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Using Metabolomics to Identify the Exposure and Functional Biomarkers of Ginger
Daniel Esquivel-Alvarado1, Shuwei Zhang1, Changling Hu1
1Laboratory for Functional Foods and Human Health, Center for Excellence in Post-Harvest Technologies, North Carolina Agricultural and Technical State University, Kannapolis, North Carolina 28081, United States.
Creating specialized mass spectral libraries, like one for ginger, is crucial for identifying dietary biomarkers and understanding how food impacts health. This research highlights the limitations of current databases for accurate food metabolite identification.
Area of Science:
- Metabolomics
- Analytical Chemistry
- Nutritional Science
Background:
- Liquid chromatography-mass spectrometry (LC-MS) metabolomics is vital for studying diet-human health interactions.
- Limited public and commercial mass spectral libraries for dietary metabolites hinder the interpretation of LC-MS data.
- Accurate identification of food biomarkers is challenging due to insufficient spectral databases.
Purpose of the Study:
- To demonstrate the importance of constructing LC-MS/MS spectral libraries for dietary compounds using ginger as an example.
- To investigate functional and exposure biomarkers of ginger in a mouse model.
- To highlight the necessity of specialized libraries for accurate food metabolite identification.
Main Methods:
- Construction of an in-house LC-MS/MS ginger spectral library.
- Analysis of plasma samples from mice fed control and ginger extract diets using LC-MS/MS.
- Comparison of metabolite profiles and identification of ginger-specific compounds.
Main Results:
- Significant metabolic differences were observed between control and ginger-fed mice.
- An in-house ginger library enabled the identification of 20 ginger metabolites as exposure biomarkers.
- Ginger metabolites could not be accurately identified using only online mass databases, underscoring the need for specialized libraries.
- Ginger consumption impacted endogenous metabolisms, including purine metabolism and amino acid biosynthesis pathways.
Conclusions:
- The development of LC-MS/MS spectral libraries for dietary compounds is essential for advancing food biomarker discovery.
- Specialized libraries significantly enhance the identification accuracy of food metabolites compared to general databases.
- This approach facilitates the correlation of dietary intake with potential health benefits.
