Issue 12, 2020

FRET-based sensor for visualizing pH variation with colorimetric/ratiometric strategy and application for bioimaging in living cells, bacteria and zebrafish

Abstract

Acid–base balance plays a key role in regulating biological processes, and the cells must stabilize the pH within a certain range, and pH instability will cause a series of diseases. Therefore, tracking intracellular pH changes was important for understanding physiological and pathological processes. Fluorescent probes were favored by researchers as simple, fast and efficient pH detection tools, which have potential research value. In this work, a ratiometric and colorimetric sensor based on rhodamine (Rh-TPE) was fabricated for monitoring the pH change through the mechanism of fluorescence resonance energy transfer (FRET). Rh-TPE has demonstrated the advantages of high sensitivity, outstanding cell permeability and low toxicity. Moreover, the fluorescence ratio (F593/F455) of Rh-TPE displays a pH-sensitive response from 2.0 to 8.4 (pKa = 4.27) and a linear response from pH 3.3 to 5.0, which was ideal for mapping pH in living biosystems. Additionally, the results confirmed that the response signal was pH-dependent and regulated via switchable forms between closed and opened spirolactam ring forms. Spectacularly, Rh-TPE has successfully realized sensing and mapping of pH in living cells, bacteria and zebrafish. The above results exhibited that Rh-TPE could be a powerful tool for sensing and visualizing pH in living biosystems.

Graphical abstract: FRET-based sensor for visualizing pH variation with colorimetric/ratiometric strategy and application for bioimaging in living cells, bacteria and zebrafish

Supplementary files

Article information

Article type
Paper
Submitted
27 Apr 2020
Accepted
13 May 2020
First published
14 May 2020

Analyst, 2020,145, 4283-4294

FRET-based sensor for visualizing pH variation with colorimetric/ratiometric strategy and application for bioimaging in living cells, bacteria and zebrafish

H. Chen, F. Ding, Z. Zhou, X. He and J. Shen, Analyst, 2020, 145, 4283 DOI: 10.1039/D0AN00841A

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