Manu Veliparambil Subrahmanian, Ivan Vuckovic, Slobodan Macura and Gianluigi Veglia*,
{"title":"利用人工智能设计的水辐照无脉冲检测核磁共振代谢组学分析中的可交换质子","authors":"Manu Veliparambil Subrahmanian, Ivan Vuckovic, Slobodan Macura and Gianluigi Veglia*, ","doi":"10.1021/acs.analchem.4c0553010.1021/acs.analchem.4c05530","DOIUrl":null,"url":null,"abstract":"<p ><sup>1</sup>H NMR spectroscopy has enabled the quantitative profiling of metabolites in various biofluids, emerging as a possible diagnostic tool for metabolic disorders and other diseases. To boost the signal-to-noise ratio and detect proton resonances near the water signal, current <sup>1</sup>H NMR experiments require solvent suppression schemes (<i>e.g.</i>, presaturation, jump-and-return, WATERGATE, excitation sculpting, <i>etc</i>.). Unfortunately, these techniques affect the quantitative assessment of analytes containing exchangeable protons. To address this issue, we introduce two new one-dimensional (1D) <sup>1</sup>H NMR techniques that eliminate the water signal, preserving the intensities of exchangeable protons. Using GENETICS-AI, a software that combines an evolutionary algorithm and artificial intelligence, we tailored new water irradiation devoid (WADE) pulses and optimized the 1D <sup>1</sup>H NOESY sequence for metabolomic analysis. When applied to human urine samples, kidney tissue extract, and plasma, the WADE technique allowed for accurate measurement of typical metabolites and direct quantification of urea, which is usually challenging to measure using standard NMR experiments. We anticipate that these new NMR techniques will significantly improve the accuracy and reliability of metabolite quantitative assessment for a wide range of biological fluids.</p>","PeriodicalId":27,"journal":{"name":"Analytical Chemistry","volume":"97 6","pages":"3412–3417 3412–3417"},"PeriodicalIF":6.7000,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Detection of Exchangeable Protons in NMR Metabolomic Analysis Using AI-Designed Water Irradiation Devoid Pulses\",\"authors\":\"Manu Veliparambil Subrahmanian, Ivan Vuckovic, Slobodan Macura and Gianluigi Veglia*, \",\"doi\":\"10.1021/acs.analchem.4c0553010.1021/acs.analchem.4c05530\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p ><sup>1</sup>H NMR spectroscopy has enabled the quantitative profiling of metabolites in various biofluids, emerging as a possible diagnostic tool for metabolic disorders and other diseases. To boost the signal-to-noise ratio and detect proton resonances near the water signal, current <sup>1</sup>H NMR experiments require solvent suppression schemes (<i>e.g.</i>, presaturation, jump-and-return, WATERGATE, excitation sculpting, <i>etc</i>.). Unfortunately, these techniques affect the quantitative assessment of analytes containing exchangeable protons. To address this issue, we introduce two new one-dimensional (1D) <sup>1</sup>H NMR techniques that eliminate the water signal, preserving the intensities of exchangeable protons. Using GENETICS-AI, a software that combines an evolutionary algorithm and artificial intelligence, we tailored new water irradiation devoid (WADE) pulses and optimized the 1D <sup>1</sup>H NOESY sequence for metabolomic analysis. When applied to human urine samples, kidney tissue extract, and plasma, the WADE technique allowed for accurate measurement of typical metabolites and direct quantification of urea, which is usually challenging to measure using standard NMR experiments. We anticipate that these new NMR techniques will significantly improve the accuracy and reliability of metabolite quantitative assessment for a wide range of biological fluids.</p>\",\"PeriodicalId\":27,\"journal\":{\"name\":\"Analytical Chemistry\",\"volume\":\"97 6\",\"pages\":\"3412–3417 3412–3417\"},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2025-02-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Analytical Chemistry\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://pubs.acs.org/doi/10.1021/acs.analchem.4c05530\",\"RegionNum\":1,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, ANALYTICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Analytical Chemistry","FirstCategoryId":"92","ListUrlMain":"https://pubs.acs.org/doi/10.1021/acs.analchem.4c05530","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
Detection of Exchangeable Protons in NMR Metabolomic Analysis Using AI-Designed Water Irradiation Devoid Pulses
1H NMR spectroscopy has enabled the quantitative profiling of metabolites in various biofluids, emerging as a possible diagnostic tool for metabolic disorders and other diseases. To boost the signal-to-noise ratio and detect proton resonances near the water signal, current 1H NMR experiments require solvent suppression schemes (e.g., presaturation, jump-and-return, WATERGATE, excitation sculpting, etc.). Unfortunately, these techniques affect the quantitative assessment of analytes containing exchangeable protons. To address this issue, we introduce two new one-dimensional (1D) 1H NMR techniques that eliminate the water signal, preserving the intensities of exchangeable protons. Using GENETICS-AI, a software that combines an evolutionary algorithm and artificial intelligence, we tailored new water irradiation devoid (WADE) pulses and optimized the 1D 1H NOESY sequence for metabolomic analysis. When applied to human urine samples, kidney tissue extract, and plasma, the WADE technique allowed for accurate measurement of typical metabolites and direct quantification of urea, which is usually challenging to measure using standard NMR experiments. We anticipate that these new NMR techniques will significantly improve the accuracy and reliability of metabolite quantitative assessment for a wide range of biological fluids.
期刊介绍:
Analytical Chemistry, a peer-reviewed research journal, focuses on disseminating new and original knowledge across all branches of analytical chemistry. Fundamental articles may explore general principles of chemical measurement science and need not directly address existing or potential analytical methodology. They can be entirely theoretical or report experimental results. Contributions may cover various phases of analytical operations, including sampling, bioanalysis, electrochemistry, mass spectrometry, microscale and nanoscale systems, environmental analysis, separations, spectroscopy, chemical reactions and selectivity, instrumentation, imaging, surface analysis, and data processing. Papers discussing known analytical methods should present a significant, original application of the method, a notable improvement, or results on an important analyte.