Discrimination of flavonoids and red wine varietals by arrays of differential peptidic sensors

TLDR

Natural product structures and concentrations vary with genome and environment, producing complex metabolite mixtures from plants and fermentation processes. The study aims to develop supramolecular sensor arrays that discriminate flavonoids and wine varietals. The arrays employ indicator displacement, with UV‑vis absorbance changes analyzed by pattern‑recognition protocols. The arrays differentiated flavonoids by structure and concentration and classified red wines by varietal, showing that differential sensor arrays can identify mixtures based on metabolite distribution even when the natural products are unknown.

Abstract

The chemical structures and concentrations of an organism's natural products are dependent upon its genome and environmental factors. Examples are the complex metabolite solutions resulting from plant and fermentation processes. Here, we describe sensor arrays composed of supramolecular ensembles that undergo indicator displacement and discriminate selected flavonoids and mixtures thereof: wine varietals. Changes in UV-vis absorbance upon indicator displacement in the array were analyzed using pattern recognition protocols. The flavonoids were differentiated in terms of structure and concentration, while red wines were generally classified by varietals, even from different vintners. The technique highlights the power of differential sensor arrays to classify mixtures by metabolite distribution, even when the natural products are not known.