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Evaluation of Non-Uniform Sampling 2D (1)H–(13)C HSQC Spectra for Semi-Quantitative Metabolomics

Metabolomics is the comprehensive study of metabolism, the biochemical processes that sustain life. By comparing metabolites between healthy and disease states, new insights into disease mechanisms can be uncovered. NMR is a powerful analytical method to detect and quantify metabolites. Standard one...

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Detalles Bibliográficos
Autores principales: Zhang, Bo, Powers, Robert, O’Day, Elizabeth M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7281502/
https://www.ncbi.nlm.nih.gov/pubmed/32429340
http://dx.doi.org/10.3390/metabo10050203
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author Zhang, Bo
Powers, Robert
O’Day, Elizabeth M.
author_facet Zhang, Bo
Powers, Robert
O’Day, Elizabeth M.
author_sort Zhang, Bo
collection PubMed
description Metabolomics is the comprehensive study of metabolism, the biochemical processes that sustain life. By comparing metabolites between healthy and disease states, new insights into disease mechanisms can be uncovered. NMR is a powerful analytical method to detect and quantify metabolites. Standard one-dimensional (1D) (1)H-NMR metabolite profiling is informative but challenged by significant chemical shift overlap. Multi-dimensional NMR can increase resolution, but the required long acquisition times lead to limited throughput. Non-uniform sampling (NUS) is a well-accepted mode of acquiring multi-dimensional NMR data, enabling either reduced acquisition times or increased sensitivity in equivalent time. Despite these advantages, the technique is not widely applied to metabolomics. In this study, we evaluated the utility of NUS (1)H–(13)C heteronuclear single quantum coherence (HSQC) for semi-quantitative metabolomics. We demonstrated that NUS improved sensitivity compared to uniform sampling (US). We verified that the NUS measurement maintains linearity, making it possible to detect metabolite changes across samples and studies. Furthermore, we calculated the lower limit of detection and quantification (LOD/LOQ) of common metabolites. Finally, we demonstrate that the measurements are repeatable on the same system and across different systems. In conclusion, our results detail the analytical capability of NUS and, in doing so, empower the future use of NUS (1)H–(13)C HSQC in metabolomic studies.
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spelling pubmed-72815022020-06-17 Evaluation of Non-Uniform Sampling 2D (1)H–(13)C HSQC Spectra for Semi-Quantitative Metabolomics Zhang, Bo Powers, Robert O’Day, Elizabeth M. Metabolites Article Metabolomics is the comprehensive study of metabolism, the biochemical processes that sustain life. By comparing metabolites between healthy and disease states, new insights into disease mechanisms can be uncovered. NMR is a powerful analytical method to detect and quantify metabolites. Standard one-dimensional (1D) (1)H-NMR metabolite profiling is informative but challenged by significant chemical shift overlap. Multi-dimensional NMR can increase resolution, but the required long acquisition times lead to limited throughput. Non-uniform sampling (NUS) is a well-accepted mode of acquiring multi-dimensional NMR data, enabling either reduced acquisition times or increased sensitivity in equivalent time. Despite these advantages, the technique is not widely applied to metabolomics. In this study, we evaluated the utility of NUS (1)H–(13)C heteronuclear single quantum coherence (HSQC) for semi-quantitative metabolomics. We demonstrated that NUS improved sensitivity compared to uniform sampling (US). We verified that the NUS measurement maintains linearity, making it possible to detect metabolite changes across samples and studies. Furthermore, we calculated the lower limit of detection and quantification (LOD/LOQ) of common metabolites. Finally, we demonstrate that the measurements are repeatable on the same system and across different systems. In conclusion, our results detail the analytical capability of NUS and, in doing so, empower the future use of NUS (1)H–(13)C HSQC in metabolomic studies. MDPI 2020-05-16 /pmc/articles/PMC7281502/ /pubmed/32429340 http://dx.doi.org/10.3390/metabo10050203 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Bo
Powers, Robert
O’Day, Elizabeth M.
Evaluation of Non-Uniform Sampling 2D (1)H–(13)C HSQC Spectra for Semi-Quantitative Metabolomics
title Evaluation of Non-Uniform Sampling 2D (1)H–(13)C HSQC Spectra for Semi-Quantitative Metabolomics
title_full Evaluation of Non-Uniform Sampling 2D (1)H–(13)C HSQC Spectra for Semi-Quantitative Metabolomics
title_fullStr Evaluation of Non-Uniform Sampling 2D (1)H–(13)C HSQC Spectra for Semi-Quantitative Metabolomics
title_full_unstemmed Evaluation of Non-Uniform Sampling 2D (1)H–(13)C HSQC Spectra for Semi-Quantitative Metabolomics
title_short Evaluation of Non-Uniform Sampling 2D (1)H–(13)C HSQC Spectra for Semi-Quantitative Metabolomics
title_sort evaluation of non-uniform sampling 2d (1)h–(13)c hsqc spectra for semi-quantitative metabolomics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7281502/
https://www.ncbi.nlm.nih.gov/pubmed/32429340
http://dx.doi.org/10.3390/metabo10050203
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