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Development of Novel MS and NMR Tool...

Rigel, Nicholas R.,

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Development of Novel MS and NMR Tools for the Efficient Discovery of Unknown Metabolites in Complex Biological Samples and Their Application /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Development of Novel MS and NMR Tools for the Efficient Discovery of Unknown Metabolites in Complex Biological Samples and Their Application // Nicholas R Rigel.
Author:	Rigel, Nicholas R.,
Description:	1 electronic resource (190 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-11, Section: B.
Contained By:	Dissertations Abstracts International86-11B.
Subject:	Analytical chemistry. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=32111888
ISBN:	9798314890424

Development of Novel MS and NMR Tools for the Efficient Discovery of Unknown Metabolites in Complex Biological Samples and Their Application /
Rigel, Nicholas R.,

Development of Novel MS and NMR Tools for the Efficient Discovery of Unknown Metabolites in Complex Biological Samples and Their Application /Nicholas R Rigel. - 1 electronic resource (190 pages)

Source: Dissertations Abstracts International, Volume: 86-11, Section: B.

Systems biology has made great strides in the comprehensive characterization of the molecular complexity of living systems, such as nuclei acids and proteins. When it comes to the world of metabolites, however, many spectroscopic signatures observed in complex biological mixtures remain undefined and belong to unknown molecules, also known as the "dark metabolome." Strikingly, there is currently no standardized approach for the identification and characterization of the structures of such molecules, many of which can serve as biomarkers for disease.This dissertation describes new strategies that combine nuclear magnetic resonance (NMR) with mass spectrometry (MS) to comprehensively identify known and unknown metabolites from complex mixtures. Chapter 1 introduces metabolomics and gives an overview of NMR and MS metabolomics methods. Chapter 2 presents COLMARppm, a tool developed for rapid and accurate NMR chemical shift prediction of small molecules. It relies on high quality NMR spectra from the COLMAR database to predict chemical shifts for molecules that are unknown to NMR. Chapter 3 focuses on the implementation of COLMARppm into a new strategy for determining chemical structures of unknown metabolites: COLMARu. The COLMARu workflow uses experimental 2D NMR-derived chemical shifts and high-resolution accurate mass (MS) information directly obtained from the complex biological mixture of interest to assemble candidate molecules that match its unknown metabolites. Candidates are ranked based on a combined MS/NMR accuracy score to prioritize the most reasonable molecules for characterization. The COLMARu strategy was applied to several complex mixtures, e.g., mouse urine and Staphylococcus aureus, resulting in the identification of several unknown metabolites.

English

ISBN: 9798314890424Subjects--Topical Terms:

3168300
Analytical chemistry.
Subjects--Index Terms:

Metabolomics

Development of Novel MS and NMR Tools for the Efficient Discovery of Unknown Metabolites in Complex Biological Samples and Their Application /
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520 $a Systems biology has made great strides in the comprehensive characterization of the molecular complexity of living systems, such as nuclei acids and proteins. When it comes to the world of metabolites, however, many spectroscopic signatures observed in complex biological mixtures remain undefined and belong to unknown molecules, also known as the "dark metabolome." Strikingly, there is currently no standardized approach for the identification and characterization of the structures of such molecules, many of which can serve as biomarkers for disease.This dissertation describes new strategies that combine nuclear magnetic resonance (NMR) with mass spectrometry (MS) to comprehensively identify known and unknown metabolites from complex mixtures. Chapter 1 introduces metabolomics and gives an overview of NMR and MS metabolomics methods. Chapter 2 presents COLMARppm, a tool developed for rapid and accurate NMR chemical shift prediction of small molecules. It relies on high quality NMR spectra from the COLMAR database to predict chemical shifts for molecules that are unknown to NMR. Chapter 3 focuses on the implementation of COLMARppm into a new strategy for determining chemical structures of unknown metabolites: COLMARu. The COLMARu workflow uses experimental 2D NMR-derived chemical shifts and high-resolution accurate mass (MS) information directly obtained from the complex biological mixture of interest to assemble candidate molecules that match its unknown metabolites. Candidates are ranked based on a combined MS/NMR accuracy score to prioritize the most reasonable molecules for characterization. The COLMARu strategy was applied to several complex mixtures, e.g., mouse urine and Staphylococcus aureus, resulting in the identification of several unknown metabolites.
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650 4 $a Systematic biology. $3 3173492
650 4 $a Chemistry. $3 516420
650 4 $a Molecular chemistry. $3 1071612
653 $a Metabolomics
653 $a Nuclear magnetic resonance
653 $a Mass spectrometry
653 $a Metabolite identification
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