Abstract
Introduction
Nuclear Magnetic Resonance (NMR) spectroscopy stands as a preeminent analytical tool in the field of metabolomics. Nevertheless, when it comes to identifying metabolites present in scant amounts within various types of complex mixtures such as plants, honey, milk, and biological fluids and tissues, NMR-based metabolomics presents a formidable challenge. This predicament arises primarily from the fact that the signals emanating from metabolites existing in low concentrations tend to be overshadowed by the signals of highly concentrated metabolites within NMR spectra.
Objectives
The aim of this study is to tackle the issue of intense sugar signals overshadowing the desired metabolite signals, an optimal pulse sequence with band-selective excitation has been proposed for the suppression of sugar’s moiety signals (SSMS). This sequence serves the crucial purpose of suppressing unwanted signals, with a particular emphasis on mitigating the interference caused by sugar moieties' signals.
Methods
We have implemented this comprehensive approach to various NMR techniques, including 1D 1H presaturation (presat), 2D J-resolved (RES), 2D 1H-1H Total Correlation Spectroscopy (TOCSY), and 2D 1H-13C Heteronuclear Single Quantum Coherence (HSQC) for the samples of dates-flesh, honey, a standard stock solution of glucose, and nine amino acids, and commercial fetal bovine serum (FBS).
Results
The outcomes of this approach were significant. The suppression of the high-intensity sugar signals has considerably enhanced the visibility and sensitivity of the signals emanating from the desired metabolites.
Conclusion
This, in turn, enables the identification of a greater number of metabolites. Additionally, it streamlines the experimental process, reducing the time required for the comparative quantification of metabolites in statistical studies in the field of metabolomics.
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Acknowledgements
The authors would like to thank King Abdullah University of Science and Technology (KAUST) for financial support. The Smart Health Initiative (SHI) is also acknowledged by Mariusz Jaremko for grants from the Baseline (BAS/1/1085-01-01) program for the period of 2021 to 2023.
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US was primarily responsible for the design of the methods, execution of these methods, studies, data collection, and data analysis. Additionally, US prepared the figures and tables and wrote the main manuscript text and RAl-N provided considerable assistance in the execution of these methods, studies, data collection, data analysis, figures, tables, and writing manuscript text. FA contributed significantly to providing honey samples, studies, data analysis, and editing the manuscript text. A-HE and MJ contributed significantly to assisting in designing methods, execution of these methods, studies, data collection, data analysis, writing, and editing manuscript text. All authors reviewed the manuscript. The NMR analysis was performed at the Core Lab of NMR, King Abdullah University of Science and Technology (KAUST). NMR core facility is funded by the Mariusz Jaremko-Smart-Health Initiative (SHI) and Red Sea Research Center (RSRC), Division of Biological and Environmental Sciences and Engineering (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Makkah, 23955-6900, Saudi Arabia and Authority.
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Experimental acquisition and processing parameters tables, in 1D and 2D NMR spectral for comparison of honey, dates-flesh, a mixture of glucose and nine metabolites as well as fetal bovine serum samples, Table of overall estimation of SNR, pulse sequences of current modified 1D and 2D NMR experiments, their pulse programming. (DOCX 7335 kb)
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Singh, U., Al-Nemi, R., Alahmari, F. et al. Improving quality of analysis by suppression of unwanted signals through band-selective excitation in NMR spectroscopy for metabolomics studies. Metabolomics 20, 7 (2024). https://doi.org/10.1007/s11306-023-02069-9
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DOI: https://doi.org/10.1007/s11306-023-02069-9