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Bouhlel J, Caffin F, Gros-Désormeaux F, Douki T, Benoist JF, Castelli FA, Chu-Van E, Piérard C, Junot C, Fenaille F. Metabolomics Analysis of Rabbit Plasma after Ocular Exposure to Vapors of Sulfur Mustard. Metabolites 2024; 14:349. [PMID: 39057672 PMCID: PMC11279318 DOI: 10.3390/metabo14070349] [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: 06/11/2024] [Revised: 06/19/2024] [Accepted: 06/20/2024] [Indexed: 07/28/2024] Open
Abstract
Sulfur mustard (SM) is a highly potent alkylating vesicant agent and remains a relevant threat to both civilians and military personnel. The eyes are the most sensitive organ after airborne SM exposure, causing ocular injuries with no antidote or specific therapeutics available. In order to identify relevant biomarkers and to obtain a deeper understanding of the underlying biochemical events, we performed an untargeted metabolomics analysis using liquid chromatography coupled to high-resolution mass spectrometry of plasma samples from New Zealand white rabbits ocularly exposed to vapors of SM. Metabolic profiles (332 unique metabolites) from SM-exposed (n = 16) and unexposed rabbits (n = 8) were compared at different time intervals from 1 to 28 days. The observed time-dependent changes in metabolic profiles highlighted the profound dysregulation of the sulfur amino acids, the phenylalanine, the tyrosine and tryptophan pathway, and the polyamine and purine biosynthesis, which could reflect antioxidant and anti-inflammatory activities. Taurine and 3,4-dihydroxy-phenylalanine (Dopa) seem to be specifically related to SM exposure and correspond well with the different phases of ocular damage, while the dysregulation of adenosine, polyamines, and acylcarnitines might be related to ocular neovascularization. Additionally, neither cysteine, N-acetylcysteine, or guanine SM adducts were detected in the plasma of exposed rabbits at any time point. Overall, our study provides an unprecedented view of the plasma metabolic changes post-SM ocular exposure, which may open up the development of potential new treatment strategies.
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Affiliation(s)
- Jihéne Bouhlel
- CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, MetaboHUB-IDF, Université Paris-Saclay, 91191 Gif-sur-Yvette, France; (J.B.); (J.-F.B.); (F.A.C.); (E.C.-V.); (C.J.)
| | - Fanny Caffin
- Institut de Recherche Biomédicale des Armées (IRBA), 91223 Brétigny-sur-Orge, France; (F.C.); (F.G.-D.)
| | - Fanny Gros-Désormeaux
- Institut de Recherche Biomédicale des Armées (IRBA), 91223 Brétigny-sur-Orge, France; (F.C.); (F.G.-D.)
| | - Thierry Douki
- CEA, CNRS, IRIG, SyMMES, Université Grenoble Alpes, 38000 Grenoble, France;
| | - Jean-François Benoist
- CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, MetaboHUB-IDF, Université Paris-Saclay, 91191 Gif-sur-Yvette, France; (J.B.); (J.-F.B.); (F.A.C.); (E.C.-V.); (C.J.)
- Biochemistry Laboratory, APHP, Hôpital Universitaire Necker Enfants Malades, 75015 Paris, France
| | - Florence A. Castelli
- CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, MetaboHUB-IDF, Université Paris-Saclay, 91191 Gif-sur-Yvette, France; (J.B.); (J.-F.B.); (F.A.C.); (E.C.-V.); (C.J.)
| | - Emeline Chu-Van
- CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, MetaboHUB-IDF, Université Paris-Saclay, 91191 Gif-sur-Yvette, France; (J.B.); (J.-F.B.); (F.A.C.); (E.C.-V.); (C.J.)
| | - Christophe Piérard
- Institut de Recherche Biomédicale des Armées (IRBA), 91223 Brétigny-sur-Orge, France; (F.C.); (F.G.-D.)
| | - Christophe Junot
- CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, MetaboHUB-IDF, Université Paris-Saclay, 91191 Gif-sur-Yvette, France; (J.B.); (J.-F.B.); (F.A.C.); (E.C.-V.); (C.J.)
| | - François Fenaille
- CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), SPI, MetaboHUB-IDF, Université Paris-Saclay, 91191 Gif-sur-Yvette, France; (J.B.); (J.-F.B.); (F.A.C.); (E.C.-V.); (C.J.)
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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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Calabrese V, Brunet TA, Degli-Esposti D, Chaumot A, Geffard O, Salvador A, Clément Y, Ayciriex S. Electron-activated dissociation (EAD) for the complementary annotation of metabolites and lipids through data-dependent acquisition analysis and feature-based molecular networking, applied to the sentinel amphipod Gammarus fossarum. Anal Bioanal Chem 2024:10.1007/s00216-024-05232-w. [PMID: 38492024 DOI: 10.1007/s00216-024-05232-w] [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: 12/12/2023] [Revised: 02/23/2024] [Accepted: 02/27/2024] [Indexed: 03/18/2024]
Abstract
The past decades have marked the rise of metabolomics and lipidomics as the -omics sciences which reflect the most phenotypes in living systems. Mass spectrometry-based approaches are acknowledged for both quantification and identification of molecular signatures, the latter relying primarily on fragmentation spectra interpretation. However, the high structural diversity of biological small molecules poses a considerable challenge in compound annotation. Feature-based molecular networking (FBMN) combined with database searches currently sets the gold standard for annotation of large datasets. Nevertheless, FBMN is usually based on collision-induced dissociation (CID) data, which may lead to unsatisfying information. The use of alternative fragmentation methods, such as electron-activated dissociation (EAD), is undergoing a re-evaluation for the annotation of small molecules, as it gives access to additional fragmentation routes. In this study, we apply the performances of data-dependent acquisition mass spectrometry (DDA-MS) under CID and EAD fragmentation along with FBMN construction, to perform extensive compound annotation in the crude extracts of the freshwater sentinel organism Gammarus fossarum. We discuss the analytical aspects of the use of the two fragmentation modes, perform a general comparison of the information delivered, and compare the CID and EAD fragmentation pathways for specific classes of compounds, including previously unstudied species. In addition, we discuss the potential use of FBMN constructed with EAD fragmentation spectra to improve lipid annotation, compared to the classic CID-based networks. Our approach has enabled higher confidence annotations and finer structure characterization of 823 features, including both metabolites and lipids detected in G. fossarum extracts.
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Affiliation(s)
- Valentina Calabrese
- Universite Claude Bernard Lyon1, ISA, UMR 5280, CNRS, 5 Rue de La Doua, 69100, Villeurbanne, France.
| | - Thomas Alexandre Brunet
- Universite Claude Bernard Lyon1, ISA, UMR 5280, CNRS, 5 Rue de La Doua, 69100, Villeurbanne, France
| | | | - Arnaud Chaumot
- Laboratoire d'écotoxicologie, INRAE, UR RiverLy, 69625, Villeurbanne, France
| | - Olivier Geffard
- Laboratoire d'écotoxicologie, INRAE, UR RiverLy, 69625, Villeurbanne, France
| | - Arnaud Salvador
- Universite Claude Bernard Lyon1, ISA, UMR 5280, CNRS, 5 Rue de La Doua, 69100, Villeurbanne, France
| | - Yohann Clément
- Universite Claude Bernard Lyon1, ISA, UMR 5280, CNRS, 5 Rue de La Doua, 69100, Villeurbanne, France
| | - Sophie Ayciriex
- Universite Claude Bernard Lyon1, ISA, UMR 5280, CNRS, 5 Rue de La Doua, 69100, Villeurbanne, France.
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Chang JK, Teo G, Pewzner-Jung Y, Cuthbertson DJ, Futerman AH, Wenk MR, Choi H, Torta F. Q-RAI data-independent acquisition for lipidomic quantitative profiling. Sci Rep 2023; 13:19281. [PMID: 37935746 PMCID: PMC10630469 DOI: 10.1038/s41598-023-46312-8] [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: 01/31/2023] [Accepted: 10/30/2023] [Indexed: 11/09/2023] Open
Abstract
Untargeted lipidomics has been increasingly adopted for hypothesis generation in a biological context or discovery of disease biomarkers. Most of the current liquid chromatography mass spectrometry (LC-MS) based untargeted methodologies utilize a data dependent acquisition (DDA) approach in pooled samples for identification and MS-only acquisition for semi-quantification in individual samples. In this study, we present for the first time an untargeted lipidomic workflow that makes use of the newly implemented Quadrupole Resolved All-Ions (Q-RAI) acquisition function on the Agilent 6546 quadrupole time-of-flight (Q-TOF) mass spectrometer to acquire MS2 spectra in data independent acquisition (DIA) mode. This is followed by data processing and analysis on MetaboKit, a software enabling DDA-based spectral library construction and extraction of MS1 and MS2 peak areas, for reproducible identification and quantification of lipids in DIA analysis. This workflow was tested on lipid extracts from human plasma and showed quantification at MS1 and MS2 levels comparable to multiple reaction monitoring (MRM) targeted analysis of the same samples. Analysis of serum from Ceramide Synthase 2 (CerS2) null mice using the Q-RAI DIA workflow identified 88 lipid species significantly different between CerS2 null and wild type mice, including well-characterized changes previously associated with this phenotype. Our results show the Q-RAI DIA as a reliable option to perform simultaneous identification and reproducible relative quantification of lipids in exploratory biological studies.
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Affiliation(s)
- Jing Kai Chang
- Precision Medicine Translational Research Programme and Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- SLING, Singapore Lipidomics Incubator, Life Sciences Institute, National University of Singapore, Singapore, Singapore
| | - Guoshou Teo
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Yael Pewzner-Jung
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | | | - Anthony H Futerman
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Markus R Wenk
- Precision Medicine Translational Research Programme and Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- SLING, Singapore Lipidomics Incubator, Life Sciences Institute, National University of Singapore, Singapore, Singapore
| | - Hyungwon Choi
- Precision Medicine Translational Research Programme and Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Federico Torta
- Precision Medicine Translational Research Programme and Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
- SLING, Singapore Lipidomics Incubator, Life Sciences Institute, National University of Singapore, Singapore, Singapore.
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5
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Damont A, Legrand A, Cao C, Fenaille F, Tabet JC. Hydrogen/deuterium exchange mass spectrometry in the world of small molecules. MASS SPECTROMETRY REVIEWS 2023; 42:1300-1331. [PMID: 34859466 DOI: 10.1002/mas.21765] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 11/19/2021] [Accepted: 11/19/2021] [Indexed: 06/07/2023]
Abstract
The combined use of hydrogen/deuterium exchange (HDX) and mass spectrometry (MS), referred to as HDX-MS, is a powerful tool for exploring molecular edifices and has been used for over 60 years. Initially for structural and mechanistic investigation of low-molecular weight organic compounds, then to study protein structure and dynamics, then, the craze to study small molecules by HDX-MS accelerated and has not stopped yet. The purpose of this review is to present its different facets with particular emphasis on recent developments and applications. Reversible H/D exchanges of mobilizable protons as well as stable exchanges of non-labile hydrogen are considered whether they are taking place in solution or in the gas phase, or enzymatically in a biological media. Some fundamental principles are restated, especially for gas-phase processes, and an overview of recent applications, ranging from identification to quantification through the study of metabolic pathways, is given.
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Affiliation(s)
- Annelaure Damont
- Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, Université Paris-Saclay, CEA, INRAE, Gif-sur-Yvette, France
| | - Anaïs Legrand
- Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, Université Paris-Saclay, CEA, INRAE, Gif-sur-Yvette, France
| | - Chenqin Cao
- Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, Université Paris-Saclay, CEA, INRAE, Gif-sur-Yvette, France
| | - François Fenaille
- Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, Université Paris-Saclay, CEA, INRAE, Gif-sur-Yvette, France
| | - Jean-Claude Tabet
- Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, Université Paris-Saclay, CEA, INRAE, Gif-sur-Yvette, France
- Faculté des Sciences et de l'Ingénierie, Institut Parisien de Chimie Moléculaire (IPCM), Sorbonne Université, Paris, France
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Larson TS, Worthington CD, Verber MD, Keating JE, Lockett MR, Glish GL. DiffN Selection of Tandem Mass Spectrometry Precursors. Anal Chem 2023; 95:9581-9588. [PMID: 37310720 PMCID: PMC10640856 DOI: 10.1021/acs.analchem.3c01085] [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] [Indexed: 06/14/2023]
Abstract
Current data-dependent acquisition (DDA) approaches select precursor ions for tandem mass spectrometry (MS/MS) characterization based on their absolute intensity, known as a TopN approach. Low-abundance species may not be identified as biomarkers in a TopN approach. Herein, a new DDA approach is proposed, DiffN, which uses the relative differential intensity of ions between two samples to selectively target species undergoing the largest fold changes for MS/MS. Using a dual nano-electrospray (nESI) ionization source which allows samples contained in separate capillaries to be analyzed in parallel, the DiffN approach was developed and validated with well-defined lipid extracts. A dual nESI source and DiffN DDA approach was applied to quantify the differences in lipid abundance between two colorectal cancer cell lines. The SW480 and SW620 lines represent a matched pair from the same patient: the SW480 cells from a primary tumor and the SW620 cells from a metastatic lesion. A comparison of TopN and DiffN DDA approaches on these cancer cell samples highlights the ability of DiffN to increase the likelihood of biomarker discovery and the decreased probability of TopN to efficiently select lipid species that undergo large fold changes. The ability of the DiffN approach to efficiently select precursor ions of interest makes it a strong candidate for lipidomic analyses. This DiffN DDA approach may also apply to other molecule classes (e.g., other metabolites or proteins) that are amenable to shotgun analyses.
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Affiliation(s)
- Tyler S. Larson
- Department of Chemistry, University of North Carolina at Chapel Hill, Kenan and Caudill Laboratories, Chapel Hill, NC, 27599-3290, United States
| | - Cameron D. Worthington
- Department of Chemistry, University of North Carolina at Chapel Hill, Kenan and Caudill Laboratories, Chapel Hill, NC, 27599-3290, United States
| | - Matthew D. Verber
- Chemistry Electronics Core Laboratory, University of North Carolina at Chapel Hill, Kenan Laboratory, Chapel Hill, NC, 27599-3290, United States
| | - James E. Keating
- Department of Chemistry, University of North Carolina at Chapel Hill, Kenan and Caudill Laboratories, Chapel Hill, NC, 27599-3290, United States
| | - Matthew R. Lockett
- Department of Chemistry, University of North Carolina at Chapel Hill, Kenan and Caudill Laboratories, Chapel Hill, NC, 27599-3290, United States
- Lineberger Comprehensive Cancer Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599-7295, United States
| | - Gary L. Glish
- Department of Chemistry, University of North Carolina at Chapel Hill, Kenan and Caudill Laboratories, Chapel Hill, NC, 27599-3290, United States
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Nijssen R, Blokland MH, Wegh RS, de Lange E, van Leeuwen SPJ, Berendsen BJA, van de Schans MGM. Comparison of Compound Identification Tools Using Data Dependent and Data Independent High-Resolution Mass Spectrometry Spectra. Metabolites 2023; 13:777. [PMID: 37512484 PMCID: PMC10383988 DOI: 10.3390/metabo13070777] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 06/09/2023] [Accepted: 06/20/2023] [Indexed: 07/30/2023] Open
Abstract
Liquid chromatography combined with high-resolution mass spectrometry (LC-HRMS) is a frequently applied technique for suspect screening (SS) and non-target screening (NTS) in metabolomics and environmental toxicology. However, correctly identifying compounds based on SS or NTS approaches remains challenging, especially when using data-independent acquisition (DIA). This study assessed the performance of four HRMS-spectra identification tools to annotate in-house generated data-dependent acquisition (DDA) and DIA HRMS spectra of 32 pesticides, veterinary drugs, and their metabolites. The identification tools were challenged with a diversity of compounds, including isomeric compounds. The identification power was evaluated in solvent standards and spiked feed extract. In DDA spectra, the mass spectral library mzCloud provided the highest success rate, with 84% and 88% of the compounds correctly identified in the top three in solvent standard and spiked feed extract, respectively. The in silico tools MSfinder, CFM-ID, and Chemdistiller also performed well in DDA data, with identification success rates above 75% for both solvent standard and spiked feed extract. MSfinder provided the highest identification success rates using DIA spectra with 72% and 75% (solvent standard and spiked feed extract, respectively), and CFM-ID performed almost similarly in solvent standard and slightly less in spiked feed extract (72% and 63%). The identification success rates for Chemdistiller (66% and 38%) and mzCloud (66% and 31%) were lower, especially in spiked feed extract. The difference in success rates between DDA and DIA is most likely caused by the higher complexity of the DIA spectra, making direct spectral matching more complex. However, this study demonstrates that DIA spectra can be used for compound annotation in certain software tools, although the success rate is lower than for DDA spectra.
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Affiliation(s)
- Rosalie Nijssen
- Wageningen Food Safety Research, Part of Wageningen University and Research, Akkermaalsbos 2, 6708 WB Wageningen, The Netherlands
| | - Marco H Blokland
- Wageningen Food Safety Research, Part of Wageningen University and Research, Akkermaalsbos 2, 6708 WB Wageningen, The Netherlands
| | - Robin S Wegh
- Wageningen Food Safety Research, Part of Wageningen University and Research, Akkermaalsbos 2, 6708 WB Wageningen, The Netherlands
| | - Erik de Lange
- Wageningen Food Safety Research, Part of Wageningen University and Research, Akkermaalsbos 2, 6708 WB Wageningen, The Netherlands
| | - Stefan P J van Leeuwen
- Wageningen Food Safety Research, Part of Wageningen University and Research, Akkermaalsbos 2, 6708 WB Wageningen, The Netherlands
| | - Bjorn J A Berendsen
- Wageningen Food Safety Research, Part of Wageningen University and Research, Akkermaalsbos 2, 6708 WB Wageningen, The Netherlands
| | - Milou G M van de Schans
- Wageningen Food Safety Research, Part of Wageningen University and Research, Akkermaalsbos 2, 6708 WB Wageningen, The Netherlands
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Guo J, Huan T. Mechanistic Understanding of the Discrepancies between Common Peak Picking Algorithms in Liquid Chromatography–Mass Spectrometry-Based Metabolomics. Anal Chem 2023; 95:5894-5902. [PMID: 36972195 DOI: 10.1021/acs.analchem.2c04887] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
Abstract
Inconsistent peak picking outcomes are a critical concern in processing liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics data. This work systematically studied the mechanisms behind the discrepancies among five commonly used peak picking algorithms, including CentWave in XCMS, linear-weighted moving average in MS-DIAL, automated data analysis pipeline (ADAP) in MZmine 2, Savitzky-Golay in El-MAVEN, and FeatureFinderMetabo in OpenMS. We first collected 10 public metabolomics datasets representing various LC-MS analytical conditions. We then incorporated several novel strategies to (i) acquire the optimal peak picking parameters of each algorithm for a fair comparison, (ii) automatically recognize false metabolic features with poor chromatographic peak shapes, and (iii) evaluate the real metabolic features that are missed by the algorithms. By applying these strategies, we compared the true, false, and undetected metabolic features in each data processing outcome. Our results show that linear-weighted moving average consistently outperforms the other peak picking algorithms. To facilitate a mechanistic understanding of the differences, we proposed six peak attributes: ideal slope, sharpness, peak height, mass deviation, peak width, and scan number. We also developed an R program to automatically measure these attributes for detected and undetected true metabolic features. From the results of the 10 datasets, we concluded that four peak attributes, including ideal slope, scan number, peak width, and mass deviation, are critical for the detectability of a peak. For instance, the focus on ideal slope critically hinders the extraction of true metabolic features with low ideal slope scores in linear-weighted moving average, Savitzky-Golay, and ADAP. The relationships between peak picking algorithms and peak attributes were also visualized in a principal component analysis biplot. Overall, the clear comparison and explanation of the differences between peak picking algorithms can lead to the design of better peak picking strategies in the future.
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Ramabulana AT, Petras D, Madala NE, Tugizimana F. Mass spectrometry DDA parameters and global coverage of the metabolome: Spectral molecular networks of momordica cardiospermoides plants. Metabolomics 2023; 19:18. [PMID: 36920561 DOI: 10.1007/s11306-023-01981-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 02/15/2023] [Indexed: 03/16/2023]
Abstract
INTRODUCTION Molecular networking (MN) has emerged as a key strategy to organize and annotate untargeted tandem mass spectrometry (MS/MS) data generated using either data independent- or dependent acquisition (DIA or DDA). The latter presents a time-efficient approach where full scan (MS1) and MS2 spectra are obtained with shorter cycle times. However, there are limitations related to DDA parameters, some of which are (i) intensity threshold and (ii) collision energy. The former determines ion prioritization for fragmentation, and the latter defines the fragmentation of selected ions. These DDA parameters inevitably determine the coverage and quality of spectral data, which would affect the outputs of MN methods. OBJECTIVES This study assessed the extent to which the quality of the tandem spectral data relates to MN topology and subsequent implications in the annotation of metabolites and chemical classification relative to the different DDA parameters employed. METHODS Herein, characterising the metabolome of Momordica cardiospermoides plants, we employ classical MN performance indicators to investigate the effects of collision energies and intensity thresholds on the topology of generated MN and propagated annotations. RESULTS We demonstrated that the lowest predefined intensity thresholds and collision energies result in comprehensive molecular networks. Comparatively, higher intensity thresholds and collision energies resulted in fewer MS2 spectra acquisition, subsequently fewer nodes, and a limited exploration of the metabolome through MN. CONCLUSION Contributing to ongoing efforts and conversations on improving DDA strategies, this study proposes a framework in which multiple DDA parameters are utilized to increase the coverage of ions acquired and improve the global coverage of MN, propagated annotations, and the chemical classification performed.
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Affiliation(s)
| | - Daniel Petras
- CMFI Cluster of Excellence, Interfaculty Institute of Microbiology and Medicine, University of Tubingen, Auf der Morgenstelle 28, Tubingen, 72076, Germany
| | - Ntakadzeni E Madala
- Department of Biochemistry and Microbiology, University of Venda, Thohoyandou, South Africa
| | - Fidele Tugizimana
- Department of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg, South Africa.
- International Research and Development Division, Omnia Group, Ltd, Johannesburg, South Africa.
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Development of an Untargeted Metabolomics Strategy to Study the Metabolic Rewiring of Dendritic Cells upon Lipopolysaccharide Activation. Metabolites 2023; 13:metabo13030311. [PMID: 36984754 PMCID: PMC10058937 DOI: 10.3390/metabo13030311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 02/15/2023] [Accepted: 02/17/2023] [Indexed: 02/23/2023] Open
Abstract
Dendritic cells (DCs) are essential immune cells for defense against external pathogens. Upon activation, DCs undergo profound metabolic alterations whose precise nature remains poorly studied at a large scale and is thus far from being fully understood. The goal of the present work was to develop a reliable and accurate untargeted metabolomics workflow to get a deeper insight into the metabolism of DCs when exposed to an infectious agent (lipopolysaccharide, LPS, was used to mimic bacterial infection). As DCs transition rapidly from a non-adherent to an adherent state upon LPS exposure, one of the leading analytical challenges was to implement a single protocol suitable for getting comparable metabolomic snapshots of those two cellular states. Thus, a thoroughly optimized and robust sample preparation method consisting of a one-pot solvent-assisted method for the simultaneous cell lysis/metabolism quenching and metabolite extraction was first implemented to measure intracellular DC metabolites in an unbiased manner. We also placed special emphasis on metabolome coverage and annotation by using a combination of hydrophilic interaction liquid chromatography and reverse phase columns coupled to high-resolution mass spectrometry in conjunction with an in-house developed spectral database to identify metabolites at a high confidence level. Overall, we were able to characterize up to 171 unique meaningful metabolites in DCs. We then preliminarily compared the metabolic profiles of DCs derived from monocytes of 12 healthy donors upon in vitro LPS activation in a time-course experiment. Interestingly, the resulting data revealed differential and time-dependent activation of some particular metabolic pathways, the most impacted being nucleotides, nucleotide sugars, polyamines pathways, the TCA cycle, and to a lesser extent, the arginine pathway.
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11
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Liu M, Xu X, Wang X, Wang H, Mi Y, Gao X, Guo D, Yang W. Enhanced Identification of Ginsenosides Simultaneously from Seven Panax Herbal Extracts by Data-Dependent Acquisition Including a Preferred Precursor Ions List Derived from an In-House Programmed Virtual Library. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2022; 70:13796-13807. [PMID: 36239255 DOI: 10.1021/acs.jafc.2c06781] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Data-dependent acquisition (DDA) is widely utilized for metabolite identification in natural product research and food science, which, however, can suffer from low coverage. A potential solution to improve DDA coverage is to include the precursor ions list (PIL). Here, we aimed to construct a PIL-containing DDA strategy based on an in-house library of ginsenosides (VLG) and identify ginsenosides simultaneously from seven Panax herbal extracts. VLG, combined with mass defect filtering, could efficiently screen the ginsenoside precursors and elaborate the separate PIL involved in DDA for each ginseng extract. Consequently, we could characterize 500 ginsenosides, including 176 ones with unknown masses. Using the Panax ginseng extract, the superiority of this strategy was embodied in targeting more known ginsenoside masses and newly acquiring the MS2 spectra of 13 components. Conclusively, knowledge-based large-scale molecular prediction and PIL-DDA can represent a powerful targeted/untargeted strategy beneficial to novel natural compound discovery.
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Affiliation(s)
- Meiyu Liu
- State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, China
- Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, China
| | - Xiaoyan Xu
- State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, China
- Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, China
| | - Xiaoyan Wang
- State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, China
- Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, China
| | - Hongda Wang
- State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, China
- Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, China
| | - Yueguang Mi
- State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, China
- Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, China
| | - Xiumei Gao
- State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, China
- Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, China
- Key Laboratory of Pharmacology of Traditional Chinese Medical Formulae, Ministry of Education, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, China
| | - Dean Guo
- State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, China
- Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, China
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 501 Haike Road, Shanghai 201203, China
| | - Wenzhi Yang
- State Key Laboratory of Component-based Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, China
- Haihe Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, China
- Key Laboratory of Pharmacology of Traditional Chinese Medical Formulae, Ministry of Education, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai, Tianjin 301617, China
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12
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Guo J, Yu H, Xing S, Huan T. Addressing big data challenges in mass spectrometry-based metabolomics. Chem Commun (Camb) 2022; 58:9979-9990. [PMID: 35997016 DOI: 10.1039/d2cc03598g] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Advancements in computer science and software engineering have greatly facilitated mass spectrometry (MS)-based untargeted metabolomics. Nowadays, gigabytes of metabolomics data are routinely generated from MS platforms, containing condensed structural and quantitative information from thousands of metabolites. Manual data processing is almost impossible due to the large data size. Therefore, in the "omics" era, we are faced with new challenges, the big data challenges of how to accurately and efficiently process the raw data, extract the biological information, and visualize the results from the gigantic amount of collected data. Although important, proposing solutions to address these big data challenges requires broad interdisciplinary knowledge, which can be challenging for many metabolomics practitioners. Our laboratory in the Department of Chemistry at the University of British Columbia is committed to combining analytical chemistry, computer science, and statistics to develop bioinformatics tools that address these big data challenges. In this Feature Article, we elaborate on the major big data challenges in metabolomics, including data acquisition, feature extraction, quantitative measurements, statistical analysis, and metabolite annotation. We also introduce our recently developed bioinformatics solutions for these challenges. Notably, all of the bioinformatics tools and source codes are freely available on GitHub (https://www.github.com/HuanLab), along with revised and regularly updated content.
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Affiliation(s)
- Jian Guo
- Department of Chemistry, University of British Columbia, 2036 Main Mall, Vancouver, BC Canada, V6T 1Z1, Canada.
| | - Huaxu Yu
- Department of Chemistry, University of British Columbia, 2036 Main Mall, Vancouver, BC Canada, V6T 1Z1, Canada.
| | - Shipei Xing
- Department of Chemistry, University of British Columbia, 2036 Main Mall, Vancouver, BC Canada, V6T 1Z1, Canada.
| | - Tao Huan
- Department of Chemistry, University of British Columbia, 2036 Main Mall, Vancouver, BC Canada, V6T 1Z1, Canada.
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13
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Shah SMZ, Ali A, Khan MN, Khadim A, Asmari M, Uddin J, Musharraf SG. Sensitive Detection of Pharmaceutical Drugs and Metabolites in Serum Using Data-Independent Acquisition Mass Spectrometry and Open-Access Data Acquisition Tools. Pharmaceuticals (Basel) 2022; 15:ph15070901. [PMID: 35890199 PMCID: PMC9317224 DOI: 10.3390/ph15070901] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 07/07/2022] [Accepted: 07/11/2022] [Indexed: 12/19/2022] Open
Abstract
Data-independent acquisition (DIA) based strategies have been explored in recent years for improving quantitative analysis of metabolites. However, the data analysis is challenging for DIA methods as the resulting spectra are highly multiplexed. Thus, the DIA mode requires advanced software analysis to facilitate the data deconvolution process. We proposed a pipeline for quantitative profiling of pharmaceutical drugs and serum metabolites in DIA mode after comparing the results obtained from full-scan, Data-dependent acquisition (DDA) and DIA modes. using open-access software. Pharmaceutical drugs (10) were pooled in healthy human serum and analysed by LC-ESI-QTOF-MS. MS1 full-scan and Data-dependent (MS2) results were used for identification using MS-DIAL software while deconvolution of MS1/MS2 spectra in DIA mode was achieved by using Skyline software. The results of acquisition methods for quantitative analysis validated the remarkable analytical performance of the constructed workflow, proving it to be a sensitive and reproducible pipeline for biological complex fluids.
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Affiliation(s)
- Syed Muhammad Zaki Shah
- International Center for Chemical and Biological Sciences, H.E.J. Research Institute of Chemistry, University of Karachi, Karachi 75270, Pakistan; (S.M.Z.S.); (M.N.K.); (A.K.)
| | - Arslan Ali
- Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan
- Correspondence: or (A.A.); or or (S.G.M.); Tel.: +92-34819010-174 (A.A.); +92-34819010-134 (S.G.M.)
| | - Muhammad Noman Khan
- International Center for Chemical and Biological Sciences, H.E.J. Research Institute of Chemistry, University of Karachi, Karachi 75270, Pakistan; (S.M.Z.S.); (M.N.K.); (A.K.)
| | - Adeeba Khadim
- International Center for Chemical and Biological Sciences, H.E.J. Research Institute of Chemistry, University of Karachi, Karachi 75270, Pakistan; (S.M.Z.S.); (M.N.K.); (A.K.)
| | - Mufarreh Asmari
- Department of Pharmaceutical Chemistry, College of Pharmacy, Abha 62529, Saudi Arabia; (M.A.); (J.U.)
| | - Jalal Uddin
- Department of Pharmaceutical Chemistry, College of Pharmacy, Abha 62529, Saudi Arabia; (M.A.); (J.U.)
| | - Syed Ghulam Musharraf
- International Center for Chemical and Biological Sciences, H.E.J. Research Institute of Chemistry, University of Karachi, Karachi 75270, Pakistan; (S.M.Z.S.); (M.N.K.); (A.K.)
- Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan
- The Affiliated T.C.M Hospital of Southwest Medical University, Luzhou 646099, China
- Correspondence: or (A.A.); or or (S.G.M.); Tel.: +92-34819010-174 (A.A.); +92-34819010-134 (S.G.M.)
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Magny R, Auzeil N, Lefrère B, Mégarbane B, Houzé P, Labat L. Molecular Network-Based Identification of Tramadol Metabolites in a Fatal Tramadol Poisoning. Metabolites 2022; 12:metabo12070665. [PMID: 35888789 PMCID: PMC9323855 DOI: 10.3390/metabo12070665] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 07/13/2022] [Accepted: 07/14/2022] [Indexed: 01/19/2023] Open
Abstract
Identification of xenobiotics and their phase I/II metabolites in poisoned patients remains challenging. Systematic approaches using bioinformatic tools are needed to detect all compounds as exhaustively as possible. Here, we aimed to assess an analytical workflow using liquid chromatography coupled to high-resolution mass spectrometry with data processing based on a molecular network to identify tramadol metabolites in urine and plasma in poisoned patients. The generated molecular network from liquid chromatography coupled to high-resolution tandem mass spectrometry data acquired in both positive and negative ion modes allowed for the identification of 25 tramadol metabolites in urine and plasma, including four methylated metabolites that have not been previously reported in humans or in vitro models. While positive ion mode is reliable for generating a network of tramadol metabolites displaying a dimethylamino radical in their structure, negative ion mode was useful to cluster phase II metabolites. In conclusion, the combined use of molecular networks in positive and negative ion modes is a suitable and robust tool to identify a broad range of metabolites in poisoned patients, as shown in a fatal tramadol-poisoned patient.
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Affiliation(s)
- Romain Magny
- Laboratoire de Toxicologie, Fédération de Toxicologie, AP-HP, Hôpital Lariboisière, 75006 Paris, France; (B.L.); (P.H.); (L.L.)
- Université Paris Cité, CNRS, CiTCoM, 75006 Paris, France;
- Correspondence:
| | - Nicolas Auzeil
- Université Paris Cité, CNRS, CiTCoM, 75006 Paris, France;
| | - Bertrand Lefrère
- Laboratoire de Toxicologie, Fédération de Toxicologie, AP-HP, Hôpital Lariboisière, 75006 Paris, France; (B.L.); (P.H.); (L.L.)
| | - Bruno Mégarbane
- Réanimation Médicale et Toxicologique, Fédération de Toxicologie, AP-HP, Hôpital Lariboisière, 75010 Paris, France;
- Inserm, UMRS-1144, Université Paris Cité, 75006 Paris, France
| | - Pascal Houzé
- Laboratoire de Toxicologie, Fédération de Toxicologie, AP-HP, Hôpital Lariboisière, 75006 Paris, France; (B.L.); (P.H.); (L.L.)
- Université Paris Cité, CNRS, INSERM, Unité des Technologies Chimiques Et Biologiques Pour La Santé (UTCBS), 75006 Paris, France
| | - Laurence Labat
- Laboratoire de Toxicologie, Fédération de Toxicologie, AP-HP, Hôpital Lariboisière, 75006 Paris, France; (B.L.); (P.H.); (L.L.)
- Inserm, UMRS-1144, Université Paris Cité, 75006 Paris, France
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15
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High Sesitivity and High-Confidence Compound Identification with a Flexible BoxCar Acquisition Method. J Pharm Biomed Anal 2022; 219:114973. [DOI: 10.1016/j.jpba.2022.114973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Revised: 07/24/2022] [Accepted: 07/27/2022] [Indexed: 11/19/2022]
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16
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Anh NH, Yoon YC, Min YJ, Long NP, Jung CW, Kim SJ, Kim SW, Lee EG, Wang D, Wang X, Kwon SW. Caenorhabditis elegans deep lipidome profiling by using integrative mass spectrometry acquisitions reveals significantly altered lipid networks. J Pharm Anal 2022; 12:743-754. [PMID: 36320604 PMCID: PMC9615529 DOI: 10.1016/j.jpha.2022.06.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 06/14/2022] [Accepted: 06/15/2022] [Indexed: 12/02/2022] Open
Abstract
Lipidomics coverage improvement is essential for functional lipid and pathway construction. A powerful approach to discovering organism lipidome is to combine various data acquisitions, such as full scan mass spectrometry (full MS), data-dependent acquisition (DDA), and data-independent acquisition (DIA). Caenorhabditis elegans (C. elegans) is a useful model for discovering toxic-induced metabolism, high-throughput drug screening, and a variety of human disease pathways. To determine the lipidome of C. elegans and investigate lipid disruption from the molecular level to the system biology level, we used integrative data acquisition. The methyl-tert-butyl ether method was used to extract L4 stage C. elegans after exposure to triclosan (TCS), perfluorooctanoic acid, and nanopolystyrene (nPS). Full MS, DDA, and DIA integrations were performed to comprehensively profile the C. elegans lipidome by Q-Exactive Plus MS. All annotated lipids were then analyzed using lipid ontology and pathway analysis. We annotated up to 940 lipids from 20 lipid classes involved in various functions and pathways. The biological investigations revealed that when C. elegans were exposed to nPS, lipid droplets were disrupted, whereas plasma membrane-functionalized lipids were likely to be changed in the TCS treatment group. The nPS treatment caused a significant disruption in lipid storage. Triacylglycerol, glycerophospholipid, and ether class lipids were those primarily hindered by toxicants. Finally, toxicant exposure frequently involved numerous lipid-related pathways, including the phosphoinositide 3-kinase/protein kinase B pathway. In conclusion, an integrative data acquisition strategy was used to characterize the C. elegans lipidome, providing valuable biological insights into hypothesis generation and validation. Multiple data acquisitions were used to profile the lipidome of C. elegans. 940 detected lipids of 20 main classes involved in various pathways. Relevant hypotheses were generated using high-coverable lipidomics and pathways analysis.
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17
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Tabone M, García-Merino JA, Bressa C, Rocha Guzman NE, Herrera Rocha K, Chu Van E, Castelli FA, Fenaille F, Larrosa M. Chronic Consumption of Cocoa Rich in Procyanidins Has a Marginal Impact on Gut Microbiota and on Serum and Fecal Metabolomes in Male Endurance Athletes. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2022; 70:1878-1889. [PMID: 35112856 DOI: 10.1021/acs.jafc.1c07547] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Cocoa is used in the sports world as a supplement, although there is no consensus on its use. We investigated the effect of cocoa intake on intestinal ischemia (intestinal fatty acid-binding protein (I-FABP)), serum lipopolysaccharide (LPS) levels, gastrointestinal symptoms, and gut microbiota in endurance athletes during their training period on an unrestricted diet. We also performed a metabolomics analysis of serum and feces after a bout of exercise before and after supplementation. Cocoa consumption had no effect on I-FABP, LPS, or gastrointestinal symptoms. Cocoa intake significantly increased the abundance of Blautia and Lachnospira genera and decreased the abundance of the Agathobacter genus, which was accompanied by elevated levels of polyphenol fecal metabolites 4-hydroxy-5-(phenyl)-valeric acid and O-methyl-epicatechin-O-glucuronide. Our untargeted approach revealed that cocoa had no significant effects on serum and fecal metabolites and that its consumption had little impact on the metabolome after a bout of physical exercise.
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Affiliation(s)
- Mariangela Tabone
- MAS Microbiota Group, Faculty of Biomedical and Health Sciences, Universidad Europea de Madrid, Madrid 28670, Spain
| | - Jose Angel García-Merino
- MAS Microbiota Group, Faculty of Biomedical and Health Sciences, Universidad Europea de Madrid, Madrid 28670, Spain
| | - Carlo Bressa
- MAS Microbiota Group, Faculty of Biomedical and Health Sciences, Universidad Europea de Madrid, Madrid 28670, Spain
- Facultad de Ciencias Experimentales, Universidad Francisco de Vitoria, Pozuelo de Alarcón, Madrid 28223, Spain
| | - Nuria Elizabeth Rocha Guzman
- Grupo de Investigación en Alimentos Funcionales y Nutracéuticos, Unidad de Posgrado, Investigación y Desarrollo Tecnológico, TecNM/Instituto Tecnológico de Durango, Durango 34080, México
| | - Karen Herrera Rocha
- Grupo de Investigación en Alimentos Funcionales y Nutracéuticos, Unidad de Posgrado, Investigación y Desarrollo Tecnológico, TecNM/Instituto Tecnológico de Durango, Durango 34080, México
| | - Emeline Chu Van
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, F-91191 Gif sur Yvette, France
| | - Florence A Castelli
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, F-91191 Gif sur Yvette, France
| | - François Fenaille
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, F-91191 Gif sur Yvette, France
| | - Mar Larrosa
- MAS Microbiota Group, Faculty of Biomedical and Health Sciences, Universidad Europea de Madrid, Madrid 28670, Spain
- Department of Nutrition and Food Science, School of Pharmacy, Complutense University of Madrid (UCM), Madrid 28040, Spain
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18
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Recent Developments in Clinical Plasma Proteomics—Applied to Cardiovascular Research. Biomedicines 2022; 10:biomedicines10010162. [PMID: 35052841 PMCID: PMC8773619 DOI: 10.3390/biomedicines10010162] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 01/05/2022] [Accepted: 01/12/2022] [Indexed: 01/27/2023] Open
Abstract
The human plasma proteome mirrors the physiological state of the cardiovascular system, a fact that has been used to analyze plasma biomarkers in routine analysis for the diagnosis and monitoring of cardiovascular diseases for decades. These biomarkers address, however, only a very limited subset of cardiovascular diseases, such as acute myocardial infarct or acute deep vein thrombosis, and clinical plasma biomarkers for the diagnosis and stratification cardiovascular diseases that are growing in incidence, such as heart failure and abdominal aortic aneurysm, do not exist and are urgently needed. The discovery of novel biomarkers in plasma has been hindered by the complexity of the human plasma proteome that again transforms into an extreme analytical complexity when it comes to the discovery of novel plasma biomarkers. This complexity is, however, addressed by recent achievements in technologies for analyzing the human plasma proteome, thereby facilitating the possibility for novel biomarker discoveries. The aims of this article is to provide an overview of the recent achievements in technologies for proteomic analysis of the human plasma proteome and their applications in cardiovascular medicine.
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Castelli FA, Rosati G, Moguet C, Fuentes C, Marrugo-Ramírez J, Lefebvre T, Volland H, Merkoçi A, Simon S, Fenaille F, Junot C. Metabolomics for personalized medicine: the input of analytical chemistry from biomarker discovery to point-of-care tests. Anal Bioanal Chem 2022; 414:759-789. [PMID: 34432105 PMCID: PMC8386160 DOI: 10.1007/s00216-021-03586-z] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 07/24/2021] [Accepted: 07/27/2021] [Indexed: 12/30/2022]
Abstract
Metabolomics refers to the large-scale detection, quantification, and analysis of small molecules (metabolites) in biological media. Although metabolomics, alone or combined with other omics data, has already demonstrated its relevance for patient stratification in the frame of research projects and clinical studies, much remains to be done to move this approach to the clinical practice. This is especially true in the perspective of being applied to personalized/precision medicine, which aims at stratifying patients according to their risk of developing diseases, and tailoring medical treatments of patients according to individual characteristics in order to improve their efficacy and limit their toxicity. In this review article, we discuss the main challenges linked to analytical chemistry that need to be addressed to foster the implementation of metabolomics in the clinics and the use of the data produced by this approach in personalized medicine. First of all, there are already well-known issues related to untargeted metabolomics workflows at the levels of data production (lack of standardization), metabolite identification (small proportion of annotated features and identified metabolites), and data processing (from automatic detection of features to multi-omic data integration) that hamper the inter-operability and reusability of metabolomics data. Furthermore, the outputs of metabolomics workflows are complex molecular signatures of few tens of metabolites, often with small abundance variations, and obtained with expensive laboratory equipment. It is thus necessary to simplify these molecular signatures so that they can be produced and used in the field. This last point, which is still poorly addressed by the metabolomics community, may be crucial in a near future with the increased availability of molecular signatures of medical relevance and the increased societal demand for participatory medicine.
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Affiliation(s)
- Florence Anne Castelli
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (MTS), Gif-sur-Yvette cedex, 91191, France
- MetaboHUB, Gif-sur-Yvette, France
| | - Giulio Rosati
- Institut Català de Nanociència i Nanotecnologia (ICN2), Edifici ICN2 Campus UAB, 08193 Bellaterra, Barcelona, Spain
| | - Christian Moguet
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (MTS), Gif-sur-Yvette cedex, 91191, France
| | - Celia Fuentes
- Institut Català de Nanociència i Nanotecnologia (ICN2), Edifici ICN2 Campus UAB, 08193 Bellaterra, Barcelona, Spain
| | - Jose Marrugo-Ramírez
- Institut Català de Nanociència i Nanotecnologia (ICN2), Edifici ICN2 Campus UAB, 08193 Bellaterra, Barcelona, Spain
| | - Thibaud Lefebvre
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (MTS), Gif-sur-Yvette cedex, 91191, France
- Centre de Recherche sur l'Inflammation/CRI, Université de Paris, Inserm, Paris, France
- CRMR Porphyrie, Hôpital Louis Mourier, AP-HP Nord - Université de Paris, Colombes, France
| | - Hervé Volland
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (MTS), Gif-sur-Yvette cedex, 91191, France
| | - Arben Merkoçi
- Institut Català de Nanociència i Nanotecnologia (ICN2), Edifici ICN2 Campus UAB, 08193 Bellaterra, Barcelona, Spain
| | - Stéphanie Simon
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (MTS), Gif-sur-Yvette cedex, 91191, France
| | - François Fenaille
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (MTS), Gif-sur-Yvette cedex, 91191, France
- MetaboHUB, Gif-sur-Yvette, France
| | - Christophe Junot
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (MTS), Gif-sur-Yvette cedex, 91191, France.
- MetaboHUB, Gif-sur-Yvette, France.
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20
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Ye D, Li X, Shen J, Xia X. Microbial metabolomics: From novel technologies to diversified applications. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116540] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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21
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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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22
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Wang C, Pang X, Zhu T, Ma S, Liang Y, Zhang Y, Lan X, Wang T, Han L. Rapid discovery of potential ADR compounds from injection of total saponins from Panax notoginseng using data-independent acquisition untargeted metabolomics. Anal Bioanal Chem 2021; 414:1081-1093. [PMID: 34697654 DOI: 10.1007/s00216-021-03734-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 10/09/2021] [Accepted: 10/12/2021] [Indexed: 11/24/2022]
Abstract
Injection of total saponins from Panax notoginseng (ISPN) is a modern preparation derived from traditional Chinese medicine (TCM) and is widely applied in the treatment of cardiovascular, cerebrovascular, ophthalmology, and endocrine system diseases. With the increase in the clinical application of ISPN, its adverse drug reactions (ADRs) and related safety issues have attracted much attention. In the present study, a data-independent acquisition (DIA) strategy was proposed to comprehensively characterize the saponins contained in ISPN based on the ultra-high-performance liquid chromatography/quadrupole-Orbitrap MS (UHPLC/Q-Orbitrap MS) platform. As many as 276 saponins were detected, and 250 compounds were identified or tentatively identified based on the retention times and MS/MS data. Furthermore, a metabolomic strategy was utilized to discover the discriminative saponins between normal and ADR batches. The results showed that six saponins, including ginsenoside Rh4, ginsenoside Rk3, ginsenoside Rg5, ginsenoside Rk1, ginsenoside Rg6, and 20(S)-ginsenoside Rh2, were significantly different between the two groups. According to cytotoxicity analysis and degranulation detection of RBL-2H3 cells, ginsenoside Rg5, ginsenoside Rk1, and 20(S)-ginsenoside Rh2 were considered the potential compounds responsible for clinical ADRs, ultimately. In addition, the quantitative analysis showed that the content of these three compounds in ISPN samples with ADRs was generally higher than that in samples without ADRs. This study demonstrated that it is advisable to screen out potential markers related to ADRs for developing the quality standard of ISPN by the integration of untargeted metabolomic analysis and cell biology study, and thus reduce its ADRs in the clinic.
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Affiliation(s)
- Chenxi Wang
- State Key Laboratory of Component-based Chinese Medicine, Tianjin Key Laboratory of TCM Chemistry and Analysis, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai District, Tianjin, 301617, People's Republic of China
| | - Xu Pang
- State Key Laboratory of Component-based Chinese Medicine, Tianjin Key Laboratory of TCM Chemistry and Analysis, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai District, Tianjin, 301617, People's Republic of China
| | - Tongtong Zhu
- State Key Laboratory of Component-based Chinese Medicine, Tianjin Key Laboratory of TCM Chemistry and Analysis, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai District, Tianjin, 301617, People's Republic of China
| | - Shuhua Ma
- Beijing Key Laboratory of TCM Basic Research on Prevention and Treatment of Major Disease, Experimental Research Center, China Academy of Chinese Medical Sciences, 16 Nanxiao Road, Dongzhimen, Beijing, 100700, People's Republic of China
| | - Yunfei Liang
- Guangxi Wuzhou Pharmaceutical (Group) Co., LTD., No.1 Industrial Avenue, Wuzhou Industrial Park, Guangxi, 543002, People's Republic of China
| | - Yi Zhang
- State Key Laboratory of Component-based Chinese Medicine, Tianjin Key Laboratory of TCM Chemistry and Analysis, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai District, Tianjin, 301617, People's Republic of China
| | - Xing Lan
- Guangxi Wuzhou Pharmaceutical (Group) Co., LTD., No.1 Industrial Avenue, Wuzhou Industrial Park, Guangxi, 543002, People's Republic of China
| | - Tao Wang
- State Key Laboratory of Component-based Chinese Medicine, Tianjin Key Laboratory of TCM Chemistry and Analysis, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai District, Tianjin, 301617, People's Republic of China.
| | - Lifeng Han
- State Key Laboratory of Component-based Chinese Medicine, Tianjin Key Laboratory of TCM Chemistry and Analysis, Tianjin University of Traditional Chinese Medicine, 10 Poyanghu Road, Jinghai District, Tianjin, 301617, People's Republic of China.
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23
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Furlani IL, da Cruz Nunes E, Canuto GAB, Macedo AN, Oliveira RV. Liquid Chromatography-Mass Spectrometry for Clinical Metabolomics: An Overview. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1336:179-213. [PMID: 34628633 DOI: 10.1007/978-3-030-77252-9_10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/28/2023]
Abstract
Metabolomics is a discipline that offers a comprehensive analysis of metabolites in biological samples. In the last decades, the notable evolution in liquid chromatography and mass spectrometry technologies has driven an exponential progress in LC-MS-based metabolomics. Targeted and untargeted metabolomics strategies are important tools in health and medical science, especially in the study of disease-related biomarkers, drug discovery and development, toxicology, diet, physical exercise, and precision medicine. Clinical and biological problems can now be understood in terms of metabolic phenotyping. This overview highlights the current approaches to LC-MS-based metabolomics analysis and its applications in the clinical research.
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Affiliation(s)
- Izadora L Furlani
- Núcleo de Pesquisa em Cromatografia (Separare), Department of Chemistry, Federal University of São Carlos, São Carlos, SP, Brazil
| | - Estéfane da Cruz Nunes
- Department of Analytical Chemistry, Institute of Chemistry, Federal University of Bahia, Salvador, BA, Brazil
| | - Gisele A B Canuto
- Department of Analytical Chemistry, Institute of Chemistry, Federal University of Bahia, Salvador, BA, Brazil
| | - Adriana N Macedo
- Department of Chemistry, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil
| | - Regina V Oliveira
- Núcleo de Pesquisa em Cromatografia (Separare), Department of Chemistry, Federal University of São Carlos, São Carlos, SP, Brazil.
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24
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Tabet JC, Gimbert Y, Damont A, Touboul D, Fenaille F, Woods AS. Combining Chemical Knowledge and Quantum Calculation for Interpreting Low-Energy Product Ion Spectra of Metabolite Adduct Ions: Sodiated Diterpene Diester Species as a Case Study. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2021; 32:2499-2504. [PMID: 34469144 PMCID: PMC8903029 DOI: 10.1021/jasms.1c00154] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
We investigated the product ion spectra of [M + Na]+ from diterpene diester species and low molecular mass metabolites analyzed by electrospray ionization (ESI). Mainly, the formation of protonated salt structures was proposed to explain the observed neutral losses of carboxylic acids. It also facilitates understanding sodium retention on product ions or on neutral losses. In addition, the occurrence of consecutive carboxylic acid losses is rather unexpected under resonant excitation conditions. Quantum calculation demonstrated that the exothermic character of such neutral losses can represent a relevant explanation. There is no doubt that the formation and role of the protonated salt structures will be helpful for a better understanding and software-assisted interpretation of tandem mass spectra from small molecules, especially in the ever-growing metabolomics field.
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Affiliation(s)
- Jean-Claude Tabet
- Sorbonne Université, Faculté des Sciences et de l’Ingénierie, Institut Parisien de Chimie Moléculaire (IPCM), F-75005 Paris, France
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, F-91191 Gif sur Yvette, France
| | - Yves Gimbert
- Sorbonne Université, Faculté des Sciences et de l’Ingénierie, Institut Parisien de Chimie Moléculaire (IPCM), F-75005 Paris, France
- Département de Chimie Moléculaire, UMR CNRS 5250, Université Grenoble Alpes, 38058 Grenoble, France
| | - Annelaure Damont
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, F-91191 Gif sur Yvette, France
| | - David Touboul
- Université Paris-Saclay, CNRS, Institut de Chimie des Substances Naturelles, UPR 2301, 91198, Gif-sur-Yvette, France
| | - François Fenaille
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, F-91191 Gif sur Yvette, France
| | - Amina S. Woods
- NIDA IRP, NIH Structural Biology Unit Integrative Neuroscience Branch, 333 Cassell Drive, Baltimore, Maryland 21224, United States
- The Johns Hopkins University School of Medicine, Pharmacology and Molecular Sciences, Baltimore, MD 21205
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25
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Villaseñor A, Godzien J, Barker-Tejeda TC, Gonzalez-Riano C, López-López Á, Dudzik D, Gradillas A, Barbas C. Analytical approaches for studying oxygenated lipids in the search of potential biomarkers by LC-MS. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2021.116367] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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26
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Shanthamoorthy P, Young A, Röst H. Analyzing Assay Specificity in Metabolomics Using Unique Ion Signature Simulations. Anal Chem 2021; 93:11415-11423. [PMID: 34375078 DOI: 10.1021/acs.analchem.1c01204] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Targeted, untargeted, and data-independent acquisition (DIA) metabolomics workflows are often hampered by ambiguous identification based on either MS1 information alone or relatively few MS2 fragment ions. While DIA methods have been popularized in proteomics, it is less clear whether they are suitable for metabolomics workflows due to their large precursor isolation windows and complex coisolation patterns. Here, we quantitatively investigate the conditions necessary for unique metabolite detection in complex backgrounds using precursor and fragment ion mass-to-charge (m/z) separation, comparing three benchmarked mass spectrometry (MS) methods [MS1, MRM (multiple reaction monitoring), and DIA]. Our simulations show that DIA outperformed MS1-only and MRM-based methods with regards to specificity by factors of ∼2.8-fold and ∼1.8-fold, respectively. Additionally, we show that our results are not dependent on the number of transitions used or the complexity of the background matrix. Finally, we show that collision energy is an important factor in unambiguous detection and that a single collision energy setting per compound cannot achieve optimal pairwise differentiation of compounds. Our analysis demonstrates the power of using both high-resolution precursor and high-resolution fragment ion m/z for unambiguous compound detection. This work also establishes DIA as an emerging MS acquisition method with high selectivity for metabolomics, outperforming both data-dependent acquisition (DDA) and MRM with regards to unique compound identification potential.
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Affiliation(s)
- Premy Shanthamoorthy
- Terrence Donnelly Centre for Cellular Biomolecular Research, University of Toronto, 160 College Street, Toronto, Ontario M5S 3E1, Canada.,Department of Molecular Genetics, University of Toronto, 160 College Street, Toronto, Ontario M5S 3E1, Canada
| | - Adamo Young
- Terrence Donnelly Centre for Cellular Biomolecular Research, University of Toronto, 160 College Street, Toronto, Ontario M5S 3E1, Canada.,Department of Computer Science, University of Toronto, 160 College Street, Toronto, Ontario M5S 3E1, Canada
| | - Hannes Röst
- Terrence Donnelly Centre for Cellular Biomolecular Research, University of Toronto, 160 College Street, Toronto, Ontario M5S 3E1, Canada.,Department of Molecular Genetics, University of Toronto, 160 College Street, Toronto, Ontario M5S 3E1, Canada.,Department of Computer Science, University of Toronto, 160 College Street, Toronto, Ontario M5S 3E1, Canada
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27
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Xu R, Lee J, Chen L, Zhu J. Enhanced detection and annotation of small molecules in metabolomics using molecular-network-oriented parameter optimization. Mol Omics 2021; 17:665-676. [PMID: 34355227 DOI: 10.1039/d1mo00005e] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Metabolomics, especially the large-scale untargeted metabolomics, generates massive amounts of data on a regular basis, which often needs to be filtered, screened, analyzed and annotated via a variety of approaches. Data-dependent-acquisition (DDA) mode including inclusion and exclusion rules for tandem mass spectrometry (MS) is routinely used to perform such analyses. While the parameters of data acquisition are important in these processes, there is a lack of systematic studies on these parameters that can be used in data collection to generate metabolic features for molecular-network (MN) analysis on the Global Natural Products Social Molecular Networking (GNPS) platform. To explore the key parameters that impact the formation and quality of MNs, several data-acquisition parameters for metabolomic studies were proposed in this study. The influences of MS1 resolution, normalized collision energy (NCE), intensity threshold, and exclusion time on GNPS analyses were demonstrated. Moreover, an optimization workflow dedicated to Thermo Scientific QE Hybrid Orbitrap instruments is described, and a comparison of phytochemical contents from two forms of black raspberry extract was performed based on the GNPS MN results. Overall, we expect this study to provide additional thoughts on developing a natural-product-analysis workflow using the GNPS network, and to shed some light on future analyses that utilize similar instrumental setups.
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Affiliation(s)
- Rui Xu
- Human Nutrition Program, The Ohio State University, Columbus, Ohio 43210, USA.
| | - Jisun Lee
- Human Nutrition Program, The Ohio State University, Columbus, Ohio 43210, USA.
| | - Li Chen
- Human Nutrition Program, The Ohio State University, Columbus, Ohio 43210, USA.
| | - Jiangjiang Zhu
- Human Nutrition Program, The Ohio State University, Columbus, Ohio 43210, USA. and James Comprehensive Cancer Center, The Ohio State University, 400 W 12th Ave, Columbus, Ohio 43210, USA
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28
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Ruan Q, Comstock K. A New Workflow for Drug Metabolite Profiling by Utilizing Advanced Tribrid Mass Spectrometry and Data-Processing Techniques. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2021; 32:2050-2061. [PMID: 33998806 DOI: 10.1021/jasms.0c00436] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Drug metabolite profiling utilizes liquid chromatography with tandem mass spectrometry (LC/MS/MS) to acquire ample information for metabolite identification and structural elucidation. However, there are still challenges in detecting and characterizing all potential metabolites that can be masked by a high biological background, especially the unknown and uncommon ones. In this work, a novel metabolite profiling workflow was established on a platform using a state-of-the-art tribrid high-resolution mass spectrometry (HRMS) system. Primarily, an instrumental method was developed based on the novel design of the tribrid system that facilitates in-depth MSn scans with two fragmentation devices. Additionally, different advanced data acquisition techniques were assessed and compared, and automatic background exclusion and deep-scan approaches were adopted to promote assay efficiency and metabolite coverage. Finally, different data-analysis techniques were explored to fully extract metabolite data from the information-rich MS/MS data sets. Overall, a workflow combining tribrid mass spectrometry and advanced acquisition methodology has been developed for metabolite characterization in drug discovery and development. It maximizes the tribrid HRMS platform's utility and enhances the coverage, efficiency, quality, and speed of metabolite profiling assays.
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Affiliation(s)
- Qian Ruan
- Non-clinical Disposition and Bioanalysis, BMS, Princeton, New Jersey 08540, United States
| | - Kate Comstock
- Thermo Fisher Scientific, San Jose, California 95134, United States
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29
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Rocchetti G, O’Callaghan TF. Application of metabolomics to assess milk quality and traceability. Curr Opin Food Sci 2021. [DOI: 10.1016/j.cofs.2021.04.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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30
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Kim HM, Kang JS. Metabolomic Studies for the Evaluation of Toxicity Induced by Environmental Toxicants on Model Organisms. Metabolites 2021; 11:485. [PMID: 34436425 PMCID: PMC8402193 DOI: 10.3390/metabo11080485] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Revised: 07/23/2021] [Accepted: 07/26/2021] [Indexed: 12/11/2022] Open
Abstract
Environmental pollution causes significant toxicity to ecosystems. Thus, acquiring a deeper understanding of the concentration of environmental pollutants in ecosystems and, clarifying their potential toxicities is of great significance. Environmental metabolomics is a powerful technique in investigating the effects of pollutants on living organisms in the environment. In this review, we cover the different aspects of the environmental metabolomics approach, which allows the acquisition of reliable data. A step-by-step procedure from sample preparation to data interpretation is also discussed. Additionally, other factors, including model organisms and various types of emerging environmental toxicants are discussed. Moreover, we cover the considerations for successful environmental metabolomics as well as the identification of toxic effects based on data interpretation in combination with phenotype assays. Finally, the effects induced by various types of environmental toxicants in model organisms based on the application of environmental metabolomics are also discussed.
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Affiliation(s)
- Hyung Min Kim
- College of Pharmacy, Chungnam National University, Daejeon 34134, Korea
| | - Jong Seong Kang
- College of Pharmacy, Chungnam National University, Daejeon 34134, Korea
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31
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Changes in the chemical and sensory profile of ripened Italian salami following the addition of different microbial starters. Meat Sci 2021; 180:108584. [PMID: 34087663 DOI: 10.1016/j.meatsci.2021.108584] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 05/26/2021] [Accepted: 05/26/2021] [Indexed: 12/25/2022]
Abstract
In this work, Italian salami were produced using microbial starters (Pediococcus pentosaceus, Lactobacillus sakei, and Staphylococcus xylosus) and compared to a control sample (without starter). Metabolomics in combination with microbiological and sensory analyses were used to investigate the overall quality. Samples were analyzed immediately after stuffing, following 7, 30, and 45 days of ripening. Each microbial starter imposed distinctive metabolomic signatures at the end of ripening. The accumulated discriminant compounds were mainly related to lipid oxidation (including hydroxy- and epoxy derivatives of fatty acids) following the inoculation with L. sakei. However, the inoculation with P. pentosaceus resulted in the accumulation of γ-glutamyl peptides, compounds driving a kokumi-related taste. Noteworthy, our findings supported the involvement of the chemical compounds profiled in the definition of final taste and aroma. This information paves the way towards the definition of more objective and tailored starters-related flavours enhancement approaches in the sector of cured meat.
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32
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Andean Blueberry of the Genus Disterigma: A High-Resolution Mass Spectrometric Approach for the Comprehensive Characterization of Phenolic Compounds. SEPARATIONS 2021. [DOI: 10.3390/separations8050058] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Wild neotropical blueberries, endemic of Central and South American areas, are promising yet still undisclosed sources of bioactive compounds. Most research studies have addressed wild and cultivated blueberries from Europe and North America, despite the extremely wide variety of wild neotropical species. In the present paper, for the first time, the phenolic composition of Disterigma alaternoides was investigated through ultra-high-performance liquid chromatography coupled to high-resolution mass-spectrometric analysis followed by accurate data analysis and compound validation with a dedicated structure-based workflow. D. alaternoides, which belongs to a closely related genus to that of the common blueberry, grows exclusively in the Andean regions over 2000 above sea level. Thanks to the dedicated analytical platform, 249 phenolic compounds were tentatively identified, including several anthocyanins, flavonoids, phenolic acids, and proanthocyanidins. Thenature and heterogeneity of identified phenolic compounds demonstrate once more the need for a more profound knowledge of such still uncharted matrices.
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33
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Pak H, Michaux J, Huber F, Chong C, Stevenson BJ, Müller M, Coukos G, Bassani-Sternberg M. Sensitive Immunopeptidomics by Leveraging Available Large-Scale Multi-HLA Spectral Libraries, Data-Independent Acquisition, and MS/MS Prediction. Mol Cell Proteomics 2021; 20:100080. [PMID: 33845167 PMCID: PMC8724634 DOI: 10.1016/j.mcpro.2021.100080] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 03/18/2021] [Accepted: 04/05/2021] [Indexed: 12/15/2022] Open
Abstract
Mass spectrometry (MS) is the state-of-the-art methodology for capturing the breadth and depth of the immunopeptidome across human leukocyte antigen (HLA) allotypes and cell types. The majority of studies in the immunopeptidomics field are discovery driven. Hence, data-dependent tandem MS (MS/MS) acquisition (DDA) is widely used, as it generates high-quality references of peptide fingerprints. However, DDA suffers from the stochastic selection of abundant ions that impairs sensitivity and reproducibility. In contrast, in data-independent acquisition (DIA), the systematic fragmentation and acquisition of all fragment ions within given isolation m/z windows yield a comprehensive map for a given sample. However, many DIA approaches commonly require generating comprehensive DDA-based spectrum libraries, which can become impractical for studying noncanonical and personalized neoantigens. Because the amount of HLA peptides eluted from biological samples such as small tissue biopsies is typically not sufficient for acquiring both meaningful DDA data necessary for generating comprehensive spectral libraries and DIA MS measurements, the implementation of DIA in the immunopeptidomics translational research domain has remained limited. We implemented a DIA immunopeptidomics workflow and assessed its sensitivity and accuracy by matching DIA data against libraries with growing complexity-from sample-specific libraries to libraries combining 2 to 40 different immunopeptidomics samples. Analyzing DIA immunopeptidomics data against a complex multi-HLA spectral library resulted in a two-fold increase in peptide identification compared with sample-specific library and in a three-fold increase compared with DDA measurements, yet with no detrimental effect on the specificity. Furthermore, we demonstrated the implementation of DIA for sensitive personalized neoantigen discovery through the analysis of DIA data with predicted MS/MS spectra of clinically relevant HLA ligands. We conclude that a comprehensive multi-HLA library for DIA approach in combination with MS/MS prediction is highly advantageous for clinical immunopeptidomics, especially when low amounts of biological samples are available.
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Affiliation(s)
- HuiSong Pak
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland
| | - Justine Michaux
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland
| | - Florian Huber
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland
| | - Chloe Chong
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland
| | | | - Markus Müller
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland; SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - George Coukos
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland
| | - Michal Bassani-Sternberg
- Department of Oncology, Ludwig Institute for Cancer Research Lausanne, Lausanne University Hospital and the University of Lausanne, Lausanne, Switzerland.
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34
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Cho K, Schwaiger-Haber M, Naser FJ, Stancliffe E, Sindelar M, Patti GJ. Targeting unique biological signals on the fly to improve MS/MS coverage and identification efficiency in metabolomics. Anal Chim Acta 2021; 1149:338210. [PMID: 33551064 PMCID: PMC8189644 DOI: 10.1016/j.aca.2021.338210] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 12/16/2020] [Accepted: 01/05/2021] [Indexed: 12/22/2022]
Abstract
When using liquid chromatography/mass spectrometry (LC/MS) to perform untargeted metabolomics, it is common to detect thousands of features from a biological extract. Although it is impractical to collect non-chimeric MS/MS data for each in a single chromatographic run, this is generally unnecessary because most features do not correspond to unique metabolites of biological relevance. Here we show that relatively simple data-processing strategies that can be applied on the fly during acquisition of data with an Orbitrap ID-X, such as blank subtraction and well-established adduct or isotope calculations, decrease the number of features to target for MS/MS analysis by up to an order of magnitude for various types of biological matrices. We demonstrate that annotating these non-biological contaminants and redundancies in real time during data acquisition enables comprehensive MS/MS data to be acquired on each remaining feature at a single collision energy. To ensure that an appropriate collision energy is applied, we introduce a method using a series of hidden ion-trap scans in an Orbitrap ID-X to find an optimal value for each feature that can then be applied in a subsequent high-resolution Orbitrap scan. Data from 100 metabolite standards indicate that this real-time optimization of collision energies leads to more informative MS/MS patterns compared to using a single fixed collision energy alone. As a benchmark to evaluate the overall workflow, we manually annotated unique biological features by independently subjecting E. coli samples to a credentialing analysis. While credentialing led to a more rigorous reduction in feature number, on-the-fly annotation with blank subtraction on an Orbitrap ID-X did not inappropriately discard unique biological metabolites. Taken together, our results reveal that optimal fragmentation data can be obtained in a single LC/MS/MS run for >90% of the unique biological metabolites in a sample when features are annotated during acquisition and collision energies are selected by using parallel mass spectrometry detection.
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Affiliation(s)
- Kevin Cho
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO, USA; Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Michaela Schwaiger-Haber
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO, USA; Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Fuad J Naser
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO, USA; Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Ethan Stancliffe
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO, USA; Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Miriam Sindelar
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO, USA; Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Gary J Patti
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO, USA; Department of Medicine, Washington University in St. Louis, St. Louis, MO, USA.
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Tabone M, Bressa C, García-Merino JA, Moreno-Pérez D, Van EC, Castelli FA, Fenaille F, Larrosa M. The effect of acute moderate-intensity exercise on the serum and fecal metabolomes and the gut microbiota of cross-country endurance athletes. Sci Rep 2021; 11:3558. [PMID: 33574413 PMCID: PMC7878499 DOI: 10.1038/s41598-021-82947-1] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Accepted: 11/06/2020] [Indexed: 01/30/2023] Open
Abstract
Physical exercise can produce changes in the microbiota, conferring health benefits through mechanisms that are not fully understood. We sought to determine the changes driven by exercise on the gut microbiota and on the serum and fecal metabolome using 16S rRNA gene analysis and untargeted metabolomics. A total of 85 serum and 12 fecal metabolites and six bacterial taxa (Romboutsia, Escherichia coli TOP498, Ruminococcaceae UCG-005, Blautia, Ruminiclostridium 9 and Clostridium phoceensis) were modified following a controlled acute exercise session. Among the bacterial taxa, Ruminiclostridium 9 was the most influenced by fecal and serum metabolites, as revealed by linear multivariate regression analysis. Exercise significantly increased the fecal ammonia content. Functional analysis revealed that alanine, aspartate and glutamate metabolism and the arginine and aminoacyl-tRNA biosynthesis pathways were the most relevant modified pathways in serum, whereas the phenylalanine, tyrosine and tryptophan biosynthesis pathway was the most relevant pathway modified in feces. Correlation analysis between fecal and serum metabolites suggested an exchange of metabolites between both compartments. Thus, the performance of a single exercise bout in cross-country non-professional athletes produces significant changes in the microbiota and in the serum and fecal metabolome, which may have health implications.
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Affiliation(s)
- Mariangela Tabone
- MAS Microbiota Research Group, Faculty of Biomedical Sciences, Universidad Europea de Madrid, 28670, Villaviciosa de Odón, Madrid, Spain
| | - Carlo Bressa
- MAS Microbiota Research Group, Faculty of Biomedical Sciences, Universidad Europea de Madrid, 28670, Villaviciosa de Odón, Madrid, Spain
| | - Jose Angel García-Merino
- MAS Microbiota Research Group, Faculty of Biomedical Sciences, Universidad Europea de Madrid, 28670, Villaviciosa de Odón, Madrid, Spain
| | - Diego Moreno-Pérez
- Departamento de Educación, Métodos de Investigación y Evaluación, Universidad Pontificia de Comillas, ICAI-ICADE, 28015, Cantoblanco, Madrid, Spain
| | - Emeline Chu Van
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, 91191, Gif sur Yvette, France
| | - Florence A Castelli
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, 91191, Gif sur Yvette, France
| | - François Fenaille
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé (DMTS), MetaboHUB, 91191, Gif sur Yvette, France.
| | - Mar Larrosa
- MAS Microbiota Research Group, Faculty of Biomedical Sciences, Universidad Europea de Madrid, 28670, Villaviciosa de Odón, Madrid, Spain.
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Guo J, Shen S, Xing S, Huan T. DaDIA: Hybridizing Data-Dependent and Data-Independent Acquisition Modes for Generating High-Quality Metabolomic Data. Anal Chem 2021; 93:2669-2677. [DOI: 10.1021/acs.analchem.0c05022] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Affiliation(s)
- Jian Guo
- Department of Chemistry, Faculty of Science, University of British Columbia, Vancouver Campus, 2036 Main Mall, Vancouver V6T 1Z1, British Columbia, Canada
| | - Sam Shen
- Department of Chemistry, Faculty of Science, University of British Columbia, Vancouver Campus, 2036 Main Mall, Vancouver V6T 1Z1, British Columbia, Canada
| | - Shipei Xing
- Department of Chemistry, Faculty of Science, University of British Columbia, Vancouver Campus, 2036 Main Mall, Vancouver V6T 1Z1, British Columbia, Canada
| | - Tao Huan
- Department of Chemistry, Faculty of Science, University of British Columbia, Vancouver Campus, 2036 Main Mall, Vancouver V6T 1Z1, British Columbia, Canada
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Rampler E, Abiead YE, Schoeny H, Rusz M, Hildebrand F, Fitz V, Koellensperger G. Recurrent Topics in Mass Spectrometry-Based Metabolomics and Lipidomics-Standardization, Coverage, and Throughput. Anal Chem 2021; 93:519-545. [PMID: 33249827 PMCID: PMC7807424 DOI: 10.1021/acs.analchem.0c04698] [Citation(s) in RCA: 81] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Evelyn Rampler
- Department of Analytical
Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, Austria
- Vienna Metabolomics Center (VIME), University of Vienna, Althanstraße 14, 1090 Vienna, Austria
- University of Vienna, Althanstraße 14, 1090 Vienna, Austria
| | - Yasin El Abiead
- Department of Analytical
Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, Austria
| | - Harald Schoeny
- Department of Analytical
Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, Austria
| | - Mate Rusz
- Department of Analytical
Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, Austria
- Institute of Inorganic
Chemistry, University of Vienna, Währinger Straße 42, 1090 Vienna, Austria
| | - Felina Hildebrand
- Department of Analytical
Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, Austria
| | - Veronika Fitz
- Department of Analytical
Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, Austria
| | - Gunda Koellensperger
- Department of Analytical
Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, Austria
- Vienna Metabolomics Center (VIME), University of Vienna, Althanstraße 14, 1090 Vienna, Austria
- University of Vienna, Althanstraße 14, 1090 Vienna, Austria
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Pezzatti J, González-Ruiz V, Boccard J, Guillarme D, Rudaz S. Evaluation of Different Tandem MS Acquisition Modes to Support Metabolite Annotation in Human Plasma Using Ultra High-Performance Liquid Chromatography High-Resolution Mass Spectrometry for Untargeted Metabolomics. Metabolites 2020; 10:metabo10110464. [PMID: 33203160 PMCID: PMC7697060 DOI: 10.3390/metabo10110464] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Revised: 10/23/2020] [Accepted: 11/09/2020] [Indexed: 12/18/2022] Open
Abstract
Ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS) is a powerful and essential technique for metabolite annotation in untargeted metabolomic applications. The aim of this study was to evaluate the performance of diverse tandem MS (MS/MS) acquisition modes, i.e., all ion fragmentation (AIF) and data-dependent analysis (DDA), with and without ion mobility spectrometry (IM), to annotate metabolites in human plasma. The influence of the LC separation was also evaluated by comparing the performance of MS/MS acquisition in combination with three complementary chromatographic separation modes: reversed-phase chromatography (RPLC) and hydrophilic interaction chromatography (HILIC) with either an amide (aHILIC) or a zwitterionic (zHILIC) stationary phase. RPLC conditions were first chosen to investigate all the tandem MS modes, and we found out that DDA did not provide a significant additional amount of chemical coverage and that cleaner MS/MS spectra can be obtained by performing AIF acquisitions in combination with IM. Finally, we were able to annotate 338 unique metabolites and demonstrated that zHILIC was a powerful complementary approach to both the RPLC and aHILIC chromatographic modes. Moreover, a better analytical throughput was reached for an almost negligible loss of metabolite coverage when IM-AIF and AIF using ramped instead of fixed collision energies were used.
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Affiliation(s)
- Julian Pezzatti
- School of Pharmaceutical Sciences, University of Geneva, Rue Michel-Servet 1, 1211 Geneva 4, Switzerland; (J.P.); (V.G.-R.); (J.B.); (D.G.)
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, 1211 Geneva 4, Switzerland
| | - Víctor González-Ruiz
- School of Pharmaceutical Sciences, University of Geneva, Rue Michel-Servet 1, 1211 Geneva 4, Switzerland; (J.P.); (V.G.-R.); (J.B.); (D.G.)
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, 1211 Geneva 4, Switzerland
- Swiss Centre for Applied Human Toxicology (SCATH), 4055 Basel, Switzerland
| | - Julien Boccard
- School of Pharmaceutical Sciences, University of Geneva, Rue Michel-Servet 1, 1211 Geneva 4, Switzerland; (J.P.); (V.G.-R.); (J.B.); (D.G.)
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, 1211 Geneva 4, Switzerland
- Swiss Centre for Applied Human Toxicology (SCATH), 4055 Basel, Switzerland
| | - Davy Guillarme
- School of Pharmaceutical Sciences, University of Geneva, Rue Michel-Servet 1, 1211 Geneva 4, Switzerland; (J.P.); (V.G.-R.); (J.B.); (D.G.)
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, 1211 Geneva 4, Switzerland
| | - Serge Rudaz
- School of Pharmaceutical Sciences, University of Geneva, Rue Michel-Servet 1, 1211 Geneva 4, Switzerland; (J.P.); (V.G.-R.); (J.B.); (D.G.)
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, 1211 Geneva 4, Switzerland
- Swiss Centre for Applied Human Toxicology (SCATH), 4055 Basel, Switzerland
- Correspondence: ; Tel.: +41-2‐2379-6572
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