The Spectro-Electro Array: A Novel Platform for the Measurement of Secondary Metabolites in Botanicals, Supplements, and Beverages

Jun 01, 2012
Volume 30, Issue 6, pg 492–503

Targeted Analyses


Table II: Abundance (µg/g) of different analytes in supplements and herbs
As shown in Figure 3, numerous phenol and polyphenol analytes can be resolved using this approach (see Table I for identification). It should be noted that there are six compounds designated UV1–UV6 that showed poor response by ECD, but they are readily detectable by UV. The limits of detection were typically 10–50 pg on-column by ECD and 100–500 pg by UV. The limits of quantification were 200–1000 pg (on-column) by ECD and 500–5000 pg by UV. The response ranges were over seven orders of magnitude by ECD and five by UV. Typical R 2 values were ~0.999 or better for all compounds. The average interday retention time precision for all analytes averaged 0.55% RSD over a 10-day period, with a range of 0.30–1.22%.


Figure 4: Measurement of phytochemicals in St. John’s wort by UV detection at 254 nm (upper figure) and 16-channel coulometric electrochemical-array detection (lower figure).
The targeted approach was used to measure the levels of phenols and polyphenols in a variety of supplements and culinary herbs. Analyte levels (Table II) were in good agreement with levels reported in previous publications (9,34–36). St. John's wort (Hypericum perforatum) is reportedly effective in the treatment of moderate depression in a number of clinical trials. The two major polyphenols in St. John's wort, hypericin and pseudohypericin, were easily measured using both UV detection and ECD (Figure 4, ~18 min). Rosemary is particularly rich in carnosic acid, a potent antioxidant and anticarcinogen that is a major constituent of the dried leaf. Another major component of rosemary is rosemarinic acid, which is also known for its antioxidant properties.

Metabolite Patterns


Table III: Some of the more abundant analytes measured in different wine samples; wine 1: cabernet sauvignon, Argentina; wine 2: cabernet sauvignon, South Africa; wine 3: cabernet sauvignon, United States; wine 4: cabernet sauvignon, Chile; and wine 5: hearty burgundy, United States
Examination of the pattern of both known and unknown metabolites can be used to authenticate a sample or measure contamination and adulteration. Two simple experiments were used to evaluate the application of the spectro-electro array to metabolomic studies. The first examined the metabolite profiles of a selection of red wines. The general polyphenol method was used to analyze five red wines (four cabernet sauvignon samples and one burgundy sample). Several hundred analytes, including both known (see Table III) and unknown compounds, were measured in each sample. Levels of known compounds were similar to those previously published (8,9). Principal component analysis (PCA) was able to identify wine samples as either burgundy or cabernet sauvignon (Figure 5). Although this study is preliminary it does show the capability of the system to differentiate samples by grape varietal or blend and growing region. This approach is important when trying to authenticate a sample or for identifying product adulteration.


Figure 5: Initial study showing principal component analysis of wines.
In the second application, the metabolomics approach was investigated as a means to authenticate or detect adulteration of orange juice samples (33). The study was intended to detect the lowest level of adulteration (by blending with other juices or through the addition of orange peel or pulp-wash) that could be detected in orange juice samples. Blending of as little as 10% grapefruit juice into orange juice could easily be measured. Similarly, blending only 10% orange peel or 10% pulp-wash into orange juice could be detected.


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