Mohd Naeem Mohd Nawi, Ranina Radzi, Azizan Ali, Siti Zubaidah Che Lem, Azlina Zulkapli, Ezarul Faradianna Lokman, Mansor Fazliana, Sreelakshmi Sankara Narayanan, Karuthan Chinna, Mohd Fairulnizal Md Noh, Zulfitri Azuan Mat Daud, Tilakavati Karupaiah
{"title":"啮齿动物血浆中的1H核磁共振(NMR)代谢组学:临床前生物标志物发现的可重复框架。","authors":"Mohd Naeem Mohd Nawi, Ranina Radzi, Azizan Ali, Siti Zubaidah Che Lem, Azlina Zulkapli, Ezarul Faradianna Lokman, Mansor Fazliana, Sreelakshmi Sankara Narayanan, Karuthan Chinna, Mohd Fairulnizal Md Noh, Zulfitri Azuan Mat Daud, Tilakavati Karupaiah","doi":"10.3390/mps8040092","DOIUrl":null,"url":null,"abstract":"<p><p>This protocol paper outlines a robust and reproducible framework for a <sup>1</sup>H nuclear magnetic resonance (NMR) metabolomics analysis of rodent plasma, designed to facilitate preclinical biomarker discovery. The protocol details optimised steps for plasma collection in a preclinical rodent model, sample preparation, and NMR data acquisition using presaturation Carr-Purcell-Meiboom-Gill (PRESAT-CPMG) pulse sequences, ensuring high-quality spectral data and effective suppression of macromolecule signals. Comprehensive spectral processing and metabolite assignment are described, with guidance on multivariate and univariate statistical analyses to identify metabolic changes and potential biomarkers. The framework emphasises methodological rigour and reproducibility, enabling accurate quantification and interpretation of metabolites relevant to disease mechanisms or therapeutic interventions. By providing a standardised approach, this protocol supports longitudinal and translational studies, bridging findings from rodent models to clinical applications and advancing the reliability of metabolomics-based biomarker discovery in preclinical research.</p>","PeriodicalId":18715,"journal":{"name":"Methods and Protocols","volume":"8 4","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12388194/pdf/","citationCount":"0","resultStr":"{\"title\":\"<sup>1</sup>H Nuclear Magnetic Resonance (NMR) Metabolomics in Rodent Plasma: A Reproducible Framework for Preclinical Biomarker Discovery.\",\"authors\":\"Mohd Naeem Mohd Nawi, Ranina Radzi, Azizan Ali, Siti Zubaidah Che Lem, Azlina Zulkapli, Ezarul Faradianna Lokman, Mansor Fazliana, Sreelakshmi Sankara Narayanan, Karuthan Chinna, Mohd Fairulnizal Md Noh, Zulfitri Azuan Mat Daud, Tilakavati Karupaiah\",\"doi\":\"10.3390/mps8040092\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This protocol paper outlines a robust and reproducible framework for a <sup>1</sup>H nuclear magnetic resonance (NMR) metabolomics analysis of rodent plasma, designed to facilitate preclinical biomarker discovery. The protocol details optimised steps for plasma collection in a preclinical rodent model, sample preparation, and NMR data acquisition using presaturation Carr-Purcell-Meiboom-Gill (PRESAT-CPMG) pulse sequences, ensuring high-quality spectral data and effective suppression of macromolecule signals. Comprehensive spectral processing and metabolite assignment are described, with guidance on multivariate and univariate statistical analyses to identify metabolic changes and potential biomarkers. The framework emphasises methodological rigour and reproducibility, enabling accurate quantification and interpretation of metabolites relevant to disease mechanisms or therapeutic interventions. By providing a standardised approach, this protocol supports longitudinal and translational studies, bridging findings from rodent models to clinical applications and advancing the reliability of metabolomics-based biomarker discovery in preclinical research.</p>\",\"PeriodicalId\":18715,\"journal\":{\"name\":\"Methods and Protocols\",\"volume\":\"8 4\",\"pages\":\"\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2025-08-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12388194/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Methods and Protocols\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/mps8040092\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Methods and Protocols","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/mps8040092","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
1H Nuclear Magnetic Resonance (NMR) Metabolomics in Rodent Plasma: A Reproducible Framework for Preclinical Biomarker Discovery.
This protocol paper outlines a robust and reproducible framework for a 1H nuclear magnetic resonance (NMR) metabolomics analysis of rodent plasma, designed to facilitate preclinical biomarker discovery. The protocol details optimised steps for plasma collection in a preclinical rodent model, sample preparation, and NMR data acquisition using presaturation Carr-Purcell-Meiboom-Gill (PRESAT-CPMG) pulse sequences, ensuring high-quality spectral data and effective suppression of macromolecule signals. Comprehensive spectral processing and metabolite assignment are described, with guidance on multivariate and univariate statistical analyses to identify metabolic changes and potential biomarkers. The framework emphasises methodological rigour and reproducibility, enabling accurate quantification and interpretation of metabolites relevant to disease mechanisms or therapeutic interventions. By providing a standardised approach, this protocol supports longitudinal and translational studies, bridging findings from rodent models to clinical applications and advancing the reliability of metabolomics-based biomarker discovery in preclinical research.