Example of Metabolomic Analysis

Profiling Analysis of Green Tea Leaves

The example below introduces profiling analysis on green tea leaves as a method for determining the components that contribute to tea quality.

1.Pretreatment and Analysis

Analytical samples were prepared from nine types of high-grade green tea leaves ranked at a tea fair, and analyzed by Prominence UFLC/LCMS-IT-TOF.

2. Peak Extraction and List Creation – Peak extraction by Profiling Solution software

Peaks were extracted from the results of MS1 analysis and peak lists created using the peak signal intensity values. Retention time sorting, isotope peak elimination, and p-Value filtering were applied to the 3798 peaks detected to extract 479 significant peaks. The data were then exported to commercial multivariate analysis software (SIMCA-P by Umetrics).

3. Multivariate Analysis

PCR score and PCR loading plots were produced. The green tea leaves that were highly ranked and lowly ranked at the tea fair are divided to the left and right of the PCR score plot, such that the primary component axis indicates differences in rank.

The PCR loading plot of the primary component axis (PC1), which indicates the contribution of each component to tea quality, shows the components contained in large quantities in highly ranked green tea as positive values.

4.Formula Prediction for Unknown Compounds

The formula was predicted for the Peak X candidate compound, which was selected as a typical unknown compound that contributes to tea quality. The formula was predicted from the accurate mass information obtained in MS3 analysis. The formula prediction software (Formula Predictor) indicated Peak X to be C14H16O10.

5.Candidate Compound Prediction of Unknown Compounds

A search for the formula C14H16O10 in a database published on the Internet suggested that the compound may be a polyphenol called theogallin. Attributing a mass spectrum based on the structure of theogallin suggested that Peak X was theogallin.

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