Issue 18, 2023

A large Stokes shift NIR fluorescent probe for visual monitoring of mitochondrial peroxynitrite during inflammation and ferroptosis and in an Alzheimer's disease model

Abstract

The excessive formation of peroxynitrite (ONOO) in mitochondria has been implicated in various pathophysiological processes and diseases. However, owing to short emission wavelengths and small Stokes shifts, previously reported fluorescent probes pose significant challenges for mitochondrial ONOO imaging in biological systems. In this study, a near-infrared (NIR) fluorescent probe, denoted as DCO-POT, is designed for the visual monitoring of mitochondrial ONOO, displaying a remarkable Stokes shift of 170 nm. The NIR fluorophore of DCO-CHO is released by DCO-POT upon the addition of ONOO, resulting in off–on NIR fluorescence at 670 nm. This phenomenon facilitates the high-resolution confocal laser scanning imaging of ONOO generated in biological systems. The practical applications of DCO-POT as an efficient fluorescence imaging tool are verified in this study. DCO-POT enables the fluorometric visualization of ONOO in organelles, cells, and organisms. In particular, ONOO generation is analyzed during cellular and organism-level (zebrafish) inflammation during ferroptosis and in an Alzheimer's disease mouse model. The excellent visual monitoring performance of DCO-POT in vivo makes it a promising tool for exploring the pathophysiological effects of ONOO.

Graphical abstract: A large Stokes shift NIR fluorescent probe for visual monitoring of mitochondrial peroxynitrite during inflammation and ferroptosis and in an Alzheimer's disease model

Supplementary files

Article information

Article type
Paper
Submitted
13 juin 2023
Accepted
19 juil. 2023
First published
20 juil. 2023

Analyst, 2023,148, 4331-4338

A large Stokes shift NIR fluorescent probe for visual monitoring of mitochondrial peroxynitrite during inflammation and ferroptosis and in an Alzheimer's disease model

S. Chen, W. Huang, H. Tan, G. Yin, S. Chen, K. Zhao, Y. Huang, Y. Zhang, H. Li and C. Wu, Analyst, 2023, 148, 4331 DOI: 10.1039/D3AN00956D

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