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Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
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Software-assisted serum metabolite quantification using NMR
Young-Sang Jung1, Jin-Seong Hyeon1, Geum-Sook Hwang2
1Integrated Metabolomics Research Group, Western Seoul Center, Korea Basic Science Institute, Seoul, 120-140, Republic of Korea.
Analytica Chimica Acta
|August 11, 2016
Summary
Accurate metabolite quantification in NMR-based serum profiling is essential. The new software-assisted serum metabolite quantification (SASMeQ) method provides reliable absolute concentration measurements, improving upon existing techniques.
Area of Science:
- Metabolomics
- Analytical Chemistry
- Biochemistry
Background:
- Metabolomics aims to comprehensively analyze metabolites under specific conditions.
- Accurate metabolite quantitation is critical for reliable metabolic profiling.
- Current NMR-based methods often yield relative, not absolute, concentrations, limiting accuracy due to overlapping peaks.
Purpose of the Study:
- To introduce a novel method for accurate and reliable absolute quantification of serum metabolites using Nuclear Magnetic Resonance (NMR) spectroscopy.
- To address the limitations of existing bin-based and full data point quantification methods in NMR-based serum metabolic profiling.
Main Methods:
- Development and application of the software-assisted serum metabolite quantification (SASMeQ) method.
- Utilizing Chenomx software and the ERETIC2 utility within TopSpin for spectral analysis.
- Involves adding a digitally synthesized reference peak to NMR spectra for quantification.
Main Results:
- The SASMeQ method enables the identification and quantification of metabolites in NMR spectra.
- Provides a reliable approach for achieving absolute concentration values of metabolites.
- Demonstrates superiority over traditional bin-based quantification, especially when metabolite peaks overlap.
Conclusions:
- The SASMeQ method represents a significant advancement in NMR-based serum metabolic profiling.
- Offers a more accurate and reliable alternative for absolute metabolite quantification.
- Enhances the precision and trustworthiness of metabolomic data derived from NMR spectra.
