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Single-Molecule Sensing of Acidic Catecholamine Metabolites Using a Programmable Nanopore.

Chengzhen HuWendong JiaYao LiuYuqin WangPan-Ke ZhangHong-Yuan ChenShuo Huang
Published in: Chemistry (Weinheim an der Bergstrasse, Germany) (2022)
Acidic catecholamine metabolites, which could serve as diagnostic markers for many diseases, demonstrate an importance of accurate sensing. However, they share a highly similar chemical structure, which is a challenge in the design of sensing strategies. A nanopore may be engineered to sense these metabolites in a single molecule manner. To achieve this, a recently developed programmable nano-reactor for stochastic sensing (PNRSS) technique adapted with a phenylboronic acid (PBA) adaptor was applied. Three acidic catecholamine metabolites, including 3,4-dihydroxyphenylacetic acid (DOPAC), 3,4-dihydroxymandelic acid (DHMA) and 3-methoxy-4-hydroxymandetic acid (VMA) were investigated by PNRSS. Specifically, DHMA, which contains an α-hydroxycarboxylate moiety and an adjacent cis-hydroxyl groups on its benzene ring, reports two binding modes simultaneously resolvable by PNRSS. Assisted with the high resolution of PNRSS, direct regulation of these two binding modes by pH can also be observed. A custom machine learning algorithm was also developed to achieve automatic event classification.
Keyphrases
  • single molecule
  • machine learning
  • atomic force microscopy
  • ms ms
  • high resolution
  • deep learning
  • living cells
  • mass spectrometry
  • emergency department
  • big data
  • dna binding
  • anaerobic digestion