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A Strategy for Sensitive, Large Scale Quantitative Metabolomics
Published on: May 27, 2014
2D NMR metabonomic analysis: a novel method for automated peak alignment
Ming Zheng1, Peng Lu, Yanzhou Liu
1Department of Genetics & Genomics, Roche Palo Alto LLC, Palo Alto, CA 94304, USA.
Bioinformatics (Oxford, England)
|September 12, 2007
Summary
A new automated method accurately aligns peaks in 2D NMR spectra, crucial for comparing metabolic profiles and understanding drug response differences. This advance aids comparative metabonomics research.
Area of Science:
- Metabolomics
- Nuclear Magnetic Resonance (NMR) Spectroscopy
- Computational Chemistry
Background:
- Comparative metabolic profiling using NMR shows potential for personalized drug response prediction.
- Two-dimensional (2D) NMR reduces spectral overlap but lacks adequate peak alignment tools.
- A robust method for 2D NMR peak alignment is needed for advanced metabonomic analysis.
Purpose of the Study:
- To develop an automated and statistically robust method for aligning peaks in 2D NMR spectra.
- To enable accurate comparative metabonomic analysis using 2D NMR data.
Main Methods:
- A novel statistical method using a similarity measure and a heuristic algorithm was developed for peak alignment.
- The method assesses local pattern match among peaks across multiple spectra.
- The algorithm was applied to 2D NMR spectra of liver extracts from mice.
Main Results:
- The automated method successfully aligned NMR peaks representing the same chemical groups across different 2D NMR spectra.
- Validation showed 96.7% accuracy in aligning 1810 out of 1872 peaks across 39 spectra.
- The method was applied to study acetaminophen-induced liver toxicity in mice.
Conclusions:
- The developed automated peak alignment method is effective and accurate for 2D NMR spectra.
- This method facilitates comparative metabonomic studies, particularly in drug response research.
- The algorithm provides a valuable tool for analyzing complex 2D NMR datasets.
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