1
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Chappel JR, Kirkwood-Donelson KI, Dodds JN, Fleming J, Reif DM, Baker ES. Streamlining Phenotype Classification and Highlighting Feature Candidates: A Screening Method for Non-Targeted Ion Mobility Spectrometry-Mass Spectrometry (IMS-MS) Data. Anal Chem 2024; 96:15970-15979. [PMID: 39292613 DOI: 10.1021/acs.analchem.4c03256] [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: 09/20/2024]
Abstract
Nontargeted analysis (NTA) is increasingly utilized for its ability to identify key molecular features beyond known targets in complex samples. NTA is particularly advantageous in exploratory studies aimed at identifying phenotype-associated features or molecules able to classify various sample types. However, implementing NTA involves extensive data analyses and labor-intensive annotations. To address these limitations, we developed a rapid data screening capability compatible with NTA data collected on a liquid chromatography, ion mobility spectrometry, and mass spectrometry (LC-IMS-MS) platform that allows for sample classification while highlighting potential features of interest. Specifically, this method aggregates the thousands of IMS-MS spectra collected across the LC space for each sample and collapses the LC dimension, resulting in a single summed IMS-MS spectrum for screening. The summed IMS-MS spectra are then analyzed with a bootstrapped Lasso technique to identify key regions or coordinates for phenotype classification via support vector machines. Molecular annotations are then performed by examining the features present in the selected coordinates, highlighting potential molecular candidates. To demonstrate this summed IMS-MS screening approach, we applied it to clinical plasma lipidomic NTA data and exposomic NTA data from water sites with varying contaminant levels. Distinguishing coordinates were observed in both studies, enabling the evaluation of phenotypic molecular annotations and resulting in screening models capable of classifying samples with up to a 25% increase in accuracy compared to models using annotated data.
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Affiliation(s)
- Jessie R Chappel
- Bioinformatics Research Center, Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina 27606, United States
| | - Kaylie I Kirkwood-Donelson
- Immunity, Inflammation, and Disease Laboratory, National Institute of Environmental Health Sciences, Durham, North Carolina 27709, United States
| | - James N Dodds
- Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514, United States
| | - Jonathon Fleming
- Bioinformatics Research Center, Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina 27606, United States
| | - David M Reif
- Predictive Toxicology Branch, Division of Translational Toxicology, National Institute of Environmental Health Sciences, Durham, North Carolina 27709, United States
| | - Erin S Baker
- Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514, United States
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2
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Rosli MAF, Syed Jaafar SN, Azizan KA, Yaakop S, Aizat WM. Omics approaches to unravel insecticide resistance mechanism in Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae). PeerJ 2024; 12:e17843. [PMID: 39247549 PMCID: PMC11380842 DOI: 10.7717/peerj.17843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 07/10/2024] [Indexed: 09/10/2024] Open
Abstract
Bemisia tabaci (Gennadius) whitefly (BtWf) is an invasive pest that has already spread worldwide and caused major crop losses. Numerous strategies have been implemented to control their infestation, including the use of insecticides. However, prolonged insecticide exposures have evolved BtWf to resist these chemicals. Such resistance mechanism is known to be regulated at the molecular level and systems biology omics approaches could shed some light on understanding this regulation wholistically. In this review, we discuss the use of various omics techniques (genomics, transcriptomics, proteomics, and metabolomics) to unravel the mechanism of insecticide resistance in BtWf. We summarize key genes, enzymes, and metabolic regulation that are associated with the resistance mechanism and review their impact on BtWf resistance. Evidently, key enzymes involved in the detoxification system such as cytochrome P450 (CYP), glutathione S-transferases (GST), carboxylesterases (COE), UDP-glucuronosyltransferases (UGT), and ATP binding cassette transporters (ABC) family played key roles in the resistance. These genes/proteins can then serve as the foundation for other targeted techniques, such as gene silencing techniques using RNA interference and CRISPR. In the future, such techniques will be useful to knock down detoxifying genes and crucial neutralizing enzymes involved in the resistance mechanism, which could lead to solutions for coping against BtWf infestation.
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Affiliation(s)
| | - Sharifah Nabihah Syed Jaafar
- Department of Applied Physics, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
| | - Kamalrul Azlan Azizan
- Institute of Systems Biology (INBIOSIS), Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
| | - Salmah Yaakop
- Centre for Insect Systematics, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
| | - Wan Mohd Aizat
- Institute of Systems Biology (INBIOSIS), Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
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3
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Dang TC, Fields L, Li L. MotifQuest: An Automated Pipeline for Motif Database Creation to Improve Peptidomics Database Searching Programs. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024; 35:1902-1912. [PMID: 39058243 DOI: 10.1021/jasms.4c00192] [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: 07/28/2024]
Abstract
Endogenous peptides are an abundant and versatile class of biomolecules with vital roles pertinent to the functionality of the nervous, endocrine, and immune systems and others. Mass spectrometry stands as a premier technique for identifying endogenous peptides, yet the field still faces challenges due to the lack of optimized computational resources for reliable raw mass spectra analysis and interpretation. Current database searching programs can exhibit discrepancies due to the unique properties of endogenous peptides, which typically require specialized search considerations. Herein, we present a high throughput, novel scoring algorithm for the extraction and ranking of conserved amino acid sequence motifs within any endogenous peptide database. Motifs are conserved patterns across organisms, representing sequence moieties crucial for biological functions, including maintenance of homeostasis. MotifQuest, our novel motif database generation algorithm, is designed to work in partnership with EndoGenius, a program optimized for database searching of endogenous peptides and that is powered by a motif database to capitalize on biological context to produce identifications. MotifQuest aims to quickly develop motif databases without any prior knowledge, a laborious task not possible with traditional sequence alignment resources. In this work we illustrate the utility of MotifQuest to expand EndoGenius' identification utility to other endogenous peptides by showcasing its ability to identify antimicrobial peptides. Additionally, we discuss the potential utility of MotifQuest to parse out motifs from a FASTA database file that can be further validated as new peptide drug candidates.
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Affiliation(s)
- Tina C Dang
- School of Pharmacy, University of Wisconsin-Madison, 777 Highland Avenue, Madison, Wisconsin 53705, United States
| | - Lauren Fields
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Lingjun Li
- School of Pharmacy, University of Wisconsin-Madison, 777 Highland Avenue, Madison, Wisconsin 53705, United States
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States
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4
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Beger RD, Goodacre R, Jones CM, Lippa KA, Mayboroda OA, O'Neill D, Najdekr L, Ntai I, Wilson ID, Dunn WB. Analysis types and quantification methods applied in UHPLC-MS metabolomics research: a tutorial. Metabolomics 2024; 20:95. [PMID: 39110307 PMCID: PMC11306277 DOI: 10.1007/s11306-024-02155-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 07/16/2024] [Indexed: 08/10/2024]
Abstract
BACKGROUND Different types of analytical methods, with different characteristics, are applied in metabolomics and lipidomics research and include untargeted, targeted and semi-targeted methods. Ultra High Performance Liquid Chromatography-Mass Spectrometry is one of the most frequently applied measurement instruments in metabolomics because of its ability to detect a large number of water-soluble and lipid metabolites over a wide range of concentrations in short analysis times. Methods applied for the detection and quantification of metabolites differ and can either report a (normalised) peak area or an absolute concentration. AIM OF REVIEW In this tutorial we aim to (1) define similarities and differences between different analytical approaches applied in metabolomics and (2) define how amounts or absolute concentrations of endogenous metabolites can be determined together with the advantages and limitations of each approach in relation to the accuracy and precision when concentrations are reported. KEY SCIENTIFIC CONCEPTS OF REVIEW The pre-analysis knowledge of metabolites to be targeted, the requirement for (normalised) peak responses or absolute concentrations to be reported and the number of metabolites to be reported define whether an untargeted, targeted or semi-targeted method is applied. Fully untargeted methods can only provide (normalised) peak responses and fold changes which can be reported even when the structural identity of the metabolite is not known. Targeted methods, where the analytes are known prior to the analysis, can also report fold changes. Semi-targeted methods apply a mix of characteristics of both untargeted and targeted assays. For the reporting of absolute concentrations of metabolites, the analytes are not only predefined but optimized analytical methods should be developed and validated for each analyte so that the accuracy and precision of concentration data collected for biological samples can be reported as fit for purpose and be reviewed by the scientific community.
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Affiliation(s)
- Richard D Beger
- National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Royston Goodacre
- Department of Biochemistry, Cell and Systems Biology, Centre for Metabolomics Research, Institute of Systems, Molecular, and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK
| | - Christina M Jones
- Office of Advanced Manufacturing, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA
| | - Katrice A Lippa
- Office of Weights and Measures, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA
| | - Oleg A Mayboroda
- Center for Proteomics and Metabolomics, Leiden University Medical Centre, Leiden, The Netherlands
| | - Donna O'Neill
- School of Biosciences and Phenome Centre Birmingham, University of Birmingham, Birmingham, UK
| | - Lukas Najdekr
- Faculty of Medicine and Dentistry, Institute of Molecular and Translational Medicine, Palacký University Olomouc, 779 00, Olomouc, Czech Republic
| | - Ioanna Ntai
- BioMarin Pharmaceutical Inc., San Rafael, CA, USA
| | - Ian D Wilson
- Department of Biochemistry, Cell and Systems Biology, Centre for Metabolomics Research, Institute of Systems, Molecular, and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK
- Computational and Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Warwick B Dunn
- Department of Biochemistry, Cell and Systems Biology, Centre for Metabolomics Research, Institute of Systems, Molecular, and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK.
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Ovbude ST, Sharmeen S, Kyei I, Olupathage H, Jones J, Bell RJ, Powers R, Hage DS. Applications of chromatographic methods in metabolomics: A review. J Chromatogr B Analyt Technol Biomed Life Sci 2024; 1239:124124. [PMID: 38640794 DOI: 10.1016/j.jchromb.2024.124124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 03/11/2024] [Accepted: 04/10/2024] [Indexed: 04/21/2024]
Abstract
Chromatography is a robust and reliable separation method that can use various stationary phases to separate complex mixtures commonly seen in metabolomics. This review examines the types of chromatography and stationary phases that have been used in targeted or untargeted metabolomics with methods such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. General considerations for sample pretreatment and separations in metabolomics are considered, along with the various supports and separation formats for chromatography that have been used in such work. The types of liquid chromatography (LC) that have been most extensively used in metabolomics will be examined, such as reversed-phase liquid chromatography and hydrophilic liquid interaction chromatography. In addition, other forms of LC that have been used in more limited applications for metabolomics (e.g., ion-exchange, size-exclusion, and affinity methods) will be discussed to illustrate how these techniques may be utilized for new and future research in this field. Multidimensional LC methods are also discussed, as well as the use of gas chromatography and supercritical fluid chromatography in metabolomics. In addition, the roles of chromatography in NMR- vs. MS-based metabolomics are considered. Applications are given within the field of metabolomics for each type of chromatography, along with potential advantages or limitations of these separation methods.
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Affiliation(s)
- Susan T Ovbude
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA
| | - Sadia Sharmeen
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA
| | - Isaac Kyei
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA
| | - Harshana Olupathage
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA
| | - Jacob Jones
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA
| | - Richard J Bell
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA
| | - Robert Powers
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA; Nebraska Center for Integrated Biomolecular Communication, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA
| | - David S Hage
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA.
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6
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Gowda SGB, Hou F, Gowda D, Chiba H, Kawakami K, Fukiya S, Yokota A, Hui SP. Synthesis and quantification of short-chain fatty acid esters of hydroxy fatty acids in rat intestinal contents and fecal samples by LC-MS/MS. Anal Chim Acta 2024; 1288:342145. [PMID: 38220280 DOI: 10.1016/j.aca.2023.342145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 12/12/2023] [Accepted: 12/14/2023] [Indexed: 01/16/2024]
Abstract
Short-chain fatty acid esters of hydroxy fatty acids (SFAHFAs) are a new class of endogenous lipids belonging to the fatty acid esters of the hydroxy fatty acid family. We previously uncovered their chemical structure and discussed their potential biological significance. We anticipate an increased need for SFAHFA measurements as markers of metabolic and inflammatory health. In this study, we synthesized sixty isomeric SFAHFAs by combining 12 hydroxy fatty acids (C16-C24) and five short-chain fatty acids (C2-C6) including a labelled internal standard. SFAHFA enrichment was achieved by solid-phase extraction and established a sensitive method for their quantitation by targeted LC-MS/MS. The method was applied to profile SFAHFAs in intestinal contents and fecal samples collected from rats fed a high-fat diet (HFD). The results demonstrated a significant decrease in SFAHFAs in the intestinal contents of the HFD group compared with the control group. The fecal time course (0-8 weeks) profile of SFAHFAs showed significant downregulation of acetic and propanoic acid esters in just 2 weeks after HFD administration. This study offers the first synthesis and quantitation method for SFAHFAs, demonstrating their potential use in elucidating SFAHFA sources, their role in various diseases, and potential biochemical signalling pathways.
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Affiliation(s)
- Siddabasave Gowda B Gowda
- Faculty of Health Sciences, Hokkaido University, Kita-12, Nishi-5, Kita-ku, Sapporo, 060-0812, Japan; Graduate School of Global Food Resources, Hokkaido University, Kita-9, Nishi-9, Kita-ku, Sapporo, 060-0809, Japan
| | - Fengjue Hou
- Graduate School of Health Sciences, Hokkaido University, Kita-12, Nishi-5, Kita-ku, Sapporo, 060-0812, Japan
| | - Divyavani Gowda
- Faculty of Health Sciences, Hokkaido University, Kita-12, Nishi-5, Kita-ku, Sapporo, 060-0812, Japan
| | - Hitoshi Chiba
- Department of Nutrition, Sapporo University of Health Sciences, Nakanuma, Nishi-4-3-1-15, Higashi-ku, Sapporo, 007-0894, Japan
| | - Kentaro Kawakami
- Research Faculty of Agriculture, Hokkaido University, Kita-9 Nishi-9, Kita-ku, Sapporo, 060-8589, Japan
| | - Satoru Fukiya
- Research Faculty of Agriculture, Hokkaido University, Kita-9 Nishi-9, Kita-ku, Sapporo, 060-8589, Japan
| | - Atsushi Yokota
- Research Faculty of Agriculture, Hokkaido University, Kita-9 Nishi-9, Kita-ku, Sapporo, 060-8589, Japan
| | - Shu-Ping Hui
- Faculty of Health Sciences, Hokkaido University, Kita-12, Nishi-5, Kita-ku, Sapporo, 060-0812, Japan.
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7
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Li W, Hao S, Li H, An Q, Yang L, Guo B, Xue Z, Liu Y, Guo L, Zheng Y, Zhang D. Exploring Antioxidant and α-Glucosidase Inhibitory Activities in Mulberry Leaves ( Morus alba L.) across Growth Stages: A Comprehensive Metabolomic Analysis with Chemometrics. Molecules 2023; 29:171. [PMID: 38202754 PMCID: PMC10780005 DOI: 10.3390/molecules29010171] [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: 11/27/2023] [Revised: 12/19/2023] [Accepted: 12/25/2023] [Indexed: 01/12/2024] Open
Abstract
Metabolic product accumulation exhibited variations among mulberry (Morus alba L.) leaves (MLs) at distinct growth stages, and this assessment was conducted using a combination of analytical techniques including high-performance liquid chromatography (HPLC), gas chromatography-mass spectrometry (GC-MS), and liquid chromatography-mass spectrometry (LC-MS). Multivariate analysis was applied to the data, and the findings were correlated with antioxidant activity and α-glucosidase inhibitory effects in vitro. Statistical analyses divided the 27 batches of MLs at different growth stages into three distinct groups. In vitro assays for antioxidant activity and α-glucosidase inhibition revealed that IC50 values were highest at the Y23 stage, which corresponds to the 'Frost Descends' solar term. In summary, the results of this study indicate that MLs at different growth stages throughout the year can be categorized into three primary growth stages using traditional Chinese solar terms as reference points, based on the observed variations in metabolite content.
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Affiliation(s)
- Wenjie Li
- Traditional Chinese Medicine Processing Technology Innovation Centre of Hebei Province, College of Pharmacy, Hebei University of Chinese Medicine, Shijiazhuang 050200, China; (W.L.); (S.H.); (H.L.); (L.Y.); (B.G.); (Z.X.); (L.G.)
| | - Shenghui Hao
- Traditional Chinese Medicine Processing Technology Innovation Centre of Hebei Province, College of Pharmacy, Hebei University of Chinese Medicine, Shijiazhuang 050200, China; (W.L.); (S.H.); (H.L.); (L.Y.); (B.G.); (Z.X.); (L.G.)
| | - Hengyang Li
- Traditional Chinese Medicine Processing Technology Innovation Centre of Hebei Province, College of Pharmacy, Hebei University of Chinese Medicine, Shijiazhuang 050200, China; (W.L.); (S.H.); (H.L.); (L.Y.); (B.G.); (Z.X.); (L.G.)
| | - Qi An
- Department of Chinese Materia Medica, Hebei Institute for Drug and Medical Device Control, Shijiazhuang 050200, China; (Q.A.); (Y.L.)
| | - Lina Yang
- Traditional Chinese Medicine Processing Technology Innovation Centre of Hebei Province, College of Pharmacy, Hebei University of Chinese Medicine, Shijiazhuang 050200, China; (W.L.); (S.H.); (H.L.); (L.Y.); (B.G.); (Z.X.); (L.G.)
| | - Bing Guo
- Traditional Chinese Medicine Processing Technology Innovation Centre of Hebei Province, College of Pharmacy, Hebei University of Chinese Medicine, Shijiazhuang 050200, China; (W.L.); (S.H.); (H.L.); (L.Y.); (B.G.); (Z.X.); (L.G.)
| | - Zijing Xue
- Traditional Chinese Medicine Processing Technology Innovation Centre of Hebei Province, College of Pharmacy, Hebei University of Chinese Medicine, Shijiazhuang 050200, China; (W.L.); (S.H.); (H.L.); (L.Y.); (B.G.); (Z.X.); (L.G.)
| | - Yongli Liu
- Department of Chinese Materia Medica, Hebei Institute for Drug and Medical Device Control, Shijiazhuang 050200, China; (Q.A.); (Y.L.)
| | - Long Guo
- Traditional Chinese Medicine Processing Technology Innovation Centre of Hebei Province, College of Pharmacy, Hebei University of Chinese Medicine, Shijiazhuang 050200, China; (W.L.); (S.H.); (H.L.); (L.Y.); (B.G.); (Z.X.); (L.G.)
| | - Yuguang Zheng
- Traditional Chinese Medicine Processing Technology Innovation Centre of Hebei Province, College of Pharmacy, Hebei University of Chinese Medicine, Shijiazhuang 050200, China; (W.L.); (S.H.); (H.L.); (L.Y.); (B.G.); (Z.X.); (L.G.)
- Department of Pharmaceutical Engineering, Hebei Chemical and Pharmaceutical College, Shijiazhuang 050026, China
| | - Dan Zhang
- Traditional Chinese Medicine Processing Technology Innovation Centre of Hebei Province, College of Pharmacy, Hebei University of Chinese Medicine, Shijiazhuang 050200, China; (W.L.); (S.H.); (H.L.); (L.Y.); (B.G.); (Z.X.); (L.G.)
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8
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Grochowski ET, Pietrowska K, Godlewski A, Gosk W, Buczynska A, Wojnar M, Konopinska J, Kretowski A, Ciborowski M, Dmuchowska DA. Simultaneous Comparison of Aqueous Humor and Serum Metabolic Profiles of Diabetic and Nondiabetic Patients Undergoing Cataract Surgery-A Targeted and Quantitative Metabolomics Study. Int J Mol Sci 2023; 24:12671. [PMID: 37628855 PMCID: PMC10454064 DOI: 10.3390/ijms241612671] [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: 07/03/2023] [Revised: 08/08/2023] [Accepted: 08/09/2023] [Indexed: 08/27/2023] Open
Abstract
The aim of this study was to compare the aqueous humor (AH) and serum concentrations of metabolites in diabetic (n = 36) and nondiabetic (n = 36) senior adults undergoing cataract surgery. Blood samples were collected before surgery and AH during surgery. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS)-based targeted metabolomic and lipidomic analyses of samples were performed using the AbsoluteIDQ® p180 kit. Out of 188 metabolites targeted by the kit, 41 and 133 were detected in >80% of AH and serum samples, respectively. Statistical analysis performed to indicate metabolites differentiating diabetic and nondiabetic patients showed 8 and 20 significant metabolites in AH and serum, respectively. Pathway analysis performed for significant metabolites revealed that galactose metabolism is mostly affected in the AH, while arginine biosynthesis is mostly affected in the serum. Among metabolites that differentiate diabetic and nondiabetic patients, arginine was the only metabolite common to both serum and AH samples, as well as the only one with a decreased concentration in both body fluids of diabetic patients. Concentrations of the rest were elevated in AH and lowered in serum. This may suggest different mechanisms of diabetes-related dysregulation of the local metabolism in the eye in comparison to systemic changes observed in the blood.
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Affiliation(s)
- Emil Tomasz Grochowski
- Department of Ophthalmology, Medical University of Bialystok, M. Sklodowskiej Curie 24a, 15-276 Bialystok, Poland; (E.T.G.); (M.W.); (J.K.)
| | - Karolina Pietrowska
- Metabolomics Laboratory, Clinical Research Center, Medical University of Bialystok, M. Sklodowskiej Curie 24a, 15-276 Bialystok, Poland; (K.P.); (A.G.); (W.G.); (A.B.); (A.K.)
| | - Adrian Godlewski
- Metabolomics Laboratory, Clinical Research Center, Medical University of Bialystok, M. Sklodowskiej Curie 24a, 15-276 Bialystok, Poland; (K.P.); (A.G.); (W.G.); (A.B.); (A.K.)
| | - Wioleta Gosk
- Metabolomics Laboratory, Clinical Research Center, Medical University of Bialystok, M. Sklodowskiej Curie 24a, 15-276 Bialystok, Poland; (K.P.); (A.G.); (W.G.); (A.B.); (A.K.)
| | - Angelika Buczynska
- Metabolomics Laboratory, Clinical Research Center, Medical University of Bialystok, M. Sklodowskiej Curie 24a, 15-276 Bialystok, Poland; (K.P.); (A.G.); (W.G.); (A.B.); (A.K.)
| | - Malgorzata Wojnar
- Department of Ophthalmology, Medical University of Bialystok, M. Sklodowskiej Curie 24a, 15-276 Bialystok, Poland; (E.T.G.); (M.W.); (J.K.)
| | - Joanna Konopinska
- Department of Ophthalmology, Medical University of Bialystok, M. Sklodowskiej Curie 24a, 15-276 Bialystok, Poland; (E.T.G.); (M.W.); (J.K.)
| | - Adam Kretowski
- Metabolomics Laboratory, Clinical Research Center, Medical University of Bialystok, M. Sklodowskiej Curie 24a, 15-276 Bialystok, Poland; (K.P.); (A.G.); (W.G.); (A.B.); (A.K.)
- Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, M. Sklodowskiej Curie 24a, 15-276 Bialystok, Poland
| | - Michal Ciborowski
- Metabolomics Laboratory, Clinical Research Center, Medical University of Bialystok, M. Sklodowskiej Curie 24a, 15-276 Bialystok, Poland; (K.P.); (A.G.); (W.G.); (A.B.); (A.K.)
| | - Diana Anna Dmuchowska
- Department of Ophthalmology, Medical University of Bialystok, M. Sklodowskiej Curie 24a, 15-276 Bialystok, Poland; (E.T.G.); (M.W.); (J.K.)
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9
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Assress H, Ferruzzi MG, Lan RS. Optimization of Mass Spectrometric Parameters in Data Dependent Acquisition for Untargeted Metabolomics on the Basis of Putative Assignments. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:1621-1631. [PMID: 37419493 PMCID: PMC10402710 DOI: 10.1021/jasms.3c00084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 06/19/2023] [Accepted: 06/21/2023] [Indexed: 07/09/2023]
Abstract
Optimization of mass spectrometric parameters for a data dependent acquisition (DDA) experiment is essential to increase the MS/MS coverage and hence increase metabolite identifications in untargeted metabolomics. We explored the influence of mass spectrometric parameters including mass resolution, radio frequency (RF) level, signal intensity threshold, number of MS/MS events, cycle time, collision energy, maximum ion injection time (MIT), dynamic exclusion, and automatic gain control (AGC) target value on metabolite annotations on an Exploris 480-Orbitrap mass spectrometer. Optimal annotation results were obtained by performing ten data dependent MS/MS scans with a mass isolation window of 2.0 m/z and a minimum signal intensity threshold of 1 × 104 at a mass resolution of 180,000 for MS and 30,000 for MS/MS, while maintaining the RF level at 70%. Furthermore, combining an AGC target value of 5 × 106 and MIT of 100 ms for MS and an AGC target value of 1 × 105 and an MIT of 50 ms for MS/MS scans provided an improved number of annotated metabolites. A 10 s exclusion duration and a two stepped collision energy were optimal for higher spectral quality. These findings confirm that MS parameters do influence metabolomics results, and propose strategies for increasing metabolite coverage in untargeted metabolomics. A limitation of this work is that our parameters were only optimized for one RPLC method on single matrix and may be different for other protocols. Additionally, no metabolites were identified at level 1 confidence. The results presented here are based on metabolite annotations and need to be validated with authentic standards.
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Affiliation(s)
- Hailemariam
Abrha Assress
- Arkansas
Children’s Nutrition Center, Little Rock, Arkansas 72202, United States
- Department
of Pediatrics, University of Arkansas for
Medical Sciences, Little
Rock, Arkansas 72205, United States
| | - Mario G. Ferruzzi
- Arkansas
Children’s Nutrition Center, Little Rock, Arkansas 72202, United States
- Department
of Pediatrics, University of Arkansas for
Medical Sciences, Little
Rock, Arkansas 72205, United States
| | - Renny S. Lan
- Arkansas
Children’s Nutrition Center, Little Rock, Arkansas 72202, United States
- Department
of Pediatrics, University of Arkansas for
Medical Sciences, Little
Rock, Arkansas 72205, United States
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10
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Fecke A, Saw NMMT, Kale D, Kasarla SS, Sickmann A, Phapale P. Quantitative Analytical and Computational Workflow for Large-Scale Targeted Plasma Metabolomics. Metabolites 2023; 13:844. [PMID: 37512551 PMCID: PMC10383057 DOI: 10.3390/metabo13070844] [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: 07/04/2023] [Accepted: 07/11/2023] [Indexed: 07/30/2023] Open
Abstract
Quantifying metabolites from various biological samples is necessary for the clinical and biomedical translation of metabolomics research. One of the ongoing challenges in biomedical metabolomics studies is the large-scale quantification of targeted metabolites, mainly due to the complexity of biological sample matrices. Furthermore, in LC-MS analysis, the response of compounds is influenced by their physicochemical properties, chromatographic conditions, eluent composition, sample preparation, type of MS ionization source, and analyzer used. To facilitate large-scale metabolite quantification, we evaluated the relative response factor (RRF) approach combined with an integrated analytical and computational workflow. This approach considers a compound's individual response in LC-MS analysis relative to that of a non-endogenous reference compound to correct matrix effects. We created a quantitative LC-MS library using the Skyline/Panorama web platform for data processing and public sharing of data. In this study, we developed and validated a metabolomics method for over 280 standard metabolites and quantified over 90 metabolites. The RRF quantification was validated and compared with conventional external calibration approaches as well as literature reports. The Skyline software environment was adapted for processing such metabolomics data, and the results are shared as a "quantitative chromatogram library" with the Panorama web application. This new workflow was found to be suitable for large-scale quantification of metabolites in human plasma samples. In conclusion, we report a novel quantitative chromatogram library with a targeted data analysis workflow for biomedical metabolomic applications.
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Affiliation(s)
- Antonia Fecke
- Leibniz-Institut für Analytische Wissenschaften-ISAS-e.V., Otto-Hahn-Str. 6b, 44227 Dortmund, Germany
- Department Hamm 2, Hochschule Hamm-Lippstadt, Marker-Allee 76-78, 59063 Hamm, Germany
| | - Nay Min Min Thaw Saw
- Leibniz-Institut für Analytische Wissenschaften-ISAS-e.V., Otto-Hahn-Str. 6b, 44227 Dortmund, Germany
| | - Dipali Kale
- Leibniz-Institut für Analytische Wissenschaften-ISAS-e.V., Otto-Hahn-Str. 6b, 44227 Dortmund, Germany
| | - Siva Swapna Kasarla
- Leibniz-Institut für Analytische Wissenschaften-ISAS-e.V., Otto-Hahn-Str. 6b, 44227 Dortmund, Germany
| | - Albert Sickmann
- Leibniz-Institut für Analytische Wissenschaften-ISAS-e.V., Otto-Hahn-Str. 6b, 44227 Dortmund, Germany
| | - Prasad Phapale
- Leibniz-Institut für Analytische Wissenschaften-ISAS-e.V., Otto-Hahn-Str. 6b, 44227 Dortmund, Germany
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11
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Yang Y, Zhou Y, Lyu Y, Shao B, Xu Y. High-throughput multitarget quantitative assay to profile the whole grain-specific phytochemicals alkylresorcinols, benzoxazinoids and avenanthramides in whole grain and grain-based foods. Food Chem 2023; 426:136663. [PMID: 37352717 DOI: 10.1016/j.foodchem.2023.136663] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 05/31/2023] [Accepted: 06/16/2023] [Indexed: 06/25/2023]
Abstract
Currently, there is a growing interest in using whole grain (WG)-specific phytochemicals to perform WG research, including research on dietary assessment, health mechanisms, and quality control. However, the current approaches used for WG-specific phytochemical analysis cannot simultaneously achieve coverage, specificity, and sensitivity. In the present study, a series of WG-specific phytochemicals (alkylresorcinols (ARs), benzoxazinoids (BXs) and avenanthramides (AVAs)) were identified, and their mass spectrometry (MS) fragmentation mechanism was studied by TOF MS. Based on diagnostic fragmentation ions and retention time prediction models, a LC-MS/MS method was developed. Through this method, 56 ARs, 13 BXs, and 19 AVAs in WGs and grain-based foods were quantified for the first time. This method was validated and yielded excellent specificity, high sensitivity and negligible matrix effects. Finally, we established WG-specific phytochemical fingerprints in a variety of WG and grain-based foods. This method can be used for WG quality control and WG precision nutrition research.
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Affiliation(s)
- Yunjia Yang
- Department of Nutrition and Food Hygiene, School of Public Health, Peking University, Beijing 100083, China; Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Peking University, NO. 38 Xueyuan Road, Beijing 100083, China; Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing Center for Disease Prevention and Control, Beijing 100013, China
| | - Yalin Zhou
- Department of Nutrition and Food Hygiene, School of Public Health, Peking University, Beijing 100083, China; Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Peking University, NO. 38 Xueyuan Road, Beijing 100083, China
| | - Ying Lyu
- Department of Nutrition and Food Hygiene, School of Public Health, Peking University, Beijing 100083, China; Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Peking University, NO. 38 Xueyuan Road, Beijing 100083, China
| | - Bing Shao
- Beijing Key Laboratory of Diagnostic and Traceability Technologies for Food Poisoning, Beijing Center for Disease Prevention and Control, Beijing 100013, China
| | - Yajun Xu
- Department of Nutrition and Food Hygiene, School of Public Health, Peking University, Beijing 100083, China; Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Peking University, NO. 38 Xueyuan Road, Beijing 100083, China; PKUHSC-China Feihe Joint Research Institute of Nutrition and Healthy Lifespan Development, NO. 38 Xueyuan Road, Beijing 100083, China.
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12
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Amer B, Deshpande RR, Bird SS. Simultaneous Quantitation and Discovery (SQUAD) Analysis: Combining the Best of Targeted and Untargeted Mass Spectrometry-Based Metabolomics. Metabolites 2023; 13:metabo13050648. [PMID: 37233689 DOI: 10.3390/metabo13050648] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 04/27/2023] [Accepted: 05/05/2023] [Indexed: 05/27/2023] Open
Abstract
Untargeted and targeted approaches are the traditional metabolomics workflows acquired for a wider understanding of the metabolome under focus. Both approaches have their strengths and weaknesses. The untargeted, for example, is maximizing the detection and accurate identification of thousands of metabolites, while the targeted is maximizing the linear dynamic range and quantification sensitivity. These workflows, however, are acquired separately, so researchers compromise either a low-accuracy overview of total molecular changes (i.e., untargeted analysis) or a detailed yet blinkered snapshot of a selected group of metabolites (i.e., targeted analysis) by selecting one of the workflows over the other. In this review, we present a novel single injection simultaneous quantitation and discovery (SQUAD) metabolomics that combines targeted and untargeted workflows. It is used to identify and accurately quantify a targeted set of metabolites. It also allows data retro-mining to look for global metabolic changes that were not part of the original focus. This offers a way to strike the balance between targeted and untargeted approaches in one single experiment and address the two approaches' limitations. This simultaneous acquisition of hypothesis-led and discovery-led datasets allows scientists to gain more knowledge about biological systems in a single experiment.
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Affiliation(s)
- Bashar Amer
- Thermo Fisher Scientific, San Jose, 95134 CA, USA
| | | | - Susan S Bird
- Thermo Fisher Scientific, San Jose, 95134 CA, USA
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13
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Lee JY, Han Y, Styczynski MP. Towards inferring absolute concentrations from relative abundance in time-course GC-MS metabolomics data. Mol Omics 2023; 19:126-136. [PMID: 36374123 PMCID: PMC9974747 DOI: 10.1039/d2mo00168c] [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: 11/06/2022]
Abstract
Metabolomics, the large-scale study of metabolites, has significant appeal as a source of information for metabolic modeling and other scientific applications. One common approach for measuring metabolomics data is gas chromatography-mass spectrometry (GC-MS). However, GC-MS metabolomics data are typically reported as relative abundances, precluding their use with approaches and tools where absolute concentrations are necessary. While chemical standards can be used to help provide quantification, their use is time-consuming, expensive, or even impossible due to their limited availability. The ability to infer absolute concentrations from GC-MS metabolomics data without chemical standards would have significant value. We hypothesized that when analyzing time-course metabolomics datasets, the mass balances of metabolism and other biological information could provide sufficient information towards inference of absolute concentrations. To demonstrate this, we developed and characterized MetaboPAC, a computational framework that uses two approaches-one based on kinetic equations and another using biological heuristics-to predict the most likely response factors that allow translation between relative abundances and absolute concentrations. When used to analyze noiseless synthetic data generated from multiple types of kinetic rate laws, MetaboPAC performs significantly better than negative control approaches when 20% of kinetic terms are known a priori. Under conditions of lower sampling frequency and high noise, MetaboPAC is still able to provide significant inference of concentrations in 3 of 4 models studied. This provides a starting point for leveraging biological knowledge to extract concentration information from time-course intracellular GC-MS metabolomics datasets, particularly for systems that are well-studied and have partially known kinetic structures.
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Affiliation(s)
- Justin Y Lee
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
| | - Yue Han
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
| | - Mark P Styczynski
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
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14
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Midzi H, Vengesai A, Muleya V, Kasambala M, Mduluza-Jokonya TL, Chipako I, Siamayuwa CE, Mutapi F, Naicker T, Mduluza T. Metabolomics for biomarker discovery in schistosomiasis: A systematic scoping review. FRONTIERS IN TROPICAL DISEASES 2023. [DOI: 10.3389/fitd.2023.1108317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
BackgroundMetabolomic based approaches are essential tools in the discovery of unique biomarkers for infectious diseases via high-throughput global assessment of metabolites and metabolite pathway dysregulation. This in-turn allows the development of diagnostic tools and provision of therapeutics. In this review, we aimed to give an overview of metabolite biomarkers and metabolic pathway alterations during Schistosoma haematobium and Schistosoma mansoni infections.MethodsWe conducted the review by systematically searching electronic databases and grey literature to identify relevant metabolomics studies on schistosomiasis. Arksey and O’Malley methodology for conducting systematic scoping reviews was applied. A narrative summary of results was conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for scoping review guidelines.ResultsTwelve articles included in the review identified 127 metabolites, whose concentrations were considerably altered during S. mansoni and S. haematobium infections. The metabolites were assigned to metabolic pathways involved in energy (34.6%), gut microbial (11.0%), amino acid (25.2%), nucleic acids (6.3%), immune proteins (8.7%) hormones (2.4%) and structural proteins/lipids (11.8%). Energy related metabolic pathways were the most affected during schistosome infections with metabolites such as succinate, citrate, aconitate and fumarate of the tricarbocylic acid cycle being significantly altered in organ, serum and plasma samples. Amino acid metabolism was also impacted during schistosome infections as phenylacetylglycine, alanine, taurine, 2-oxoisocaproate and 2-oxoisovalerate emerged as potent biomarkers. Elevated structural proteins such as actin, collagen and keratin concentrations were identified as biomarkers of liver fibrosis, a common pathological feature in chronic schistosomiasis infections. Hippurate was a major metabolite biomarker in the gut microbial related pathway.ConclusionsThe analysis of the literature revealed that energy related metabolic pathways are considerably altered during S. mansoni and S. haematobium infections. Therefore, their metabolites may provide biomarkers for diagnosis and prognosis in addition to providing therapeutics for parasitic infections. This scoping review has identified a need to replicate more schistosomiasis metabolomic studies in humans to complement animal-model based studies.
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15
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Krausová M, Braun D, Buerki-Thurnherr T, Gundacker C, Schernhammer E, Wisgrill L, Warth B. Understanding the Chemical Exposome During Fetal Development and Early Childhood: A Review. Annu Rev Pharmacol Toxicol 2023; 63:517-540. [PMID: 36202091 DOI: 10.1146/annurev-pharmtox-051922-113350] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Early human life is considered a critical window of susceptibility to external exposures. Infants are exposed to a multitude of environmental factors, collectively referred to as the exposome. The chemical exposome can be summarized as the sum of all xenobiotics that humans are exposed to throughout a lifetime. We review different exposure classes and routes that impact fetal and infant metabolism and the potential toxicological role of mixture effects. We also discuss the progress in human biomonitoring and present possiblemodels for studying maternal-fetal transfer. Data gaps on prenatal and infant exposure to xenobiotic mixtures are identified and include natural biotoxins, in addition to commonly reported synthetic toxicants, to obtain a more holistic assessment of the chemical exposome. We highlight the lack of large-scale studies covering a broad range of xenobiotics. Several recommendations to advance our understanding of the early-life chemical exposome and the subsequent impact on health outcomes are proposed.
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Affiliation(s)
- Magdaléna Krausová
- Department of Food Chemistry and Toxicology, Faculty of Chemistry, University of Vienna, Vienna, Austria; , ,
| | - Dominik Braun
- Department of Food Chemistry and Toxicology, Faculty of Chemistry, University of Vienna, Vienna, Austria; , ,
| | - Tina Buerki-Thurnherr
- Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Particles Biology Interactions, St. Gallen, Switzerland;
| | - Claudia Gundacker
- Center for Pathobiochemistry and Genetics, Institute of Medical Genetics, Medical University of Vienna, Vienna, Austria; .,Exposome Austria, Research Infrastructure and National EIRENE Hub, Austria
| | - Eva Schernhammer
- Exposome Austria, Research Infrastructure and National EIRENE Hub, Austria.,Center for Public Health, Department of Epidemiology, Medical University of Vienna, Vienna, Austria; .,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
| | - Lukas Wisgrill
- Exposome Austria, Research Infrastructure and National EIRENE Hub, Austria.,Division of Neonatology, Pediatric Intensive Care and Neuropediatrics, Department of Pediatrics and Adolescent Medicine, Comprehensive Center for Pediatrics, Medical University of Vienna, Vienna, Austria;
| | - Benedikt Warth
- Department of Food Chemistry and Toxicology, Faculty of Chemistry, University of Vienna, Vienna, Austria; , , .,Exposome Austria, Research Infrastructure and National EIRENE Hub, Austria
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16
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Letourneau DR, August DD, Volmer DA. New algorithms demonstrate untargeted detection of chemically meaningful changing units and formula assignment for HRMS data of polymeric mixtures in the open-source constellation web application. J Cheminform 2023; 15:7. [PMID: 36653829 PMCID: PMC9850690 DOI: 10.1186/s13321-023-00680-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Accepted: 01/06/2023] [Indexed: 01/19/2023] Open
Abstract
The field of high-resolution mass spectrometry (HRMS) and ancillary hyphenated techniques comprise a rapidly expanding and evolving area. As popularity of HRMS instruments grows, there is a concurrent need for tools and solutions to simplify and automate the processing of the large and complex datasets that result from these analyses. Constellation is one such of these tools, developed by our group over the last two years to perform unsupervised trend detection for repeating, polymeric units in HRMS data of complex mixtures such as natural organic matter, oil, or lignin. In this work, we develop two new unsupervised algorithms for finding chemically-meaningful changing units in HRMS data, and incorporate a molecular-formula-finding algorithm from the open-source CoreMS software package, both demonstrated here in the Constellation software environment. These algorithms are evaluated on a collection of open-source HRMS datasets containing polymeric analytes (PEG 400 and NIST standard reference material 1950, both metabolites in human plasma, as well as a swab extract containing polymers), and are able to successfully identify all known changing units in the data, including assigning the correct formulas. Through these new developments, we are excited to add to a growing body of open-source software specialized in extracting useful information from complex datasets without the high costs, technical knowledge, and processor-demand typically associated with such tools.
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Affiliation(s)
- Dane R. Letourneau
- grid.7468.d0000 0001 2248 7639Department of Chemistry, Humboldt University Berlin, 12489 Berlin, Germany
| | - Dennis D. August
- grid.7468.d0000 0001 2248 7639Department of Chemistry, Humboldt University Berlin, 12489 Berlin, Germany
| | - Dietrich A. Volmer
- grid.7468.d0000 0001 2248 7639Department of Chemistry, Humboldt University Berlin, 12489 Berlin, Germany
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17
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Liu X, Wang Z, Gmitter FG, Grosser JW, Wang Y. Effects of Different Rootstocks on the Metabolites of Huanglongbing-Affected Sweet Orange Juices Using a Novel Combined Strategy of Untargeted Metabolomics and Machine Learning. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2023; 71:1246-1257. [PMID: 36606748 DOI: 10.1021/acs.jafc.2c07456] [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: 06/17/2023]
Abstract
Huanglongbing (HLB) is one of the most destructive citrus diseases, mainly caused by the Gram-negative bacteria Candidatus Liberibacter asiaticus. Aiming at unraveling the mechanisms of different scion/rootstock combinations on improving HLB-affected orange juice quality, the effects of rootstocks on the metabolites of HLB-affected sweet orange juices were investigated using a combined strategy of untargeted metabolomics and machine learning. A total of 2531 ion features were detected using UHPLC-Q-Orbitrap high-resolution electrospray ionization mass spectrometry, and 54 metabolites including amino acids, amines, flavonoids, coumarins, fatty acids, and glycosides were definitely or tentatively identified as the differential markers based on the random forest algorithm. Furthermore, 24 metabolites were verified and semi-quantified using authentic standards. Notably, the presence of specific amino acids and amines, especially polyamines, indicated that different rootstocks might affect glutamate, aspartate, proline, and arginine metabolism to regulate the physiological response against HLB. Meanwhile, the production of flavonoids and prenylated coumarins suggested that rootstocks influenced phenylalanine and phenylpropanoid metabolism. The possible metabolic pathways were proposed, and the important intermediates were verified by authentic standards. These results provide new insights on the effects of rootstocks on the metabolites of HLB-affected sweet orange juices.
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Affiliation(s)
- Xin Liu
- Citrus Research and Education Center, University of Florida, Lake Alfred, Florida 33850, United States
- Department of Food Science and Human Nutrition, University of Florida, Gainesville, Florida 32611, United States
| | - Zhixin Wang
- Citrus Research and Education Center, University of Florida, Lake Alfred, Florida 33850, United States
- Department of Food Science and Human Nutrition, University of Florida, Gainesville, Florida 32611, United States
| | - Frederick G Gmitter
- Citrus Research and Education Center, University of Florida, Lake Alfred, Florida 33850, United States
| | - Jude W Grosser
- Citrus Research and Education Center, University of Florida, Lake Alfred, Florida 33850, United States
| | - Yu Wang
- Citrus Research and Education Center, University of Florida, Lake Alfred, Florida 33850, United States
- Department of Food Science and Human Nutrition, University of Florida, Gainesville, Florida 32611, United States
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18
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Kartsova LA, Bessonova EA, Deev VA, Kolobova EA. Current Role of Modern Chromatography with Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy in the Investigation of Biomarkers of Endometriosis. Crit Rev Anal Chem 2023:1-24. [PMID: 36625278 DOI: 10.1080/10408347.2022.2156770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Endometriosis has a wide range of clinical manifestations, and the disease course is unpredictable, making the diagnosis a challenging task. Despite significant advances in the pathophysiology of endometriosis and various proposed theories, the exact etiology is not fully understood and is still unknown. The most commonly used biomarker of endometriosis is CA-125, however, it is nonspecific and is applied for cancers diagnosis. Therefore, the development of reliable noninvasive diagnostic tests for the early diagnosis of endometriosis remains one of the top priorities. Omics technologies are very promising approaches for constructing diagnostic models and biomarker discovery. Their use can greatly facilitate the study of such a complex disease as endometriosis. Nowadays, powerful analytical platforms commonly used in omics, such as gas and liquid chromatography with mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy, have proven to be a promising tools for biomarker discovery. The aim of this review is to summarize the various features of the analytical approaches, practical challenges and features of gas and liquid chromatography with MS and NMR spectroscopy (including sample processing protocols, technological advancements, and methodology) used for profiling of metabolites, lipids, peptides and proteins in physiological fluids and tissues from patients with endometriosis. In addition, this report devotes special attention to the issue of how comprehensive analyses of these profiles can effectively contribute to the study of endometriosis. The search query included reports published between 2012 and 2022 years in PubMed, Web-of-Science, SCOPUS, Science Direct.
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Affiliation(s)
| | | | | | - Ekaterina Alekseevna Kolobova
- Institute of Chemistry, St. Petersburg State University, St. Petersburg, Russia
- The Federal State Institute of Public Health 'The Nikiforov Russian Center of Emergency and Radiation Medicine', The Ministry of Russian Federation for Civil Defence, Emergencies and Elimination of Consequences of Natural Disasters, St. Petersburg, Russia
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19
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Abstract
Major stress has systemic effects on the body that can have adverse consequences for physical and mental health. However, the molecular basis of these damaging effects remains incompletely understood. Here we use a longitudinal approach to characterise the acute systemic impact of major psychological stress in a pig model. We perform untargeted metabolomics on non-invasively obtained saliva samples from pigs before and 24 h after transfer to the novel physical and social environment of a slaughterhouse. The main molecular changes occurring include decreases in amino acids, B-vitamins, and amino acid-derived metabolites synthesized in B-vitamin-dependent reactions, as well as yet-unidentified metabolite features. Decreased levels of several of the identified metabolites are implicated in the pathology of human psychological disorders and neurodegenerative disease, suggesting a possible neuroprotective function. Our results provide a fingerprint of the acute effect of psychological stress on the metabolome and suggest candidate biomarkers with potential roles in stress-related disorders.
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20
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The Age-Accompanied and Diet-Associated Remodeling of the Phospholipid, Amino Acid, and SCFA Metabolism of Healthy Centenarians from a Chinese Longevous Region: A Window into Exceptional Longevity. Nutrients 2022; 14:nu14204420. [PMID: 36297104 PMCID: PMC9612356 DOI: 10.3390/nu14204420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 09/29/2022] [Accepted: 10/13/2022] [Indexed: 11/05/2022] Open
Abstract
As centenarians provide a paradigm of healthy aging, investigating the comprehensive metabolic profiles of healthy centenarians is of utmost importance for the pursuit of health and longevity. However, relevant reports, especially studies considering the dietary influence on metabolism, are still limited, mostly lacking the guidance of a model of healthy aging. Therefore, exploring the signatures of the integrative metabolic profiles of the healthy centenarians from a famous longevous region, Bama County, China, should be an effective way. The global metabolome in urine and the short-chain fatty acids (SCFAs) in the feces of 30 healthy centenarians and 31 elderly people aged 60−70 from the longevous region were analyzed by non-targeted metabolomics combined with metabolic target analysis. The results showed that the characteristic metabolites related to longevity were mostly summarized into phosphatidylserine, lyso-phosphatidylethanolamine, phosphatidylcholine, phosphatidylinositol, bile acids, and amino acids (p < 0.05). Six metabolic pathways were found significant relevant to longevity. Furthermore, acetic acid, propionic acid, butyric acid, valeric acid, and total SCFA were significantly increased in the centenarian group (p < 0.05) and were also positively associated with the dietary fiber intake (p < 0.01). It was age-accompanied and diet-associated remodeling of phospholipid, amino acid, and SCFA metabolism that expressed the unique metabolic signatures related to exceptional longevity. This metabolic remodeling is suggestive of cognitive benefits, better antioxidant capacity, the attenuation of local inflammation, and health-span-promoting processes, which play a critical and positive role in shaping healthy aging.
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21
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Innovative Application of Metabolomics on Bioactive Ingredients of Foods. Foods 2022; 11:foods11192974. [PMID: 36230049 PMCID: PMC9562173 DOI: 10.3390/foods11192974] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 09/12/2022] [Accepted: 09/20/2022] [Indexed: 11/17/2022] Open
Abstract
Metabolomics, as a new omics technology, has been widely accepted by researchers and has shown great potential in the field of nutrition and health in recent years. This review briefly introduces the process of metabolomics analysis, including sample preparation and extraction, derivatization, separation and detection, and data processing. This paper focuses on the application of metabolomics in food-derived bioactive ingredients. For example, metabolomics techniques are used to analyze metabolites in food to find bioactive substances or new metabolites in food materials. Moreover, bioactive substances have been tested in vitro and in vivo, as well as in humans, to investigate the changes of metabolites and the underlying metabolic pathways, among which metabolomics is used to find potential biomarkers and targets. Metabolomics provides a new approach for the prevention and regulation of chronic diseases and the study of the underlying mechanisms. It also provides strong support for the development of functional food or drugs. Although metabolomics has some limitations such as low sensitivity, poor repeatability, and limited detection range, it is developing rapidly in general, and also in the field of nutrition and health. At the end of this paper, we put forward our own insights on the development prospects of metabolomics in the application of bioactive ingredients in food.
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22
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Liu Z, Zhang M, Chen P, Harnly JM, Sun J. Mass Spectrometry-Based Nontargeted and Targeted Analytical Approaches in Fingerprinting and Metabolomics of Food and Agricultural Research. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2022; 70:11138-11153. [PMID: 35998657 DOI: 10.1021/acs.jafc.2c01878] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Mass spectrometry (MS)-based techniques have been extensively applied in food and agricultural research. This review aims to address the advances and applications of MS-based analytical strategies in nontargeted and targeted analysis and summarizes the recent publications of MS-based techniques, including flow injection MS fingerprinting, chromatography-tandem MS metabolomics, direct analysis using ambient mass spectrometry, as well as development in MS data deconvolution software packages and databases for metabolomic studies. Various nontargeted and targeted approaches are employed in marker compounds identification, material adulteration detection, and the analysis of specific classes of secondary metabolites. In the newly emerged applications, the recent advances in computer tools for the fast deconvolution of MS data in targeted secondary metabolite analysis are highlighted.
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Affiliation(s)
- Zhihao Liu
- United States Department of Agriculture, Methods and Application of Food Composition Laboratory, Beltsville Human Nutrition Research Center, Agricultural Research Service, Beltsville, Maryland 20705, United States
- Department of Nutrition and Food Science, University of Maryland, College Park, Maryland 20742, United States
| | - Mengliang Zhang
- Department of Chemistry, Middle Tennessee State University, Murfreesboro, Tennessee 37132, United States
| | - Pei Chen
- United States Department of Agriculture, Methods and Application of Food Composition Laboratory, Beltsville Human Nutrition Research Center, Agricultural Research Service, Beltsville, Maryland 20705, United States
| | - James M Harnly
- United States Department of Agriculture, Methods and Application of Food Composition Laboratory, Beltsville Human Nutrition Research Center, Agricultural Research Service, Beltsville, Maryland 20705, United States
| | - Jianghao Sun
- United States Department of Agriculture, Methods and Application of Food Composition Laboratory, Beltsville Human Nutrition Research Center, Agricultural Research Service, Beltsville, Maryland 20705, United States
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23
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Chen J, Li T, Qin X, Du G, Zhou Y. Integration of Non-Targeted Metabolomics and Targeted Quantitative Analysis to Elucidate the Synergistic Antidepressant Effect of Bupleurum Chinense DC-Paeonia Lactiflora Pall Herb Pair by Regulating Purine Metabolism. Front Pharmacol 2022; 13:900459. [PMID: 35847012 PMCID: PMC9280301 DOI: 10.3389/fphar.2022.900459] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 05/23/2022] [Indexed: 12/03/2022] Open
Abstract
Bupleurum chinense DC (Chaihu)-Paeonia lactiflora Pall (Baishao) is among the most accepted herb pairs in many classic antidepressant prescriptions. Our previous study has shown that the Chaihu–Baishao herb pair (CBHP) had a better antidepressant effect than Chaihu or Baishao. Nevertheless, the synergistic antidepressant mechanism of this herb pair was not clearly understood. This study aimed to investigate the compatibility mechanism of Chaihu and Baishao for treating depression through a strategy of non-targeted metabolomics combined with targeted quantitative analysis and molecular biology techniques. First, the compatibility effects of CBHP were assessed by the chronic unpredictable mild stress (CUMS) rat model. Next, cortex metabolomics based on ultra-high-performance liquid chromatography combined with quadrupole orbitrap mass spectrometry (UPLC-Q-Orbitrap/MS) was used to discover the metabolic pathway that was synergistically regulated by CBHP. Based on the results of metabolomics analysis, metabolites were quantitatively validated by UPLC-MS/MS combined with the MRM mode in the crucial metabolic pathway. In addition, the signaling pathway associated with this metabolic pathway was detected by molecular biology techniques to further identify the biological meaning of the crucial metabolite on the synergistic antidepressant effect of CBHP. The antidepressant effect of CBHP was significantly better than that of Chaihu or Baishao single administrated in the behavioral test. According to cortex metabolomics, a total of 21 differential metabolites were screened out, and purine metabolism was selected as the crucial metabolic pathway by the enrichment analysis of differential metabolites. Subsequently, purine metabolism was confirmed as disorder in the CUMS group by targeted quantitative analysis, CBHP regulated more purine metabolites (six) than individual administration (two and two). The results showed that purine metabolism was modulated by CBHP through synergistically decreasing xanthine levels and inhibiting the conversion of xanthine dehydrogenase (XDH) to xanthine oxidase (XOD). Finally, the synergistic regulation effect of CBHP on xanthine synthesis was found to be related to inhibition of malondialdehyde (MDA) production, Nod-like receptor protein 3 (NLRP3) inflammasome expression, and interleukin (IL)-1β, IL-6, and tumor necrosis factor (TNF)-α secretion. The present study demonstrated that the regulation of purine metabolism, the suppression of oxidative stress, and inflammatory responses in the cortex were involved in the synergistic antidepressant effect of CBHP.
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Affiliation(s)
- Jiajun Chen
- Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan, China
- The Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education, Shanxi University, Taiyuan, China
- The Key Laboratory of Effective Substances Research and Utilization in TCM of Shanxi Province, Taiyuan, China
| | - Tian Li
- Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan, China
- The Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education, Shanxi University, Taiyuan, China
- The Key Laboratory of Effective Substances Research and Utilization in TCM of Shanxi Province, Taiyuan, China
| | - Xuemei Qin
- Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan, China
- The Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education, Shanxi University, Taiyuan, China
- The Key Laboratory of Effective Substances Research and Utilization in TCM of Shanxi Province, Taiyuan, China
| | - Guanhua Du
- Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan, China
- Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yuzhi Zhou
- Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan, China
- The Key Laboratory of Chemical Biology and Molecular Engineering of Ministry of Education, Shanxi University, Taiyuan, China
- The Key Laboratory of Effective Substances Research and Utilization in TCM of Shanxi Province, Taiyuan, China
- *Correspondence: Yuzhi Zhou,
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Shroff T, Aina K, Maass C, Cipriano M, Lambrecht J, Tacke F, Mosig A, Loskill P. Studying metabolism with multi-organ chips: new tools for disease modelling, pharmacokinetics and pharmacodynamics. Open Biol 2022; 12:210333. [PMID: 35232251 PMCID: PMC8889168 DOI: 10.1098/rsob.210333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
Non-clinical models to study metabolism including animal models and cell assays are often limited in terms of species translatability and predictability of human biology. This field urgently requires a push towards more physiologically accurate recapitulations of drug interactions and disease progression in the body. Organ-on-chip systems, specifically multi-organ chips (MOCs), are an emerging technology that is well suited to providing a species-specific platform to study the various types of metabolism (glucose, lipid, protein and drug) by recreating organ-level function. This review provides a resource for scientists aiming to study human metabolism by providing an overview of MOCs recapitulating aspects of metabolism, by addressing the technical aspects of MOC development and by providing guidelines for correlation with in silico models. The current state and challenges are presented for two application areas: (i) disease modelling and (ii) pharmacokinetics/pharmacodynamics. Additionally, the guidelines to integrate the MOC data into in silico models could strengthen the predictive power of the technology. Finally, the translational aspects of metabolizing MOCs are addressed, including adoption for personalized medicine and prospects for the clinic. Predictive MOCs could enable a significantly reduced dependence on animal models and open doors towards economical non-clinical testing and understanding of disease mechanisms.
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Affiliation(s)
- Tanvi Shroff
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen, Germany,Department for Microphysiological Systems, Institute for Biomedical Engineering, Faculty of Medicine, Eberhard Karls University Tübingen, Österbergstraße 3, 72074 Tübingen, Germany
| | - Kehinde Aina
- Institute of Biochemistry II, Center for Sepsis Control and Care, Jena University Hospital, Jena, Germany
| | | | - Madalena Cipriano
- Department for Microphysiological Systems, Institute for Biomedical Engineering, Faculty of Medicine, Eberhard Karls University Tübingen, Österbergstraße 3, 72074 Tübingen, Germany
| | - Joeri Lambrecht
- Department of Hepatology and Gastroenterology, Charité University Medicine Berlin, Campus Virchow Klinikum and Campus Charité Mitte, Berlin, Germany
| | - Frank Tacke
- Department of Hepatology and Gastroenterology, Charité University Medicine Berlin, Campus Virchow Klinikum and Campus Charité Mitte, Berlin, Germany
| | - Alexander Mosig
- Institute of Biochemistry II, Center for Sepsis Control and Care, Jena University Hospital, Jena, Germany
| | - Peter Loskill
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Reutlingen, Germany,Department for Microphysiological Systems, Institute for Biomedical Engineering, Faculty of Medicine, Eberhard Karls University Tübingen, Österbergstraße 3, 72074 Tübingen, Germany,3R-Center for In vitro Models and Alternatives to Animal Testing, Eberhard Karls University Tübingen, Tübingen, Germany
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25
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Lee SY, Shaari K. LC-MS metabolomics analysis of Stevia rebaudiana Bertoni leaves cultivated in Malaysia in relation to different developmental stages. PHYTOCHEMICAL ANALYSIS : PCA 2022; 33:249-261. [PMID: 34490671 DOI: 10.1002/pca.3084] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 07/19/2021] [Accepted: 07/20/2021] [Indexed: 06/13/2023]
Abstract
INTRODUCTION Stevia is known for its sweet taste, attributed to the presence of steviol glycosides. Although reports on the dynamic changes of steviol glycosides during development of stevia are available, the data are mainly focused on stevioside and rebaudioside A. Information concerning the comprehensive metabolite profile of stevia in relation to different developmental stages is still lacking. OBJECTIVE This study investigated the metabolite changes along the developmental stages of a local stevia cultivar. METHODOLOGY Stevia leaves were harvested at 4 different developmental stages (early vegetative, late vegetative, budding, and flowering). Samples were then subjected to LC-MS metabolomics analysis to determine the metabolite variations. RESULTS A total of 55 metabolites, comprising phenolic acids, flavonoids, and terpenoids were identified by MS/MS analysis of the stevia leaf extracts, revealing a metabolite profile which was comparatively similar with those of cultivars grown in other countries. PLS-DA differentiated the early vegetative stage stevia leaf samples from those of the later stages by higher content of phenolic acids. The leaf metabolomes of the later 3 stages (late vegetative, budding, and flowering) were collectively richer in flavonoids. Meanwhile, the content of steviol glycosides is highest during the late vegetative and budding stages. CONCLUSION The present study provided, for the first time, a general overview of the metabolite variations with regard to the different developmental stages of stevia. The information may facilitate decision making of suitable harvesting times for higher yields of steviol glycosides or a more balanced metabolite profile in terms of pharmacologically useful metabolites.
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Affiliation(s)
- Soo Yee Lee
- Natural Medicines and Products Research Laboratory (NaturMeds), Institute of Bioscience, Universiti Putra Malaysia, UPM Serdang, Selangor, 43400, Malaysia
| | - Khozirah Shaari
- Natural Medicines and Products Research Laboratory (NaturMeds), Institute of Bioscience, Universiti Putra Malaysia, UPM Serdang, Selangor, 43400, Malaysia
- Department of Chemistry, Faculty of Science, Universiti Putra Malaysia, UPM Serdang, Selangor, 43400, Malaysia
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Chandris P, Giannouli CC, Panayotou G. Imaging Approaches for the Study of Metabolism in Real Time Using Genetically Encoded Reporters. Front Cell Dev Biol 2022; 9:725114. [PMID: 35118062 PMCID: PMC8804523 DOI: 10.3389/fcell.2021.725114] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 12/13/2021] [Indexed: 11/23/2022] Open
Abstract
Metabolism comprises of two axes in order to serve homeostasis: anabolism and catabolism. Both axes are interbranched with the so-called bioenergetics aspect of metabolism. There is a plethora of analytical biochemical methods to monitor metabolites and reactions in lysates, yet there is a rising need to monitor, quantify and elucidate in real time the spatiotemporal orchestration of complex biochemical reactions in living systems and furthermore to analyze the metabolic effect of chemical compounds that are destined for the clinic. The ongoing technological burst in the field of imaging creates opportunities to establish new tools that will allow investigators to monitor dynamics of biochemical reactions and kinetics of metabolites at a resolution that ranges from subcellular organelle to whole system for some key metabolites. This article provides a mini review of available toolkits to achieve this goal but also presents a perspective on the open space that can be exploited to develop novel methodologies that will merge classic biochemistry of metabolism with advanced imaging. In other words, a perspective of "watching metabolism in real time."
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Affiliation(s)
- Panagiotis Chandris
- Institute for Bioinnovation, Biomedical Sciences Research Center “Alexander Fleming”, Vari, Greece
| | | | - George Panayotou
- Institute for Bioinnovation, Biomedical Sciences Research Center “Alexander Fleming”, Vari, Greece
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Zhang M, Yang H. Perspectives from metabolomics in the early diagnosis and prognosis of gestational diabetes mellitus. Front Endocrinol (Lausanne) 2022; 13:967191. [PMID: 36246890 PMCID: PMC9554488 DOI: 10.3389/fendo.2022.967191] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Accepted: 09/05/2022] [Indexed: 11/26/2022] Open
Abstract
Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders in pregnant women. The early detection of GDM provides an opportunity for the effective treatment of hyperglycemia in pregnancy, thus decreasing the risk of adverse perinatal outcomes for mothers and newborns. Metabolomics, an emerging technique, offers a novel point of view in understanding the onset and development of diseases and has been repeatedly used in various gestational periods in recent studies of GDM. Moreover, metabolomics provides varied opportunities in the different diagnoses of GDM from prediabetes or predisposition to diabetes, the diagnosis of GDM at a gestational age several weeks earlier than that used in the traditional method, and the assessment of prognosis considering the physiologic subtypes of GDM and clinical indexes. Longitudinal metabolomics truly facilitates the dynamic monitoring of metabolic alterations over the course of pregnancy. Herein, we review recent advancements in metabolomics and summarize evidence from studies on the application of metabolomics in GDM, highlighting the aspects of the diagnosis and differential diagnoses of GDM in an early stage. We also discuss future study directions concerning the physiologic subtypes, prognosis, and limitations of metabolomics.
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Wahman R, Moser S, Bieber S, Cruzeiro C, Schröder P, Gilg A, Lesske F, Letzel T. Untargeted Analysis of Lemna minor Metabolites: Workflow and Prioritization Strategy Comparing Highly Confident Features between Different Mass Spectrometers. Metabolites 2021; 11:832. [PMID: 34940590 PMCID: PMC8706044 DOI: 10.3390/metabo11120832] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 11/05/2021] [Accepted: 11/30/2021] [Indexed: 11/29/2022] Open
Abstract
Metabolomics approaches provide a vast array of analytical datasets, which require a comprehensive analytical, statistical, and biochemical workflow to reveal changes in metabolic profiles. The biological interpretation of mass spectrometric metabolomics results is still obstructed by the reliable identification of the metabolites as well as annotation and/or classification. In this work, the whole Lemna minor (common duckweed) was extracted using various solvents and analyzed utilizing polarity-extended liquid chromatography (reversed-phase liquid chromatography (RPLC)-hydrophilic interaction liquid chromatography (HILIC)) connected to two time-of-flight (TOF) mass spectrometer types, individually. This study (introduces and) discusses three relevant topics for the untargeted workflow: (1) A comparison study of metabolome samples was performed with an untargeted data handling workflow in two different labs with two different mass spectrometers using the same plant material type. (2) A statistical procedure was observed prioritizing significant detected features (dependent and independent of the mass spectrometer using the predictive methodology Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA). (3) Relevant features were transferred to a prioritization tool (the FOR-IDENT platform (FI)) and were compared with the implemented compound database PLANT-IDENT (PI). This compound database is filled with relevant compounds of the Lemnaceae, Poaceae, Brassicaceae, and Nymphaceae families according to analytical criteria such as retention time (polarity and LogD (pH 7)) and accurate mass (empirical formula). Thus, an untargeted analysis was performed using the new tool as a prioritization and identification source for a hidden-target screening strategy. Consequently, forty-two compounds (amino acids, vitamins, flavonoids) could be recognized and subsequently validated in Lemna metabolic profile using reference standards. The class of flavonoids includes free aglycons and their glycosides. Further, according to our knowledge, the validated flavonoids robinetin and norwogonin were for the first time identified in the Lemna minor extracts.
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Affiliation(s)
- Rofida Wahman
- Chair of Urban Water Systems Engineering, Technical University of Munich, Am Coulombwall 3, 85748 Garching, Germany;
- Pharmacognosy Department, Faculty of Pharmacy, Assiut University, 71526 Assiut, Egypt
| | - Stefan Moser
- Stefan Moser Process Optimization, Weberweg 3, 83131 Nußdorf am Inn, Germany;
| | - Stefan Bieber
- Analytisches Forschungsinstitut für Non-Target Screening GmbH (AFIN-TS), Am Mittleren Moos 48, 86167 Augsburg, Germany;
| | - Catarina Cruzeiro
- Research Unit Comparative Microbiome Analysis, German Research Center for Environmental Health, Helmholtz Centrum Munich, Ingolstädter Strasse 1, 85764 Neuherberg, Germany; (C.C.); (P.S.)
| | - Peter Schröder
- Research Unit Comparative Microbiome Analysis, German Research Center for Environmental Health, Helmholtz Centrum Munich, Ingolstädter Strasse 1, 85764 Neuherberg, Germany; (C.C.); (P.S.)
| | - August Gilg
- Departement of Bioengineering Sciences, Weihenstephan-Triesdorf University of Applied Sciences, Am Hofgarten 4, Weihenstephan, 85354 Freising, Germany; (A.G.); (F.L.)
| | - Frank Lesske
- Departement of Bioengineering Sciences, Weihenstephan-Triesdorf University of Applied Sciences, Am Hofgarten 4, Weihenstephan, 85354 Freising, Germany; (A.G.); (F.L.)
| | - Thomas Letzel
- Chair of Urban Water Systems Engineering, Technical University of Munich, Am Coulombwall 3, 85748 Garching, Germany;
- Analytisches Forschungsinstitut für Non-Target Screening GmbH (AFIN-TS), Am Mittleren Moos 48, 86167 Augsburg, Germany;
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Duraj T, Carrión-Navarro J, Seyfried TN, García-Romero N, Ayuso-Sacido A. Metabolic therapy and bioenergetic analysis: The missing piece of the puzzle. Mol Metab 2021; 54:101389. [PMID: 34749013 PMCID: PMC8637646 DOI: 10.1016/j.molmet.2021.101389] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 10/29/2021] [Accepted: 11/01/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Aberrant metabolism is recognized as a hallmark of cancer, a pillar necessary for cellular proliferation. Regarding bioenergetics (ATP generation), most cancers display a preference not only toward aerobic glycolysis ("Warburg effect") and glutaminolysis (mitochondrial substrate level-phosphorylation) but also toward other metabolites such as lactate, pyruvate, and fat-derived sources. These secondary metabolites can assist in proliferation but cannot fully cover ATP demands. SCOPE OF REVIEW The concept of a static metabolic profile is challenged by instances of heterogeneity and flexibility to meet fuel/anaplerotic demands. Although metabolic therapies are a promising tool to improve therapeutic outcomes, either via pharmacological targets or press-pulse interventions, metabolic plasticity is rarely considered. Lack of bioenergetic analysis in vitro and patient-derived models is hindering translational potential. Here, we review the bioenergetics of cancer and propose a simple analysis of major metabolic pathways, encompassing both affordable and advanced techniques. A comprehensive compendium of Seahorse XF bioenergetic measurements is presented for the first time. MAJOR CONCLUSIONS Standardization of principal readouts might help researchers to collect a complete metabolic picture of cancer using the most appropriate methods depending on the sample of interest.
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Affiliation(s)
- Tomás Duraj
- Faculty of Medicine, Institute for Applied Molecular Medicine (IMMA), CEU San Pablo University, 28668, Madrid, Spain.
| | - Josefa Carrión-Navarro
- Faculty of Experimental Sciences, Universidad Francisco de Vitoria, 28223, Madrid, Spain; Brain Tumor Laboratory, Fundación Vithas, Grupo Hospitales Vithas, 28043, Madrid, Spain.
| | - Thomas N Seyfried
- Biology Department, Boston College, 140 Commonwealth Ave, Chestnut Hill, MA, 02467, USA.
| | - Noemí García-Romero
- Faculty of Experimental Sciences, Universidad Francisco de Vitoria, 28223, Madrid, Spain; Brain Tumor Laboratory, Fundación Vithas, Grupo Hospitales Vithas, 28043, Madrid, Spain.
| | - Angel Ayuso-Sacido
- Faculty of Experimental Sciences, Universidad Francisco de Vitoria, 28223, Madrid, Spain; Brain Tumor Laboratory, Fundación Vithas, Grupo Hospitales Vithas, 28043, Madrid, Spain; Faculty of Medicine, Universidad Francisco de Vitoria, 28223, Madrid, Spain.
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Gupta S, Sharma U. Metabolomics of neurological disorders in India. ANALYTICAL SCIENCE ADVANCES 2021; 2:594-610. [PMID: 38715858 PMCID: PMC10989583 DOI: 10.1002/ansa.202000169] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Revised: 10/31/2021] [Accepted: 11/01/2021] [Indexed: 06/11/2024]
Abstract
Metabolomics is the comprehensive study of the metabolome and its alterations within biological fluids and tissues. Over the years, applications of metabolomics have been explored in several areas, including personalised medicine in diseases, metabolome-wide association studies (MWAS), pharmacometabolomics and in combination with other branches of omics such as proteomics, transcriptomics and genomics. Mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy are the major analytical techniques widely employed in metabolomics. In addition, MS is coupled with chromatography techniques like gas chromatography (GC) and liquid chromatography (LC) to separate metabolites before analysis. These analytical techniques have made possible identification and quantification of large numbers of metabolites, encompassing characterization of diseases and facilitating a systematic and rational therapeutic strategy based on metabolic patterns. In recent years, the metabolomics approach has been used to obtain a deeper insight into the underlying biochemistry of neurodegenerative disorders and the discovery of biomarkers of clinical implications. The current review mainly focuses on an Indian perspective of metabolomics for the identification of metabolites and metabolic alterations serving as potential diagnostic biomarkers for neurological diseases including acute spinal cord injury, amyotrophic lateral sclerosis, tethered cord syndrome, spina bifida, stroke, Parkinson's disease, glioblastoma and neurological disorders with inborn errors of metabolism.
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Affiliation(s)
- Sangeetha Gupta
- Amity Institute of PharmacyAmity UniversityNoidaUttar PradeshIndia
| | - Uma Sharma
- Department of NMR & MRI FacilityAll India Institute of Medical SciencesNew DelhiIndia
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Metabolomics in Autoimmune Diseases: Focus on Rheumatoid Arthritis, Systemic Lupus Erythematous, and Multiple Sclerosis. Metabolites 2021; 11:metabo11120812. [PMID: 34940570 PMCID: PMC8708401 DOI: 10.3390/metabo11120812] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 11/24/2021] [Accepted: 11/24/2021] [Indexed: 12/18/2022] Open
Abstract
The metabolomics approach represents the last downstream phenotype and is widely used in clinical studies and drug discovery. In this paper, we outline recent advances in the metabolomics research of autoimmune diseases (ADs) such as rheumatoid arthritis (RA), multiple sclerosis (MuS), and systemic lupus erythematosus (SLE). The newly discovered biomarkers and the metabolic mechanism studies for these ADs are described here. In addition, studies elucidating the metabolic mechanisms underlying these ADs are presented. Metabolomics has the potential to contribute to pharmacotherapy personalization; thus, we summarize the biomarker studies performed to predict the personalization of medicine and drug response.
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Zhang T, Chen C, Xie K, Wang J, Pan Z. Current State of Metabolomics Research in Meat Quality Analysis and Authentication. Foods 2021; 10:2388. [PMID: 34681437 PMCID: PMC8535928 DOI: 10.3390/foods10102388] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 09/27/2021] [Accepted: 09/28/2021] [Indexed: 12/23/2022] Open
Abstract
In the past decades, as an emerging omic, metabolomics has been widely used in meat science research, showing promise in meat quality analysis and meat authentication. This review first provides a brief overview of the concept, analytical techniques, and analysis workflow of metabolomics. Additionally, the metabolomics research in quality analysis and authentication of meat is comprehensively described. Finally, the limitations, challenges, and future trends of metabolomics application in meat quality analysis and meat authentication are critically discussed. We hope to provide valuable insights for further research in meat quality.
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Affiliation(s)
- Tao Zhang
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (T.Z.); (C.C.); (K.X.)
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Yangzhou University, Yangzhou 225009, China;
| | - Can Chen
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (T.Z.); (C.C.); (K.X.)
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Yangzhou University, Yangzhou 225009, China;
| | - Kaizhou Xie
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (T.Z.); (C.C.); (K.X.)
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Yangzhou University, Yangzhou 225009, China;
| | - Jinyu Wang
- College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China; (T.Z.); (C.C.); (K.X.)
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Yangzhou University, Yangzhou 225009, China;
| | - Zhiming Pan
- Joint International Research Laboratory of Agriculture and Agri-Product Safety, Ministry of Education, Yangzhou University, Yangzhou 225009, China;
- Jiangsu Key Laboratory of Zoonosis, Key Laboratory of Prevention and Control of Biological Hazard Factors (Animal Origin) for Agrifood Safety and Quality, Ministry of Agriculture and Rural Affairs of the People’s Republic of China, Yangzhou University, Yangzhou 225009, China
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Chaby LE, Lasseter HC, Contrepois K, Salek RM, Turck CW, Thompson A, Vaughan T, Haas M, Jeromin A. Cross-Platform Evaluation of Commercially Targeted and Untargeted Metabolomics Approaches to Optimize the Investigation of Psychiatric Disease. Metabolites 2021; 11:609. [PMID: 34564425 PMCID: PMC8466258 DOI: 10.3390/metabo11090609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 08/24/2021] [Accepted: 08/26/2021] [Indexed: 11/17/2022] Open
Abstract
Metabolomics methods often encounter trade-offs between quantification accuracy and coverage, with truly comprehensive coverage only attainable through a multitude of complementary assays. Due to the lack of standardization and the variety of metabolomics assays, it is difficult to integrate datasets across studies or assays. To inform metabolomics platform selection, with a focus on posttraumatic stress disorder (PTSD), we review platform use and sample sizes in psychiatric metabolomics studies and then evaluate five prominent metabolomics platforms for coverage and performance, including intra-/inter-assay precision, accuracy, and linearity. We found performance was variable between metabolite classes, but comparable across targeted and untargeted approaches. Within all platforms, precision and accuracy were highly variable across classes, ranging from 0.9-63.2% (coefficient of variation) and 0.6-99.1% for accuracy to reference plasma. Several classes had high inter-assay variance, potentially impeding dissociation of a biological signal, including glycerophospholipids, organooxygen compounds, and fatty acids. Coverage was platform-specific and ranged from 16-70% of PTSD-associated metabolites. Non-overlapping coverage is challenging; however, benefits of applying multiple metabolomics technologies must be weighed against cost, biospecimen availability, platform-specific normative levels, and challenges in merging datasets. Our findings and open-access cross-platform dataset can inform platform selection and dataset integration based on platform-specific coverage breadth/overlap and metabolite-specific performance.
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Affiliation(s)
- Lauren E. Chaby
- Cohen Veterans Bioscience, New York, NY 10018, USA; (L.E.C.); (H.C.L.); (A.T.); (T.V.); (M.H.)
| | - Heather C. Lasseter
- Cohen Veterans Bioscience, New York, NY 10018, USA; (L.E.C.); (H.C.L.); (A.T.); (T.V.); (M.H.)
| | - Kévin Contrepois
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA;
| | - Reza M. Salek
- International Agency for Research on Cancer, Nutrition and Metabolism Branch, World Health Organisation, 150 Cours Albert Thomas, CEDEX 08, 69372 Lyon, France;
| | - Christoph W. Turck
- Max Planck Institute of Psychiatry, Proteomics and Biomarkers, 80804 Munich, Germany;
| | - Andrew Thompson
- Cohen Veterans Bioscience, New York, NY 10018, USA; (L.E.C.); (H.C.L.); (A.T.); (T.V.); (M.H.)
| | - Timothy Vaughan
- Cohen Veterans Bioscience, New York, NY 10018, USA; (L.E.C.); (H.C.L.); (A.T.); (T.V.); (M.H.)
| | - Magali Haas
- Cohen Veterans Bioscience, New York, NY 10018, USA; (L.E.C.); (H.C.L.); (A.T.); (T.V.); (M.H.)
| | - Andreas Jeromin
- Cohen Veterans Bioscience, New York, NY 10018, USA; (L.E.C.); (H.C.L.); (A.T.); (T.V.); (M.H.)
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Magliocco G, Desmeules J, Matthey A, Quirós-Guerrero LM, Bararpour N, Joye T, Marcourt L, F Queiroz E, Wolfender JL, Gloor Y, Thomas A, Daali Y. METABOLOMICS REVEALS BIOMARKERS IN HUMAN URINE AND PLASMA TO PREDICT CYP2D6 ACTIVITY. Br J Pharmacol 2021; 178:4708-4725. [PMID: 34363609 PMCID: PMC9290485 DOI: 10.1111/bph.15651] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 06/30/2021] [Accepted: 08/02/2021] [Indexed: 12/01/2022] Open
Abstract
Background and Purpose Individualized assessment of cytochrome P450 2D6 (CYP2D6) activity is usually performed through phenotyping following administration of a probe drug to measure the enzyme's activity. To avoid any iatrogenic harm (allergic drug reaction, dosing error) related to the probe drug, the development of non‐burdensome tools for real‐time phenotyping of CYP2D6 could significantly contribute to precision medicine. This study focuses on the identification of markers of the CYP2D6 enzyme in human biofluids using an LC‐high‐resolution mass spectrometry‐based metabolomic approach. Experimental Approach Plasma and urine samples from healthy volunteers were analysed before and after intake of a daily dose of paroxetine 20 mg over 7 days. CYP2D6 genotyping and phenotyping, using single oral dose of dextromethorphan 5 mg, were also performed in all participants. Key Results We report four metabolites of solanidine and two unknown compounds as possible novel CYP2D6 markers. Mean relative intensities of these features were significantly reduced during the inhibition session compared with the control session (n = 37). Semi‐quantitative analysis showed that the largest decrease (−85%) was observed for the ion m/z 432.3108 normalized to solanidine (m/z 398.3417). Mean relative intensities of these ions were significantly higher in the CYP2D6 normal–ultrarapid metabolizer group (n = 37) compared with the poor metabolizer group (n = 6). Solanidine intensity was more than 15 times higher in CYP2D6‐deficient individuals compared with other volunteers. Conclusion and Implications The applied untargeted metabolomic strategy identified potential novel markers capable of semi‐quantitatively predicting CYP2D6 activity, a promising discovery for personalized medicine.
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Affiliation(s)
- Gaëlle Magliocco
- Division of Clinical Pharmacology and Toxicology, Geneva University Hospitals, Geneva, Switzerland.,School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland.,Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland
| | - Jules Desmeules
- Division of Clinical Pharmacology and Toxicology, Geneva University Hospitals, Geneva, Switzerland.,School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland.,Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland.,Clinical Research Center, Geneva University Hospitals, Geneva, Switzerland
| | - Alain Matthey
- Division of Clinical Pharmacology and Toxicology, Geneva University Hospitals, Geneva, Switzerland.,Clinical Research Center, Geneva University Hospitals, Geneva, Switzerland
| | - Luis M Quirós-Guerrero
- School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland.,Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland
| | - Nasim Bararpour
- Forensic Toxicology and Chemistry Unit, CURML, Lausanne University Hospital, Geneva University Hospitals, Lausanne, Geneva, Switzerland.,Faculty Unit of Toxicology, CURML, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Timothée Joye
- Forensic Toxicology and Chemistry Unit, CURML, Lausanne University Hospital, Geneva University Hospitals, Lausanne, Geneva, Switzerland.,Faculty Unit of Toxicology, CURML, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Laurence Marcourt
- School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland.,Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland
| | - Emerson F Queiroz
- School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland.,Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland
| | - Jean-Luc Wolfender
- School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland.,Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland
| | - Yvonne Gloor
- Division of Clinical Pharmacology and Toxicology, Geneva University Hospitals, Geneva, Switzerland
| | - Aurélien Thomas
- Forensic Toxicology and Chemistry Unit, CURML, Lausanne University Hospital, Geneva University Hospitals, Lausanne, Geneva, Switzerland.,Faculty Unit of Toxicology, CURML, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Youssef Daali
- Division of Clinical Pharmacology and Toxicology, Geneva University Hospitals, Geneva, Switzerland.,School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland.,Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Geneva, Switzerland
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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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Comparison of Targeted and Untargeted Approaches in Breath Analysis for the Discrimination of Lung Cancer from Benign Pulmonary Diseases and Healthy Persons. Molecules 2021; 26:molecules26092609. [PMID: 33946997 PMCID: PMC8125376 DOI: 10.3390/molecules26092609] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Revised: 04/23/2021] [Accepted: 04/27/2021] [Indexed: 11/25/2022] Open
Abstract
The aim of the present study was to compare the efficiency of targeted and untargeted breath analysis in the discrimination of lung cancer (Ca+) patients from healthy people (HC) and patients with benign pulmonary diseases (Ca−). Exhaled breath samples from 49 Ca+ patients, 36 Ca− patients and 52 healthy controls (HC) were analyzed by an SPME–GC–MS method. Untargeted treatment of the acquired data was performed with the use of the web-based platform XCMS Online combined with manual reprocessing of raw chromatographic data. Machine learning methods were applied to estimate the efficiency of breath analysis in the classification of the participants. Results: Untargeted analysis revealed 29 informative VOCs, from which 17 were identified by mass spectra and retention time/retention index evaluation. The untargeted analysis yielded slightly better results in discriminating Ca+ patients from HC (accuracy: 91.0%, AUC: 0.96 and accuracy 89.1%, AUC: 0.97 for untargeted and targeted analysis, respectively) but significantly improved the efficiency of discrimination between Ca+ and Ca− patients, increasing the accuracy of the classification from 52.9 to 75.3% and the AUC from 0.55 to 0.82. Conclusions: The untargeted breath analysis through the inclusion and utilization of newly identified compounds that were not considered in targeted analysis allowed the discrimination of the Ca+ from Ca− patients, which was not achieved by the targeted approach.
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Yahia A, Stevanin G. The History of Gene Hunting in Hereditary Spinocerebellar Degeneration: Lessons From the Past and Future Perspectives. Front Genet 2021; 12:638730. [PMID: 33833777 PMCID: PMC8021710 DOI: 10.3389/fgene.2021.638730] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 03/02/2021] [Indexed: 01/02/2023] Open
Abstract
Hereditary spinocerebellar degeneration (SCD) encompasses an expanding list of rare diseases with a broad clinical and genetic heterogeneity, complicating their diagnosis and management in daily clinical practice. Correct diagnosis is a pillar for precision medicine, a branch of medicine that promises to flourish with the progressive improvements in studying the human genome. Discovering the genes causing novel Mendelian phenotypes contributes to precision medicine by diagnosing subsets of patients with previously undiagnosed conditions, guiding the management of these patients and their families, and enabling the discovery of more causes of Mendelian diseases. This new knowledge provides insight into the biological processes involved in health and disease, including the more common complex disorders. This review discusses the evolution of the clinical and genetic approaches used to diagnose hereditary SCD and the potential of new tools for future discoveries.
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Affiliation(s)
- Ashraf Yahia
- Department of Biochemistry, Faculty of Medicine, University of Khartoum, Khartoum, Sudan
- Department of Biochemistry, Faculty of Medicine, National University, Khartoum, Sudan
- Institut du Cerveau, INSERM U1127, CNRS UMR7225, Sorbonne Université, Paris, France
- Ecole Pratique des Hautes Etudes, EPHE, PSL Research University, Paris, France
| | - Giovanni Stevanin
- Institut du Cerveau, INSERM U1127, CNRS UMR7225, Sorbonne Université, Paris, France
- Ecole Pratique des Hautes Etudes, EPHE, PSL Research University, Paris, France
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Kiousi DE, Rathosi M, Tsifintaris M, Chondrou P, Galanis A. Pro-biomics: Omics Technologies To Unravel the Role of Probiotics in Health and Disease. Adv Nutr 2021; 12:1802-1820. [PMID: 33626128 PMCID: PMC8483974 DOI: 10.1093/advances/nmab014] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 12/29/2020] [Accepted: 01/26/2021] [Indexed: 12/11/2022] Open
Abstract
The comprehensive characterization of probiotic action has flourished during the past few decades, alongside the evolution of high-throughput, multiomics platforms. The integration of these platforms into probiotic animal and human studies has provided valuable insights into the holistic effects of probiotic supplementation on intestinal and extraintestinal diseases. Indeed, these methodologies have informed about global molecular changes induced in the host and residing commensals at multiple levels, providing a bulk of metagenomic, transcriptomic, proteomic, and metabolomic data. The meaningful interpretation of generated data remains a challenge; however, the maturation of the field of systems biology and artificial intelligence has supported analysis of results. In this review article, we present current literature on the use of multiomics approaches in probiotic studies, we discuss current trends in probiotic research, and examine the possibility of tailor-made probiotic supplementation. Lastly, we delve deeper into newer technologies that have been developed in the last few years, such as single-cell multiomics analyses, and provide future directions for the maximization of probiotic efficacy.
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Affiliation(s)
- Despoina Eugenia Kiousi
- Department of Molecular Biology and Genetics, Faculty of Health Sciences, Democritus University of Thrace, Alexandroupolis, Greece
| | - Marina Rathosi
- Department of Molecular Biology and Genetics, Faculty of Health Sciences, Democritus University of Thrace, Alexandroupolis, Greece
| | - Margaritis Tsifintaris
- Department of Molecular Biology and Genetics, Faculty of Health Sciences, Democritus University of Thrace, Alexandroupolis, Greece
| | - Pelagia Chondrou
- Department of Molecular Biology and Genetics, Faculty of Health Sciences, Democritus University of Thrace, Alexandroupolis, Greece
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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: 85] [Impact Index Per Article: 28.3] [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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