1
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Marín-Sáez J, Hernández-Mesa M, Cano-Sancho G, García-Campaña AM. Analytical challenges and opportunities in the study of endocrine disrupting chemicals within an exposomics framework. Talanta 2024; 279:126616. [PMID: 39067205 DOI: 10.1016/j.talanta.2024.126616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Revised: 07/11/2024] [Accepted: 07/23/2024] [Indexed: 07/30/2024]
Abstract
Exposomics aims to measure human exposures throughout the lifespan and the changes they produce in the human body. Exposome-scale studies have significant potential to understand the interplay of environmental factors with complex multifactorial diseases widespread in our society and whose origin remain unclear. In this framework, the study of the chemical exposome aims to cover all chemical exposures and their effects in human health but, today, this goal still seems unfeasible or at least very challenging, which makes the exposome for now only a concept. Furthermore, the study of the chemical exposome faces several methodological challenges such as moving from specific targeted methodologies towards high-throughput multitargeted and non-targeted approaches, guaranteeing the availability and quality of biological samples to obtain quality analytical data, standardization of applied analytical methodologies, as well as the statistical assignment of increasingly complex datasets, or the identification of (un)known analytes. This review discusses the various steps involved in applying the exposome concept from an analytical perspective. It provides an overview of the wide variety of existing analytical methods and instruments, highlighting their complementarity to develop combined analytical strategies to advance towards the chemical exposome characterization. In addition, this review focuses on endocrine disrupting chemicals (EDCs) to show how studying even a minor part of the chemical exposome represents a great challenge. Analytical strategies applied in an exposomics context have shown great potential to elucidate the role of EDCs in health outcomes. However, translating innovative methods into etiological research and chemical risk assessment will require a multidisciplinary effort. Unlike other review articles focused on exposomics, this review offers a holistic view from the perspective of analytical chemistry and discuss the entire analytical workflow to finally obtain valuable results.
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Affiliation(s)
- Jesús Marín-Sáez
- Department of Analytical Chemistry, Faculty of Sciences, University of Granada, Campus Fuentenueva s/n, E-18071, Granada, Spain; Research Group "Analytical Chemistry of Contaminants", Department of Chemistry and Physics, Research Centre for Mediterranean Intensive Agrosystems and Agri-Food Biotechnology (CIAIMBITAL), University of Almeria, Agrifood Campus of International Excellence, ceiA3, E-04120, Almeria, Spain.
| | - Maykel Hernández-Mesa
- Department of Analytical Chemistry, Faculty of Sciences, University of Granada, Campus Fuentenueva s/n, E-18071, Granada, Spain.
| | | | - Ana M García-Campaña
- Department of Analytical Chemistry, Faculty of Sciences, University of Granada, Campus Fuentenueva s/n, E-18071, Granada, Spain
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2
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Carlo MJ, Nanney ALM, Patrick AL. Energy-Resolved In-Source Collison-Induced Dissociation for Isomer Discrimination. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024. [PMID: 39016059 DOI: 10.1021/jasms.4c00118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/18/2024]
Abstract
While mass spectrometry remains a gold-standard tool for analyte detection, characterization, and quantitation, isomer differentiation is often a challenge. Tandem mass spectrometry is a common approach to increase the selectivity of mass spectrometry and energy-resolved measurements can provide further improvements. However, not all mass spectrometers, especially those that are very compact and affordable, are amenable to such experiments. For instance, single-stage mass spectrometers with soft ionization provide no dissociation information and quadrupole ion trap instruments with resonant excitation do not necessarily provide as informative of energy-resolved curves, for instance when extensive sequential dissociation is responsible for much of the "fingerprint". In-source collision-induced dissociation (IS-CID) is one approach to overcoming these barriers to exploit the analytical selectivity of energy-resolved CID without the need for additional instrumentation; this approach could broaden the reach of these selectivity gains to additional user bases (e.g., educational settings, field portable devices). Here, we specifically investigate energy-resolved IS-CID with the goal of (1) comparing between energy-resolved appearance curves measured with true tandem mass spectrometry on a quadrupole time-of-flight instrument and those obtained using IS-CID, (2) evaluating the approach as a means of differentiating isomers/isobar sets, especially those with similar dissociation patterns, and (3) exploring additional analytical considerations relevant to method development and implementation. This proof-of-concept work establishes the analytical potential of this approach, opening doors for future method development for specific applications.
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Affiliation(s)
- Matthew J Carlo
- Department of Chemistry, Mississippi State University, Mississippi State, Mississippi 39762, United States
| | - Andie L M Nanney
- Department of Chemistry, Mississippi State University, Mississippi State, Mississippi 39762, United States
| | - Amanda L Patrick
- Department of Chemistry, Mississippi State University, Mississippi State, Mississippi 39762, United States
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3
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Bazzano C, de Felicio R, Alves LFG, Costa JH, Ortega R, Vieira BD, Morais-Urano RP, Furtado LC, Ferreira ELF, Gubiani JR, Berlinck RGS, Costa-Lotufo LV, Telles GP, B. B. Trivella D. NP 3 MS Workflow: An Open-Source Software System to Empower Natural Product-Based Drug Discovery Using Untargeted Metabolomics. Anal Chem 2024; 96:7460-7469. [PMID: 38702053 PMCID: PMC11099897 DOI: 10.1021/acs.analchem.3c05829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 04/02/2024] [Accepted: 04/05/2024] [Indexed: 05/06/2024]
Abstract
Natural products (or specialized metabolites) are historically the main source of new drugs. However, the current drug discovery pipelines require miniaturization and speeds that are incompatible with traditional natural product research methods, especially in the early stages of the research. This article introduces the NP3 MS Workflow, a robust open-source software system for liquid chromatography-tandem mass spectrometry (LC-MS/MS) untargeted metabolomic data processing and analysis, designed to rank bioactive natural products directly from complex mixtures of compounds, such as bioactive biota samples. NP3 MS Workflow allows minimal user intervention as well as customization of each step of LC-MS/MS data processing, with diagnostic statistics to allow interpretation and optimization of LC-MS/MS data processing by the user. NP3 MS Workflow adds improved computing of the MS2 spectra in an LC-MS/MS data set and provides tools for automatic [M + H]+ ion deconvolution using fragmentation rules; chemical structural annotation against MS2 databases; and relative quantification of the precursor ions for bioactivity correlation scoring. The software will be presented with case studies and comparisons with equivalent tools currently available. NP3 MS Workflow shows a robust and useful approach to select bioactive natural products from complex mixtures, improving the set of tools available for untargeted metabolomics. It can be easily integrated into natural product-based drug-discovery pipelines and to other fields of research at the interface of chemistry and biology.
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Affiliation(s)
- Cristina
F. Bazzano
- Brazilian
Biosciences National Laboratory (LNBio), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas 13083-970, State of São Paulo, Brazil
- Institute
of Computing, University of Campinas (UNICAMP), Campinas 13083-852, State of São Paulo, Brazil
| | - Rafael de Felicio
- Brazilian
Biosciences National Laboratory (LNBio), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas 13083-970, State of São Paulo, Brazil
| | - Luiz Fernando Giolo Alves
- Brazilian
Biosciences National Laboratory (LNBio), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas 13083-970, State of São Paulo, Brazil
| | - Jonas Henrique Costa
- Brazilian
Biosciences National Laboratory (LNBio), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas 13083-970, State of São Paulo, Brazil
| | - Raquel Ortega
- Brazilian
Biosciences National Laboratory (LNBio), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas 13083-970, State of São Paulo, Brazil
- Institute
of Biology, University of Campinas (UNICAMP), Campinas 13083-852, State of São Paulo, Brazil
| | - Bruna Domingues Vieira
- Brazilian
Biosciences National Laboratory (LNBio), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas 13083-970, State of São Paulo, Brazil
| | - Raquel Peres Morais-Urano
- Instituto
de Química de São Carlos, Universidade de São Paulo, CP 780, São Carlos CEP 13560-970, State of São Paulo, Brazil
| | - Luciana Costa Furtado
- Department
of Pharmacology, Institute of Biomedical Sciences, University of São Paulo, São Paulo 05508-000, State of São Paulo, Brazil
| | - Everton L. F. Ferreira
- Instituto
de Química de São Carlos, Universidade de São Paulo, CP 780, São Carlos CEP 13560-970, State of São Paulo, Brazil
| | - Juliana R. Gubiani
- Instituto
de Química de São Carlos, Universidade de São Paulo, CP 780, São Carlos CEP 13560-970, State of São Paulo, Brazil
| | - Roberto G. S. Berlinck
- Instituto
de Química de São Carlos, Universidade de São Paulo, CP 780, São Carlos CEP 13560-970, State of São Paulo, Brazil
| | - Leticia V. Costa-Lotufo
- Department
of Pharmacology, Institute of Biomedical Sciences, University of São Paulo, São Paulo 05508-000, State of São Paulo, Brazil
| | - Guilherme P. Telles
- Institute
of Computing, University of Campinas (UNICAMP), Campinas 13083-852, State of São Paulo, Brazil
| | - Daniela B. B. Trivella
- Brazilian
Biosciences National Laboratory (LNBio), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas 13083-970, State of São Paulo, Brazil
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4
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Pang Z, Xu L, Viau C, Lu Y, Salavati R, Basu N, Xia J. MetaboAnalystR 4.0: a unified LC-MS workflow for global metabolomics. Nat Commun 2024; 15:3675. [PMID: 38693118 PMCID: PMC11063062 DOI: 10.1038/s41467-024-48009-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 04/18/2024] [Indexed: 05/03/2024] Open
Abstract
The wide applications of liquid chromatography - mass spectrometry (LC-MS) in untargeted metabolomics demand an easy-to-use, comprehensive computational workflow to support efficient and reproducible data analysis. However, current tools were primarily developed to perform specific tasks in LC-MS based metabolomics data analysis. Here we introduce MetaboAnalystR 4.0 as a streamlined pipeline covering raw spectra processing, compound identification, statistical analysis, and functional interpretation. The key features of MetaboAnalystR 4.0 includes an auto-optimized feature detection and quantification algorithm for LC-MS1 spectra processing, efficient MS2 spectra deconvolution and compound identification for data-dependent or data-independent acquisition, and more accurate functional interpretation through integrated spectral annotation. Comprehensive validation studies using LC-MS1 and MS2 spectra obtained from standards mixtures, dilution series and clinical metabolomics samples have shown its excellent performance across a wide range of common tasks such as peak picking, spectral deconvolution, and compound identification with good computing efficiency. Together with its existing statistical analysis utilities, MetaboAnalystR 4.0 represents a significant step toward a unified, end-to-end workflow for LC-MS based global metabolomics in the open-source R environment.
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Affiliation(s)
- Zhiqiang Pang
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, QC, Canada
| | - Lei Xu
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, QC, Canada
| | - Charles Viau
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, QC, Canada
| | - Yao Lu
- Department of Microbiology and Immunology, McGill University, Montreal, QC, Canada
| | - Reza Salavati
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, QC, Canada
| | - Niladri Basu
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, QC, Canada
| | - Jianguo Xia
- Faculty of Agricultural and Environmental Sciences, McGill University, Ste-Anne-de-Bellevue, QC, Canada.
- Department of Microbiology and Immunology, McGill University, Montreal, QC, Canada.
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5
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Fernandez Requena B, Gonzalez-Riano C, Barbas C. Addressing the untargeted lipidomics challenge in urine samples: Comparative study of extraction methods by UHPLC-ESI-QTOF-MS. Anal Chim Acta 2024; 1299:342433. [PMID: 38499427 DOI: 10.1016/j.aca.2024.342433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 02/23/2024] [Accepted: 02/26/2024] [Indexed: 03/20/2024]
Abstract
Urine analysis has remained a fundamental and widely used method in clinical diagnostics for over a century. With its minimal invasive nature and comprehensive range of analytes, urine has established itself as a clinical diagnostic tool for various disorders, including renal, urological, metabolic, and endocrine diseases. Furthermore, urine's unique attributes make it an attractive matrix for biomarker discovery, as well as in assessing the metabolic and physiological states of patients and healthy individuals alike. However, limitations in our knowledge of average values and sources of urinary lipids decrease the wider clinical application of urinary lipidomics. In this context, untargeted lipidomics analysis relies heavily on the extraction and analysis of lipids in biological samples. Nevertheless, this type of analysis presents challenges in lipid identification due to the diverse nature of lipids. Therefore, proper sample treatment before analysis is crucial to obtain robust and reproducible lipidomic profiles. To address this gap, we conducted a comparative study of a urine pool sample collected from twenty healthy volunteers using four different lipid extraction methods: one biphasic and three monophasic protocols. The extracted lipids were then analyzed using UHPLC-MS and MS/MS, and the semi-quantification of all the accurately annotated lipid species was performed for each extraction method.
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Affiliation(s)
- Belen Fernandez Requena
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, 28660 Boadilla del Monte, Madrid, España
| | - Carolina Gonzalez-Riano
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, 28660 Boadilla del Monte, Madrid, España
| | - Coral Barbas
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, 28660 Boadilla del Monte, Madrid, España.
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6
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Alves MF, Katchborian-Neto A, Bueno PCP, Carnevale-Neto F, Casoti R, Ferreira MS, Murgu M, de Paula ACC, Dias DF, Soares MG, Chagas-Paula DA. LC-MS/DIA-based strategy for comprehensive flavonoid profiling: an Ocotea spp. applicability case. RSC Adv 2024; 14:10481-10498. [PMID: 38567345 PMCID: PMC10985591 DOI: 10.1039/d4ra01384k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Accepted: 03/22/2024] [Indexed: 04/04/2024] Open
Abstract
We introduce a liquid chromatography - mass spectrometry with data-independent acquisition (LC-MS/DIA)-based strategy, specifically tailored to achieve comprehensive and reliable glycosylated flavonoid profiling. This approach facilitates in-depth and simultaneous exploration of all detected precursors and fragments during data processing, employing the widely-used open-source MZmine 3 software. It was applied to a dataset of six Ocotea plant species. This framework suggested 49 flavonoids potentially newly described for these plant species, alongside 45 known features within the genus. Flavonols kaempferol and quercetin, both exhibiting O-glycosylation patterns, were particularly prevalent. Gas-phase fragmentation reactions further supported these findings. For the first time, the apigenin flavone backbone was also annotated in most of the examined Ocotea species. Apigenin derivatives were found mainly in the C-glycoside form, with O. porosa displaying the highest flavone : flavonol ratio. The approach also allowed an unprecedented detection of kaempferol and quercetin in O. porosa species, and it has underscored the untapped potential of LC-MS/DIA data for broad and reliable flavonoid profiling. Our study annotated more than 50 flavonoid backbones in each species, surpassing the current literature.
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Affiliation(s)
- Matheus Fernandes Alves
- Institute of Chemistry, Federal University of Alfenas-MG 37130-001 Alfenas Minas Gerais Brazil
| | - Albert Katchborian-Neto
- Institute of Chemistry, Federal University of Alfenas-MG 37130-001 Alfenas Minas Gerais Brazil
| | - Paula Carolina Pires Bueno
- Leibniz Institute of Vegetable and Ornamental Crops (IGZ) Theodor-Echtermeyer-Weg 1 14979 Großbeeren Germany
| | - Fausto Carnevale-Neto
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington 850 Republican Street Seattle Washington 98109 USA
| | - Rosana Casoti
- Antibiotics Department, Federal University of Pernambuco 50670-901 Recife Pernambuco Brazil
| | - Miller Santos Ferreira
- Institute of Chemistry, Federal University of Alfenas-MG 37130-001 Alfenas Minas Gerais Brazil
| | - Michael Murgu
- Waters Corporation Alameda Tocantins 125, Alphaville 06455-020 São Paulo Brazil
| | | | - Danielle Ferreira Dias
- Institute of Chemistry, Federal University of Alfenas-MG 37130-001 Alfenas Minas Gerais Brazil
| | - Marisi Gomes Soares
- Institute of Chemistry, Federal University of Alfenas-MG 37130-001 Alfenas Minas Gerais Brazil
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7
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Vosough M, Salemi A, Rockel S, Schmidt TC. Enhanced efficiency of MS/MS all-ion fragmentation for non-targeted analysis of trace contaminants in surface water using multivariate curve resolution and data fusion. Anal Bioanal Chem 2024; 416:1165-1177. [PMID: 38206346 PMCID: PMC10850027 DOI: 10.1007/s00216-023-05102-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 11/18/2023] [Accepted: 11/30/2023] [Indexed: 01/12/2024]
Abstract
Data-independent acquisition-all-ion fragmentation (DIA-AIF) mode of mass spectrometry can facilitate wide-scope non-target analysis of contaminants in surface water due to comprehensive spectral identification. However, because of the complexity of the resulting MS2 AIF spectra, identifying unknown pollutants remains a significant challenge, with a significant bottleneck in translating non-targeted chemical signatures into environmental impacts. The present study proposes to process fused MS1 and MS2 data sets obtained from LC-HRMS/MS measurements in non-targeted AIF workflows on surface water samples using multivariate curve resolution-alternating least squares (MCR-ALS). This enables straightforward assignment between precursor ions obtained from resolved MS1 spectra and their corresponding MS2 spectra. The method was evaluated for two sets of tap water and surface water contaminated with 14 target chemicals as a proof of concept. The data set of surface water samples consisting of 3506 MS1 and 2170 MS2 AIF mass spectral features was reduced to 81 components via a fused MS1-MS2 MCR model that describes at least 98.8% of the data. Each component summarizes the distinct chromatographic elution of components together with their corresponding MS1 and MS2 spectra. MS2 spectral similarity of more than 82% was obtained for most target chemicals. This highlights the potential of this method for unraveling the composition of MS/MS complex data in a water environment. Ultimately, the developed approach was applied to the retrospective non-target analysis of an independent set of surface water samples.
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Affiliation(s)
- Maryam Vosough
- Instrumental Analytical Chemistry and Centre for Water and Environmental Research (ZWU), University of Duisburg-Essen, Universitätsstr. 5, Essen, 45141, Germany.
- Department of Clean Technologies, Chemistry and Chemical Engineering Research Center of Iran, P.O. Box 14335-186, Tehran, Iran.
| | - Amir Salemi
- Instrumental Analytical Chemistry and Centre for Water and Environmental Research (ZWU), University of Duisburg-Essen, Universitätsstr. 5, Essen, 45141, Germany
| | - Sarah Rockel
- Instrumental Analytical Chemistry and Centre for Water and Environmental Research (ZWU), University of Duisburg-Essen, Universitätsstr. 5, Essen, 45141, Germany
| | - Torsten C Schmidt
- Instrumental Analytical Chemistry and Centre for Water and Environmental Research (ZWU), University of Duisburg-Essen, Universitätsstr. 5, Essen, 45141, Germany
- IWW Water Centre, Moritzstr. 26, Mülheim an der Ruhr, 45476, Germany
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8
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Latz M, Böhme A, Ulrich N. Reactivity-based identification of oxygen containing functional groups of chemicals applied as potential classifier in non-target analysis. Sci Rep 2023; 13:22828. [PMID: 38129561 PMCID: PMC10739825 DOI: 10.1038/s41598-023-50240-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 12/17/2023] [Indexed: 12/23/2023] Open
Abstract
In this work, we developed a reactivity-based strategy to identify functional groups of unknown analytes, which can be applied as classifier in non-target analysis with gas chromatography. The aim of this strategy is to reduce the number of potential candidate structures generated for a molecular formula determined by high resolution mass spectrometry. We selected an example of 18 isomers with the molecular formula C12H10O2 to test the performance of different derivatization reagents, whereas our aim was to select mild and fast reaction conditions. Based on the results for the isomers, we developed a four-step workflow for the identification of functional groups containing oxygen.
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Affiliation(s)
- Milena Latz
- Department of Ecological Chemistry, Helmholtz Centre for Environmental Research - UFZ, 04318, Leipzig, Germany
- Faculty of Chemistry and Mineralogy, Leipzig University, 04103, Leipzig, Germany
| | - Alexander Böhme
- Department of Ecological Chemistry, Helmholtz Centre for Environmental Research - UFZ, 04318, Leipzig, Germany
| | - Nadin Ulrich
- Department of Ecological Chemistry, Helmholtz Centre for Environmental Research - UFZ, 04318, Leipzig, Germany.
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9
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van Herwerden D, O’Brien JW, Lege S, Pirok BWJ, Thomas KV, Samanipour S. Cumulative Neutral Loss Model for Fragment Deconvolution in Electrospray Ionization High-Resolution Mass Spectrometry Data. Anal Chem 2023; 95:12247-12255. [PMID: 37549176 PMCID: PMC10448439 DOI: 10.1021/acs.analchem.3c00896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 07/03/2023] [Indexed: 08/09/2023]
Abstract
Clean high-resolution mass spectra (HRMS) are essential to a successful structural elucidation of an unknown feature during nontarget analysis (NTA) workflows. This is a crucial step, particularly for the spectra generated during data-independent acquisition or during direct infusion experiments. The most commonly available tools only take advantage of the time domain for spectral cleanup. Here, we present an algorithm that combines the time domain and mass domain information to perform spectral deconvolution. The algorithm employs a probability-based cumulative neutral loss (CNL) model for fragment deconvolution. The optimized model, with a mass tolerance of 0.005 Da and a scoreCNL threshold of 0.00, was able to achieve a true positive rate (TPr) of 95.0%, a false discovery rate (FDr) of 20.6%, and a reduction rate of 35.4%. Additionally, the CNL model was extensively tested on real samples containing predominantly pesticides at different concentration levels and with matrix effects. Overall, the model was able to obtain a TPr above 88.8% with FD rates between 33 and 79% and reduction rates between 9 and 45%. Finally, the CNL model was compared with the retention time difference method and peak shape correlation analysis, showing that a combination of correlation analysis and the CNL model was the most effective for fragment deconvolution, obtaining a TPr of 84.7%, an FDr of 54.4%, and a reduction rate of 51.0%.
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Affiliation(s)
- Denice van Herwerden
- Van
’t Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Amsterdam 1012 WX, The Netherlands
| | - Jake W. O’Brien
- Van
’t Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Amsterdam 1012 WX, The Netherlands
- Queensland
Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Brisbane 4102, Australia
| | - Sascha Lege
- Agilent
Technologies Deutschland GmbH, Waldbronn 76337, Germany
| | - Bob W. J. Pirok
- Van
’t Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Amsterdam 1012 WX, The Netherlands
| | - Kevin V. Thomas
- Queensland
Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Brisbane 4102, Australia
| | - Saer Samanipour
- Van
’t Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Amsterdam 1012 WX, The Netherlands
- Queensland
Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Brisbane 4102, Australia
- UvA
Data Science Center, University of Amsterdam, Amsterdam 1012 WP, The Netherlands
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10
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Baygi SF, Kumar Y, Barupal DK. IDSL.CSA: Composite Spectra Analysis for Chemical Annotation of Untargeted Metabolomics Datasets. Anal Chem 2023; 95:9480-9487. [PMID: 37311059 PMCID: PMC11080491 DOI: 10.1021/acs.analchem.3c00376] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Poor chemical annotation of high-resolution mass spectrometry data limits applications of untargeted metabolomics datasets. Our new software, the Integrated Data Science Laboratory for Metabolomics and Exposomics─Composite Spectra Analysis (IDSL.CSA) R package, generates composite mass spectra libraries from MS1-only data, enabling the chemical annotation of high-resolution mass spectrometry coupled with liquid chromatography peaks regardless of the availability of MS2 fragmentation spectra. We demonstrate comparable annotation rates for commonly detected endogenous metabolites in human blood samples using IDSL.CSA libraries versus MS/MS libraries in validation tests. IDSL.CSA can create and search composite spectra libraries from any untargeted metabolomics dataset generated using high-resolution mass spectrometry coupled to liquid or gas chromatography instruments. The cross-applicability of these libraries across independent studies may provide access to new biological insights that may be missed due to the lack of MS2 fragmentation data. The IDSL.CSA package is available in the R-CRAN repository at https://cran.r-project.org/package=IDSL.CSA. Detailed documentation and tutorials are provided at https://github.com/idslme/IDSL.CSA.
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Affiliation(s)
- Sadjad Fakouri Baygi
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Yashwant Kumar
- Non-communicable Diseases Division, Translational Health Science and Technology Institute, Faridabad, Haryana, 121001, India
| | - Dinesh Kumar Barupal
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
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11
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Ebbels TMD, van der Hooft JJJ, Chatelaine H, Broeckling C, Zamboni N, Hassoun S, Mathé EA. Recent advances in mass spectrometry-based computational metabolomics. Curr Opin Chem Biol 2023; 74:102288. [PMID: 36966702 PMCID: PMC11075003 DOI: 10.1016/j.cbpa.2023.102288] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 02/16/2023] [Accepted: 02/21/2023] [Indexed: 04/03/2023]
Abstract
The computational metabolomics field brings together computer scientists, bioinformaticians, chemists, clinicians, and biologists to maximize the impact of metabolomics across a wide array of scientific and medical disciplines. The field continues to expand as modern instrumentation produces datasets with increasing complexity, resolution, and sensitivity. These datasets must be processed, annotated, modeled, and interpreted to enable biological insight. Techniques for visualization, integration (within or between omics), and interpretation of metabolomics data have evolved along with innovation in the databases and knowledge resources required to aid understanding. In this review, we highlight recent advances in the field and reflect on opportunities and innovations in response to the most pressing challenges. This review was compiled from discussions from the 2022 Dagstuhl seminar entitled "Computational Metabolomics: From Spectra to Knowledge".
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Affiliation(s)
- Timothy M D Ebbels
- Section of Bioinformatics, Department of Metabolism, Digestion & Reproduction, Imperial College London, Burlington Danes Building, Hammersmith Hospital, Du Cane Road, London W12 0NN, UK.
| | - Justin J J van der Hooft
- Bioinformatics Group, Wageningen University & Research, Wageningen 6708 PB, the Netherlands; Department of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg 2006, South Africa
| | - Haley Chatelaine
- Informatics Core, Division of Preclinical Innovation, National Center for Advancing Translational Sciences, Rockville, MD, USA
| | - Corey Broeckling
- Bioanalysis and Omics Center, Analytical Resources Core, Colorado State University, Fort Collins, CO, USA
| | - Nicola Zamboni
- Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland
| | - Soha Hassoun
- Department of Computer Science, Tufts University, Medford, MA, USA; Department of Chemical and Biological Engineering, Tufts University, Medford, MA, USA
| | - Ewy A Mathé
- Informatics Core, Division of Preclinical Innovation, National Center for Advancing Translational Sciences, Rockville, MD, USA.
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12
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Curtis BJ, Schwertfeger TJ, Burkhardt RN, Fox BW, Andrzejewski J, Wrobel CJJ, Yu J, Rodrigues PR, Tauffenberger A, Schroeder FC. Oligonucleotide Catabolism-Derived Gluconucleosides in Caenorhabditis elegans. J Am Chem Soc 2023; 145:11611-11621. [PMID: 37192367 PMCID: PMC10536790 DOI: 10.1021/jacs.3c01151] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Nucleosides are essential cornerstones of life, and nucleoside derivatives and synthetic analogues have important biomedical applications. Correspondingly, production of non-canonical nucleoside derivatives in animal model systems is of particular interest. Here, we report the discovery of diverse glucose-based nucleosides in Caenorhabditis elegans and related nematodes. Using a mass spectrometric screen based on all-ion fragmentation in combination with total synthesis, we show that C. elegans selectively glucosylates a series of modified purines but not the canonical purine and pyrimidine bases. Analogous to ribonucleosides, the resulting gluconucleosides exist as phosphorylated and non-phosphorylated forms. The phosphorylated gluconucleosides can be additionally decorated with diverse acyl moieties from amino acid catabolism. Syntheses of representative variants, facilitated by a novel 2'-O- to 3'-O-dibenzyl phosphoryl transesterification reaction, demonstrated selective incorporation of different nucleobases and acyl moieties. Using stable-isotope labeling, we further show that gluconucleosides incorporate modified nucleobases derived from RNA and possibly DNA breakdown, revealing extensive recycling of oligonucleotide catabolites. Gluconucleosides are conserved in other nematodes, and biosynthesis of specific subsets is increased in germline mutants and during aging. Bioassays indicate that gluconucleosides may function in stress response pathways.
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Affiliation(s)
- Brian J Curtis
- Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States
| | - Tyler J Schwertfeger
- Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States
| | - Russell N Burkhardt
- Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States
| | - Bennett W Fox
- Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States
| | - Jude Andrzejewski
- Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States
| | - Chester J J Wrobel
- Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States
| | - Jingfang Yu
- Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States
| | - Pedro R Rodrigues
- Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States
| | - Arnaud Tauffenberger
- Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States
| | - Frank C Schroeder
- Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States
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13
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Baygi SF, Kumar Y, Barupal DK. IDSL.CSA: Composite Spectra Analysis for Chemical Annotation of Untargeted Metabolomics Datasets. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.09.527886. [PMID: 36798308 PMCID: PMC9934657 DOI: 10.1101/2023.02.09.527886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
Abstract
Poor chemical annotation of high-resolution mass spectrometry data limit applications of untargeted metabolomics datasets. Our new software, the Integrated Data Science Laboratory for Metabolomics and Exposomics - Composite Spectra Analysis (IDSL.CSA) R package, generates composite mass spectra libraries from MS1-only data, enabling the chemical annotation of LC/HRMS peaks regardless of the availability of MS2 fragmentation spectra. We demonstrate comparable annotation rates for commonly detected endogenous metabolites in human blood samples using IDSL.CSA libraries versus MS/MS libraries in validation tests. IDSL.CSA can create and search composite spectra libraries from any untargeted metabolomics dataset generated using high-resolution mass spectrometry coupled to liquid or gas chromatography instruments. The cross-applicability of these libraries across independent studies may provide access to new biological insights that may be missed due to the lack of MS2 fragmentation data. The IDSL.CSA package is available in the R CRAN repository at https://cran.r-project.org/package=IDSL.CSA . Detailed documentation and tutorials are provided at https://github.com/idslme/IDSL.CSA . For Table of Contents Only
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Affiliation(s)
- Sadjad Fakouri Baygi
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Yashwant Kumar
- Non-communicable Diseases Division, Translational Health Science and Technology Institute, Faridabad, Haryana, 121001, India
| | - Dinesh Kumar Barupal
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
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14
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Guan F, You Y, Fay S, Adreance MA, McGoldrick LK, Robinson MA. Factors affecting untargeted detection of doping agents in biological samples. Talanta 2023; 258:124446. [PMID: 36940570 DOI: 10.1016/j.talanta.2023.124446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 03/06/2023] [Accepted: 03/09/2023] [Indexed: 03/12/2023]
Abstract
Doping control is essential for sports, and untargeted detection of doping agents (UDDA) is the holy grail for anti-doping strategies. The present study examined major factors impacting UDDA with metabolomic data processing, including the use of blank samples, signal-to-noise ratio thresholds, and the minimum chromatographic peak intensity. Contrary to data processing in metabolomics studies, both blank sample use (either blank solvent or plasma) and marking of background compounds were found to be unnecessary for UDDA in biological samples, the first such report to the authors' knowledge. The minimum peak intensity required to detect chromatographic peaks affected the limit of detection (LOD) and data processing time for untargeted detection of 57 drugs spiked into equine plasma. The ratio of the mean (ROM) of the extracted ion chromatographic peak area of a compound in the sample group (SG) to that in the control group (CG) impacted its LOD, and a small ROM value such as 2 is recommended for UDDA. Mathematical modeling of the required signal-to-noise ratio (S/N) for UDDA provided insights into the effect of the number of samples in the SG, the number of positive samples, and the ROM on the required S/N, highlighting the power of mathematics in addressing issues in analytical chemistry. The UDDA method was validated by its successful identification of untargeted doping agents in real-world post-competition equine plasma samples. This advancement in UDDA methodology will be a useful addition to the arsenal of approaches used to combat doping in sports.
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Affiliation(s)
- Fuyu Guan
- Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, New Bolton Center Campus, 382 West Street Road, Kennett Square, PA, 19348, USA; Pennsylvania Equine Toxicology and Research Laboratory, 220 East Rosedale Avenue, West Chester, PA, 19382, USA.
| | - Youwen You
- Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, New Bolton Center Campus, 382 West Street Road, Kennett Square, PA, 19348, USA; Pennsylvania Equine Toxicology and Research Laboratory, 220 East Rosedale Avenue, West Chester, PA, 19382, USA
| | - Savannah Fay
- Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, New Bolton Center Campus, 382 West Street Road, Kennett Square, PA, 19348, USA; Pennsylvania Equine Toxicology and Research Laboratory, 220 East Rosedale Avenue, West Chester, PA, 19382, USA
| | - Matthew A Adreance
- Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, New Bolton Center Campus, 382 West Street Road, Kennett Square, PA, 19348, USA; Pennsylvania Equine Toxicology and Research Laboratory, 220 East Rosedale Avenue, West Chester, PA, 19382, USA
| | - Leif K McGoldrick
- Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, New Bolton Center Campus, 382 West Street Road, Kennett Square, PA, 19348, USA; Pennsylvania Equine Toxicology and Research Laboratory, 220 East Rosedale Avenue, West Chester, PA, 19382, USA
| | - Mary A Robinson
- Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, New Bolton Center Campus, 382 West Street Road, Kennett Square, PA, 19348, USA; Pennsylvania Equine Toxicology and Research Laboratory, 220 East Rosedale Avenue, West Chester, PA, 19382, USA
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15
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Zulfiqar M, Gadelha L, Steinbeck C, Sorokina M, Peters K. MAW: the reproducible Metabolome Annotation Workflow for untargeted tandem mass spectrometry. J Cheminform 2023; 15:32. [PMID: 36871033 PMCID: PMC9985203 DOI: 10.1186/s13321-023-00695-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 02/06/2023] [Indexed: 03/06/2023] Open
Abstract
Mapping the chemical space of compounds to chemical structures remains a challenge in metabolomics. Despite the advancements in untargeted liquid chromatography-mass spectrometry (LC-MS) to achieve a high-throughput profile of metabolites from complex biological resources, only a small fraction of these metabolites can be annotated with confidence. Many novel computational methods and tools have been developed to enable chemical structure annotation to known and unknown compounds such as in silico generated spectra and molecular networking. Here, we present an automated and reproducible Metabolome Annotation Workflow (MAW) for untargeted metabolomics data to further facilitate and automate the complex annotation by combining tandem mass spectrometry (MS2) input data pre-processing, spectral and compound database matching with computational classification, and in silico annotation. MAW takes the LC-MS2 spectra as input and generates a list of putative candidates from spectral and compound databases. The databases are integrated via the R package Spectra and the metabolite annotation tool SIRIUS as part of the R segment of the workflow (MAW-R). The final candidate selection is performed using the cheminformatics tool RDKit in the Python segment (MAW-Py). Furthermore, each feature is assigned a chemical structure and can be imported to a chemical structure similarity network. MAW is following the FAIR (Findable, Accessible, Interoperable, Reusable) principles and has been made available as the docker images, maw-r and maw-py. The source code and documentation are available on GitHub ( https://github.com/zmahnoor14/MAW ). The performance of MAW is evaluated on two case studies. MAW can improve candidate ranking by integrating spectral databases with annotation tools like SIRIUS which contributes to an efficient candidate selection procedure. The results from MAW are also reproducible and traceable, compliant with the FAIR guidelines. Taken together, MAW could greatly facilitate automated metabolite characterization in diverse fields such as clinical metabolomics and natural product discovery.
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Affiliation(s)
- Mahnoor Zulfiqar
- Institute for Inorganic and Analytical Chemistry, Friedrich Schiller University, 07743, Jena, Germany.
| | - Luiz Gadelha
- Institute for Inorganic and Analytical Chemistry, Friedrich Schiller University, 07743, Jena, Germany
| | - Christoph Steinbeck
- Institute for Inorganic and Analytical Chemistry, Friedrich Schiller University, 07743, Jena, Germany.
| | - Maria Sorokina
- Institute for Inorganic and Analytical Chemistry, Friedrich Schiller University, 07743, Jena, Germany.,Data Science and Artificial Intelligence, Research and Development, Bayer Pharmaceuticals, 13353, Berlin, Germany
| | - Kristian Peters
- iDiv - German Centre for Integrative Biodiversity Research, Halle-Jena-Leipzig, Leipzig, 04103, Germany. .,Geobotany and Botanical Gardens, Martin-Luther University of Halle-Wittenberg, 06108, Halle, Germany. .,Leibniz Institute of Plant Biochemistry, 06120, Halle, Germany.
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16
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Wandy J, McBride R, Rogers S, Terzis N, Weidt S, van der Hooft JJJ, Bryson K, Daly R, Davies V. Simulated-to-real benchmarking of acquisition methods in untargeted metabolomics. Front Mol Biosci 2023; 10:1130781. [PMID: 36959982 PMCID: PMC10027714 DOI: 10.3389/fmolb.2023.1130781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Accepted: 02/24/2023] [Indexed: 03/09/2023] Open
Abstract
Data-Dependent and Data-Independent Acquisition modes (DDA and DIA, respectively) are both widely used to acquire MS2 spectra in untargeted liquid chromatography tandem mass spectrometry (LC-MS/MS) metabolomics analyses. Despite their wide use, little work has been attempted to systematically compare their MS/MS spectral annotation performance in untargeted settings due to the lack of ground truth and the costs involved in running a large number of acquisitions. Here, we present a systematic in silico comparison of these two acquisition methods in untargeted metabolomics by extending our Virtual Metabolomics Mass Spectrometer (ViMMS) framework with a DIA module. Our results show that the performance of these methods varies with the average number of co-eluting ions as the most important factor. At low numbers, DIA outperforms DDA, but at higher numbers, DDA has an advantage as DIA can no longer deal with the large amount of overlapping ion chromatograms. Results from simulation were further validated on an actual mass spectrometer, demonstrating that using ViMMS we can draw conclusions from simulation that translate well into the real world. The versatility of the Virtual Metabolomics Mass Spectrometer (ViMMS) framework in simulating different parameters of both Data-Dependent and Data-Independent Acquisition (DDA and DIA) modes is a key advantage of this work. Researchers can easily explore and compare the performance of different acquisition methods within the ViMMS framework, without the need for expensive and time-consuming experiments with real experimental data. By identifying the strengths and limitations of each acquisition method, researchers can optimize their choice and obtain more accurate and robust results. Furthermore, the ability to simulate and validate results using the ViMMS framework can save significant time and resources, as it eliminates the need for numerous experiments. This work not only provides valuable insights into the performance of DDA and DIA, but it also opens the door for further advancements in LC-MS/MS data acquisition methods.
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Affiliation(s)
- Joe Wandy
- Glasgow Polyomics, University of Glasgow, Glasgow, United Kingdom
| | - Ross McBride
- School of Computing Science, University of Glasgow, Glasgow, United Kingdom
| | - Simon Rogers
- School of Computing Science, University of Glasgow, Glasgow, United Kingdom
| | - Nikolaos Terzis
- School of Mathematics and Statistics, University of Glasgow, Glasgow, United Kingdom
| | - Stefan Weidt
- Glasgow Polyomics, University of Glasgow, Glasgow, United Kingdom
| | | | - Kevin Bryson
- School of Computing Science, University of Glasgow, Glasgow, United Kingdom
| | - Rónán Daly
- Glasgow Polyomics, University of Glasgow, Glasgow, United Kingdom
| | - Vinny Davies
- School of Mathematics and Statistics, University of Glasgow, Glasgow, United Kingdom
- *Correspondence: Vinny Davies,
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17
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NMR-Based Chromatography Readouts: Indispensable Tools to “Translate” Analytical Features into Molecular Structures. Cells 2022; 11:cells11213526. [DOI: 10.3390/cells11213526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 10/29/2022] [Accepted: 11/04/2022] [Indexed: 11/09/2022] Open
Abstract
Gaining structural information is a must to allow the unequivocal structural characterization of analytes from natural sources. In liquid state, NMR spectroscopy is almost the only possible alternative to HPLC-MS and hyphenating the effluent of an analyte separation device to the probe head of an NMR spectrometer has therefore been pursued for more than three decades. The purpose of this review article was to demonstrate that, while it is possible to use mass spectrometry and similar methods to differentiate, group, and often assign the differentiating variables to entities that can be recognized as single molecules, the structural characterization of these putative biomarkers usually requires the use of NMR spectroscopy.
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18
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Palmblad M, Asein E, Bergman NP, Ivanova A, Ramasauskas L, Reyes HM, Ruchti S, Soto-Jácome L, Bergquist J. Semantic Annotation of Experimental Methods in Analytical Chemistry. Anal Chem 2022; 94:15464-15471. [DOI: 10.1021/acs.analchem.2c03565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Magnus Palmblad
- Center for Proteomics and Metabolomics, Leiden University Medical Center, 2300 RCLeiden, The Netherlands
| | - Enahoro Asein
- Institute of Chemistry, University of Tartu, Ravila 14a, 50411Tartu, Estonia
| | - Nina P. Bergman
- Analytical Pharmaceutical Chemistry, Department of Medicinal Chemistry - BMC, Uppsala University, SE-75123Uppsala, Sweden
| | - Arina Ivanova
- Analytical Chemistry and Neurochemistry, Department of Chemistry─BMC, Uppsala University, SE-75124Uppsala, Sweden
| | - Lukas Ramasauskas
- Analytical Chemistry and Neurochemistry, Department of Chemistry─BMC, Uppsala University, SE-75124Uppsala, Sweden
| | | | - Stefan Ruchti
- Institute of Chemistry, University of Tartu, Ravila 14a, 50411Tartu, Estonia
- Analytical Chemistry and Neurochemistry, Department of Chemistry─BMC, Uppsala University, SE-75124Uppsala, Sweden
| | | | - Jonas Bergquist
- Analytical Chemistry and Neurochemistry, Department of Chemistry─BMC, Uppsala University, SE-75124Uppsala, Sweden
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19
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Antibacterial Activity from Momordica charantia L. Leaves and Flavones Enriched Phase. Pharmaceutics 2022; 14:pharmaceutics14091796. [PMID: 36145544 PMCID: PMC9505480 DOI: 10.3390/pharmaceutics14091796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Revised: 08/01/2022] [Accepted: 08/04/2022] [Indexed: 11/23/2022] Open
Abstract
Momordica charantia L. (Cucurbitaceae) is a plant known in Brazil as “melão de São Caetano”, which has been related to many therapeutic applications in folk medicine. Herein, we describe antibacterial activities and related metabolites for an extract and fractions obtained from the leaves of that species. An ethanolic extract and its three fractions were used to perform in vitro antibacterial assays. In addition, liquid chromatography coupled to mass spectrometry and the molecular networking approach were used for the metabolite annotation process. Overall, 25 compounds were annotated in the ethanolic extract from M. charantia leaves, including flavones, terpenes, organic acids, and inositol pyrophosphate derivatives. The ethanolic extract exhibited low activity against Proteus mirabilis (MIC 312.5 µg·mL−1) and Klebsiella pneumoniae (MIC 625 µg·mL−1). The ethyl acetate phase showed interesting antibacterial activity (MIC 156.2 µg·mL−1) against Klebsiella pneumoniae, and it was well justified by the high content of glycosylated flavones. Therefore, based on the ethyl acetate phase antibacterial result, we suggest that M. charantia leaves could be considered as an alternative antibacterial source against K. pneumoniae and can serve as a pillar for future studies as well as pharmacological application against the bacteria.
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