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Forsberg J, Rasmussen CT, van den Berg FWJ, Engelsen SB, Aru V. Fermentation Analytical Technology (FAT): Monitoring industrial E. coli fermentations using absolute quantitative 1H NMR spectroscopy. Anal Chim Acta 2024; 1311:342722. [PMID: 38816156 DOI: 10.1016/j.aca.2024.342722] [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: 03/04/2024] [Revised: 05/09/2024] [Accepted: 05/12/2024] [Indexed: 06/01/2024]
Abstract
BACKGROUND To perform fast, reproducible, and absolute quantitative measurements in an automated manner has become of paramount importance when monitoring industrial processes, including fermentations. Due to its numerous advantages - including its inherent quantitative nature - Proton Nuclear Magnetic Resonance (1H NMR) spectroscopy provides an ideal tool for the time-resolved monitoring of fermentations. However, analytical conditions, including non-automated sample preparation and long relaxation times (T1) of some metabolites, can significantly lengthen the experimental time and make implementation in an industrial set up unfeasible. RESULTS We present a high throughput method based on Standard Operating Procedures (SOPs) and 1H NMR, which lays the foundation for what we call Fermentation Analytical Technology (FAT). Our method was developed for the accurate absolute quantification of metabolites produced during Escherichia coli industrial fermentations. The method includes: (1) a stopped flow system for non-invasive sample collection followed by sample quenching, (2) automatic robot-assisted sample preparation, (3) fast 1H NMR measurements, (4) metabolites quantification using multivariate curve resolution (MCR), and (5) metabolites absolute quantitation using a novel correction factor (k) to compensate for the short recycle delay (D1) employed in the 1H NMR measurements. The quantification performance was tested using two sample types: buffer solutions of chemical standards and real fermentation samples. Five metabolites - glucose, acetate, alanine, phenylalanine and betaine - were quantified. Absolute quantitation ranged between 0.64 and 3.40 mM in pure buffer, and 0.71-7.76 mM in real samples. SIGNIFICANCE The proposed method is generic and can be straight forward implemented to other types of fermentations, such as lactic acid, ethanol and acetic acid fermentations. It provides a high throughput automated solution for monitoring fermentation processes and for quality control through absolute quantification of key metabolites in fermentation broth. It can be easily implemented in an at-line industrial setting, facilitating the optimization of the manufacturing process towards higher yields and more efficient and sustainable use of resources.
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Affiliation(s)
- Jakob Forsberg
- Department of Food Science, University of Copenhagen, Rolighedsvej 26, 1958, Frederiksberg C, Denmark; Novo Nordisk A/S, Hagedornsvej 1, 2820, Gentofte, Denmark.
| | | | - Frans W J van den Berg
- Department of Food Science, University of Copenhagen, Rolighedsvej 26, 1958, Frederiksberg C, Denmark
| | - Søren Balling Engelsen
- Department of Food Science, University of Copenhagen, Rolighedsvej 26, 1958, Frederiksberg C, Denmark
| | - Violetta Aru
- Department of Food Science, University of Copenhagen, Rolighedsvej 26, 1958, Frederiksberg C, Denmark.
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Vion C, Le Mao I, Yeramian N, Muro M, Bernard M, Da Costa G, Richard T, Marullo P. Targeted 1-H-NMR wine analyses revealed specific metabolomic signatures of yeast populations belonging to the Saccharomyces genus. Food Microbiol 2024; 120:104463. [PMID: 38431337 DOI: 10.1016/j.fm.2024.104463] [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: 05/11/2023] [Revised: 01/02/2024] [Accepted: 01/03/2024] [Indexed: 03/05/2024]
Abstract
This study aimed to explore the non-volatile metabolomic variability of a large panel of strains (44) belonging to the Saccharomyces cerevisiae and Saccharomyces uvarum species in the context of the wine alcoholic fermentation. For the S. cerevisiae strains flor, fruit and wine strains isolated from different anthropic niches were compared. This phenotypic survey was achieved with a special focus on acidity management by using natural grape juices showing opposite level of acidity. A 1H NMR based metabolomics approach was developed for quantifying fifteen wine metabolites that showed important quantitative variability within the strains. Thanks to the robustness of the assay and the low amount of sample required, this tool is relevant for the analysis of the metabolomic profile of numerous wines. The S. cerevisiae and S. uvarum species displayed significant differences for malic, succinic, and pyruvic acids, as well as for glycerol and 2,3-butanediol production. As expected, S. uvarum showed weaker fermentation fitness but interesting acidifying properties. The three groups of S. cerevisiae strains showed different metabolic profiles mostly related to their production and consumption of organic acids. More specifically, flor yeast consumed more malic acid and produced more acetic acid than the other S. cerevisiae strains which was never reported before. These features might be linked to the ability of flor yeasts to shift their metabolism during wine oxidation.
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Affiliation(s)
- Charlotte Vion
- Biolaffort, Bordeaux, France; UMR 1366 Œnologie, Université de Bordeaux, INRAE, Bordeaux INP, BSA, ISVV, France
| | - Ines Le Mao
- UMR 1366 Œnologie, Université de Bordeaux, INRAE, Bordeaux INP, BSA, ISVV, France
| | - Nadine Yeramian
- Microbiology Division, Department of Biotechnology and Food Science, Faculty of Science-University of Burgos, Spain
| | - Maïtena Muro
- Biolaffort, Bordeaux, France; UMR 1366 Œnologie, Université de Bordeaux, INRAE, Bordeaux INP, BSA, ISVV, France
| | - Margaux Bernard
- Biolaffort, Bordeaux, France; UMR 1366 Œnologie, Université de Bordeaux, INRAE, Bordeaux INP, BSA, ISVV, France
| | - Grégory Da Costa
- UMR 1366 Œnologie, Université de Bordeaux, INRAE, Bordeaux INP, BSA, ISVV, France
| | - Tristan Richard
- UMR 1366 Œnologie, Université de Bordeaux, INRAE, Bordeaux INP, BSA, ISVV, France
| | - Philippe Marullo
- Biolaffort, Bordeaux, France; UMR 1366 Œnologie, Université de Bordeaux, INRAE, Bordeaux INP, BSA, ISVV, France.
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Alothman A, Emwas AH, Singh U, Jaremko M, Agusti S. Metabolomics-based analysis of the diatom Cheatoceros tenuissimus combining NMR and GC-MS techniques. MethodsX 2024; 12:102695. [PMID: 38595808 PMCID: PMC11001764 DOI: 10.1016/j.mex.2024.102695] [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: 02/22/2024] [Accepted: 04/02/2024] [Indexed: 04/11/2024] Open
Abstract
Metabolomics, a recent addition to omics sciences, studies small molecules across plants, animals, humans, and marine organisms. Nuclear magnetic resonance (NMR) and gas chromatography-mass spectrometry (GC-MS) are widely used in those studies, including microalgae metabolomics. NMR is non-destructive and highly reproducible but has limited sensitivity, which could be supplemented by joining GC-MS analysis. Extracting metabolites from macromolecules requires optimization for trustworthy results. Different extraction methods yield distinct profiles, emphasizing the need for optimization. The results indicated that the optimized extraction procedure successfully identified NMR and GC-MS-based metabolites in MeOH, CHCl3, and H2O extraction solvents. The findings represented the spectral information related to carbohydrates, organic molecules, and amino acids from the water-soluble metabolites fraction and a series of fatty acid chains, lipids, and sterols from the lipid fraction. Our study underscores the benefit of combining NMR and GC-MS techniques to comprehensively understand microalgae metabolomes, including high and low metabolite concentrations and abundances.•In this study, we focused on optimizing the extraction procedure and combining NMR and GC-MS techniques to overcome the low NMR sensitivity and the different detected range limits of NMR and GC-MS.•We explored metabolome diversity in a tropical strain of the small cells' diatom Cheatoceros tenuissimus.
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Affiliation(s)
- Afrah Alothman
- King Abdullah University of Science and Technology (KAUST), Biological and Environmental and Science and Engineering, Marine Science Program, Thuwal, 23955-6900, Saudi Arabia
| | - Abdul-Hamid Emwas
- King Abdullah University of Science and Technology (KAUST), Core Labs, Thuwal, 23955-6900, Saudi Arabia
| | - Upendra Singh
- King Abdullah University of Science and Technology (KAUST), Biological and Environmental and Science and Engineering, Thuwal, 23955-6900, Saudi Arabia
| | - Mariusz Jaremko
- King Abdullah University of Science and Technology (KAUST), Biological and Environmental and Science and Engineering, Thuwal, 23955-6900, Saudi Arabia
| | - Susana Agusti
- King Abdullah University of Science and Technology (KAUST), Biological and Environmental and Science and Engineering, Marine Science Program, Thuwal, 23955-6900, Saudi Arabia
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Wang X, Peng R, Zhao L. Multiscale metabolomics techniques: Insights into neuroscience research. Neurobiol Dis 2024; 198:106541. [PMID: 38806132 DOI: 10.1016/j.nbd.2024.106541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Revised: 05/21/2024] [Accepted: 05/23/2024] [Indexed: 05/30/2024] Open
Abstract
The field of metabolomics examines the overall composition and dynamic patterns of metabolites in living organisms. The primary methods used in metabolomics include liquid chromatography (LC), nuclear magnetic resonance (NMR), and mass spectrometry (MS) analysis. These methods enable the identification and examination of metabolite types and contents within organisms, as well as modifications to metabolic pathways and their connection to the emergence of diseases. Research in metabolomics has extensive value in basic and applied sciences. The field of metabolomics is growing quickly, with the majority of studies concentrating on biomedicine, particularly early disease diagnosis, therapeutic management of human diseases, and mechanistic knowledge of biochemical processes. Multiscale metabolomics is an approach that integrates metabolomics techniques at various scales, including the holistic, tissue, cellular, and organelle scales, to enable more thorough and in-depth studies of metabolic processes in organisms. Multiscale metabolomics can be combined with methods from systems biology and bioinformatics. In recent years, multiscale metabolomics approaches have become increasingly important in neuroscience research due to the nervous system's high metabolic demands. Multiscale metabolomics can offer novel concepts and approaches for the diagnosis, treatment, and development of medication for neurological illnesses in addition to a more thorough understanding of brain metabolism and nervous system function. In this review, we summarize the use of multiscale metabolomics techniques in neuroscience, address the promise and constraints of these techniques, and provide an overview of the metabolome and its applications in neuroscience.
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Affiliation(s)
- Xiaoya Wang
- Beijing Institute of Radiation Medicine, Beijing 100850, China
| | - Ruiyun Peng
- Beijing Institute of Radiation Medicine, Beijing 100850, China.
| | - Li Zhao
- Beijing Institute of Radiation Medicine, Beijing 100850, China.
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Zolkeflee NKZ, Wong PL, Maulidiani M, Ramli NS, Azlan A, Mediani A, Tham CL, Abas F. Revealing metabolic and biochemical variations via 1H NMR metabolomics in streptozotocin-nicotinamide-induced diabetic rats treated with metformin. Biochem Biophys Res Commun 2024; 708:149778. [PMID: 38507867 DOI: 10.1016/j.bbrc.2024.149778] [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: 12/14/2023] [Revised: 03/03/2024] [Accepted: 03/11/2024] [Indexed: 03/22/2024]
Abstract
The increasing prevalence of lean diabetes has prompted the generation of animal models that mimic metabolic disease in humans. This study aimed to determine the optimum streptozotocin-nicotinamide (STZ-NA) dosage ratio to elicit lean diabetic features in a rat model. It also used a proton nuclear magnetic resonance (1H NMR) urinary metabolomics approach to identify the metabolic effect of metformin treatment on this novel rat model. Three different STZ-NA dosage regimens (by body weight: Group A: 110 mg/kg NA and 45 mg/kg STZ; Group B: 180 mg/kg NA and 65 mg/kg STZ and Group C: 120 mg/kg NA and 60 mg/kg STZ) were administered to Sprague-Dawley rats along with oral metformin. Group A diabetic rats (A-DC) showed favorable serum biochemical analyses and a more positive response toward oral metformin administration relative to the other STZ-NA dosage ratio groups. Orthogonal partial least squares-discriminant analysis (OPLS-DA) revealed that glucose, citrate, pyruvate, hippurate, and methylnicotinamide differentiating the OPLS-DA of A-MTF rats (Group A diabetic rats treated with metformin) and A-DC model rats. Subsequent metabolic pathway analyses revealed that metformin treatment was associated with improvement in dysfunctions caused by STZ-NA induction, including carbohydrate metabolism, cofactor metabolism, and vitamin and amino acid metabolism. In conclusion, our results identify the best STZ-NA dosage ratio for a rat model to exhibit lean type 2 diabetic features with optimum sensitivity to metformin treatment. The data presented here could be informative to improve our understanding of non-obese diabetes in humans through the identification of possible activated metabolic pathways in the STZ-NA-induced diabetic rats model.
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Affiliation(s)
- Nur Khaleeda Zulaikha Zolkeflee
- Natural Medicines and Products Research Laboratory, Institute of Bioscience, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - Pei Lou Wong
- Department of Food Science, Faculty of Food Science and Technology, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - M Maulidiani
- School of Fundamental Science, Universiti Malaysia Terengganu, Kuala Nerus, Terengganu, Malaysia
| | - Nurul Shazini Ramli
- Department of Food Science, Faculty of Food Science and Technology, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - Azrina Azlan
- Department of Nutrition and Dietetics, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - Ahmed Mediani
- Metabolomics Research Laboratory, Institute of Systems Biology (INBIOSIS), Universiti Kebangsaan Malaysia, Bangi, Malaysia
| | - Chau Ling Tham
- Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Selangor, Malaysia
| | - Faridah Abas
- Natural Medicines and Products Research Laboratory, Institute of Bioscience, Universiti Putra Malaysia, Serdang, Selangor, Malaysia; Department of Food Science, Faculty of Food Science and Technology, Universiti Putra Malaysia, Serdang, Selangor, Malaysia.
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Nováková S, Baranovičová E, Hatoková Z, Beke G, Pálešová J, Záhumenská R, Baďurová B, Janíčková M, Strnádel J, Halašová E, Škovierová H. Comparison of Various Extraction Approaches for Optimized Preparation of Intracellular Metabolites from Human Mesenchymal Stem Cells and Fibroblasts for NMR-Based Study. Metabolites 2024; 14:268. [PMID: 38786745 PMCID: PMC11122815 DOI: 10.3390/metabo14050268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 05/02/2024] [Accepted: 05/03/2024] [Indexed: 05/25/2024] Open
Abstract
Metabolomics has proven to be a sensitive tool for monitoring biochemical processes in cell culture. It enables multi-analysis, clarifying the correlation between numerous metabolic pathways. Together with other analysis, it thus provides a global view of a cell's physiological state. A comprehensive analysis of molecular changes is also required in the case of mesenchymal stem cells (MSCs), which currently represent an essential portion of cells used in regenerative medicine. Reproducibility and correct measurement are closely connected to careful metabolite extraction, and sample preparation is always a critical point. Our study aimed to compare the efficiencies of four harvesting and six extraction methods. Several organic reagents (methanol, ethanol, acetonitrile, methanol-chloroform, MTBE) and harvesting approaches (trypsinization vs. scraping) were tested. We used untargeted nuclear magnetic resonance spectroscopy (NMR) to determine the most efficient method for the extraction of metabolites from human adherent cells, specifically human dermal fibroblasts adult (HDFa) and dental pulp stem cells (DPSCs). A comprehensive dataset of 29 identified and quantified metabolites were determined to possess statistically significant differences in the abundances of several metabolites when the cells were detached mechanically to organic solvent compared to when applying enzymes mainly in the classes of amino acids and peptides for both types of cells. Direct scraping to organic solvent is a method that yields higher abundances of determined metabolites. Extraction with the use of different polar reagents, 50% and 80% methanol, or acetonitrile, mostly showed the same quality. For both HDFa and DPSC cells, the MTBE method, methanol-chloroform, and 80% ethanol extractions showed higher extraction efficiency for the most identified and quantified metabolites Thus, preparation procedures provided a cell sample processing protocol that focuses on maximizing extraction yield. Our approach may be useful for large-scale comparative metabolomic studies of human mesenchymal stem cell samples.
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Affiliation(s)
- Slavomíra Nováková
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava (JFM CU), Malá Hora 4C, 036 01 Martin, Slovakia; (S.N.); (Z.H.); (J.P.); (R.Z.); (J.S.); (E.H.); (H.Š.)
| | - Eva Baranovičová
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava (JFM CU), Malá Hora 4C, 036 01 Martin, Slovakia; (S.N.); (Z.H.); (J.P.); (R.Z.); (J.S.); (E.H.); (H.Š.)
| | - Zuzana Hatoková
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava (JFM CU), Malá Hora 4C, 036 01 Martin, Slovakia; (S.N.); (Z.H.); (J.P.); (R.Z.); (J.S.); (E.H.); (H.Š.)
| | - Gábor Beke
- Institute of Molecular Biology, Slovak Academy of Sciences, Dúbravská Cesta 21, 845 51 Bratislava, Slovakia;
| | - Janka Pálešová
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava (JFM CU), Malá Hora 4C, 036 01 Martin, Slovakia; (S.N.); (Z.H.); (J.P.); (R.Z.); (J.S.); (E.H.); (H.Š.)
| | - Romana Záhumenská
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava (JFM CU), Malá Hora 4C, 036 01 Martin, Slovakia; (S.N.); (Z.H.); (J.P.); (R.Z.); (J.S.); (E.H.); (H.Š.)
| | - Bibiána Baďurová
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava (JFM CU), Malá Hora 4C, 036 01 Martin, Slovakia; (S.N.); (Z.H.); (J.P.); (R.Z.); (J.S.); (E.H.); (H.Š.)
| | - Mária Janíčková
- Department of Stomatology and Maxillofacial Surgery, University Hospital in Martin and JFM CU, Kollárova 2, 036 01 Martin, Slovakia;
| | - Ján Strnádel
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava (JFM CU), Malá Hora 4C, 036 01 Martin, Slovakia; (S.N.); (Z.H.); (J.P.); (R.Z.); (J.S.); (E.H.); (H.Š.)
| | - Erika Halašová
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava (JFM CU), Malá Hora 4C, 036 01 Martin, Slovakia; (S.N.); (Z.H.); (J.P.); (R.Z.); (J.S.); (E.H.); (H.Š.)
| | - Henrieta Škovierová
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava (JFM CU), Malá Hora 4C, 036 01 Martin, Slovakia; (S.N.); (Z.H.); (J.P.); (R.Z.); (J.S.); (E.H.); (H.Š.)
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Procopio N, Bonicelli A. From flesh to bones: Multi-omics approaches in forensic science. Proteomics 2024:e2200335. [PMID: 38683823 DOI: 10.1002/pmic.202200335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Revised: 03/12/2024] [Accepted: 03/26/2024] [Indexed: 05/02/2024]
Abstract
Recent advancements in omics techniques have revolutionised the study of biological systems, enabling the generation of high-throughput biomolecular data. These innovations have found diverse applications, ranging from personalised medicine to forensic sciences. While the investigation of multiple aspects of cells, tissues or entire organisms through the integration of various omics approaches (such as genomics, epigenomics, metagenomics, transcriptomics, proteomics and metabolomics) has already been established in fields like biomedicine and cancer biology, its full potential in forensic sciences remains only partially explored. In this review, we have presented a comprehensive overview of state-of-the-art analytical platforms employed in omics research, with specific emphasis on their application in the forensic field for the identification of the cadaver and the cause of death. Moreover, we have conducted a critical analysis of the computational integration of omics approaches, and highlighted the latest advancements in employing multi-omics techniques for forensic investigations.
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Affiliation(s)
- Noemi Procopio
- Research Centre for Field Archaeology and Experimental Taphonomy, School of Law and Policing, University of Central Lancashire, Preston, UK
| | - Andrea Bonicelli
- Research Centre for Field Archaeology and Experimental Taphonomy, School of Law and Policing, University of Central Lancashire, Preston, UK
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Mascellani Bergo A, Leiss K, Havlik J. Twenty Years of 1H NMR Plant Metabolomics: A Way Forward toward Assessment of Plant Metabolites for Constitutive and Inducible Defenses to Biotic Stress. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2024; 72:8332-8346. [PMID: 38501393 DOI: 10.1021/acs.jafc.3c09362] [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: 03/20/2024]
Abstract
Metabolomics has become an important tool in elucidating the complex relationship between a plant genotype and phenotype. For over 20 years, nuclear magnetic resonance (NMR) spectroscopy has been known for its robustness, quantitative capabilities, simplicity, and cost-efficiency. 1H NMR is the method of choice for analyzing a broad range of relatively abundant metabolites, which can be used for both capturing the plant chemical profile at one point in time and understanding the pathways that underpin plant defense. This systematic Review explores how 1H NMR-based plant metabolomics has contributed to understanding the role of various compounds in plant responses to biotic stress, focusing on both primary and secondary metabolites. It clarifies the challenges and advantages of using 1H NMR in plant metabolomics, interprets common trends observed, and suggests guidelines for method development and establishing standard procedures.
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Affiliation(s)
- Anna Mascellani Bergo
- Department of Food Science, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, 16500 Prague, Czechia
| | - Kirsten Leiss
- Business Unit Greenhouse Horticulture, Wageningen University & Research, 2665MV Bleiswijk, Netherlands
| | - Jaroslav Havlik
- Department of Food Science, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, 16500 Prague, Czechia
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Zniber M, Lamminen T, Taimen P, Boström PJ, Huynh TP. 1H-NMR-based urine metabolomics of prostate cancer and benign prostatic hyperplasia. Heliyon 2024; 10:e28949. [PMID: 38617934 PMCID: PMC11015411 DOI: 10.1016/j.heliyon.2024.e28949] [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: 12/30/2023] [Revised: 03/27/2024] [Accepted: 03/27/2024] [Indexed: 04/16/2024] Open
Abstract
Background Prostate cancer (PCa) and benign prostatic hyperplasia (BPH) are prevalent conditions affecting a significant portion of the male population, particularly with advancing age. Traditional diagnostic methods, such as digital rectal examination (DRE) and prostate-specific antigen (PSA) tests, have limitations in specificity and sensitivity, leading to potential overdiagnosis and unnecessary biopsies. Significance This study explores the effectiveness of 1H NMR urine metabolomics in distinguishing PCa from BPH and in differentiating various PCa grades, presenting a non-invasive diagnostic alternative with the potential to enhance early detection and patient-specific treatment strategies. Results The study demonstrated the capability of 1H NMR urine metabolomics in detecting distinct metabolic profiles between PCa and BPH, as well as among different Gleason grade groups. Notably, this method surpassed the PSA test in distinguishing PCa from BPH. Untargeted metabolomics analysis also revealed several metabolites with varying relative concentrations between PCa and BPH cases, suggesting potential biomarkers for these conditions.
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Affiliation(s)
- Mohammed Zniber
- Laboratory of Molecular Science and Engineering, Åbo Akademi University, Turku, Finland
| | - Tarja Lamminen
- Department of Urology, University of Turku and Turku University Hospital, Turku, Finland
| | - Pekka Taimen
- Institute of Biomedicine and FICAN West Cancer Centre, University of Turku and Department of Pathology, Turku University Hospital, Turku, Finland
| | - Peter J. Boström
- Department of Urology, University of Turku and Turku University Hospital, Turku, Finland
| | - Tan-Phat Huynh
- Laboratory of Molecular Science and Engineering, Åbo Akademi University, Turku, Finland
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Ge Y, Zhou C, Ma Y, Wang Z, Wang S, Wang W, Wu B. Advancing Natural Product Discovery: A Structure-Oriented Fractions Screening Platform for Compound Annotation and Isolation. Anal Chem 2024; 96:5399-5406. [PMID: 38523322 DOI: 10.1021/acs.analchem.3c05057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/26/2024]
Abstract
Natural product discovery is hindered by the lack of tools that integrate untargeted nuclear magnetic resonance and mass spectrometry data on a library scale. This article describes the first application of the innovative NMR/MS-based machine learning tool, the "Structure-Oriented Fractions Screening Platform (SFSP)", enabling functional-group-guided fractionation and accelerating the discovery and characterization of undescribed natural products. The concept was applied to the extract of a marine fungus known to be a prolific producer of diverse natural products. With the assistance of SFSP, we isolated 24 flavipidin derivatives and five phenalenone analogues from Aspergillus sp. GE2-6, revealing 27 undescribed compounds. Compounds 7-22 were proposed as isomeric derivatives featuring a 5/6-ring fusion, formed by the dimerization of flavipidin E (5). Compounds 23 and 24 were envisaged as isomeric derivatives with a 6/5/6-ring fusion, generated through the degradation of two flavipidin E molecules. Furthermore, flavipidin A (1) and asperphenalenone E (28) exhibited potent anti-influenza (PR8) activities, with IC50 values of 21.9 ± 0.2 and 12.9 ± 0.1 μM, respectively. Meanwhile, asperphenalenone (26) and asperphenalenone P (27) treatments exhibited significant inhibition of HIV pseudovirus infection in 293FT cells, boasting IC50 values of 6.1 ± 0.9 and 4.6 ± 1.1 μM, respectively. Overall, SFSP streamlines natural product isolation through NMR and MS data integration, as showcased by the discovery of numerous undescribed flavipidins and phenalenones based on NMR olefinic signals and low-field hydroxy signals.
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Affiliation(s)
- Yichao Ge
- Ocean College, Zhejiang University, Zhoushan 321000, China
- College of Pharmaceutical Sciences, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Chengzeng Zhou
- Ocean College, Zhejiang University, Zhoushan 321000, China
| | - Yihan Ma
- Ocean College, Zhejiang University, Zhoushan 321000, China
| | - Zihan Wang
- School of Medicine and Pharmacy, Ocean University of China, Qingdao 266003, China
| | - Shufan Wang
- School of Mathematical Sciences, The University of Adelaide, Adelaide, South Australia 5005, Australia
| | - Wei Wang
- School of Medicine and Pharmacy, Ocean University of China, Qingdao 266003, China
| | - Bin Wu
- Ocean College, Zhejiang University, Zhoushan 321000, China
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Chen J, Li Y, Gu X, Wu T, Du H, Bai C, Yang J, Hu K. Identifying Anti-NSCLC Bioactive Compounds in Scutellaria via 2D NMR-Based Metabolomic Analysis of Pharmacologically Classified Crude Extracts. Chem Biodivers 2024:e202400258. [PMID: 38581076 DOI: 10.1002/cbdv.202400258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 03/03/2024] [Accepted: 04/05/2024] [Indexed: 04/07/2024]
Abstract
We presented a strategy utilizing 2D NMR-based metabolomic analysis of crude extracts, categorized by different pharmacological activities, to rapidly identify the primary bioactive components of TCM. It was applied to identify the potential bioactive components from Scutellaria crude extracts that exhibit anti-non-small cell lung cancer (anti-NSCLC) activity. Four Scutellaria species were chosen as the study subjects because of their close phylogenetic relationship, but their crude extracts exhibit significantly different anti-NSCLC activity. Cell proliferation assay was used to assess the anti-NSCLC activity of four species of Scutellaria. 1H-13C HSQC spectra were acquired for the chemical profiling of these crude extracts. Based on the pharmacological classification (PCA, OPLS-DA and univariate hypothesis test) were performed to identify the bioactive constituents in Scutellaria associated with the anti-NSCLC activity. As a result, three compounds, baicalein, wogonin and scutellarin were identified as bioactive compounds. The anti-NSCLC activity of the three potential active compounds were further confirmed via cell proliferation assay. The mechanism of the anti-NSCLC activity by these active constituents was further explored via flow cytometry and western blot analyses. This study demonstrated 2D NMR-based metabolomic analysis of pharmacologically classified crude extracts to be an efficient approach to the identification of active components of herbal medicine.
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Affiliation(s)
- Jialuo Chen
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, China
- School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 611137, China
| | - Yanping Li
- School of Basic Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, No.1166 Liutai Avenue, Chengdu, Sichuan, 611137, China Tel
| | - Xiu Gu
- Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, No.1166 Liutai Avenue, Chengdu, Sichuan, 611137, China
| | - Tianren Wu
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, China
- School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 611137, China
| | - Huan Du
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, China
- School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 611137, China
| | - Caihong Bai
- School of Basic Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, No.1166 Liutai Avenue, Chengdu, Sichuan, 611137, China Tel
| | - Jiahui Yang
- School of Basic Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, No.1166 Liutai Avenue, Chengdu, Sichuan, 611137, China Tel
| | - Kaifeng Hu
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, China
- Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, No.1166 Liutai Avenue, Chengdu, Sichuan, 611137, China
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12
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Razavi SA, Khorsand B, Salehipour P, Hedayati M. Metabolite signature of human malignant thyroid tissue: A systematic review and meta-analysis. Cancer Med 2024; 13:e7184. [PMID: 38646957 PMCID: PMC11033922 DOI: 10.1002/cam4.7184] [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: 08/19/2023] [Revised: 02/13/2024] [Accepted: 03/26/2024] [Indexed: 04/25/2024] Open
Abstract
BACKGROUND Thyroid cancer (TC) is the predominant malignancy within the endocrine system. However, the standard method for TC diagnosis lacks the capability to identify the pathological condition of all thyroid lesions. The metabolomics approach has the potential to manage this problem by identifying differential metabolites. AIMS This study conducted a systematic review and meta-analysis of the NMR-based metabolomics studies in order to identify significant altered metabolites associated with TC. METHODS A systematic search of published literature in any language in three databases including Embase, PubMed, and Scopus was conducted. Out of 353 primary articles, 12 studies met the criteria for inclusion in the systematic review. Among these, five reports belonging to three articles were eligible for meta-analysis. The correlation coefficient of the orthogonal partial least squares discriminant analysis, a popular model in the multivariate statistical analysis of metabolomic data, was chosen for meta-analysis. The altered metabolites were chosen based on the fact that they had been found in at least three studies. RESULTS In total, 49 compounds were identified, 40 of which were metabolites. The increased metabolites in thyroid lesions compared normal samples included lactate, taurine, alanine, glutamic acid, glutamine, leucine, lysine, phenylalanine, serine, tyrosine, valine, choline, glycine, and isoleucine. Lipids were the decreased compounds in thyroid lesions. Lactate and alanine were increased in malignant versus benign thyroid lesions, while, myo-inositol, scyllo-inositol, citrate, choline, and phosphocholine were found to be decreased. The meta-analysis yielded significant results for three metabolites of lactate, alanine, and citrate in malignant versus benign specimens. DISCUSSION In this study, we provided a concise summary of 12 included metabolomic studies, making it easier for future researchers to compare their results with the prior findings. CONCLUSION It appears that the field of TC metabolomics will experience notable advancement, leading to the discovery of trustworthy diagnostic and prognostic biomarkers.
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Affiliation(s)
- S. Adeleh Razavi
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine SciencesShahid Beheshti University of Medical SciencesTehranIran
| | - Babak Khorsand
- Department of NeurologyUniversity of CaliforniaIrvineCaliforniaUSA
- Department of Computer Engineering, Faculty of EngineeringFerdowsi University of MashhadMashhadIran
| | - Pouya Salehipour
- Department of Medical Genetics, School of MedicineTehran University of Medical SciencesTehranIran
| | - Mehdi Hedayati
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine SciencesShahid Beheshti University of Medical SciencesTehranIran
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Salem MB, El-Lakkany NM, Seif el-Din SH, Hammam OA, Samir S. Diosmin alleviates ulcerative colitis in mice by increasing Akkermansia muciniphila abundance, improving intestinal barrier function, and modulating the NF-κB and Nrf2 pathways. Heliyon 2024; 10:e27527. [PMID: 38500992 PMCID: PMC10945203 DOI: 10.1016/j.heliyon.2024.e27527] [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: 11/01/2023] [Revised: 02/29/2024] [Accepted: 03/01/2024] [Indexed: 03/20/2024] Open
Abstract
Ulcerative colitis is a common type of inflammatory bowel disease that affects millions of individuals around the world. Traditional UC treatment has focused on suppressing immune responses rather than treating the underlying causes of UC, which include oxidative stress, inflammation, and microbiota dysbiosis. Diosmin (DIO), a naturally occurring flavonoid, possesses antioxidant and anti-inflammatory properties. This study aimed to assess the efficacy of DIO in treating dextran-sulfate sodium (DSS)-induced colitis, and to investigate some of its underlying mechanisms, with an emphasis on Akkermansia muciniphila abundance, inflammatory markers, and intestinal barrier function. C57BL/6 mice were given 4% (w/v) DSS to induce colitis. DSS-induced mice were administered DIO (100 and 200 mg/kg) or sulfasalazine orally for 7 days. Every day, the disease activity index (DAI) was determined by recording body weight, diarrhea, and bloody stool. Changes in fecal A. muciniphila abundance, colonic MUC1 and MUC2 expression, as well as oxidative stress and inflammatory markers were all assessed. Histopathological changes, colonic PIK3PR3 and ZO-1 levels, and immunohistochemical examinations of occludin and claudin-1, were investigated. DIO administration resulted in a dose-dependent decrease in DAI, as well as increase in A. muciniphila abundance and MUC2 expression while decreasing MUC1 expression. DIO also dramatically reduced colonic oxidative stress and inflammation by regulating the NF-κB and Nrf2 cascades, restored intestinal barrier integrity by inhibiting PIK3R3 and inducing ZO-1, and improved occludin/claudin-1 gene expression and immunostaining. This study provides the first evidence that DIO preserves intestinal barrier integrity and increases A. muciniphila abundance in DSS-induced colitis. However, more research is required to explore the impact of DIO on the overall composition and diversity of the gut microbiota. Likewise, it will be important to fully understand the molecular mechanisms by which A. muciniphila maintains intestinal barrier function and its potential use as an adjuvant in the treatment of UC.
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Affiliation(s)
- Maha Badr Salem
- Department of Pharmacology, Theodor Bilharz Research Institute, Warrak El-Hadar, Imbaba, Giza, 12411, Egypt
| | - Naglaa Mohamed El-Lakkany
- Department of Pharmacology, Theodor Bilharz Research Institute, Warrak El-Hadar, Imbaba, Giza, 12411, Egypt
| | - Sayed Hassan Seif el-Din
- Department of Pharmacology, Theodor Bilharz Research Institute, Warrak El-Hadar, Imbaba, Giza, 12411, Egypt
| | - Olfat Ali Hammam
- Department of Pathology, Theodor Bilharz Research Institute, Warrak El-Hadar, Imbaba, Giza, 12411, Egypt
| | - Safia Samir
- Department of Biochemistry and Molecular Biology, Theodor Bilharz Research Institute, Warrak El-Hadar, Imbaba, Giza, 12411, Egypt
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14
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Jiang T, Zhou Q, Yu KK, Chen SY, Li K. Identification and quantification of N6-methyladenosine by chemical derivatization coupled with 19F NMR spectroscopy. Org Biomol Chem 2024; 22:2566-2573. [PMID: 38465392 DOI: 10.1039/d4ob00169a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
N 6-Methyladenosine (6mA) is a well-known prokaryotic DNA modification that has been shown to play epigenetic roles in eukaryotic DNA. Accurate detection and quantification of 6mA are prerequisites for molecular understanding of the impact of 6mA modification on DNA. However, the existing methods have several problems, such as high false-positive rate, time-consuming and complex operating procedures. Chemical sensors for the selective detection of 6mA modification are rarely reported in the literature. Fluorinated phenylboronic acid combined with 19F NMR analysis is an effective method for determining DNA or RNA modification. In this study, we presented a simple and fast chemical method for labelling the 6th imino group of 6mA using a boric-acid-derived probe. Besides, the trifluoromethyl group of trifluoromethyl phenylboronic acid (2a) could detect 6mA modification through 19F NMR. Combined with this sensor system, 6mA modification could be detected well and quickly in 6 types of deoxynucleoside mixtures and DNA samples. Taken together, the method developed in the current study has potential for specific detection of 6mA in biological samples.
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Affiliation(s)
- Ting Jiang
- Key Laboratory of Green Chemistry and Technology (Ministry of Education), College of Chemistry, Sichuan University, Chengdu 610064, P. R. China.
| | - Qian Zhou
- Department of Chemistry, Xihua University, Chengdu 610039, P. R. China
| | - Kang-Kang Yu
- Key Laboratory of Green Chemistry and Technology (Ministry of Education), College of Chemistry, Sichuan University, Chengdu 610064, P. R. China.
| | - Shan-Yong Chen
- Key Laboratory of Green Chemistry and Technology (Ministry of Education), College of Chemistry, Sichuan University, Chengdu 610064, P. R. China.
| | - Kun Li
- Key Laboratory of Green Chemistry and Technology (Ministry of Education), College of Chemistry, Sichuan University, Chengdu 610064, P. R. China.
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15
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Wang X, Guo AQ, Wang R, Gao W, Yang H. AnnoSM: An Automated Annotation Tool for Determining the Substituent Modes on the Parent Skeleton Based on a Characteristic MS/MS Fragment Ion Library. Anal Chem 2024; 96:3817-3828. [PMID: 38386850 DOI: 10.1021/acs.analchem.3c04946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2024]
Abstract
Mass spectrometry (MS) is a powerful technology for the structural elucidation of known or unknown small molecules. However, the accuracy of MS-based structure annotation is still limited due to the presence of numerous isomers in complex matrices. There are still challenges in automatically interpreting the fine structure of molecules, such as the types and positions of substituents (substituent modes, SMs) in the structure. In this study, we employed flavones, flavonols, and isoflavones as examples to develop an automated annotation method for identifying the SMs on the parent molecular skeleton based on a characteristic MS/MS fragment ion library. Importantly, user-friendly software AnnoSM was built for the convenience of researchers with limited computational backgrounds. It achieved 76.87% top-1 accuracy on the 148 authentic standards. Among them, 22 sets of flavonoid isomers were successfully differentiated. Moreover, the developed method was successfully applied to complex matrices. One such example is the extract of Ginkgo biloba L. (EGB), in which 331 possible flavonoids with SM candidates were annotated. Among them, 23 flavonoids were verified by authentic standards. The correct SMs of 13 flavonoids were ranked first on the candidate list. In the future, this software can also be extrapolated to other classes of compounds.
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Affiliation(s)
- Xing Wang
- State Key Laboratory of Natural Medicines, China Pharmaceutical University, No. 639 Longmian Dadao, Nanjing 211198, China
| | - An-Qi Guo
- State Key Laboratory of Natural Medicines, China Pharmaceutical University, No. 639 Longmian Dadao, Nanjing 211198, China
| | - Rui Wang
- State Key Laboratory of Natural Medicines, China Pharmaceutical University, No. 639 Longmian Dadao, Nanjing 211198, China
| | - Wen Gao
- State Key Laboratory of Natural Medicines, China Pharmaceutical University, No. 639 Longmian Dadao, Nanjing 211198, China
| | - Hua Yang
- State Key Laboratory of Natural Medicines, China Pharmaceutical University, No. 639 Longmian Dadao, Nanjing 211198, China
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16
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Gentile A, Fulgione A, Auzino B, Iovane V, Gallo D, Garramone R, Iaccarino N, Randazzo A, Iovane G, Cuomo P, Capparelli R, Iannelli D. In vivo biological validation of in silico analysis: A novel approach for predicting the effects of TLR4 exon 3 polymorphisms on brucellosis. INFECTION, GENETICS AND EVOLUTION : JOURNAL OF MOLECULAR EPIDEMIOLOGY AND EVOLUTIONARY GENETICS IN INFECTIOUS DISEASES 2024; 118:105552. [PMID: 38218390 DOI: 10.1016/j.meegid.2024.105552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 01/09/2024] [Accepted: 01/10/2024] [Indexed: 01/15/2024]
Abstract
The role of the Toll-like receptor 4 (TLR4) is of recognising intracellular and extracellular pathogens and of activating the immune response. This process can be compromised by single nucleotide polymorphisms (SNPs) which might affect the activity of several TLRs. The aim of this study is of ascertaining whether SNPs in the TLR4 of Bubalus bubalis infected by Brucella abortus, compromise the protein functionality. For this purpose, a computational analysis was performed. Next, computational predictions were confirmed by performing genotyping analysis. Finally, NMR-based metabolomics analysis was performed to identify potential biomarkers for brucellosis. The results indicate two SNPs (c. 672 A > C and c. 902 G > C) as risk factor for brucellosis in Bubalus bubalis, and three metabolites (lactate, 3-hydroxybutyrate and acetate) as biological markers for predicting the risk of developing the disease. These metabolites, together with TLR4 structural modifications in the MD2 interaction domain, are a clear signature of the immune system alteration during diverse Gram-negative bacterial infections. This suggests the possibility to extend this study to other pathogens, including Mycobacterium tuberculosis. In conclusion, this study combines multidisciplinary approaches to evaluate the biological and structural effects of SNPs on protein function.
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Affiliation(s)
- Antonio Gentile
- Department of Agricultural Sciences, University of Naples Federico II, Portici, Naples 80055, Italy
| | - Andrea Fulgione
- Department of Agricultural Sciences, University of Naples Federico II, Portici, Naples 80055, Italy
| | - Barbara Auzino
- Department of Agricultural Sciences, University of Naples Federico II, Portici, Naples 80055, Italy
| | - Valentina Iovane
- Department of Agricultural Sciences, University of Naples Federico II, Portici, Naples 80055, Italy
| | - Daniela Gallo
- Department of Agricultural Sciences, University of Naples Federico II, Portici, Naples 80055, Italy
| | - Raffaele Garramone
- Department of Agricultural Sciences, University of Naples Federico II, Portici, Naples 80055, Italy
| | - Nunzia Iaccarino
- Department of Pharmacy, University of Naples Federico II, Naples 80131, Italy
| | - Antonio Randazzo
- Department of Pharmacy, University of Naples Federico II, Naples 80131, Italy
| | - Giuseppe Iovane
- Department of Veterinary Medicine and Animal Productions, University of Naples Federico II, Naples 80137, Italy
| | - Paola Cuomo
- Department of Agricultural Sciences, University of Naples Federico II, Portici, Naples 80055, Italy
| | - Rosanna Capparelli
- Department of Agricultural Sciences, University of Naples Federico II, Portici, Naples 80055, Italy.
| | - Domenico Iannelli
- Department of Agricultural Sciences, University of Naples Federico II, Portici, Naples 80055, Italy
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17
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Flores AC, Zhang X, Kris-Etherton PM, Sliwinski MJ, Shearer GC, Gao X, Na M. Metabolomics and Risk of Dementia: A Systematic Review of Prospective Studies. J Nutr 2024; 154:826-845. [PMID: 38219861 DOI: 10.1016/j.tjnut.2024.01.012] [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: 10/31/2023] [Revised: 01/05/2024] [Accepted: 01/10/2024] [Indexed: 01/16/2024] Open
Abstract
BACKGROUND The projected increase in the prevalence of dementia has sparked interest in understanding the pathophysiology and underlying causal factors in its development and progression. Identifying novel biomarkers in the preclinical or prodromal phase of dementia may be important for predicting early disease risk. Applying metabolomic techniques to prediagnostic samples in prospective studies provides the opportunity to identify potential disease biomarkers. OBJECTIVE The objective of this systematic review was to summarize the evidence on the associations between metabolite markers and risk of dementia and related dementia subtypes in human studies with a prospective design. DESIGN We searched PubMed, PsycINFO, and Web of Science databases from inception through December 8, 2023. Thirteen studies (mean/median follow-up years: 2.1-21.0 y) were included in the review. RESULTS Several metabolites detected in biological samples, including amino acids, fatty acids, acylcarnitines, lipid and lipoprotein variations, hormones, and other related metabolites, were associated with risk of developing dementia. Our systematic review summarized the adjusted associations between metabolites and dementia risk; however, our findings should be interpreted with caution because of the heterogeneity across the included studies and potential sources of bias. Further studies are warranted with well-designed prospective cohort studies that have defined study populations, longer follow-up durations, the inclusion of additional diverse biological samples, standardization of techniques in metabolomics and ascertainment methods for diagnosing dementia, and inclusion of other related dementia subtypes. CONCLUSIONS This study contributes to the limited systematic reviews on metabolomics and dementia by summarizing the prospective associations between metabolites in prediagnostic biological samples with dementia risk. Our review discovered additional metabolite markers associated with the onset of developing dementia and may help aid in the understanding of dementia etiology. The protocol is registered in the International Prospective Register of Systematic Reviews (PROSPERO) database (https://www.crd.york.ac.uk/prospero/; registration ID: CRD42022357521).
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Affiliation(s)
- Ashley C Flores
- Department of Nutritional Sciences, The Pennsylvania State University, University Park, PA, United States
| | - Xinyuan Zhang
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States
| | - Penny M Kris-Etherton
- Department of Nutritional Sciences, The Pennsylvania State University, University Park, PA, United States
| | - Martin J Sliwinski
- Center for Healthy Aging, The Pennsylvania State University, University Park, PA, United States; Department of Human Development and Family Studies, The Pennsylvania State University, University Park, PA, United States
| | - Greg C Shearer
- Department of Nutritional Sciences, The Pennsylvania State University, University Park, PA, United States
| | - Xiang Gao
- School of Public Health, Institute of Nutrition, Fudan University, Shanghai, China.
| | - Muzi Na
- Department of Nutritional Sciences, The Pennsylvania State University, University Park, PA, United States.
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18
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Kumari M, Yagnik KN, Gupta V, Singh IK, Gupta R, Verma PK, Singh A. Metabolomics-driven investigation of plant defense response against pest and pathogen attack. PHYSIOLOGIA PLANTARUM 2024; 176:e14270. [PMID: 38566280 DOI: 10.1111/ppl.14270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 02/27/2024] [Accepted: 02/29/2024] [Indexed: 04/04/2024]
Abstract
The advancement of metabolomics has assisted in the identification of various bewildering characteristics of the biological system. Metabolomics is a standard approach, facilitating crucial aspects of system biology with absolute quantification of metabolites using minimum samples, based on liquid/gas chromatography, mass spectrometry and nuclear magnetic resonance. The metabolome profiling has narrowed the wide gaps of missing information and has enhanced the understanding of a wide spectrum of plant-environment interactions by highlighting the complex pathways regulating biochemical reactions and cellular physiology under a particular set of conditions. This high throughput technique also plays a prominent role in combined analyses of plant metabolomics and other omics datasets. Plant metabolomics has opened a wide paradigm of opportunities for developing stress-tolerant plants, ensuring better food quality and quantity. However, despite advantageous methods and databases, the technique has a few limitations, such as ineffective 3D capturing of metabolites, low comprehensiveness, and lack of cell-based sampling. In the future, an expansion of plant-pathogen and plant-pest response towards the metabolite architecture is necessary to understand the intricacies of plant defence against invaders, elucidation of metabolic pathway operational during defence and developing a direct correlation between metabolites and biotic stresses. Our aim is to provide an overview of metabolomics and its utilities for the identification of biomarkers or key metabolites associated with biotic stress, devising improved diagnostic methods to efficiently assess pest and pathogen attack and generating improved crop varieties with the help of combined application of analytical and molecular tools.
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Affiliation(s)
- Megha Kumari
- Department of Plant Molecular Biology, University of Delhi South Campus, New Delhi, India
- Department of Botany, Hansraj College, University of Delhi, Delhi, India
| | - Kalpesh Nath Yagnik
- Department of Plant Molecular Biology, University of Delhi South Campus, New Delhi, India
- Department of Botany, Hansraj College, University of Delhi, Delhi, India
| | - Vaishali Gupta
- Department of Plant Molecular Biology, University of Delhi South Campus, New Delhi, India
| | - Indrakant K Singh
- Molecular Biology Research Lab, Department of Zoology, Deshbandhu College, University of Delhi, New Delhi, India
| | - Ravi Gupta
- College of General Education, Kookmin University, Seoul, Republic of Korea
| | - Praveen K Verma
- Plant-Immunity Laboratory, School of Life Sciences, Jawaharlal Nehru University, New Delhi, India
| | - Archana Singh
- Department of Plant Molecular Biology, University of Delhi South Campus, New Delhi, India
- Department of Botany, Hansraj College, University of Delhi, Delhi, India
- Delhi School of Climate Change and Sustainability, Institution of Eminence, Maharishi Karnad Bhawan, University of Delhi, India
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19
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An L, Liu H, Li M, Ma J, Zheng L, Zhou J, Zhang J, Yuan Y, Wu X. Unveiling the impact of harvest time on Dioscorea opposita Thunb. cv. Tiegun maturity by NMR-based metabolomics and LC-MS/MS analysis. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2024. [PMID: 38415792 DOI: 10.1002/jsfa.13418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 01/29/2024] [Accepted: 02/25/2024] [Indexed: 02/29/2024]
Abstract
BACKGROUND Dioscorea opposita Thunb. cv. Tiegun maturity (DM) is an important factor influencing its quality. However, there are few studies on the impact of harvest time on its maturation. In the present study, a NMR-based metabolomics approach was applied to investigate the dynamic metabolic changes of D. opposita Thunb. cv. Tiegun at six different harvest stages: stage 1 (S1), stage 2 (S2), Stage 3 (S3), stage 4 (S4), stage 5 (S5) and stage 6 (S6). RESULTS Principal component analysis showed distinct segregation of samples obtained from S1, S2 and S3 compared to those derived from S4, S5 and S6. Interestingly, these samples from the two periods were obtained before and after frost, indicating that frost descent might be important for DM. Eight differential metabolites responsible for good separation of different groups were identified by the principal component analysis loading plot and partial least squares-discriminant analysis. In addition, quantitative analysis of these metabolites using liquid chromatography-tandem mass spectrometry determined the effects of harvest time on these metabolite contents, two of which, sucrose and allantoin, were considered as potential biomarkers to determine DM. CONCLUSION The present study demonstrated that NMR-based metabolomics approach could serve as a powerful tool to identify differential metabolites during harvesting processes, also offering a fresh insight into understanding the DM and the potential mechanism of quality formation. © 2024 Society of Chemical Industry.
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Affiliation(s)
- Li An
- Institute of Quality and Safety for Agro-products, Henan Academy of Agricultural Sciences, Zhengzhou, China
- Key Laboratory of Grain Quality and Safety and Testing Henan Province, Zhengzhou, China
| | - Hao Liu
- International Joint Research Laboratory for Global Change Ecology, School of Life Sciences, Henan University, Kaifeng, China
| | - Meng Li
- Institute of Quality and Safety for Agro-products, Henan Academy of Agricultural Sciences, Zhengzhou, China
- Key Laboratory of Grain Quality and Safety and Testing Henan Province, Zhengzhou, China
| | - Jingwei Ma
- Institute of Quality and Safety for Agro-products, Henan Academy of Agricultural Sciences, Zhengzhou, China
- Key Laboratory of Grain Quality and Safety and Testing Henan Province, Zhengzhou, China
| | - Lufei Zheng
- Institute of Quality Standards and Testing Technology for Agro-products of CAAS, Beijing, China
| | - Juan Zhou
- Institute of Quality and Safety for Agro-products, Henan Academy of Agricultural Sciences, Zhengzhou, China
- Key Laboratory of Grain Quality and Safety and Testing Henan Province, Zhengzhou, China
| | - Junfeng Zhang
- Institute of Quality and Safety for Agro-products, Henan Academy of Agricultural Sciences, Zhengzhou, China
- Key Laboratory of Grain Quality and Safety and Testing Henan Province, Zhengzhou, China
| | - Yongliang Yuan
- Department of Pharmacy, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xujin Wu
- Institute of Quality and Safety for Agro-products, Henan Academy of Agricultural Sciences, Zhengzhou, China
- Key Laboratory of Grain Quality and Safety and Testing Henan Province, Zhengzhou, China
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20
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Liu D, Nagana Gowda GA, Jiang Z, Alemdjrodo K, Zhang M, Zhang D, Raftery D. Modeling blood metabolite homeostatic levels reduces sample heterogeneity across cohorts. Proc Natl Acad Sci U S A 2024; 121:e2307430121. [PMID: 38359289 PMCID: PMC10895372 DOI: 10.1073/pnas.2307430121] [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: 05/06/2023] [Accepted: 12/05/2023] [Indexed: 02/17/2024] Open
Abstract
Blood metabolite levels are affected by numerous factors, including preanalytical factors such as collection methods and geographical sites. These perturbations have caused deleterious consequences for many metabolomics studies and represent a major challenge in the metabolomics field. It is important to understand these factors and develop models to reduce their perturbations. However, to date, the lack of suitable mathematical models for blood metabolite levels under homeostasis has hindered progress. In this study, we develop quantitative models of blood metabolite levels in healthy adults based on multisite sample cohorts that mimic the current challenge. Five cohorts of samples obtained across four geographically distinct sites were investigated, focusing on approximately 50 metabolites that were quantified using 1H NMR spectroscopy. More than one-third of the variation in these metabolite profiles is due to cross-cohort variation. A dramatic reduction in the variation of metabolite levels (90%), especially their site-to-site variation (95%), was achieved by modeling each metabolite using demographic and clinical factors and especially other metabolites, as observed in the top principal components. The results also reveal that several metabolites contribute disproportionately to such variation, which could be explained by their association with biological pathways including biosynthesis and degradation. The study demonstrates an intriguing network effect of metabolites that can be utilized to better define homeostatic metabolite levels, which may have implications for improved health monitoring. As an example of the potential utility of the approach, we show that modeling gender-related metabolic differences retains the interesting variance while reducing unwanted (site-related) variance.
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Affiliation(s)
- Danni Liu
- Department of Statistics, Purdue University, West Lafayette, IN47907
| | - G. A. Nagana Gowda
- Department of Anesthesiology and Pain Medicine, Northwest Metabolomics Research Center, University of Washington, Seattle, WA98109
| | - Zhongli Jiang
- Department of Statistics, Purdue University, West Lafayette, IN47907
| | - Kangni Alemdjrodo
- Department of Statistics, Purdue University, West Lafayette, IN47907
| | - Min Zhang
- Department of Statistics, Purdue University, West Lafayette, IN47907
- Department of Epidemiology and Biostatistics, University of California, Irvine, CA92697
| | - Dabao Zhang
- Department of Statistics, Purdue University, West Lafayette, IN47907
- Department of Epidemiology and Biostatistics, University of California, Irvine, CA92697
| | - Daniel Raftery
- Department of Anesthesiology and Pain Medicine, Northwest Metabolomics Research Center, University of Washington, Seattle, WA98109
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21
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Li W, Zhang X, Wang S, Gao X, Zhang X. Research Progress on Extraction and Detection Technologies of Flavonoid Compounds in Foods. Foods 2024; 13:628. [PMID: 38397605 PMCID: PMC10887530 DOI: 10.3390/foods13040628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Revised: 02/13/2024] [Accepted: 02/14/2024] [Indexed: 02/25/2024] Open
Abstract
Flavonoid compounds have a variety of biological activities and play an essential role in preventing the occurrence of metabolic diseases. However, many structurally similar flavonoids are present in foods and are usually in low concentrations, which increases the difficulty of their isolation and identification. Therefore, developing and optimizing effective extraction and detection methods for extracting flavonoids from food is essential. In this review, we review the structure, classification, and chemical properties of flavonoids. The research progress on the extraction and detection of flavonoids in foods in recent years is comprehensively summarized, as is the application of mathematical models in optimizing experimental conditions. The results provide a theoretical basis and technical support for detecting and analyzing high-purity flavonoids in foods.
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Affiliation(s)
- Wen Li
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang 330013, China
| | - Xiaoping Zhang
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang 330013, China
| | - Shuanglong Wang
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang 330013, China
| | - Xiaofei Gao
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang 330013, China
| | - Xinglei Zhang
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang 330013, China
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22
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Kleine Büning JB, Grimme S, Bursch M. Machine learning-based correction for spin-orbit coupling effects in NMR chemical shift calculations. Phys Chem Chem Phys 2024; 26:4870-4884. [PMID: 38230684 DOI: 10.1039/d3cp05556f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2024]
Abstract
As one of the most powerful analytical methods for molecular and solid-state structure elucidation, NMR spectroscopy is an integral part of chemical laboratories associated with a great research interest in its computational simulation. Particularly when heavy atoms are present, a relativistic treatment is essential in the calculations as these influence also the nearby light atoms. In this work, we present a Δ-machine learning method that approximates the contribution to 13C and 1H NMR chemical shifts that stems from spin-orbit (SO) coupling effects. It is built on computed reference data at the spin-orbit zeroth-order regular approximation (ZORA) DFT level for a set of 6388 structures with 38 740 13C and 64 436 1H NMR chemical shifts. The scope of the methods covers the 17 most important heavy p-block elements that exhibit heavy atom on the light atom (HALA) effects to covalently bound carbon or hydrogen atoms. Evaluated on the test data set, the approach is able to recover roughly 85% of the SO contribution for 13C and 70% for 1H from a scalar-relativistic PBE0/ZORA-def2-TZVP calculation at virtually no extra computational costs. Moreover, the method is transferable to other baseline DFT methods even without retraining the model and performs well for realistic organotin and -lead compounds. Finally, we show that using a combination of the new approach with our previous Δ-ML method for correlation contributions to NMR chemical shifts, the mean absolute NMR shift deviations from non-relativistic DFT calculations to experimental values can be halved.
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Affiliation(s)
- Julius B Kleine Büning
- Mulliken Center for Theoretical Chemistry, Clausius Institute for Physical and Theoretical Chemistry, University of Bonn, Beringstr. 4, 53115 Bonn, Germany.
| | - Stefan Grimme
- Mulliken Center for Theoretical Chemistry, Clausius Institute for Physical and Theoretical Chemistry, University of Bonn, Beringstr. 4, 53115 Bonn, Germany.
| | - Markus Bursch
- Max-Planck-Institut für Kohlenforschung, Kaiser-Wilhelm-Platz 1, 45470 Mülheim an der Ruhr, Germany.
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23
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Tsermoula P, Kristensen NB, Mobaraki N, Engelsen SRB, Khakimov B. Efficient Quantification of Milk Metabolites from 1H NMR Spectra Using the Signature Mapping (SigMa) Approach: Chemical Shift Library Development for Cows' Milk and Colostrum. Anal Chem 2024; 96:1861-1871. [PMID: 38277502 DOI: 10.1021/acs.analchem.3c03449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2024]
Abstract
Cow milk contains essential nutrients for humans, and its bulk composition is usually analyzed using Fourier transform infrared spectroscopy. The higher sensitivity of nuclear magnetic resonance (NMR) spectroscopy can augment the extractible qualitative and quantitative information from milk to nearly 60 compounds, enabling us to monitor the health of cows and milk quality. Proton (1H) NMR spectroscopy produces complex spectra that require expert knowledge for identifying and quantifying metabolites. Therefore, an efficient and reproducible methodology is required to transform complex milk 1H NMR spectra into annotated and quantified milk metabolome data. In this study, standard operating procedures for screening the milk metabolome using 1H NMR spectra are developed. A chemical shift library of 63 milk metabolites was established and implemented in the open-access Signature Mapping (SigMa) software. SigMa is a spectral analysis tool that transforms 1H NMR spectra into a quantitative metabolite table. The applicability of the proposed methodology to whole milk, skim milk, and ultrafiltered milk is demonstrated, and the method is tested on ultrafiltered colostrum samples from dairy cows (n = 88) to evaluate whether metabolic changes in colostrum may reflect the metabolic status of cows.
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Affiliation(s)
- Paraskevi Tsermoula
- Department of Food Science, University of Copenhagen, Rolighedsvej 26, Frederiksberg 1958, Denmark
| | | | - Nabiollah Mobaraki
- Institute for Medicinal and Pharmaceutical Chemistry, University of Technology Braunschweig, Beethovenstraße 55, Braunschweig 38106, Germany
| | - So Ren B Engelsen
- Department of Food Science, University of Copenhagen, Rolighedsvej 26, Frederiksberg 1958, Denmark
| | - Bekzod Khakimov
- Department of Food Science, University of Copenhagen, Rolighedsvej 26, Frederiksberg 1958, Denmark
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24
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Mück F, Scotti F, Mauvisseau Q, Thorbek BLG, Wangensteen H, de Boer HJ. Three-tiered authentication of herbal traditional Chinese medicine ingredients used in women's health provides progressive qualitative and quantitative insight. Front Pharmacol 2024; 15:1353434. [PMID: 38375033 PMCID: PMC10875096 DOI: 10.3389/fphar.2024.1353434] [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: 12/10/2023] [Accepted: 01/16/2024] [Indexed: 02/21/2024] Open
Abstract
Traditional Chinese Medicine (TCM) herbal products are increasingly used in Europe, but prevalent authentication methods have significant gaps in detection. In this study, three authentication methods were tested in a tiered approach to improve accuracy on a collection of 51 TCM plant ingredients obtained on the European market. We show the relative performance of conventional barcoding, metabarcoding and standardized chromatographic profiling for TCM ingredients used in one of the most diagnosed disease patterns in women, endometriosis. DNA barcoding using marker ITS2 and chromatographic profiling are methods of choice reported by regulatory authorities and relevant national pharmacopeias. HPTLC was shown to be a valuable authentication tool, combined with metabarcoding, which gives an increased resolution on species diversity, despite dealing with highly processed herbal ingredients. Conventional DNA barcoding as a recommended method was shown to be an insufficient tool for authentication of these samples, while DNA metabarcoding yields an insight into biological contaminants. We conclude that a tiered identification strategy can provide progressive qualitative and quantitative insight in an integrative approach for quality control of processed herbal ingredients.
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Affiliation(s)
- Felicitas Mück
- Section for Pharmaceutical Chemistry, Department of Pharmacy, University of Oslo, Oslo, Norway
| | - Francesca Scotti
- Department of Pharmaceutical and Biological Chemistry, School of Pharmacy, University College London, London, United Kingdom
| | | | | | - Helle Wangensteen
- Section for Pharmaceutical Chemistry, Department of Pharmacy, University of Oslo, Oslo, Norway
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25
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Bansal N, Kumar M, Gupta A. Richer than previously probed: An application of 1H NMR reveals one hundred metabolites using only fifty microliter serum. Biophys Chem 2024; 305:107153. [PMID: 38088005 DOI: 10.1016/j.bpc.2023.107153] [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: 11/03/2023] [Revised: 11/22/2023] [Accepted: 12/04/2023] [Indexed: 01/03/2024]
Abstract
The classical approach restricts the detection of metabolites in serum samples by using nuclear magnetic resonance (NMR) spectroscopy; however, the presence of copious proteins and lipoproteins emphasize and necessitate the development of a contemporary, high-throughput tactic. To eliminate the lipoproteins and proteins from sera to engender filtered sera (FS), the study was executed with 50 μl serum obtained from five healthy individuals with 5 years of age difference from 25 to 45 years old and the application of a unique mechanical filter with molecular weight cut-off value of 2KDa. The 10 μl FS from each individual was pooled to make 50 μl final volume filled in a co-axial tube for acquisition of a battery of 1D/2D investigations at 800 MHz NMR spectrometer and the assigned metabolites was confirmed through mass spectrometry as well as by comparing 1H NMR spectra of individual metabolites. This innovative tactic is commissioning to reveal more than 100 metabolites. In contrast to the protein precipitation method, 24 new metabolites were recognized in the present study. The present innovative approach characterizes nucleosides, nitrogenous bases, and volatile metabolites that possibly produce a landmark for the delineation of a comprehensive metabolic profile applicable for detection of the molecular cause of pathogenicity, early-stage disease detection and prognosis, inborn error of metabolism, and forensic investigations exerting the least volume of FS and NMR spectroscopy. The assignment of 100 metabolites using 1H NMR-based FS is described for the first time in the present report.
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Affiliation(s)
- Navneeta Bansal
- Department of Urology, King George's Medical University, Lucknow, India
| | - Manoj Kumar
- Department of Urology, King George's Medical University, Lucknow, India.
| | - Ashish Gupta
- Centre of Biomedical Research, SGPGIMS Campus, Lucknow, India.
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26
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Duong QH, Kwahk EJ, Kim J, Park H, Cho H, Kim H. Bioinspired Fluorine Labeling for 19F NMR-Based Plasma Amine Profiling. Anal Chem 2024; 96:1614-1621. [PMID: 38244044 DOI: 10.1021/acs.analchem.3c04485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2024]
Abstract
Metabolite profiling serves as a powerful tool that advances our understanding of biological systems, disease mechanisms, and environmental interactions. In this study, we present an approach employing 19F-nuclear magnetic resonance (19F NMR) spectroscopy for plasma amine profiling. This method utilizes a highly efficient and reliable fluorine-labeling reagent, 3,5-difluorosalicylaldehyde, which effectively emulates pyridoxal phosphate, facilitating the formation of Schiff base compounds with primary amines. The fluorine labeling allows for distinct resolution of 19F NMR signals from amine mixtures, leading to precise identification and quantification of amine metabolites in human plasma. This advancement offers valuable tools for furthering metabolomics research.
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Affiliation(s)
- Quynh Huong Duong
- Department of Chemistry, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Eun-Jeong Kwahk
- Department of Chemistry, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Jumi Kim
- Department of Chemistry, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Hahyoun Park
- Department of Chemistry, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Heyjin Cho
- Department of Chemistry, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Hyunwoo Kim
- Department of Chemistry, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
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27
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Peinado RDS, Martins LG, Pacca CC, Saivish MV, Borsatto KC, Nogueira ML, Tasic L, Arni RK, Eberle RJ, Coronado MA. HR-MAS NMR Metabolomics Profile of Vero Cells under the Influence of Virus Infection and nsP2 Inhibitor: A Chikungunya Case Study. Int J Mol Sci 2024; 25:1414. [PMID: 38338694 PMCID: PMC10855909 DOI: 10.3390/ijms25031414] [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: 12/16/2023] [Revised: 01/11/2024] [Accepted: 01/16/2024] [Indexed: 02/12/2024] Open
Abstract
The arbovirus Chikungunya (CHIKV) is transmitted by Aedes mosquitoes in urban environments, and in humans, it triggers debilitating symptoms involving long-term complications, including arthritis and Guillain-Barré syndrome. The development of antiviral therapies is relevant, as no efficacious vaccine or drug has yet been approved for clinical application. As a detailed map of molecules underlying the viral infection can be obtained from the metabolome, we validated the metabolic signatures of Vero E6 cells prior to infection (CC), following CHIKV infection (CV) and also upon the inclusion of the nsP2 protease inhibitor wedelolactone (CWV), a coumestan which inhibits viral replication processes. The metabolome groups evidenced significant changes in the levels of lactate, myo-inositol, phosphocholine, glucose, betaine and a few specific amino acids. This study forms a preliminary basis for identifying metabolites through HR-MAS NMR (High Resolution Magic Angle Spinning Nuclear Magnetic Ressonance Spectroscopy) and proposing the affected metabolic pathways of cells following viral infection and upon incorporation of putative antiviral molecules.
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Affiliation(s)
- Rafaela dos S. Peinado
- Multiuser Center for Biomolecular Innovation, Department of Physics, Institute of Biosciences, Languages and Exact Sciences (Ibilce—UNESP), Sao Jose do Rio Preto, Sao Paulo 15054000, Brazil; (R.d.S.P.); (K.C.B.); (R.K.A.)
| | - Lucas G. Martins
- Department of Organic Chemistry, Institute of Chemistry, University of Campinas (UNICAMP), Campinas 13083862, Brazil; (L.G.M.); (L.T.)
| | - Carolina C. Pacca
- Virology Research Laboratory, Medical School of Sao Jose do Rio Preto (FAMERP), Sao Paulo 15090000, Brazil; (C.C.P.); (M.V.S.); (M.L.N.)
| | - Marielena V. Saivish
- Virology Research Laboratory, Medical School of Sao Jose do Rio Preto (FAMERP), Sao Paulo 15090000, Brazil; (C.C.P.); (M.V.S.); (M.L.N.)
| | - Kelly C. Borsatto
- Multiuser Center for Biomolecular Innovation, Department of Physics, Institute of Biosciences, Languages and Exact Sciences (Ibilce—UNESP), Sao Jose do Rio Preto, Sao Paulo 15054000, Brazil; (R.d.S.P.); (K.C.B.); (R.K.A.)
| | - Maurício L. Nogueira
- Virology Research Laboratory, Medical School of Sao Jose do Rio Preto (FAMERP), Sao Paulo 15090000, Brazil; (C.C.P.); (M.V.S.); (M.L.N.)
| | - Ljubica Tasic
- Department of Organic Chemistry, Institute of Chemistry, University of Campinas (UNICAMP), Campinas 13083862, Brazil; (L.G.M.); (L.T.)
| | - Raghuvir K. Arni
- Multiuser Center for Biomolecular Innovation, Department of Physics, Institute of Biosciences, Languages and Exact Sciences (Ibilce—UNESP), Sao Jose do Rio Preto, Sao Paulo 15054000, Brazil; (R.d.S.P.); (K.C.B.); (R.K.A.)
| | - Raphael J. Eberle
- Institute of Biological Information Processing IBI-7: Structural Biochemistry, Forschungszentrum Jülich, 52428 Jülich, Germany
- Institut für Physikalische Biologie, Heinrich-Heine-Universität Düsseldorf, 40225 Düsseldorf, Germany
| | - Mônika A. Coronado
- Institute of Biological Information Processing IBI-7: Structural Biochemistry, Forschungszentrum Jülich, 52428 Jülich, Germany
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28
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Ossoliński K, Ruman T, Copié V, Tripet BP, Kołodziej A, Płaza-Altamer A, Ossolińska A, Ossoliński T, Krupa Z, Nizioł J. Metabolomic profiling of human bladder tissue extracts. Metabolomics 2024; 20:14. [PMID: 38267657 DOI: 10.1007/s11306-023-02076-w] [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: 05/26/2023] [Accepted: 12/01/2023] [Indexed: 01/26/2024]
Abstract
INTRODUCTION Bladder cancer is a common malignancy affecting the urinary tract and effective biomarkers and for which monitoring therapeutic interventions have yet to be identified. OBJECTIVES Major aim of this work was to perform metabolomic profiling of human bladder cancer and adjacent normal tissue and to evaluate cancer biomarkers. METHODS This study utilized nuclear magnetic resonance (NMR) and high-resolution nanoparticle-based laser desorption/ionization mass spectrometry (LDI-MS) methods to investigate polar metabolite profiles in tissue samples from 99 bladder cancer patients. RESULTS Through NMR spectroscopy, six tissue metabolites were identified and quantified as potential indicators of bladder cancer, while LDI-MS allowed detection of 34 compounds which distinguished cancer tissue samples from adjacent normal tissue. Thirteen characteristic tissue metabolites were also found to differentiate bladder cancer tumor grades and thirteen metabolites were correlated with tumor stages. Receiver-operating characteristics analysis showed high predictive power for all three types of metabolomics data, with area under the curve (AUC) values greater than 0.853. CONCLUSION To date, this is the first study in which bladder human normal tissues adjacent to cancerous tissues are analyzed using both NMR and MS method. These findings suggest that the metabolite markers identified in this study may be useful for the detection and monitoring of bladder cancer stages and grades.
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Affiliation(s)
- Krzysztof Ossoliński
- Department of Urology, John Paul II Hospital, Grunwaldzka 4 St., 36-100, Kolbuszowa, Poland
| | - Tomasz Ruman
- Faculty of Chemistry, Rzeszów University of Technology, 6 Powstańców Warszawy Ave., 35-959, Rzeszów, Poland
| | - Valérie Copié
- The Department of Chemistry and Biochemistry, Montana State University, Bozeman, MT, 59717, USA
| | - Brian P Tripet
- The Department of Chemistry and Biochemistry, Montana State University, Bozeman, MT, 59717, USA
| | - Artur Kołodziej
- Faculty of Chemistry, Rzeszów University of Technology, 6 Powstańców Warszawy Ave., 35-959, Rzeszów, Poland
| | - Aneta Płaza-Altamer
- Faculty of Chemistry, Rzeszów University of Technology, 6 Powstańców Warszawy Ave., 35-959, Rzeszów, Poland
| | - Anna Ossolińska
- Department of Urology, John Paul II Hospital, Grunwaldzka 4 St., 36-100, Kolbuszowa, Poland
| | - Tadeusz Ossoliński
- Department of Urology, John Paul II Hospital, Grunwaldzka 4 St., 36-100, Kolbuszowa, Poland
| | - Zuzanna Krupa
- Doctoral School of Engineering and Technical Sciences, Rzeszów University of Technology, 8 Powstańców Warszawy Ave., 35-959, Rzeszów, Poland
| | - Joanna Nizioł
- Faculty of Chemistry, Rzeszów University of Technology, 6 Powstańców Warszawy Ave., 35-959, Rzeszów, Poland.
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29
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Rigel N, Li DW, Brüschweiler R. COLMARppm: A Web Server Tool for the Accurate and Rapid Prediction of 1H and 13C NMR Chemical Shifts of Organic Molecules and Metabolites. Anal Chem 2024; 96:701-709. [PMID: 38157361 PMCID: PMC10794995 DOI: 10.1021/acs.analchem.3c03677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 10/15/2023] [Accepted: 11/20/2023] [Indexed: 01/03/2024]
Abstract
Despite rapid progress in metabolomics research, a major bottleneck is the large number of metabolites whose chemical structures are unknown or whose spectra have not been deposited in metabolomics databases. Nuclear magnetic resonance (NMR) spectroscopy has a long history of elucidating chemical structures from experimentally measured 1H and 13C chemical shifts. One approach to characterizing the chemical structures of an unknown metabolite is to predict the 1H and 13C chemical shifts of candidate compounds (e.g., metabolites from the Human Metabolome Database (HMDB)) and compare them with chemical shifts of the unknown. However, accurate prediction of NMR chemical shifts in aqueous solution is challenging due to limitations of experimental chemical shift libraries and the high computational cost of quantum chemical methods. To improve NMR prediction accuracy and applicability, an empirical prediction strategy is introduced here to provide an accurately predicted chemical shift for organic molecules and metabolites within seconds. Unique features of COLMARppm include (i) the training library exclusively consisting of high quality NMR spectra measured under standard conditions in aqueous solution, (ii) utilization of NMR motif information, and (iii) leveraging of the improved prediction accuracy for the automated assignment of experimental chemical shifts for candidate structures. COLMARppm is demonstrated in terms of accuracy and speed for a set of 20 compounds taken from the HMDB for chemical shift prediction and resonance assignment. COLMARppm is applicable to a wide range of small molecules and can be directly incorporated into metabolomics workflows.
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Affiliation(s)
- Nick Rigel
- Department
of Chemistry and Biochemistry, The Ohio
State University, Columbus, Ohio 43210, United States
| | - Da-Wei Li
- Campus
Chemical Instrument Center,The Ohio State
University, Columbus, Ohio 43210, United States
| | - Rafael Brüschweiler
- Department
of Chemistry and Biochemistry, The Ohio
State University, Columbus, Ohio 43210, United States
- Campus
Chemical Instrument Center,The Ohio State
University, Columbus, Ohio 43210, United States
- Department
of Biological Chemistry and Pharmacology, The Ohio State University, Columbus, Ohio 43210, United States
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30
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Jang M, Shin J, Kim YH, Jeong TY, Jo S, Kim SJ, Devaraj V, Kang J, Choi EJ, Lee JE, Oh JW. 3D superstructure based metabolite profiling for glaucoma diagnosis. Biosens Bioelectron 2024; 244:115780. [PMID: 37939415 DOI: 10.1016/j.bios.2023.115780] [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: 06/13/2023] [Revised: 09/05/2023] [Accepted: 10/21/2023] [Indexed: 11/10/2023]
Abstract
Metabolome analysis has gained widespread application in disease diagnosis owing to its ability to provide comprehensive information, including disease phenotypes. In this study, we utilized 3D superstructures fabricated through evaporation-induced microprinting to analyze the metabolome for glaucoma diagnosis. 3D superstructures offer the following advantages: high hotspot density per unit volume of the structure extending from two to three dimensions, excellent signal repeatability due to the reproducibility and defect tolerance of 3D printing, and high thermal stability due to the PVP-enclosed capsule form. Leveraging the superior optical properties of the 3D superstructure, we aimed to classify patients with glaucoma. The signal obtained from the 3D superstructure was employed in a Deep Neural Network (DNN) classification model to accurately classify glaucoma patients. The sensitivity and specificity of the model were determined as 92.05% and 93.51%, respectively. Additionally, the fabrication of 3D superstructures can be performed at any stage, significantly reducing measurement time. Furthermore, their thermal stability allows for the analysis of smaller samples. One notable advantage of 3D superstructures is their versatility in accommodating different target materials. Consequently, they can be utilized for a wide range of metabolic analyses and disease diagnoses.
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Affiliation(s)
- Minsu Jang
- Department of Nano Fusion Technology, Pusan National University, Busan, 46241, Republic of Korea
| | - Jonghoon Shin
- Department of Ophthalmology, College of Medicine, Pusan National University Yangsan Hospital, Republic of Korea; Department of Ophthalmology, Research Institute for Convergence of Biomedical Science and Technology, Busan, Republic of Korea
| | - You Hwan Kim
- Department of Nano Fusion Technology, Pusan National University, Busan, 46241, Republic of Korea
| | - Tae-Young Jeong
- Bio-IT Fusion Technology Research Institute, Pusan National University, Busan, 46241, Republic of Korea
| | - Soojin Jo
- Department of Nano Fusion Technology, Pusan National University, Busan, 46241, Republic of Korea
| | - Sung-Jo Kim
- Bio-IT Fusion Technology Research Institute, Pusan National University, Busan, 46241, Republic of Korea
| | - Vasanthan Devaraj
- Bio-IT Fusion Technology Research Institute, Pusan National University, Busan, 46241, Republic of Korea
| | - Joonhee Kang
- Department of Nano Energy Engineering, Pusan National University, Busan, 46241, Republic of Korea
| | - Eun-Jung Choi
- Bio-IT Fusion Technology Research Institute, Pusan National University, Busan, 46241, Republic of Korea.
| | - Ji Eun Lee
- Department of Ophthalmology, College of Medicine, Pusan National University Yangsan Hospital, Republic of Korea; Department of Ophthalmology, Research Institute for Convergence of Biomedical Science and Technology, Busan, Republic of Korea.
| | - Jin-Woo Oh
- Department of Nano Fusion Technology, Pusan National University, Busan, 46241, Republic of Korea; Bio-IT Fusion Technology Research Institute, Pusan National University, Busan, 46241, Republic of Korea; Department of Nano Energy Engineering, Pusan National University, Busan, 46241, Republic of Korea.
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31
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Domżał B, Nawrocka EK, Gołowicz D, Ciach MA, Miasojedow B, Kazimierczuk K, Gambin A. Magnetstein: An Open-Source Tool for Quantitative NMR Mixture Analysis Robust to Low Resolution, Distorted Lineshapes, and Peak Shifts. Anal Chem 2024; 96:188-196. [PMID: 38117933 PMCID: PMC10782418 DOI: 10.1021/acs.analchem.3c03594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 11/30/2023] [Accepted: 11/30/2023] [Indexed: 12/22/2023]
Abstract
1H NMR spectroscopy is a powerful tool for analyzing mixtures including determining the concentrations of individual components. When signals from multiple compounds overlap, this task requires computational solutions. They are typically based on peak-picking and the comparison of obtained peak lists with libraries of individual components. This can fail if peaks are not sufficiently resolved or when peak positions differ between the library and the mixture. In this paper, we present Magnetstein, a quantification algorithm rooted in the optimal transport theory that makes it robust to unexpected frequency shifts and overlapping signals. Thanks to this, Magnetstein can quantitatively analyze difficult spectra with the estimation trueness an order of magnitude higher than that of commercial tools. Furthermore, the method is easier to use than other approaches, having only two parameters with default values applicable to a broad range of experiments and requiring little to no preprocessing of the spectra.
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Affiliation(s)
- Barbara Domżał
- Faculty
of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, Warsaw 02-097, Poland
| | - Ewa Klaudia Nawrocka
- Centre
of New Technologies, University of Warsaw, Banacha 2C, Warsaw 02-097, Poland
| | - Dariusz Gołowicz
- Institute
of Physical Chemistry, Polish Academy of
Sciences, Kasprzaka 44/52, Warsaw 01-224, Poland
| | - Michał Aleksander Ciach
- Faculty
of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, Warsaw 02-097, Poland
| | - Błażej Miasojedow
- Faculty
of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, Warsaw 02-097, Poland
| | | | - Anna Gambin
- Faculty
of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, Warsaw 02-097, Poland
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Papageorgiou MP, Theodoridou D, Nussbaumer M, Syrrou M, Filiou MD. Deciphering the Metabolome under Stress: Insights from Rodent Models. Curr Neuropharmacol 2024; 22:884-903. [PMID: 37448366 PMCID: PMC10845087 DOI: 10.2174/1570159x21666230713094843] [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: 10/30/2022] [Revised: 12/22/2022] [Accepted: 01/09/2023] [Indexed: 07/15/2023] Open
Abstract
Despite intensive research efforts to understand the molecular underpinnings of psychological stress and stress responses, the underlying molecular mechanisms remain largely elusive. Towards this direction, a plethora of stress rodent models have been established to investigate the effects of exposure to different stressors. To decipher affected molecular pathways in a holistic manner in these models, metabolomics approaches addressing altered, small molecule signatures upon stress exposure in a high-throughput, quantitative manner provide insightful information on stress-induced systemic changes in the brain. In this review, we discuss stress models in mice and rats, followed by mass spectrometry (MS) and nuclear magnetic resonance (NMR) metabolomics studies. We particularly focus on acute, chronic and early life stress paradigms, highlight how stress is assessed at the behavioral and molecular levels and focus on metabolomic outcomes in the brain and peripheral material such as plasma and serum. We then comment on common metabolomics patterns across different stress models and underline the need for unbiased -omics methodologies and follow-up studies of metabolomics outcomes to disentangle the complex pathobiology of stress and pertinent psychopathologies.
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Affiliation(s)
- Maria P. Papageorgiou
- Laboratory of Biochemistry, Department of Biological Applications and Technology, School of Health Sciences, University of Ioannina, Greece
- Biomedical Research Institute, Foundation for Research and Technology-Hellas (BRI-FORTH), Ioannina, Greece
| | - Daniela Theodoridou
- Laboratory of Biology, Faculty of Medicine, School of Health Sciences, University of Ioannina, Greece
| | - Markus Nussbaumer
- Laboratory of Biochemistry, Department of Biological Applications and Technology, School of Health Sciences, University of Ioannina, Greece
- Biomedical Research Institute, Foundation for Research and Technology-Hellas (BRI-FORTH), Ioannina, Greece
| | - Maria Syrrou
- Laboratory of Biology, Faculty of Medicine, School of Health Sciences, University of Ioannina, Greece
| | - Michaela D. Filiou
- Laboratory of Biochemistry, Department of Biological Applications and Technology, School of Health Sciences, University of Ioannina, Greece
- Biomedical Research Institute, Foundation for Research and Technology-Hellas (BRI-FORTH), Ioannina, Greece
- Ιnstitute of Biosciences, University of Ioannina, Greece
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Andrews MG, Pearson CA. Toward an understanding of glucose metabolism in radial glial biology and brain development. Life Sci Alliance 2024; 7:e202302193. [PMID: 37798120 PMCID: PMC10556723 DOI: 10.26508/lsa.202302193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 09/20/2023] [Accepted: 09/26/2023] [Indexed: 10/07/2023] Open
Abstract
Decades of research have sought to determine the intrinsic and extrinsic mechanisms underpinning the regulation of neural progenitor maintenance and differentiation. A series of precise temporal transitions within progenitor cell populations generates all the appropriate neural cell types while maintaining a pool of self-renewing progenitors throughout embryogenesis. Recent technological advances have enabled us to gain new insights at the single-cell level, revealing an interplay between metabolic state and developmental progression that impacts the timing of proliferation and neurogenesis. This can have long-term consequences for the developing brain's neuronal specification, maturation state, and organization. Furthermore, these studies have highlighted the need to reassess the instructive role of glucose metabolism in determining progenitor cell division, differentiation, and fate. This review focuses on glucose metabolism (glycolysis) in cortical progenitor cells and the emerging focus on glycolysis during neurogenic transitions. Furthermore, we discuss how the field can learn from other biological systems to improve our understanding of the spatial and temporal changes in glycolysis in progenitors and evaluate functional neurological outcomes.
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Affiliation(s)
- Madeline G Andrews
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Caroline A Pearson
- https://ror.org/02r109517 Center for Neurogenetics, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
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Wurth R, Turgeon C, Stander Z, Oglesbee D. An evaluation of untargeted metabolomics methods to characterize inborn errors of metabolism. Mol Genet Metab 2024; 141:108115. [PMID: 38181458 PMCID: PMC10843816 DOI: 10.1016/j.ymgme.2023.108115] [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: 10/10/2023] [Revised: 11/19/2023] [Accepted: 12/12/2023] [Indexed: 01/07/2024]
Abstract
Inborn errors of metabolism (IEMs) encompass a diverse group of disorders that can be difficult to classify due to heterogenous clinical, molecular, and biochemical manifestations. Untargeted metabolomics platforms have become a popular approach to analyze IEM patient samples because of their ability to detect many metabolites at once, accelerating discovery of novel biomarkers, and metabolic mechanisms of disease. However, there are concerns about the reproducibility of untargeted metabolomics research due to the absence of uniform reporting practices, data analyses, and experimental design guidelines. Therefore, we critically evaluated published untargeted metabolomic platforms used to characterize IEMs to summarize the strengths and areas for improvement of this technology as it progresses towards the clinical laboratory. A total of 96 distinct IEMs were collectively evaluated by the included studies. However, most of these IEMs were evaluated by a single untargeted metabolomic method, in a single study, with a limited cohort size (55/96, 57%). The goals of the included studies generally fell into two, often overlapping, categories: detecting known biomarkers from many biochemically distinct IEMs using a single platform, and detecting novel metabolites or metabolic pathways. There was notable diversity in the design of the untargeted metabolomic platforms. Importantly, the majority of studies reported adherence to quality metrics, including the use of quality control samples and internal standards in their experiments, as well as confirmation of at least some of their feature annotations with commercial reference standards. Future applications of untargeted metabolomics platforms to the study of IEMs should move beyond single-subject analyses, and evaluate reproducibility using a prospective, or validation cohort.
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Affiliation(s)
- Rachel Wurth
- Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, 200 1(st) St SW, Rochester, MN 55905, USA
| | - Coleman Turgeon
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 1st St SW, Rochester, MN 55905, USA
| | - Zinandré Stander
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 1st St SW, Rochester, MN 55905, USA
| | - Devin Oglesbee
- Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 1st St SW, Rochester, MN 55905, USA.
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Singh U, Al-Nemi R, Alahmari F, Emwas AH, Jaremko M. Improving quality of analysis by suppression of unwanted signals through band-selective excitation in NMR spectroscopy for metabolomics studies. Metabolomics 2023; 20:7. [PMID: 38114836 DOI: 10.1007/s11306-023-02069-9] [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: 09/26/2023] [Accepted: 11/16/2023] [Indexed: 12/21/2023]
Abstract
INTRODUCTION Nuclear Magnetic Resonance (NMR) spectroscopy stands as a preeminent analytical tool in the field of metabolomics. Nevertheless, when it comes to identifying metabolites present in scant amounts within various types of complex mixtures such as plants, honey, milk, and biological fluids and tissues, NMR-based metabolomics presents a formidable challenge. This predicament arises primarily from the fact that the signals emanating from metabolites existing in low concentrations tend to be overshadowed by the signals of highly concentrated metabolites within NMR spectra. OBJECTIVES The aim of this study is to tackle the issue of intense sugar signals overshadowing the desired metabolite signals, an optimal pulse sequence with band-selective excitation has been proposed for the suppression of sugar's moiety signals (SSMS). This sequence serves the crucial purpose of suppressing unwanted signals, with a particular emphasis on mitigating the interference caused by sugar moieties' signals. METHODS We have implemented this comprehensive approach to various NMR techniques, including 1D 1H presaturation (presat), 2D J-resolved (RES), 2D 1H-1H Total Correlation Spectroscopy (TOCSY), and 2D 1H-13C Heteronuclear Single Quantum Coherence (HSQC) for the samples of dates-flesh, honey, a standard stock solution of glucose, and nine amino acids, and commercial fetal bovine serum (FBS). RESULTS The outcomes of this approach were significant. The suppression of the high-intensity sugar signals has considerably enhanced the visibility and sensitivity of the signals emanating from the desired metabolites. CONCLUSION This, in turn, enables the identification of a greater number of metabolites. Additionally, it streamlines the experimental process, reducing the time required for the comparative quantification of metabolites in statistical studies in the field of metabolomics.
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Affiliation(s)
- Upendra Singh
- Division of Biological and Environmental Sciences and Engineering (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Makkah, 23955-6900, Saudi Arabia
| | - Ruba Al-Nemi
- Division of Biological and Environmental Sciences and Engineering (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Makkah, 23955-6900, Saudi Arabia
| | - Fatimah Alahmari
- Department of Nanomedicine Research, Institute for Research & Medical Consultations (IRMC), Imam Abdulrahman Bin Faisal University, P.O. Box 1982, Dammam, 31441, Saudi Arabia
| | - Abdul-Hamid Emwas
- Core Lab of NMR, King Abdullah University of Science and Technology (KAUST), Thuwal, Makkah, 23955-6900, Saudi Arabia.
| | - Mariusz Jaremko
- Division of Biological and Environmental Sciences and Engineering (BESE), Smart-Health Initiative (SHI) and Red Sea Research Center (RSRC), King Abdullah University of Science and Technology (KAUST), Thuwal, Makkah, 23955-6900, Saudi Arabia.
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Hou Y, Mishra R, Zhao Y, Ducrée J, Harrison JD. An Automated Centrifugal Microfluidic Platform for Efficient Multistep Blood Sample Preparation and Clean-Up towards Small Ion-Molecule Analysis. MICROMACHINES 2023; 14:2257. [PMID: 38138426 PMCID: PMC10745919 DOI: 10.3390/mi14122257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 12/14/2023] [Accepted: 12/14/2023] [Indexed: 12/24/2023]
Abstract
Sample preparation for mass spectroscopy typically involves several liquid and solid phase clean-ups, extractions, and other unit operations, which are labour-intensive and error-prone. We demonstrate a centrifugal microfluidic platform that automates the whole blood sample's preparation and clean-up by combining traditional liquid-phase and multiple solid-phase extractions for applications in mass spectroscopy (MS)-based small molecule detection. Liquid phase extraction was performed using methanol to precipitate proteins in plasma separated from a blood sample under centrifugal force. The preloaded solid phase composed of C18 beads then removed lipids with a combination of silica particles, which further cleaned up any remaining proteins. We further integrated the application of this sample prep disc with matrix-assisted laser desorption/ionization (MALDI) MS by using glancing angle deposition films, which further cleaned up the processed sample by segregating the electrolyte background from the sample salts. Additionally, hydrophilic interaction liquid chromatography (HILIC) MS was employed for detecting targeted free amino acids. Therefore, several representative ionic metabolites, including several amino acids and organic acids from blood samples, were analysed by both MALDI-MS and HILIC-MS to demonstrate the performance of this sample preparation disc. The fully automated blood sample preparation procedure only took 35 mins, with a throughput of three parallel units.
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Affiliation(s)
- Yuting Hou
- Department of Chemistry, University of Alberta, Edmonton, AB T6G 2G2, Canada; (Y.Z.); (J.D.H.)
| | - Rohit Mishra
- FPC@DCU—Fraunhofer Project Centre for Embedded Bioanalytical Systems, Dublin City University, D09 V209 Dublin, Ireland
- School of Physical Sciences, Dublin City University, D09 V209 Dublin, Ireland;
| | - Yufeng Zhao
- Department of Chemistry, University of Alberta, Edmonton, AB T6G 2G2, Canada; (Y.Z.); (J.D.H.)
- Centre for Research and Applications in Fluidic Technologies, National Research Council Canada, Toronto, ON M5S 3G8, Canada
- Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON M5S 3M2, Canada
| | - Jens Ducrée
- School of Physical Sciences, Dublin City University, D09 V209 Dublin, Ireland;
| | - Jed D. Harrison
- Department of Chemistry, University of Alberta, Edmonton, AB T6G 2G2, Canada; (Y.Z.); (J.D.H.)
- FPC@DCU—Fraunhofer Project Centre for Embedded Bioanalytical Systems, Dublin City University, D09 V209 Dublin, Ireland
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Akyol S, Ashrafi N, Yilmaz A, Turkoglu O, Graham SF. Metabolomics: An Emerging "Omics" Platform for Systems Biology and Its Implications for Huntington Disease Research. Metabolites 2023; 13:1203. [PMID: 38132886 PMCID: PMC10744751 DOI: 10.3390/metabo13121203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 11/29/2023] [Accepted: 12/02/2023] [Indexed: 12/23/2023] Open
Abstract
Huntington's disease (HD) is a progressive, fatal neurodegenerative disease characterized by motor, cognitive, and psychiatric symptoms. The precise mechanisms of HD progression are poorly understood; however, it is known that there is an expansion of the trinucleotide cytosine-adenine-guanine (CAG) repeat in the Huntingtin gene. Important new strategies are of paramount importance to identify early biomarkers with predictive value for intervening in disease progression at a stage when cellular dysfunction has not progressed irreversibly. Metabolomics is the study of global metabolite profiles in a system (cell, tissue, or organism) under certain conditions and is becoming an essential tool for the systemic characterization of metabolites to provide a snapshot of the functional and pathophysiological states of an organism and support disease diagnosis and biomarker discovery. This review briefly highlights the historical progress of metabolomic methodologies, followed by a more detailed review of the use of metabolomics in HD research to enable a greater understanding of the pathogenesis, its early prediction, and finally the main technical platforms in the field of metabolomics.
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Affiliation(s)
- Sumeyya Akyol
- NX Prenatal Inc., 4350 Brownsboro Road, Louisville KY 40207, USA;
| | - Nadia Ashrafi
- Department of Obstetrics and Gynecology, Oakland University-William Beaumont School of Medicine, 318 Meadow Brook Road, Rochester, MI 48309, USA; (N.A.); (A.Y.); (O.T.)
| | - Ali Yilmaz
- Department of Obstetrics and Gynecology, Oakland University-William Beaumont School of Medicine, 318 Meadow Brook Road, Rochester, MI 48309, USA; (N.A.); (A.Y.); (O.T.)
- Metabolomics Division, Beaumont Research Institute, 3811 W. 13 Mile Road, Royal Oak, MI 48073, USA
| | - Onur Turkoglu
- Department of Obstetrics and Gynecology, Oakland University-William Beaumont School of Medicine, 318 Meadow Brook Road, Rochester, MI 48309, USA; (N.A.); (A.Y.); (O.T.)
| | - Stewart F. Graham
- Department of Obstetrics and Gynecology, Oakland University-William Beaumont School of Medicine, 318 Meadow Brook Road, Rochester, MI 48309, USA; (N.A.); (A.Y.); (O.T.)
- Metabolomics Division, Beaumont Research Institute, 3811 W. 13 Mile Road, Royal Oak, MI 48073, USA
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Baranovicova E, Kalenska D, Kaplan P, Kovalska M, Tatarkova Z, Lehotsky J. Blood and Brain Metabolites after Cerebral Ischemia. Int J Mol Sci 2023; 24:17302. [PMID: 38139131 PMCID: PMC10743907 DOI: 10.3390/ijms242417302] [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: 10/27/2023] [Revised: 12/01/2023] [Accepted: 12/06/2023] [Indexed: 12/24/2023] Open
Abstract
The study of an organism's response to cerebral ischemia at different levels is essential to understanding the mechanism of the injury and protection. A great interest is devoted to finding the links between quantitative metabolic changes and post-ischemic damage. This work aims to summarize the outcomes of the most studied metabolites in brain tissue-lactate, glutamine, GABA (4-aminobutyric acid), glutamate, and NAA (N-acetyl aspartate)-regarding their biological function in physiological conditions and their role after cerebral ischemia/reperfusion. We focused on ischemic damage and post-ischemic recovery in both experimental-including our results-as well as clinical studies. We discuss the role of blood glucose in view of the diverse impact of hyperglycemia, whether experimentally induced, caused by insulin resistance, or developed as a stress response to the cerebral ischemic event. Additionally, based on our and other studies, we analyze and critically discuss post-ischemic alterations in energy metabolites and the elevation of blood ketone bodies observed in the studies on rodents. To complete the schema, we discuss alterations in blood plasma circulating amino acids after cerebral ischemia. So far, no fundamental brain or blood metabolite(s) has been recognized as a relevant biological marker with the feasibility to determine the post-ischemic outcome or extent of ischemic damage. However, studies from our group on rats subjected to protective ischemic preconditioning showed that these animals did not develop post-ischemic hyperglycemia and manifested a decreased metabolic infringement and faster metabolomic recovery. The metabolomic approach is an additional tool for understanding damaging and/or restorative processes within the affected brain region reflected in the blood to uncover the response of the whole organism via interorgan metabolic communications to the stressful cerebral ischemic challenge.
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Affiliation(s)
- Eva Baranovicova
- Biomedical Center BioMed, Jessenius Faculty of Medicine, Comenius University in Bratislava, Mala Hora 4, 036 01 Martin, Slovakia;
| | - Dagmar Kalenska
- Department of Anatomy, Jessenius Faculty of Medicine, Comenius University in Bratislava, Mala Hora 4, 036 01 Martin, Slovakia
| | - Peter Kaplan
- Department of Medical Biochemistry, Jessenius Faculty of Medicine, Comenius University in Bratislava, Mala Hora 4, 036 01 Martin, Slovakia (Z.T.)
| | - Maria Kovalska
- Department of Histology and Embryology, Jessenius Faculty of Medicine, Comenius University in Bratislava, Mala Hora 4, 036 01 Martin, Slovakia
| | - Zuzana Tatarkova
- Department of Medical Biochemistry, Jessenius Faculty of Medicine, Comenius University in Bratislava, Mala Hora 4, 036 01 Martin, Slovakia (Z.T.)
| | - Jan Lehotsky
- Department of Medical Biochemistry, Jessenius Faculty of Medicine, Comenius University in Bratislava, Mala Hora 4, 036 01 Martin, Slovakia (Z.T.)
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Anjitha KS, Sarath NG, Sameena PP, Janeeshma E, Shackira AM, Puthur JT. Plant response to heavy metal stress toxicity: the role of metabolomics and other omics tools. FUNCTIONAL PLANT BIOLOGY : FPB 2023; 50:965-982. [PMID: 37995340 DOI: 10.1071/fp23145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 10/31/2023] [Indexed: 11/25/2023]
Abstract
Metabolomic investigations offers a significant foundation for improved comprehension of the adaptability of plants to reconfigure the key metabolic pathways and their response to changing climatic conditions. Their application to ecophysiology and ecotoxicology help to assess potential risks caused by the contaminants, their modes of action and the elucidation of metabolic pathways associated with stress responses. Heavy metal stress is one of the most significant environmental hazards affecting the physiological and biochemical processes in plants. Metabolomic tools have been widely utilised in the massive characterisation of the molecular structure of plants at various stages for understanding the diverse aspects of the cellular functioning underlying heavy metal stress-responsive mechanisms. This review emphasises on the recent progressions in metabolomics in plants subjected to heavy metal stresses. Also, it discusses the possibility of facilitating effective management strategies concerning metabolites for mitigating the negative impacts of heavy metal contaminants on the growth and productivity of plants.
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Affiliation(s)
- K S Anjitha
- Plant Physiology and Biochemistry Division, Department of Botany, University of Calicut, C. U. Campus P.O., Malappuram, Kerala 673635, India
| | - Nair G Sarath
- Department of Botany, Mar Athanasius College, Kothamangalam, Ernakulam, Kerala 686666, India
| | - P P Sameena
- Department of Botany, PSMO College, Tirurangadi, Malappuram, Kerala 676306, India
| | - Edappayil Janeeshma
- Department of Botany, MES KEVEEYAM College, Valanchery, Malappuram, Kerala 676552, India
| | - A M Shackira
- Department of Botany, Sir Syed College, Kannur University, Kannur, Kerala 670142, India
| | - Jos T Puthur
- Plant Physiology and Biochemistry Division, Department of Botany, University of Calicut, C. U. Campus P.O., Malappuram, Kerala 673635, India
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Dodangeh S, Taghizadeh H, Hosseinkhani S, Khashayar P, Pasalar P, Meybodi HRA, Razi F, Larijani B. Metabolomics signature of cardiovascular disease in patients with diabetes, a narrative review. J Diabetes Metab Disord 2023; 22:985-994. [PMID: 37975080 PMCID: PMC10638133 DOI: 10.1007/s40200-023-01256-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 06/19/2023] [Indexed: 11/19/2023]
Abstract
Objectives The exact underlying mechanism of developing diabetes-related cardiovascular disease (CVD) among patients with type 2 diabetes (T2D) is not clear. Metabolomics can provide a platform enabling the prediction, diagnosis, and understanding of the risk of CVD in patients with diabetes mellitus. The aim of this review is to summarize the available evidence on the relationship between metabolomics and cardiovascular diseases in patients with diabetes. Methods The literature was searched to find out studies that have investigated the relationship between the alteration of specific metabolites and cardiovascular diseases in patients with diabetes. Results Evidence proposed that changes in the metabolism of certain amino acids, lipids, and carbohydrates, independent of traditional CVD risk factors, are associated with increased CVD risk. Conclusions Metabolomics can provide a platform to enable the prediction, diagnosis, and understanding of the risk of CVD in patients with diabetes mellitus. The association of the alteration in specific metabolites with CVD may be considered in the investigations for the development of new therapeutic targets for the prevention of CVD in patients with diabetes mellitus.
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Affiliation(s)
- Salimeh Dodangeh
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Hananeh Taghizadeh
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Shaghayegh Hosseinkhani
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Pouria Khashayar
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Parvin Pasalar
- Metabolic Disorders Research Center, Endocrinology and Metabolism Molecular -Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Hamid Reza Aghaei Meybodi
- Evidence-based Medicine Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Farideh Razi
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Bagher Larijani
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
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Takis PG, Aggelidou VA, Sands CJ, Louka A. Mapping of 1 H NMR chemical shifts relationship with chemical similarities for the acceleration of metabolic profiling: Application on blood products. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2023; 61:759-769. [PMID: 37666776 PMCID: PMC10946494 DOI: 10.1002/mrc.5392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 08/03/2023] [Accepted: 08/15/2023] [Indexed: 09/06/2023]
Abstract
One-dimensional (1D) proton-nuclear magnetic resonance (1 H-NMR) spectroscopy is an established technique for the deconvolution of complex biological sample types via the identification/quantification of small molecules. It is highly reproducible and could be easily automated for small to large-scale bioanalytical, epidemiological, and in general metabolomics studies. However, chemical shift variability is a serious issue that must still be solved in order to fully automate metabolite identification. Herein, we demonstrate a strategy to increase the confidence in assignments and effectively predict the chemical shifts of various NMR signals based upon the simplest form of statistical models (i.e., linear regression). To build these models, we were guided by chemical homology in serum/plasma metabolites classes (i.e., amino acids and carboxylic acids) and similarity between chemical groups such as methyl protons. Our models, built on 940 serum samples and validated in an independent cohort of 1,052 plasma-EDTA spectra, were able to successfully predict the 1 H NMR chemical shifts of 15 metabolites within ~1.5 linewidths (Δv1/2 ) error range on average. This pilot study demonstrates the potential of developing an algorithm for the accurate assignment of 1 H NMR chemical shifts based solely on chemically defined constraints.
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Affiliation(s)
- Panteleimon G. Takis
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
- National Phenome Centre, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
| | - Varvara A. Aggelidou
- Department of Biological Applications and TechnologiesUniversity of IoanninaIoanninaGreece
| | - Caroline J. Sands
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
- National Phenome Centre, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
| | - Alexandra Louka
- Department of Clinical and Experimental Epilepsy, Queen Square Institute of NeurologyUniversity College LondonLondonUK
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Catalán J, Yánez-Ortiz I, Martínez-Rodero I, Mateo-Otero Y, Nolis P, Yeste M, Miró J. Comparison of the metabolite profile of donkey and horse seminal plasma and its relationship with sperm viability and motility. Res Vet Sci 2023; 165:105046. [PMID: 37883856 DOI: 10.1016/j.rvsc.2023.105046] [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: 07/25/2023] [Revised: 09/25/2023] [Accepted: 10/05/2023] [Indexed: 10/28/2023]
Abstract
Previous research revealed that several seminal plasma (SP) metabolites are related to sperm functionality, fertility, and preservation. While it is understood that variations between species exist, whether the SP metabolome differs between donkeys and horses has not been previously investigated. The aim of this work, therefore, was to characterize and compare donkey and horse SP metabolites using nuclear magnetic resonance (NMR) spectroscopy, and relate them to sperm viability and motility. For this purpose, ejaculates from 18 different donkeys and 18 different horses were collected and separated into two aliquots: one for harvesting the SP by centrifugation and obtaining the metabolic profile through NMR, and the other for evaluating sperm viability and motility. Based on total motility and sperm viability, samples were classified as with good (GQ) or poor (PQ) quality. The metabolomic profile of donkey and horse SP revealed the presence of 28 metabolites, which coincided in the two species. Yet, differences between horses and donkeys were observed in the concentration of 18 of these 28 metabolites, as well as between ejaculates classified as GQ or PQ and in the relationship of metabolites with sperm motility and viability. These findings suggest that sperm from donkeys and horses differ in their metabolism and energetic requirements, and that the concentration of specific SP metabolites may be related to sperm functionality. Further research should shed light on the metabolic needs of donkey and horse sperm, and evaluate how the knowledge collected from the contribution of these metabolites can help improve semen preservation in the two species.
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Affiliation(s)
- Jaime Catalán
- Biotechnology of Animal and Human Reproduction (TechnoSperm), Institute of Food and Agricultural Technology, University of Girona, ES-17003 Girona, Spain; Unit of Cell Biology, Department of Biology, Faculty of Sciences, University of Girona, ES-17003 Girona, Spain; Unit of Animal Reproduction, Department of Animal Medicine and Surgery, Faculty of Veterinary Medicine, Autonomous University of Barcelona, ES-08193 Cerdanyola del Vallès, Barcelona, Spain
| | - Iván Yánez-Ortiz
- Biotechnology of Animal and Human Reproduction (TechnoSperm), Institute of Food and Agricultural Technology, University of Girona, ES-17003 Girona, Spain; Unit of Cell Biology, Department of Biology, Faculty of Sciences, University of Girona, ES-17003 Girona, Spain; Unit of Animal Reproduction, Department of Animal Medicine and Surgery, Faculty of Veterinary Medicine, Autonomous University of Barcelona, ES-08193 Cerdanyola del Vallès, Barcelona, Spain
| | - Iris Martínez-Rodero
- Unit of Animal Reproduction, Department of Animal Medicine and Surgery, Faculty of Veterinary Medicine, Autonomous University of Barcelona, ES-08193 Cerdanyola del Vallès, Barcelona, Spain
| | - Yentel Mateo-Otero
- Biotechnology of Animal and Human Reproduction (TechnoSperm), Institute of Food and Agricultural Technology, University of Girona, ES-17003 Girona, Spain; Unit of Cell Biology, Department of Biology, Faculty of Sciences, University of Girona, ES-17003 Girona, Spain
| | - Pau Nolis
- Nuclear Magnetic Resonance Facility, Autonomous University of Barcelona, Bellaterra, ES-08193, Cerdanyola del Vallès, Spain
| | - Marc Yeste
- Biotechnology of Animal and Human Reproduction (TechnoSperm), Institute of Food and Agricultural Technology, University of Girona, ES-17003 Girona, Spain; Unit of Cell Biology, Department of Biology, Faculty of Sciences, University of Girona, ES-17003 Girona, Spain; Catalan Institution for Research and Advanced Studies (ICREA), ES-08010 Barcelona, Spain.
| | - Jordi Miró
- Unit of Animal Reproduction, Department of Animal Medicine and Surgery, Faculty of Veterinary Medicine, Autonomous University of Barcelona, ES-08193 Cerdanyola del Vallès, Barcelona, Spain.
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43
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Wevers D, Ramautar R, Clark C, Hankemeier T, Ali A. Opportunities and challenges for sample preparation and enrichment in mass spectrometry for single-cell metabolomics. Electrophoresis 2023; 44:2000-2024. [PMID: 37667867 DOI: 10.1002/elps.202300105] [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: 05/11/2023] [Revised: 08/08/2023] [Accepted: 08/19/2023] [Indexed: 09/06/2023]
Abstract
Single-cell heterogeneity in metabolism, drug resistance and disease type poses the need for analytical techniques for single-cell analysis. As the metabolome provides the closest view of the status quo in the cell, studying the metabolome at single-cell resolution may unravel said heterogeneity. A challenge in single-cell metabolome analysis is that metabolites cannot be amplified, so one needs to deal with picolitre volumes and a wide range of analyte concentrations. Due to high sensitivity and resolution, MS is preferred in single-cell metabolomics. Large numbers of cells need to be analysed for proper statistics; this requires high-throughput analysis, and hence automation of the analytical workflow. Significant advances in (micro)sampling methods, CE and ion mobility spectrometry have been made, some of which have been applied in high-throughput analyses. Microfluidics has enabled an automation of cell picking and metabolite extraction; image recognition has enabled automated cell identification. Many techniques have been used for data analysis, varying from conventional techniques to novel combinations of advanced chemometric approaches. Steps have been set in making data more findable, accessible, interoperable and reusable, but significant opportunities for improvement remain. Herein, advances in single-cell analysis workflows and data analysis are discussed, and recommendations are made based on the experimental goal.
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Affiliation(s)
- Dirk Wevers
- Wageningen University and Research, Wageningen, The Netherlands
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
| | - Rawi Ramautar
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
| | - Charlie Clark
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
| | - Thomas Hankemeier
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
| | - Ahmed Ali
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
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44
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Vignoli A, Tenori L. NMR-based metabolomics in Alzheimer's disease research: a review. Front Mol Biosci 2023; 10:1308500. [PMID: 38099198 PMCID: PMC10720579 DOI: 10.3389/fmolb.2023.1308500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 11/21/2023] [Indexed: 12/17/2023] Open
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder and represents the most common cause of dementia in the elderly population worldwide. Currently, there is no cure for AD, and the continuous increase in the number of susceptible individuals poses one of the most significant emerging threats to public health. However, the molecular pathways involved in the onset and progression of AD are not fully understood. This information is crucial for developing less invasive diagnostic instruments and discovering novel potential therapeutic targets. Metabolomics studies the complete ensemble of endogenous and exogenous metabolites present in biological specimens and may provide an interesting approach to identify alterations in multiple biochemical processes associated with AD onset and evolution. In this mini review, we summarize the results from metabolomic studies conducted using nuclear magnetic resonance (NMR) spectroscopy on human biological samples (blood derivatives, cerebrospinal fluid, urine, saliva, and tissues) from AD patients. We describe the metabolic alterations identified in AD patients compared to controls and to patients diagnosed with mild cognitive impairment (MCI). Moreover, we discuss the challenges and issues associated with the application of NMR-based metabolomics in the context of AD research.
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Affiliation(s)
- Alessia Vignoli
- Department of Chemistry “Ugo Schiff”, University of Florence, Sesto Fiorentino, Italy
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy
| | - Leonardo Tenori
- Department of Chemistry “Ugo Schiff”, University of Florence, Sesto Fiorentino, Italy
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy
- Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), Sesto Fiorentino, Italy
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45
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Praud C, Ribay V, Dey A, Charrier B, Mandral J, Farjon J, Dumez JN, Giraudeau P. Optimization of heteronuclear ultrafast 2D NMR for the study of complex mixtures hyperpolarized by dynamic nuclear polarization. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2023; 15:6209-6219. [PMID: 37942549 DOI: 10.1039/d3ay01681a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
Hyperpolarized 13C NMR at natural abundance, based on dissolution dynamic nuclear polarization (d-DNP), provides rich, sensitive and repeatable 13C NMR fingerprints of complex mixtures. However, the sensitivity enhancement is associated with challenges such as peak overlap and the difficulty to assign hyperpolarized 13C signals. Ultrafast (UF) 2D NMR spectroscopy makes it possible to record heteronuclear 2D maps of d-DNP hyperpolarized samples. Heteronuclear UF 2D NMR can provide correlation peaks that link quaternary carbons and protons through long-range scalar couplings. Here, we report the analytical assessment of an optimized UF long-range HETCOR pulse sequence, applied to the detection of metabolic mixtures at natural abundance and hyperpolarized by d-DNP, based on repeatability and sensitivity considerations. We show that metabolite-dependent limits of quantification in the range of 1-50 mM (in the sample before dissolution) can be achieved, with a repeatability close to 10% and a very good linearity. We provide a detailed comparison of such analytical performance in two different dissolution solvents, D2O and MeOD. The reported pulse sequence appears as an useful analytical tool to facilitate the assignment and integration of metabolite signals in hyperpolarized complex mixtures.
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Affiliation(s)
- Clément Praud
- Nantes Université, CNRS, CEISAM, UMR 6230, F-44000 Nantes, France.
| | - Victor Ribay
- Nantes Université, CNRS, CEISAM, UMR 6230, F-44000 Nantes, France.
| | - Arnab Dey
- Nantes Université, CNRS, CEISAM, UMR 6230, F-44000 Nantes, France.
| | - Benoît Charrier
- Nantes Université, CNRS, CEISAM, UMR 6230, F-44000 Nantes, France.
| | - Joris Mandral
- Nantes Université, CNRS, CEISAM, UMR 6230, F-44000 Nantes, France.
| | - Jonathan Farjon
- Nantes Université, CNRS, CEISAM, UMR 6230, F-44000 Nantes, France.
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46
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Mix T, Janneschütz J, Ludwig R, Eichbaum J, Fischer M, Hackl T. From Nontargeted to Targeted Analysis: Feature Selection in the Differentiation of Truffle Species ( Tuber spp.) Using 1H NMR Spectroscopy and Support Vector Machine. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2023; 71:18074-18084. [PMID: 37934755 DOI: 10.1021/acs.jafc.3c05786] [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: 11/09/2023]
Abstract
The price of different truffle types varies according to their culinary value, sometimes by more than a factor of 10. Nonprofessionals can hardly distinguish visually the species within the white or black truffles, making the possibility of food fraud very easy. Therefore, the identification of different truffle species (Tuber spp.) is an analytical task that could be solved in this study. The polar extract from a total of 80 truffle samples was analyzed by 1H NMR spectroscopy in combination with chemometric methods covering five commercially relevant species. All classification models were validated applying a repeated nested cross-validation. In direct comparison, the two very similar looking and closely related black representatives Tuber melanosporum and Tuber indicum could be classified 100% correctly. The most expensive truffle Tuber magnatum could be distinguished 100% from the other relevant white truffle Tuber borchii. In addition, signals for a potential Tuber borchii and a potential Tuber melanosporum marker for targeted approaches could be detected, and the corresponding molecules were identified as betaine and ribonate. A model covering all five truffle species Tuber aestivum, Tuber borchii, Tuber indicum, Tuber magnatum, and Tuber melanosporum was able to correctly discriminate between each of the species.
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Affiliation(s)
- Thorsten Mix
- Institute of Organic Chemistry, University of Hamburg, Martin-Luther-King-Platz 6, 20146 Hamburg, Germany
| | - Jasmin Janneschütz
- Department of Pharmaceutical Sciences, University of Vienna, Josef-Holaubek-Platz 2, Vienna 1090, Austria
| | - Rami Ludwig
- Institute of Organic Chemistry, University of Hamburg, Martin-Luther-King-Platz 6, 20146 Hamburg, Germany
| | - Julia Eichbaum
- Institute of Organic Chemistry, University of Hamburg, Martin-Luther-King-Platz 6, 20146 Hamburg, Germany
| | - Markus Fischer
- Hamburg School of Food Science, Institute of Food Chemistry, University of Hamburg, Grindelallee 117, 20146 Hamburg, Germany
| | - Thomas Hackl
- Institute of Organic Chemistry, University of Hamburg, Martin-Luther-King-Platz 6, 20146 Hamburg, Germany
- Hamburg School of Food Science, Institute of Food Chemistry, University of Hamburg, Grindelallee 117, 20146 Hamburg, Germany
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47
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Ghosh Biswas R, Bermel W, Jenne A, Soong R, Simpson MJ, Simpson AJ. HR-MAS DREAMTIME NMR for Slow Spinning ex Vivo and in Vivo Samples. Anal Chem 2023; 95:17054-17063. [PMID: 37934172 DOI: 10.1021/acs.analchem.3c03800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2023]
Abstract
HR-MAS NMR is a powerful tool, capable of monitoring molecular changes in intact heterogeneous samples. However, one of the biggest limitations of 1H NMR is its narrow spectral width which leads to considerable overlap in complex natural samples. DREAMTIME NMR is a highly selective technique that allows users to isolate suites of metabolites from congested spectra. This permits targeted metabolomics by NMR and is ideal for monitoring specific processes. To date, DREAMTIME has only been employed in solution-state NMR, here it is adapted for HR-MAS applications. At high spinning speeds (>5 kHz), DREAMTIME works with minimal modifications. However, spinning over 3-4 kHz leads to cell lysis, and if maintaining sample integrity is necessary, slower spinning (<2.5 kHz) is required. Very slow spinning (≤500 Hz) is advantageous for in vivo analysis to increase organism survival; however, sidebands from water pose a problem. To address this, a version of DREAMTIME, termed DREAMTIME-SLOWMAS, is introduced. Both techniques are compared at 2500, 500, and 50 Hz, using ex vivo worm tissue. Following this, DREAMTIME-SLOWMAS is applied to monitor key metabolites of anoxic stress in living shrimp at 500 Hz. Thus, standard DREAMTIME works well under MAS conditions and is recommended for samples reswollen in D2O or spun >2500 Hz. For slow spinning in vivo or intact tissue samples, DREAMTIME-SLOWMAS provides an excellent way to target process-specific metabolites while maintaining sample integrity. Overall, DREAMTIME should find widespread application wherever targeted molecular information is required from complex samples with a high degree of spectral overlap.
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Affiliation(s)
| | - Wolfgang Bermel
- Bruker Biospin GmbH, Rudolf-Plank-Str. 23, 76275 Ettlingen, Germany
| | - Amy Jenne
- Environmental NMR Centre, University of Toronto, Toronto, ON M1C 1A4, Canada
| | - Ronald Soong
- Environmental NMR Centre, University of Toronto, Toronto, ON M1C 1A4, Canada
| | - Myrna J Simpson
- Environmental NMR Centre, University of Toronto, Toronto, ON M1C 1A4, Canada
| | - Andre J Simpson
- Environmental NMR Centre, University of Toronto, Toronto, ON M1C 1A4, Canada
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48
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Adeniji A, El-Hage R, Brinkman MC, El-Hellani A. Nontargeted Analysis in Tobacco Research: Challenges and Opportunities. Chem Res Toxicol 2023; 36:1656-1665. [PMID: 37903095 DOI: 10.1021/acs.chemrestox.3c00150] [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: 11/01/2023]
Abstract
Tobacco products are evolving at a pace that has outstripped tobacco control, leading to a high prevalence of tobacco use in the population. Researchers have been tirelessly developing suitable techniques to assess these products' emissions, toxicity, and public health impact. The nonclinical testing of tobacco products to assess the chemical profile of emissions is needed for evidence-based regulations. This testing has largely relied on targeted analytical methods that focus on constituent lists that may fall short in determining the toxicity of newly designed tobacco products. Nontargeted analysis (NTA), or the process of identifying and quantifying compounds within a complex matrix without prior knowledge of its chemical composition, is a promising technique for tobacco regulation, but it is not without challenges. The lack of standardized methods for sample generation, sample preparation, chromatographic separation, compound identification, and data analysis and reporting must be addressed so that the quality and reproducibility of the data generated by NTA can be benchmarked. This review discusses the challenges and highlights the opportunities of NTA in studying tobacco product constituents and emissions.
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Affiliation(s)
- Ayomipo Adeniji
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, Ohio 43210, United States
- Center for Tobacco Research, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio 43214, United States
| | - Rachel El-Hage
- Department of Chemistry, Faculty of Arts and Sciences, American University of Beirut, Beirut 1107 2020, Lebanon
- Center for the Study of Tobacco Products, Virginia Commonwealth University, Richmond, Virginia 23220, United States
| | - Marielle C Brinkman
- Division of Epidemiology, College of Public Health, The Ohio State University, Columbus, Ohio 43210, United States
- Center for Tobacco Research, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio 43214, United States
| | - Ahmad El-Hellani
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, Ohio 43210, United States
- Center for Tobacco Research, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio 43214, United States
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49
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Shastry A, Dunham-Snary K. Metabolomics and mitochondrial dysfunction in cardiometabolic disease. Life Sci 2023; 333:122137. [PMID: 37788764 DOI: 10.1016/j.lfs.2023.122137] [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: 08/01/2023] [Revised: 09/21/2023] [Accepted: 09/29/2023] [Indexed: 10/05/2023]
Abstract
Circulating metabolites are indicators of systemic metabolic dysfunction and can be detected through contemporary techniques in metabolomics. These metabolites are involved in numerous mitochondrial metabolic processes including glycolysis, fatty acid β-oxidation, and amino acid catabolism, and changes in the abundance of these metabolites is implicated in the pathogenesis of cardiometabolic diseases (CMDs). Epigenetic regulation and direct metabolite-protein interactions modulate metabolism, both within cells and in the circulation. Dysfunction of multiple mitochondrial components stemming from mitochondrial DNA mutations are implicated in disease pathogenesis. This review will summarize the current state of knowledge regarding: i) the interactions between metabolites found within the mitochondrial environment during CMDs, ii) various metabolites' effects on cellular and systemic function, iii) how harnessing the power of metabolomic analyses represents the next frontier of precision medicine, and iv) how these concepts integrate to expand the clinical potential for translational cardiometabolic medicine.
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Affiliation(s)
- Abhishek Shastry
- Department of Medicine, Queen's University, Kingston, ON, Canada
| | - Kimberly Dunham-Snary
- Department of Medicine, Queen's University, Kingston, ON, Canada; Department of Biomedical & Molecular Sciences, Queen's University, Kingston, ON, Canada.
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50
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Domingo-Ortí I, Ferrer-Torres P, Armiñán A, Vicent MJ, Pineda-Lucena A, Palomino-Schätzlein M. NMR-Based Mitochondria Metabolomic Profiling: A New Approach To Reveal Cancer-Associated Alterations. Anal Chem 2023; 95:16539-16548. [PMID: 37906730 DOI: 10.1021/acs.analchem.3c02432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Studying metabolism may assist in understanding the relationship between normal and dysfunctional mitochondrial activity and various diseases, such as neurodegenerative, cardiovascular, autoimmune, psychiatric, and cancer. Nuclear magnetic resonance-based metabolomics represents a powerful method to characterize the chemical content of complex samples and has been successfully applied to studying a range of conditions. However, an optimized methodology is lacking for analyzing isolated organelles, such as mitochondria. In this study, we report the development of a protocol to metabolically profile mitochondria from healthy, tumoral, and metastatic tissues. Encouragingly, this approach provided quantitative information about up to 45 metabolites in one comprehensive and robust analysis. Our results revealed significant differences between whole-cell and mitochondrial metabolites, which supports a more refined approach to metabolic analysis. We applied our optimized methodology to investigate aggressive and metastatic breast cancer in mouse tissues, discovering that lung mitochondria exhibit an altered metabolic fingerprint. Specific amino acids, organic acids, and lipids showed significant increases in levels when compared with mitochondria from healthy tissues. Our optimized methodology could promote a better understanding of the molecular mechanisms underlying breast cancer aggressiveness and mitochondrial-related diseases and support the optimization of new advanced therapies.
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Affiliation(s)
- Inés Domingo-Ortí
- Centro de Investigación Príncipe Felipe, Polymer Therapeutics Laboratory and CIBERONC, Valencia 46012, Spain
- NMR Facility, Centro de Investigación Príncipe Felipe, Valencia 46012, Spain
- Drug Discovery Unit, Instituto de Investigación Sanitaria La Fe, Valencia 46026, Spain
| | | | - Ana Armiñán
- Centro de Investigación Príncipe Felipe, Polymer Therapeutics Laboratory and CIBERONC, Valencia 46012, Spain
| | - María J Vicent
- Centro de Investigación Príncipe Felipe, Polymer Therapeutics Laboratory and CIBERONC, Valencia 46012, Spain
| | - Antonio Pineda-Lucena
- Drug Discovery Unit, Instituto de Investigación Sanitaria La Fe, Valencia 46026, Spain
- Molecular Therapeutics Program, CIMA Universidad de Navarra, Pamplona 31008, Spain
| | - Martina Palomino-Schätzlein
- NMR Facility, Centro de Investigación Príncipe Felipe, Valencia 46012, Spain
- ProtoQSAR, CEEI, Parque Tecnológico Valencia, Paterna 46980, Spain
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