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Owens DJ, Bennett S. An exercise physiologist's guide to metabolomics. Exp Physiol 2024; 109:1066-1079. [PMID: 38358958 PMCID: PMC11215473 DOI: 10.1113/ep091059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 01/25/2024] [Indexed: 02/17/2024]
Abstract
The field of exercise physiology has undergone significant technological advancements since the pioneering works of exercise physiologists in the early to mid-20th century. Historically, the ability to detect metabolites in biofluids from exercising participants was limited to single-metabolite analyses. However, the rise of metabolomics, a discipline focused on the comprehensive analysis of metabolites within a biological system, has facilitated a more intricate understanding of metabolic pathways and networks in exercise. This review explores some of the pivotal technological and bioinformatic advancements that have propelled metabolomics to the forefront of exercise physiology research. Metabolomics offers a unique 'fingerprint' of cellular activity, offering a broader spectrum than traditional single-metabolite assays. Techniques, including mass spectrometry and nuclear magnetic resonance spectroscopy, have significantly improved the speed and sensitivity of metabolite analysis. Nonetheless, challenges persist, including study design and data interpretation issues. This review aims to serve as a guide for exercise physiologists to facilitate better research design, data analysis and interpretation within metabolomics. The potential of metabolomics in bridging the gap between genotype and phenotype is emphasised, underscoring the critical importance of careful study design and the selection of appropriate metabolomics techniques. Furthermore, the paper highlights the need to deeply understand the broader scientific context to discern meaningful metabolic changes. The emerging field of fluxomics, which seeks to quantify metabolic reaction rates, is also introduced as a promising avenue for future research.
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Affiliation(s)
- Daniel J. Owens
- Research Institute of Sport and Exercise Science (RISES)Liverpool John Moores UniversityLiverpoolUK
| | - Samuel Bennett
- Center for Biological Clocks Research, Department of BiologyTexas A&M UniversityCollege StationTexasUSA
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Febra C, Saraiva J, Vaz F, Macedo J, Al-Hroub HM, Semreen MH, Maio R, Gil V, Soares N, Penque D. Acute venous thromboembolism plasma and red blood cell metabolomic profiling reveals potential new early diagnostic biomarkers: observational clinical study. J Transl Med 2024; 22:200. [PMID: 38402378 PMCID: PMC10894498 DOI: 10.1186/s12967-024-04883-8] [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: 10/28/2023] [Accepted: 01/10/2024] [Indexed: 02/26/2024] Open
Abstract
BACKGROUND Venous thromboembolism (VTE) is a leading cause of cardiovascular mortality. The diagnosis of acute VTE is based on complex imaging exams due to the lack of biomarkers. Recent multi-omics based research has contributed to the development of novel biomarkers in cardiovascular diseases. Our aim was to determine whether patients with acute VTE have differences in the metabolomic profile compared to non-acute VTE. METHODS This observational trial included 62 patients with clinical suspicion of acute deep vein thrombosis or pulmonary embolism, admitted to the emergency room. There were 50 patients diagnosed with acute VTE and 12 with non-acute VTE conditions and no significant differences were found between the two groups for clinical and demographic characteristics. Metabolomics assays identified and quantified a final number of 91 metabolites in plasma and 55 metabolites in red blood cells (RBCs). Plasma from acute VTE patients expressed tendency to a specific metabolomic signature, with univariate analyses revealing 23 significantly different molecules between acute VTE patients and controls (p < 0.05). The most relevant metabolic pathway with the strongest impact on the acute VTE phenotype was D-glutamine and D-glutamate (p = 0.001, false discovery rate = 0.06). RBCs revealed a specific metabolomic signature in patients with a confirmed diagnosis of DVT or PE that distinguished them from other acutely diseased patients, represented by 20 significantly higher metabolites and four lower metabolites. Three of those metabolites revealed high performant ROC curves, including adenosine 3',5'-diphosphate (AUC 0.983), glutathione (AUC 0.923), and adenine (AUC 0.91). Overall, the metabolic pathway most impacting to the differences observed in the RBCs was the purine metabolism (p = 0.000354, false discovery rate = 0.68). CONCLUSIONS Our findings show that metabolite differences exist between acute VTE and nonacute VTE patients admitted to the ER in the early phases. Three potential biomarkers obtained from RBCs showed high performance for acute VTE diagnosis. Further studies should investigate accessible laboratory methods for the future daily practice usefulness of these metabolites for the early diagnosis of acute VTE in the ER.
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Affiliation(s)
- Cláudia Febra
- Department of Intensive Care, Hospital da Luz Lisboa, Lisbon, Portugal.
- Faculty of Medicine, University of Porto, Porto, Portugal.
- Human Genetics Department, Instituto Nacional de Saúde Dr. Ricardo Jorge (INSA), Lisbon, Portugal.
| | - Joana Saraiva
- Human Genetics Department, Instituto Nacional de Saúde Dr. Ricardo Jorge (INSA), Lisbon, Portugal
- Center for Toxicogenomics and Human Health (ToxOmics), NOVA Medical School-FCM, UNL, Lisbon, Portugal
- NOVA School of Science and Technology, Universidade Nova de Lisboa, Lisbon, Portugal
| | - Fátima Vaz
- Human Genetics Department, Instituto Nacional de Saúde Dr. Ricardo Jorge (INSA), Lisbon, Portugal
- Center for Toxicogenomics and Human Health (ToxOmics), NOVA Medical School-FCM, UNL, Lisbon, Portugal
| | - João Macedo
- NOVA School of Science and Technology, Universidade Nova de Lisboa, Lisbon, Portugal
| | - Hamza Mohammad Al-Hroub
- Department of Medical Chemistry, College of Pharmacy, University of Sharjah, Sharjah, United Arab Emirates
- Sharjah Institute for Medical Research, University of Sharjah, Sharjah, United Arab Emirates
| | - Mohammad Harb Semreen
- Department of Medical Chemistry, College of Pharmacy, University of Sharjah, Sharjah, United Arab Emirates
- Sharjah Institute for Medical Research, University of Sharjah, Sharjah, United Arab Emirates
| | - Rui Maio
- Department of General Surgery, Hospital da Luz Lisboa, Lisbon, Portugal
| | - Vitor Gil
- Faculty of Medicine, University of Porto, Porto, Portugal
- Center of Cardiovascular Risk and Thrombosis, Hospital da Luz Torres de Lisboa, Lisbon, Portugal
| | - Nelson Soares
- Human Genetics Department, Instituto Nacional de Saúde Dr. Ricardo Jorge (INSA), Lisbon, Portugal.
- NOVA School of Science and Technology, Universidade Nova de Lisboa, Lisbon, Portugal.
- Department of Medical Chemistry, College of Pharmacy, University of Sharjah, Sharjah, United Arab Emirates.
| | - Deborah Penque
- Human Genetics Department, Instituto Nacional de Saúde Dr. Ricardo Jorge (INSA), Lisbon, Portugal.
- Center for Toxicogenomics and Human Health (ToxOmics), NOVA Medical School-FCM, UNL, Lisbon, Portugal.
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Bauman JS, Pizzey R, Beckmann M, Villarreal-Ramos B, King J, Hopkins B, Rooke D, Hewinson G, Mur LAJ. Untargeted metabolomic analysis of thoracic blood from badgers indicate changes linked to infection with bovine tuberculosis (Mycobacterium bovis): a pilot study. Metabolomics 2022; 18:61. [PMID: 35896834 PMCID: PMC9329164 DOI: 10.1007/s11306-022-01915-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 06/27/2022] [Indexed: 11/17/2022]
Abstract
INTRODUCTION Mycobacterium bovis, the causative agent of bovine tuberculosis (bTB) in cattle, represents a major disease burden to UK cattle farming, with considerable costs associated with its control. The European badger (Meles meles) is a known wildlife reservoir for bTB and better knowledge of the epidemiology of bTB through testing wildlife is required for disease control. Current tests available for the diagnosis of bTB in badgers are limited by cost, processing time or sensitivities. MATERIALS AND METHODS We assessed the ability of flow infusion electrospray-high-resolution mass spectrometry (FIE-HRMS) to determine potential differences between infected and non-infected badgers based on thoracic blood samples obtained from badgers found dead in Wales. Thoracic blood samples were autoclaved for handling in a containment level 2 (CL2) hazard laboratory. RESULTS Here we show the major differences associated with with M. bovis infection were changes to folate, pyrimidine, histidine, glycerophospholipid and phosphonate metabolism. CONCLUSIONS Our studies have indicated differences in the metabolomic signature of badgers found dead in relation to their infection status, suggesting metabolomics could hold potential for developing novel diagnostics for bTB in badgers. As well as highlighting a potential way to handle samples containing a highly pathogenic agent at CL2 for metabolomics studies.
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Affiliation(s)
- James Scott Bauman
- Institute of Biological, Environmental and Rural Science, Aberystwyth University, Aberystwyth, SY23 3DA, Ceredigion, UK
| | - Richard Pizzey
- Institute of Biological, Environmental and Rural Science, Aberystwyth University, Aberystwyth, SY23 3DA, Ceredigion, UK
| | - Manfred Beckmann
- Institute of Biological, Environmental and Rural Science, Aberystwyth University, Aberystwyth, SY23 3DA, Ceredigion, UK
| | - Bernardo Villarreal-Ramos
- Institute of Biological, Environmental and Rural Science, Aberystwyth University, Aberystwyth, SY23 3DA, Ceredigion, UK
- Centre of Excellence for Bovine Tuberculosis, Aberystwyth University, Aberystwyth, SY23 3AR, Ceredigion, UK
- TB Research Group, Animal and Plant Health Agency, New Haw, Addlestone, KT15 3NB, Surrey, UK
| | - Jonathan King
- Wales Veterinary Science Centre, Y Buarth, Aberystwyth, SY23 1ND, Ceredigion, UK
| | - Beverley Hopkins
- Wales Veterinary Science Centre, Y Buarth, Aberystwyth, SY23 1ND, Ceredigion, UK
| | | | - Glyn Hewinson
- Institute of Biological, Environmental and Rural Science, Aberystwyth University, Aberystwyth, SY23 3DA, Ceredigion, UK
- Centre of Excellence for Bovine Tuberculosis, Aberystwyth University, Aberystwyth, SY23 3AR, Ceredigion, UK
| | - Luis A J Mur
- Institute of Biological, Environmental and Rural Science, Aberystwyth University, Aberystwyth, SY23 3DA, Ceredigion, UK.
- Aberystwyth University, B2.03 Edward Llwyd, Penglais, Aberystwyth, SY23 3FL, UK.
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Scott-Baumann J, Pizzey R, Beckmann M, Villarreal-Ramos B, King J, Hopkins B, Rooke D, Hewinson G, Mur LAJ. Metabotyping the Welsh population of badgers based on thoracic fluid. Metabolomics 2022; 18:30. [PMID: 35524831 PMCID: PMC9079023 DOI: 10.1007/s11306-022-01888-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 04/11/2022] [Indexed: 11/28/2022]
Abstract
INTRODUCTION The European badger (Meles meles) is a known wildlife reservoir for bovine tuberculosis (bTB) and a better understanding of the epidemiology of bTB in this wildlife species is required for disease control in both wild and farmed animals. Flow infusion electrospray-high-resolution mass spectrometry (FIE-HRMS) may potentially identify novel metabolite biomarkers based on which new, rapid, and sensitive point of care tests for bTB infection could be developed. OBJECTIVES In this foundational study, we engaged on assessing the baseline metabolomic variation in the non-bTB infected badger population ("metabotyping") across Wales. METHODS FIE-HRMS was applied on thoracic fluid samples obtained by post-mortem of bTB negative badgers (n = 285) which were part of the Welsh Government 'All Wales Badger Found Dead' study. RESULTS Using principal component analysis and partial least squares-discriminant analyses, the major sources of variation were linked to sex, and to a much lesser extent age, as indicated by tooth wear. Within the female population, variation was seen between lactating and non-lactating individuals. No significant variation linked to the presence of bite wounds, obvious lymphatic lesions or geographical region of origin was observed. CONCLUSION Future metabolomic work when making comparisons between bTB infected and non-infected badger samples will only need be sex-matched and could focus on males only, to avoid lactation bias.
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Affiliation(s)
- James Scott-Baumann
- Institute of Biological, Environmental and Rural Science, Aberystwyth University, Aberystwyth, SY23 3DA, Ceredigion, UK
| | - Richard Pizzey
- Institute of Biological, Environmental and Rural Science, Aberystwyth University, Aberystwyth, SY23 3DA, Ceredigion, UK
| | - Manfred Beckmann
- Institute of Biological, Environmental and Rural Science, Aberystwyth University, Aberystwyth, SY23 3DA, Ceredigion, UK
| | - Bernardo Villarreal-Ramos
- Institute of Biological, Environmental and Rural Science, Aberystwyth University, Aberystwyth, SY23 3DA, Ceredigion, UK
- Centre of Excellence for Bovine Tuberculosis, Aberystwyth University, Ceredigion, SY23 3AR, UK
- TB Research Group, Animal and Plant Health Agency, New Haw, Addlestone, KT15 3NB, Surrey, UK
| | - Jonathan King
- Wales Veterinary Science Centre, Y Buarth, Aberystwyth, SY23 1ND, Ceredigion, UK
| | - Beverley Hopkins
- Wales Veterinary Science Centre, Y Buarth, Aberystwyth, SY23 1ND, Ceredigion, UK
| | | | - Glyn Hewinson
- Institute of Biological, Environmental and Rural Science, Aberystwyth University, Aberystwyth, SY23 3DA, Ceredigion, UK
- Centre of Excellence for Bovine Tuberculosis, Aberystwyth University, Ceredigion, SY23 3AR, UK
| | - Luis A J Mur
- Institute of Biological, Environmental and Rural Science, Aberystwyth University, Aberystwyth, SY23 3DA, Ceredigion, UK.
- , B2.03 Edward Llwyd, Penglais, Aberystwyth, SY23 3FL, UK.
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Gómez-Cebrián N, Vázquez Ferreiro P, Carrera Hueso FJ, Poveda Andrés JL, Puchades-Carrasco L, Pineda-Lucena A. Pharmacometabolomics by NMR in Oncology: A Systematic Review. Pharmaceuticals (Basel) 2021; 14:ph14101015. [PMID: 34681239 PMCID: PMC8539252 DOI: 10.3390/ph14101015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 09/28/2021] [Accepted: 09/29/2021] [Indexed: 12/14/2022] Open
Abstract
Pharmacometabolomics (PMx) studies aim to predict individual differences in treatment response and in the development of adverse effects associated with specific drug treatments. Overall, these studies inform us about how individuals will respond to a drug treatment based on their metabolic profiles obtained before, during, or after the therapeutic intervention. In the era of precision medicine, metabolic profiles hold great potential to guide patient selection and stratification in clinical trials, with a focus on improving drug efficacy and safety. Metabolomics is closely related to the phenotype as alterations in metabolism reflect changes in the preceding cascade of genomics, transcriptomics, and proteomics changes, thus providing a significant advance over other omics approaches. Nuclear Magnetic Resonance (NMR) is one of the most widely used analytical platforms in metabolomics studies. In fact, since the introduction of PMx studies in 2006, the number of NMR-based PMx studies has been continuously growing and has provided novel insights into the specific metabolic changes associated with different mechanisms of action and/or toxic effects. This review presents an up-to-date summary of NMR-based PMx studies performed over the last 10 years. Our main objective is to discuss the experimental approaches used for the characterization of the metabolic changes associated with specific therapeutic interventions, the most relevant results obtained so far, and some of the remaining challenges in this area.
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Affiliation(s)
- Nuria Gómez-Cebrián
- Drug Discovery Unit, Instituto de Investigación Sanitaria La Fe, 46026 Valencia, Spain;
| | | | | | | | - Leonor Puchades-Carrasco
- Drug Discovery Unit, Instituto de Investigación Sanitaria La Fe, 46026 Valencia, Spain;
- Correspondence: (L.P.-C.); (A.P.-L.); Tel.: +34-963246713 (L.P.-C.)
| | - Antonio Pineda-Lucena
- Molecular Therapeutics Program, Centro de Investigación Médica Aplicada, 31008 Navarra, Spain
- Correspondence: (L.P.-C.); (A.P.-L.); Tel.: +34-963246713 (L.P.-C.)
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Audano M, Pedretti S, Ligorio S, Giavarini F, Caruso D, Mitro N. Investigating metabolism by mass spectrometry: From steady state to dynamic view. JOURNAL OF MASS SPECTROMETRY : JMS 2021; 56:e4658. [PMID: 33084147 DOI: 10.1002/jms.4658] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 09/10/2020] [Accepted: 09/14/2020] [Indexed: 06/11/2023]
Abstract
Metabolism is the set of life-sustaining reactions in organisms. These biochemical reactions are organized in metabolic pathways, in which one metabolite is converted through a series of steps catalyzed by enzymes in another chemical compound. Metabolic reactions are categorized as catabolic, the breaking down of metabolites to produce energy, and/or anabolic, the synthesis of compounds that consume energy. The balance between catabolism of the preferential fuel substrate and anabolism defines the overall metabolism of a cell or tissue. Metabolomics is a powerful tool to gain new insights contributing to the identification of complex molecular mechanisms in the field of biomedical research, both basic and translational. The enormous potential of this kind of analyses consists of two key aspects: (i) the possibility of performing so-called targeted and untargeted experiments through which it is feasible to verify or formulate a hypothesis, respectively, and (ii) the opportunity to run either steady-state analyses to have snapshots of the metabolome at a given time under different experimental conditions or dynamic analyses through the use of labeled tracers. In this review, we will highlight the most important practical (e.g., different sample extraction approaches) and conceptual steps to consider for metabolomic analysis, describing also the main application contexts in which it is used. In addition, we will provide some insights into the most innovative approaches and progress in the field of data analysis and processing, highlighting how this part is essential for the proper extrapolation and interpretation of data.
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Affiliation(s)
- Matteo Audano
- DiSFeB, Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, 20133, Italy
| | - Silvia Pedretti
- DiSFeB, Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, 20133, Italy
| | - Simona Ligorio
- DiSFeB, Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, 20133, Italy
| | - Flavio Giavarini
- DiSFeB, Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, 20133, Italy
| | - Donatella Caruso
- DiSFeB, Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, 20133, Italy
| | - Nico Mitro
- DiSFeB, Dipartimento di Scienze Farmacologiche e Biomolecolari, Università degli Studi di Milano, Milan, 20133, Italy
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Metabolomics: A Tool for Cultivar Phenotyping and Investigation of Grain Crops. AGRONOMY-BASEL 2020. [DOI: 10.3390/agronomy10060831] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The quality of plants is often enhanced for diverse purposes such as improved resistance to environmental pressures, better taste, and higher yields. Considering the world’s dependence on plants (nutrition, medicine, or biofuel), developing new cultivars with superior characteristics is of great importance. As part of the ‘omics’ approaches, metabolomics has been employed to investigate the large number of metabolites present in plant systems under well-defined environmental conditions. Recent advances in the metabolomics field have greatly expanded our understanding of plant metabolism, largely driven by potential application to agricultural systems. The current review presents the workflow for plant metabolome analyses, current knowledge, and future directions of such research as determinants of cultivar phenotypes. Furthermore, the value of metabolome analyses in contemporary crop science is illustrated. Here, metabolomics has provided valuable information in research on grain crops and identified significant biomarkers under different conditions and/or stressors. Moreover, the value of metabolomics has been redefined from simple biomarker identification to a tool for discovering active drivers involved in biological processes. We illustrate and conclude that the rapid advances in metabolomics are driving an explosion of information that will advance modern breeding approaches for grain crops and address problems associated with crop productivity and sustainable agriculture.
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MetaboAnalystR 2.0: From Raw Spectra to Biological Insights. Metabolites 2019; 9:metabo9030057. [PMID: 30909447 PMCID: PMC6468840 DOI: 10.3390/metabo9030057] [Citation(s) in RCA: 206] [Impact Index Per Article: 41.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Revised: 03/20/2019] [Accepted: 03/21/2019] [Indexed: 02/07/2023] Open
Abstract
Global metabolomics based on high-resolution liquid chromatography mass spectrometry (LC-MS) has been increasingly employed in recent large-scale multi-omics studies. Processing and interpretation of these complex metabolomics datasets have become a key challenge in current computational metabolomics. Here, we introduce MetaboAnalystR 2.0 for comprehensive LC-MS data processing, statistical analysis, and functional interpretation. Compared to the previous version, this new release seamlessly integrates XCMS and CAMERA to support raw spectral processing and peak annotation, and also features high-performance implementations of mummichog and GSEA approaches for predictions of pathway activities. The application and utility of the MetaboAnalystR 2.0 workflow were demonstrated using a synthetic benchmark dataset and a clinical dataset. In summary, MetaboAnalystR 2.0 offers a unified and flexible workflow that enables end-to-end analysis of LC-MS metabolomics data within the open-source R environment.
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