Amperometric Identification of Single Exosomes and Their Dopamine Contents Secreted by Living Cells

Abstract

Dopamine (DA) is an important neurotransmitter, which not only participates in the regulation of neural processes but also plays critical roles in tumor progression and immunity. However, direct identification of DA-containing exosomes, as well as quantification of DA in single vesicles, is still challenging. Here, we report a nanopipette-assisted method to detect single exosomes and their dopamine contents via amperometric measurement. The resistive-pulse current measured can simultaneously provide accurate information of vesicle translocation and DA contents in single exosomes. Accordingly, DA-containing exosomes secreted from HeLa and PC12 cells under different treatment modes successfully detected the DA encapsulation efficiency and the amount of exosome secretion that distinguish between cell types. Furthermore, a custom machine learning model was constructed to classify the exosome signals from different sources, with an accuracy of more than 99%. Our strategy offers a useful tool for investigating single exosomes and their DA contents, which facilitates the analysis of DA-containing exosomes derived from other untreated or stimulated cells and may open up a new insight to the research of DA biology.

Solid‐State Glass Nanopipettes: Functionalization and Applications

“…They can capture fluorescent molecules from the surrounding cytoplasm and then perform photocatalytic degradation, which mimics the compartmentalized chemical reactions that occur within eukaryotic cells. They also developed a method using a nanopipette to identify dopamine‐containing exosomes and quantify dopamine in single vesicles [104] …”

“…They also developed a method using a nanopipette to identify dopamine-containing exosomes and quantify dopamine in single vesicles. [104] Nanopipette single-cell studies are usually performed with high electric potential or organic solvent, which could inevitably impose disturbance and damage to targeted cells. [29] Some researchers have been focused on reducing damage to cells in recent years.…”

Artificial Intelligence-Assisted Multiparameter Size Discrimination of Silver Nanoparticles through Electrochemical Collision

“…The model could predict the transmission function of all other nucleotides after training with data sets generated from all the orientations of any nucleotide inside the nanopore . Recently, a custom machine learning model was constructed to learn the features extracted from current signals and applied to classify exosome signals from different sources . Due to the faster and more efficient data processing abilities than the traditional analysis method, AI provides a new guidance for multidimensional data processing.…”