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Quantitating Metabolites in Protein Precipitated Serum Using NMR Spectroscopy
[Image: see text] Quantitative NMR-based metabolite profiling is challenged by the deleterious effects of abundant proteins in the intact blood plasma/serum, which underscores the need for alternative approaches. Protein removal by ultrafiltration using low molecular weight cutoff filters thus repre...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American
Chemical
Society
2014
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4045325/ https://www.ncbi.nlm.nih.gov/pubmed/24796490 http://dx.doi.org/10.1021/ac5005103 |
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author | Gowda, G. A. Nagana Raftery, Daniel |
author_facet | Gowda, G. A. Nagana Raftery, Daniel |
author_sort | Gowda, G. A. Nagana |
collection | PubMed |
description | [Image: see text] Quantitative NMR-based metabolite profiling is challenged by the deleterious effects of abundant proteins in the intact blood plasma/serum, which underscores the need for alternative approaches. Protein removal by ultrafiltration using low molecular weight cutoff filters thus represents an important step. However, protein precipitation, an alternative and simple approach for protein removal, lacks detailed quantitative assessment for use in NMR based metabolomics. In this study, we have comprehensively evaluated the performance of protein precipitation using methanol, acetonitrile, perchloric acid, and trichloroacetic acid and ultrafiltration approaches using 1D and 2D NMR, based on the identification and absolute quantitation of 44 human blood metabolites, including a few identified for the first time in the NMR spectra of human serum. We also investigated the use of a “smart isotope tag,” (15)N-cholamine for further resolution enhancement, which resulted in the detection of a number of additional metabolites. (1)H NMR of both protein precipitated and ultrafiltered serum detected all 44 metabolites with comparable reproducibility (average CV, 3.7% for precipitation; 3.6% for filtration). However, nearly half of the quantified metabolites in ultrafiltered serum exhibited 10–74% lower concentrations; specifically, tryptophan, benzoate, and 2-oxoisocaproate showed much lower concentrations compared to protein precipitated serum. These results indicate that protein precipitation using methanol offers a reliable approach for routine NMR-based metabolomics of human blood serum/plasma and should be considered as an alternative to ultrafiltration. Importantly, protein precipitation, which is commonly used by mass spectrometry (MS), promises avenues for direct comparison and correlation of metabolite data obtained from the two analytical platforms to exploit their combined strength in the metabolomics of blood. |
format | Online Article Text |
id | pubmed-4045325 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | American
Chemical
Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-40453252015-05-05 Quantitating Metabolites in Protein Precipitated Serum Using NMR Spectroscopy Gowda, G. A. Nagana Raftery, Daniel Anal Chem [Image: see text] Quantitative NMR-based metabolite profiling is challenged by the deleterious effects of abundant proteins in the intact blood plasma/serum, which underscores the need for alternative approaches. Protein removal by ultrafiltration using low molecular weight cutoff filters thus represents an important step. However, protein precipitation, an alternative and simple approach for protein removal, lacks detailed quantitative assessment for use in NMR based metabolomics. In this study, we have comprehensively evaluated the performance of protein precipitation using methanol, acetonitrile, perchloric acid, and trichloroacetic acid and ultrafiltration approaches using 1D and 2D NMR, based on the identification and absolute quantitation of 44 human blood metabolites, including a few identified for the first time in the NMR spectra of human serum. We also investigated the use of a “smart isotope tag,” (15)N-cholamine for further resolution enhancement, which resulted in the detection of a number of additional metabolites. (1)H NMR of both protein precipitated and ultrafiltered serum detected all 44 metabolites with comparable reproducibility (average CV, 3.7% for precipitation; 3.6% for filtration). However, nearly half of the quantified metabolites in ultrafiltered serum exhibited 10–74% lower concentrations; specifically, tryptophan, benzoate, and 2-oxoisocaproate showed much lower concentrations compared to protein precipitated serum. These results indicate that protein precipitation using methanol offers a reliable approach for routine NMR-based metabolomics of human blood serum/plasma and should be considered as an alternative to ultrafiltration. Importantly, protein precipitation, which is commonly used by mass spectrometry (MS), promises avenues for direct comparison and correlation of metabolite data obtained from the two analytical platforms to exploit their combined strength in the metabolomics of blood. American Chemical Society 2014-05-05 2014-06-03 /pmc/articles/PMC4045325/ /pubmed/24796490 http://dx.doi.org/10.1021/ac5005103 Text en Copyright © 2014 American Chemical Society |
spellingShingle | Gowda, G. A. Nagana Raftery, Daniel Quantitating Metabolites in Protein Precipitated Serum Using NMR Spectroscopy |
title | Quantitating Metabolites in Protein Precipitated Serum Using NMR Spectroscopy |
title_full | Quantitating Metabolites in Protein Precipitated Serum Using NMR Spectroscopy |
title_fullStr | Quantitating Metabolites in Protein Precipitated Serum Using NMR Spectroscopy |
title_full_unstemmed | Quantitating Metabolites in Protein Precipitated Serum Using NMR Spectroscopy |
title_short | Quantitating Metabolites in Protein Precipitated Serum Using NMR Spectroscopy |
title_sort | quantitating metabolites in protein precipitated serum using nmr spectroscopy |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4045325/ https://www.ncbi.nlm.nih.gov/pubmed/24796490 http://dx.doi.org/10.1021/ac5005103 |
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