Abstract

Alditols, which have a sweet taste but produce much lower calories than natural sugars, are widely used as artificial sweeteners. Alditols are the reduced forms of monosaccharide aldoses, and different alditols are diastereomers or epimers of each other and direct and rapid identification by conventional methods is difficult. Nanopores, which are emerging single-molecule sensors with exceptional resolution when engineered appropriately, are useful for the recognition of diastereomers and epimers. In this work, direct distinguishing of alditols corresponding to all 15 monosaccharide aldoses was achieved by a boronic acid-appended hetero-octameric Mycobacterium smegmatis porin A (MspA) nanopore (MspA-PBA). Thirteen alditols including glycerol, erythritol, threitol, adonitol, arabitol, xylitol, mannitol, sorbitol, allitol, dulcitol, iditol, talitol, and gulitol (l-sorbitol) could be fully distinguished, and their sensing features constitute a complete nanopore alditol database. To automate event classification, a custom machine-learning algorithm was developed and delivered a 99.9% validation accuracy. This strategy was also used to identify alditol components in commercially available "zero-sugar" drinks and healthcare products, suggesting their use in rapid and sensitive quality control for the food and medical industry.

Full Text
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