USA.
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34
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Morris CB, May JC, Leaptrot KL, McLean JA. Evaluating Separation Selectivity and Collision Cross Section Measurement Reproducibility in Helium, Nitrogen, Argon, and Carbon Dioxide Drift Gases for Drift Tube Ion Mobility-Mass Spectrometry. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2019; 30:1059-1068. [PMID: 30887459 DOI: 10.1021/jasms.8b06014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 02/05/2019] [Accepted: 02/06/2019] [Indexed: 05/18/2023]
Abstract
Previous ion mobility (IM) studies have demonstrated that varying the drift gas composition can be used to enhance chemical selectivity and resolution, yet there are few drift gas studies aimed at achieving quantitatively reproducible mobility measurements. Here, we critically evaluate the conditions necessary to achieve reproducible collision cross section (CCS) measurements in pure drift gases (helium, nitrogen, argon, and carbon dioxide) using a commercial uniform field drift tube instrument. Optimal experimental parameters are assessed based on the convergence of CCS measurements to reproducible values which are compared with literature values. A suite of calibration standards with diverse masses, biological classes, and charge states are examined to assess chemical selectivity and resolution achievable in each drift gas. Results indicate nitrogen and argon perform similarly and are sufficient for most applications where high resolving power and high peak capacity are desired. Carbon dioxide exhibits more selectivity for resolving structurally heterogeneous compounds, which may be preferable in specific analyte pair separations. Helium demonstrated modest separation capabilities but has utility for comparison to theoretical values and previously published work. In drift gases other than nitrogen, pressure differentials up to 230 mTorr between the drift tube and upstream chamber were optimal for improving correlation to literature values, while in nitrogen, the recommended pressure differential of 150 mTorr was found appropriate. We present recommended experimental parameters as well as gas-specific CCS measurements for structurally homogeneous sets of analytes which are suitable for use by other laboratories as standards for purposes of instrument calibration and overall assessment of IM separation performance.
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Affiliation(s)
- Caleb B Morris
- Center for Innovative Technology, Department of Chemistry, Vanderbilt Institute of Chemical Biology, Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville, TN, USA
| | - Jody C May
- Center for Innovative Technology, Department of Chemistry, Vanderbilt Institute of Chemical Biology, Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville, TN, USA
| | - Katrina L Leaptrot
- Center for Innovative Technology, Department of Chemistry, Vanderbilt Institute of Chemical Biology, Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville, TN, USA
| | - John A McLean
- Center for Innovative Technology, Department of Chemistry, Vanderbilt Institute of Chemical Biology, Vanderbilt Institute for Integrative Biosystems Research and Education, Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville, TN, USA.
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35
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Emhofer L, Himmelsbach M, Buchberger W, Klampfl CW. High-performance liquid chromatography drift-tube ion-mobility quadrupole time-of-flight/mass spectrometry for the identity confirmation and characterization of metabolites from three statins (lipid-lowering drugs) in the model plant cress (Lepidium sativum) after uptake from water. J Chromatogr A 2019; 1592:122-132. [DOI: 10.1016/j.chroma.2019.01.049] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Revised: 01/14/2019] [Accepted: 01/17/2019] [Indexed: 10/27/2022]
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36
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Sinclair E, Hollywood KA, Yan C, Blankley R, Breitling R, Barran P. Mobilising ion mobility mass spectrometry for metabolomics. Analyst 2019; 143:4783-4788. [PMID: 30209461 DOI: 10.1039/c8an00902c] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Chromatography-based mass spectrometry approaches (xC-MS) are commonly used in untargeted metabolomics, providing retention time, m/z values and metabolite-specific fragments, all of which are used to identify and validate an unknown analyte. Ion mobility-mass spectrometry (IM-MS) is emerging as an enhancement to classic xC-MS strategies, by offering additional ion separation as well as collision cross section (CCS) determination. In order to apply such an approach to a metabolomics workflow, verified data from metabolite standards is necessary. In this work we present experimental DTCCSN2 values for a range of metabolites in positive and negative ionisation modes using drift tube-ion mobility-mass spectrometry (DT-IM-MS) with nitrogen as the buffer gas. The value of DTCCSN2 measurements for application in metabolite identification relies on a robust technique that acquires measurements of high reproducibility. We report that the CCS values found for 86% of metabolites measured in replicate have a relative standard deviation lower than 0.2%. Examples of metabolites with near identical mass are demonstrated to be separated by ion mobility with over 4% difference in DTCCSN2 values. We conclude that the integration of ion mobility into current LC-MS workflows can aid in small molecule identification for both targeted and untargeted metabolite screening.
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Affiliation(s)
- Eleanor Sinclair
- Michael Barber Centre for Collaborative Mass Spectrometry, Manchester Institute of Biotechnology, School of Chemistry, The University of Manchester, Princess Street, Manchester, M1 7DN, UK.
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37
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Instrumental and technical evolution over the past decade in bioanalysis. Bioanalysis 2019; 11:601-606. [DOI: 10.4155/bio-2018-0327] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
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38
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Garcellano RC, Moinuddin SGA, Young RP, Zhou M, Bowden ME, Renslow RS, Yesiltepe Y, Thomas DG, Colby SM, Chouinard CD, Nagy G, Attah IK, Ibrahim YM, Ma R, Franzblau SG, Lewis NG, Aguinaldo AM, Cort JR. Isolation of Tryptanthrin and Reassessment of Evidence for Its Isobaric Isostere Wrightiadione in Plants of the Wrightia Genus. JOURNAL OF NATURAL PRODUCTS 2019; 82:440-448. [PMID: 30295480 DOI: 10.1021/acs.jnatprod.8b00567] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
A series of Wrightia hanleyi extracts was screened for activity against Mycobacterium tuberculosis H37Rv. One active fraction contained a compound that initially appeared to be either the isoflavonoid wrightiadione or the alkaloid tryptanthrin, both of which have been previously reported in other Wrightia species. Characterization by NMR and MS, as well as evaluation of the literature describing these compounds, led to the conclusion that wrightiadione (1) was misidentified in the first report of its isolation from W. tomentosa in 1992 and again in 2015 when reported in W. pubescens and W. religiosa. Instead, the molecule described in these reports and in the present work is almost certainly the isobaric (same nominal mass) and isosteric (same number of atoms, valency, and shape) tryptanthrin (2), a well-known quinazolinone alkaloid found in a variety of plants including Wrightia species. Tryptanthrin (2) is also accessible synthetically via several routes and has been thoroughly characterized. Wrightiadione (1) has been synthesized and characterized and may have useful biological activity; however, this compound can no longer be said to be known to exist in Nature. To our knowledge, this misidentification of wrightiadione (1) has heretofore been unrecognized.
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Affiliation(s)
- Rhea C Garcellano
- Graduate School , University of Santo Tomas , Manila 1015 , Philippines
- Palawan State University , Tiniguiban Heights, Puerto Princesa City 5300 , Palawan , Philippines
- Institute of Biological Chemistry , Washington State University , Pullman , Washington 99164-6340 , United States
| | - Syed G A Moinuddin
- Institute of Biological Chemistry , Washington State University , Pullman , Washington 99164-6340 , United States
| | - Robert P Young
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Mowei Zhou
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Mark E Bowden
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Ryan S Renslow
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Yasemin Yesiltepe
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Dennis G Thomas
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Sean M Colby
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Christopher D Chouinard
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Gabe Nagy
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Isaac K Attah
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Yehia M Ibrahim
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
| | - Rui Ma
- Institute for Tuberculosis Research, College of Pharmacy , University of Illinois at Chicago , Chicago , Illinois 60612 , United States
| | - Scott G Franzblau
- Institute for Tuberculosis Research, College of Pharmacy , University of Illinois at Chicago , Chicago , Illinois 60612 , United States
| | - Norman G Lewis
- Institute of Biological Chemistry , Washington State University , Pullman , Washington 99164-6340 , United States
| | - Alicia M Aguinaldo
- Graduate School , University of Santo Tomas , Manila 1015 , Philippines
- Phytochemistry Laboratory, Research Center for the Natural and Applied Sciences , University of Santo Tomas , Manila 1015 , Philippines
| | - John R Cort
- Institute of Biological Chemistry , Washington State University , Pullman , Washington 99164-6340 , United States
- Earth and Biological Sciences Directorate , Pacific Northwest National Laboratory , Richland , Washington 99354 , United States
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39
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Hernández-Mesa M, Monteau F, Le Bizec B, Dervilly-Pinel G. Potential of ion mobility-mass spectrometry for both targeted and non-targeted analysis of phase II steroid metabolites in urine. Anal Chim Acta X 2019; 1:100006. [PMID: 33117973 PMCID: PMC7587051 DOI: 10.1016/j.acax.2019.100006] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Revised: 01/16/2019] [Accepted: 01/21/2019] [Indexed: 12/18/2022] Open
Abstract
In recent years, the commercialization of hybrid ion mobility-mass spectrometers and their integration in traditional LC-MS workflows provide new opportunities to extend the current boundaries of targeted and non-targeted analyses. When coupled to LC-MS, ion mobility spectrometry (IMS) provides a novel characterization parameter, the so-called averaged collision cross section (CCS, Ω), as well as improves method selectivity and sensitivity by the separation of isobaric and isomeric molecules and the isolation of the analytes of interest from background noise. In this work, we have explored the potential and advantages of this technology for carrying out the determination of phase II steroid metabolites (i.e. androgen and estrogen conjugates, including glucuronide and sulfate compounds; n = 25) in urine samples. These molecules have been selected based on their relevance in the fields of chemical food safety and doping control, as well as in metabolomics studies. The influence of urine matrix on the CCS of steroid metabolites was evaluated in order to give more confidence to current CCS databases and support its use as complementary information to retention time (Rt) and mass spectra for compound identification. Samples were only diluted 10-fold with aqueous formic acid (0.1%, v/v) prior analysis. Only an almost insignificant effect of adult bovine urine matrix on the CCS of certain steroid metabolites was observed in comparison with calve urine matrix, which is a less complex sample. In addition, high accuracy was achieved for CCS measurements carried out over four months (ΔCCS < 1.3% for 99.8% of CCS measurements; n = 1806). Interestingly, it has been observed that signal-to-noise (S/N) ratio could be improved at least 2 or 7-fold when IMS is combined with LC-MS. In addition to the separation of isomeric steroid pairs (i.e. etiocholanolone glucuronide and epiandrosterone glucuronide, as well as 19-noretiocholanolone glucuronide and 19-norandrosterone glucuronide), steroid-based ions were also separated in the IMS dimension from co-eluting matrix compounds that presented similar mass-to-charge ratio (m/z). Finally, based on CCS measurements and as a proof of concept, 17α-boldenone glucuronide has been identified as one of the main metabolites resulted from boldione administration to calves.
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Affiliation(s)
- Maykel Hernández-Mesa
- Laboratoire d’Etude des Résidus et Contaminants dans les Aliments (LABERCA), Oniris, INRA UMR 1329, UBL, Nantes, F-44307, France
| | - Fabrice Monteau
- Laboratoire d’Etude des Résidus et Contaminants dans les Aliments (LABERCA), Oniris, INRA UMR 1329, UBL, Nantes, F-44307, France
| | - Bruno Le Bizec
- Laboratoire d’Etude des Résidus et Contaminants dans les Aliments (LABERCA), Oniris, INRA UMR 1329, UBL, Nantes, F-44307, France
| | - Gaud Dervilly-Pinel
- Laboratoire d’Etude des Résidus et Contaminants dans les Aliments (LABERCA), Oniris, INRA UMR 1329, UBL, Nantes, F-44307, France
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An automated framework for NMR chemical shift calculations of small organic molecules. J Cheminform 2018; 10:52. [PMID: 30367288 PMCID: PMC6755567 DOI: 10.1186/s13321-018-0305-8] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Accepted: 10/09/2018] [Indexed: 12/04/2022] Open
Abstract
When using nuclear magnetic resonance (NMR) to assist in chemical identification in complex samples, researchers commonly rely on databases for chemical shift spectra. However, authentic standards are typically depended upon to build libraries experimentally. Considering complex biological samples, such as blood and soil, the entirety of NMR spectra required for all possible compounds would be infeasible to ascertain due to limitations of available standards and experimental processing time. As an alternative, we introduce the in silico Chemical Library Engine (ISiCLE) NMR chemical shift module to accurately and automatically calculate NMR chemical shifts of small organic molecules through use of quantum chemical calculations. ISiCLE performs density functional theory (DFT)-based calculations for predicting chemical properties—specifically NMR chemical shifts in this manuscript—via the open source, high-performance computational chemistry software, NWChem. ISiCLE calculates the NMR chemical shifts of sets of molecules using any available combination of DFT method, solvent, and NMR-active nuclei, using both user-selected reference compounds and/or linear regression methods. Calculated NMR chemical shifts are provided to the user for each molecule, along with comparisons with respect to a number of metrics commonly used in the literature. Here, we demonstrate ISiCLE using a set of 312 molecules, ranging in size up to 90 carbon atoms. For each, calculation of NMR chemical shifts have been performed with 8 different levels of DFT theory, and with solvation effects using the implicit solvent Conductor-like Screening Model. The DFT method dependence of the calculated chemical shifts have been systematically investigated through benchmarking and subsequently compared to experimental data available in the literature. Furthermore, ISiCLE has been applied to a set of 80 methylcyclohexane conformers, combined via Boltzmann weighting and compared to experimental values. We demonstrate that our protocol shows promise in the automation of chemical shift calculations and, ultimately, the expansion of chemical shift libraries.
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Ma J, Casey CP, Zheng X, Ibrahim YM, Wilkins CS, Renslow RS, Thomas DG, Payne SH, Monroe ME, Smith RD, Teeguarden JG, Baker ES, Metz TO. PIXiE: an algorithm for automated ion mobility arrival time extraction and collision cross section calculation using global data association. Bioinformatics 2018; 33:2715-2722. [PMID: 28505286 PMCID: PMC5860068 DOI: 10.1093/bioinformatics/btx305] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2016] [Accepted: 05/12/2017] [Indexed: 11/24/2022] Open
Abstract
Motivation Drift tube ion mobility spectrometry coupled with mass spectrometry (DTIMS-MS) is increasingly implemented in high throughput omics workflows, and new informatics approaches are necessary for processing the associated data. To automatically extract arrival times for molecules measured by DTIMS at multiple electric fields and compute their associated collisional cross sections (CCS), we created the PNNL Ion Mobility Cross Section Extractor (PIXiE). The primary application presented for this algorithm is the extraction of data that can then be used to create a reference library of experimental CCS values for use in high throughput omics analyses. Results We demonstrate the utility of this approach by automatically extracting arrival times and calculating the associated CCSs for a set of endogenous metabolites and xenobiotics. The PIXiE-generated CCS values were within error of those calculated using commercially available instrument vendor software. Availability and implementation PIXiE is an open-source tool, freely available on Github. The documentation, source code of the software, and a GUI can be found at https://github.com/PNNL-Comp-Mass-Spec/PIXiE and the source code of the backend workflow library used by PIXiE can be found at https://github.com/PNNL-Comp-Mass-Spec/IMS-Informed-Library. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Jian Ma
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Cameron P Casey
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Xueyun Zheng
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Yehia M Ibrahim
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Christopher S Wilkins
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Ryan S Renslow
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Dennis G Thomas
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Samuel H Payne
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Matthew E Monroe
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Richard D Smith
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Justin G Teeguarden
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA.,Department of Environmental and Molecular Toxicology, Oregon State University, Corvallis, OR 93771, USA
| | - Erin S Baker
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
| | - Thomas O Metz
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
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Blaženović I, Kind T, Ji J, Fiehn O. Software Tools and Approaches for Compound Identification of LC-MS/MS Data in Metabolomics. Metabolites 2018; 8:E31. [PMID: 29748461 PMCID: PMC6027441 DOI: 10.3390/metabo8020031] [Citation(s) in RCA: 373] [Impact Index Per Article: 62.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2018] [Revised: 04/26/2018] [Accepted: 05/06/2018] [Indexed: 01/17/2023] Open
Abstract
The annotation of small molecules remains a major challenge in untargeted mass spectrometry-based metabolomics. We here critically discuss structured elucidation approaches and software that are designed to help during the annotation of unknown compounds. Only by elucidating unknown metabolites first is it possible to biologically interpret complex systems, to map compounds to pathways and to create reliable predictive metabolic models for translational and clinical research. These strategies include the construction and quality of tandem mass spectral databases such as the coalition of MassBank repositories and investigations of MS/MS matching confidence. We present in silico fragmentation tools such as MS-FINDER, CFM-ID, MetFrag, ChemDistiller and CSI:FingerID that can annotate compounds from existing structure databases and that have been used in the CASMI (critical assessment of small molecule identification) contests. Furthermore, the use of retention time models from liquid chromatography and the utility of collision cross-section modelling from ion mobility experiments are covered. Workflows and published examples of successfully annotated unknown compounds are included.
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Affiliation(s)
- Ivana Blaženović
- NIH West Coast Metabolomics Center, UC Davis Genome Center, University of California, Davis, CA 95616, USA.
| | - Tobias Kind
- NIH West Coast Metabolomics Center, UC Davis Genome Center, University of California, Davis, CA 95616, USA.
| | - Jian Ji
- State Key Laboratory of Food Science and Technology, School of Food Science of Jiangnan University, School of Food Science Synergetic Innovation Center of Food Safety and Nutrition, Wuxi 214122, China.
| | - Oliver Fiehn
- NIH West Coast Metabolomics Center, UC Davis Genome Center, University of California, Davis, CA 95616, USA.
- Department of Biochemistry, Faculty of Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
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Xu Z, Li J, Chen A, Ma X, Yang S. A new retrospective, multi-evidence veterinary drug screening method using drift tube ion mobility mass spectrometry. RAPID COMMUNICATIONS IN MASS SPECTROMETRY : RCM 2018; 32:1141-1148. [PMID: 29723930 DOI: 10.1002/rcm.8154] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Revised: 04/14/2018] [Accepted: 04/24/2018] [Indexed: 06/08/2023]
Abstract
RATIONALE The retrospectivity (the ability to retrospect to a previously unknown compound in raw data) is very meaningful for food safety and risk assessment when facing new emerging drugs. Accurate mass and retention time based screening may lead false positive and false negative results so new retrospective, reliable platform is desirable. METHODS Different concentration levels of standards with and without matrix were analyzed using ion mobility (IM)-quadrupole-time-of-flight (Q-TOF) for collecting retrospective accurate mass, retention time, drift time and tandem MS evidence for identification in a single experiment. The isomer separation ability of IM and the four-dimensional (4D) feature abundance quantification abilities were evaluated for veterinary drugs for the first time. RESULTS The sensitivity of the IM-Q-TOF workflow was obviously higher than that of the traditional database searching algorithm [find by formula (FbF) function] for Q-TOF. In addition, the IM-Q-TOF workflow contained most of the results from FbF and removed the false positive results. Some isomers were separated by IM and the 4D feature abundance quantitation removed interference with similar accurate mass and showed good linearity. CONCLUSION A new retrospective, multi-evidence platform was built for veterinary drug screening in a single experiment. The sensitivity was significantly improved and the data can be used for quantification. The platform showed its potential to be used for food safety and risk assessment.
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Affiliation(s)
- Zhenzhen Xu
- Institute of Quality Standard & Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-food Safety and Quality, Ministry of Agriculture, Beijing, 100081, China
| | | | - Ailiang Chen
- Institute of Quality Standard & Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-food Safety and Quality, Ministry of Agriculture, Beijing, 100081, China
| | - Xin Ma
- Agilent Technologies, Beijing, 100102, China
| | - Shuming Yang
- Institute of Quality Standard & Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-food Safety and Quality, Ministry of Agriculture, Beijing, 100081, China
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Recent trends in water analysis triggering future monitoring of organic micropollutants. Anal Bioanal Chem 2018; 410:3933-3941. [PMID: 29564501 PMCID: PMC6010479 DOI: 10.1007/s00216-018-1015-9] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2017] [Revised: 02/15/2018] [Accepted: 03/08/2018] [Indexed: 02/07/2023]
Abstract
Water analysis has been an important area since the beginning of analytical chemistry. The focus though has shifted substantially: from minerals and the main constituents of water in the time of Carl Remigius Fresenius to a multitude of, in particular, organic compounds at concentrations down to the sub-nanogram per liter level nowadays. This was possible only because of numerous innovations in instrumentation in recent decades, drivers of which are briefly discussed. In addition to the high demands on sensitivity, high throughput by automation and short analysis times are major requirements. In this article, some recent developments in the chemical analysis of organic micropollutants (OMPs) are presented. These include the analysis of priority pollutants in whole water samples, extension of the analytical window, in particular to encompass highly polar compounds, the trend toward more than one separation dimension before mass spectrometric detection, and ways of coping with unknown analytes by suspect and nontarget screening approaches involving high-resolution mass spectrometry. Furthermore, beyond gathering reliable concentration data for many OMPs, the question of the relevance of such data for the aquatic system under scrutiny is becoming ever more important. To that end, effect-based analytics can be used and may become part of future routine monitoring, mostly with a focus on adverse effects of OMPs in specific test systems mimicking environmental impacts. Despite advances in the field of water analysis in recent years, there are still many challenges for further analytical research. Graphical abstract Recent trends in water analysis of organic micropollutants that open new opportunities in future water monitoring. HRMS high-resolution mass spectrometry, PMOC persistent mobile organic compounds.
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The soil microbiome-from metagenomics to metaphenomics. Curr Opin Microbiol 2018; 43:162-168. [PMID: 29454931 DOI: 10.1016/j.mib.2018.01.013] [Citation(s) in RCA: 154] [Impact Index Per Article: 25.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Revised: 01/24/2018] [Accepted: 01/26/2018] [Indexed: 11/21/2022]
Abstract
Soil microorganisms carry out important processes, including support of plant growth and cycling of carbon and other nutrients. However, the majority of soil microbes have not yet been isolated and their functions are largely unknown. Although metagenomic sequencing reveals microbial identities and functional gene information, it includes DNA from microbes with vastly varying physiological states. Therefore, metagenomics is only predictive of community functional potential. We posit that the next frontier lies in understanding the metaphenome, the product of the combined genetic potential of the microbiome and available resources. Here we describe examples of opportunities towards gaining understanding of the soil metaphenome.
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Boiteau RM, Hoyt DW, Nicora CD, Kinmonth-Schultz HA, Ward JK, Bingol K. Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction. Metabolites 2018; 8:metabo8010008. [PMID: 29342073 PMCID: PMC5875998 DOI: 10.3390/metabo8010008] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2017] [Revised: 01/13/2018] [Accepted: 01/13/2018] [Indexed: 11/16/2022] Open
Abstract
We introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS²), and NMR into a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter out the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture, and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS² approach is well suited to the discovery of new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.
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Affiliation(s)
- Rene M Boiteau
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99354, USA.
| | - David W Hoyt
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99354, USA.
| | - Carrie D Nicora
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99354, USA.
| | | | - Joy K Ward
- Department of Ecology and Evolutionary Biology, University of Kansas, Lawrence, KS 66045, USA.
| | - Kerem Bingol
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99354, USA.
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Welcome to volume 10 of Bioanalysis. Bioanalysis 2018. [DOI: 10.4155/bio-2017-4972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
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Johnson CH, Athersuch TJ, Collman GW, Dhungana S, Grant DF, Jones DP, Patel CJ, Vasiliou V. Yale school of public health symposium on lifetime exposures and human health: the exposome; summary and future reflections. Hum Genomics 2017; 11:32. [PMID: 29221465 PMCID: PMC5723043 DOI: 10.1186/s40246-017-0128-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Accepted: 12/01/2017] [Indexed: 01/12/2023] Open
Abstract
The exposome is defined as "the totality of environmental exposures encountered from birth to death" and was developed to address the need for comprehensive environmental exposure assessment to better understand disease etiology. Due to the complexity of the exposome, significant efforts have been made to develop technologies for longitudinal, internal and external exposure monitoring, and bioinformatics to integrate and analyze datasets generated. Our objectives were to bring together leaders in the field of exposomics, at a recent Symposium on "Lifetime Exposures and Human Health: The Exposome," held at Yale School of Public Health. Our aim was to highlight the most recent technological advancements for measurement of the exposome, bioinformatics development, current limitations, and future needs in environmental health. In the discussions, an emphasis was placed on moving away from a one-chemical one-health outcome model toward a new paradigm of monitoring the totality of exposures that individuals may experience over their lifetime. This is critical to better understand the underlying biological impact on human health, particularly during windows of susceptibility. Recent advancements in metabolomics and bioinformatics are driving the field forward in biomonitoring and understanding the biological impact, and the technological and logistical challenges involved in the analyses were highlighted. In conclusion, further developments and support are needed for large-scale biomonitoring and management of big data, standardization for exposure and data analyses, bioinformatics tools for co-exposure or mixture analyses, and methods for data sharing.
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Affiliation(s)
- Caroline H. Johnson
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT USA
| | - Toby J. Athersuch
- Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College Norfolk Place, London, UK
| | - Gwen W. Collman
- Division of Extramural Research and Training, National Institute of Environmental Health Sciences, National Institutes of Health, Morrisville, NC USA
| | - Suraj Dhungana
- Waters Corporation, Metabolomics and Translational Research, Milford, MA USA
| | - David F. Grant
- Department of Pharmaceutical Sciences, University of Connecticut, Storrs, CT USA
| | - Dean P. Jones
- Department of Medicine, Emory University School of Medicine, Atlanta, GA USA
| | - Chirag J. Patel
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA USA
| | - Vasilis Vasiliou
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, CT USA
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D'Atri V, Causon T, Hernandez-Alba O, Mutabazi A, Veuthey JL, Cianferani S, Guillarme D. Adding a new separation dimension to MS and LC-MS: What is the utility of ion mobility spectrometry? J Sep Sci 2017; 41:20-67. [PMID: 29024509 DOI: 10.1002/jssc.201700919] [Citation(s) in RCA: 114] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2017] [Revised: 09/19/2017] [Accepted: 09/19/2017] [Indexed: 12/12/2022]
Abstract
Ion mobility spectrometry is an analytical technique known for more than 100 years, which entails separating ions in the gas phase based on their size, shape, and charge. While ion mobility spectrometry alone can be useful for some applications (mostly security analysis for detecting certain classes of narcotics and explosives), it becomes even more powerful in combination with mass spectrometry and high-performance liquid chromatography. Indeed, the limited resolving power of ion mobility spectrometry alone can be tackled when combining this analytical strategy with mass spectrometry or liquid chromatography with mass spectrometry. Over the last few years, the hyphenation of ion mobility spectrometry to mass spectrometry or liquid chromatography with mass spectrometry has attracted more and more interest, with significant progresses in both technical advances and pioneering applications. This review describes the theoretical background, available technologies, and future capabilities of these techniques. It also highlights a wide range of applications, from small molecules (natural products, metabolites, glycans, lipids) to large biomolecules (proteins, protein complexes, biopharmaceuticals, oligonucleotides).
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Affiliation(s)
- Valentina D'Atri
- School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Geneva, Switzerland
| | - Tim Causon
- Division of Analytical Chemistry, Department of Chemistry, University of Natural Resources and Life Sciences (BOKU Vienna), Vienna, Austria
| | - Oscar Hernandez-Alba
- BioOrganic Mass Spectrometry Laboratory (LSMBO), IPHC, Université de Strasbourg, CNRS, Strasbourg, France
| | - Aline Mutabazi
- School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Geneva, Switzerland
| | - Jean-Luc Veuthey
- School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Geneva, Switzerland
| | - Sarah Cianferani
- BioOrganic Mass Spectrometry Laboratory (LSMBO), IPHC, Université de Strasbourg, CNRS, Strasbourg, France
| | - Davy Guillarme
- School of Pharmaceutical Sciences, University of Geneva, University of Lausanne, Geneva, Switzerland
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Zhou Z, Tu J, Zhu ZJ. Advancing the large-scale CCS database for metabolomics and lipidomics at the machine-learning era. Curr Opin Chem Biol 2017; 42:34-41. [PMID: 29136580 DOI: 10.1016/j.cbpa.2017.10.033] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2017] [Revised: 10/28/2017] [Accepted: 10/30/2017] [Indexed: 01/02/2023]
Abstract
Metabolomics and lipidomics aim to comprehensively measure the dynamic changes of all metabolites and lipids that are present in biological systems. The use of ion mobility-mass spectrometry (IM-MS) for metabolomics and lipidomics has facilitated the separation and the identification of metabolites and lipids in complex biological samples. The collision cross-section (CCS) value derived from IM-MS is a valuable physiochemical property for the unambiguous identification of metabolites and lipids. However, CCS values obtained from experimental measurement and computational modeling are limited available, which significantly restricts the application of IM-MS. In this review, we will discuss the recently developed machine-learning based prediction approach, which could efficiently generate precise CCS databases in a large scale. We will also highlight the applications of CCS databases to support metabolomics and lipidomics.
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Affiliation(s)
- Zhiwei Zhou
- Interdisciplinary Research Center on Biology and Chemistry, and Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China
| | - Jia Tu
- Interdisciplinary Research Center on Biology and Chemistry, and Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China
| | - Zheng-Jiang Zhu
- Interdisciplinary Research Center on Biology and Chemistry, and Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, PR China.
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