Current fluorescent probes for lysosomes have practical limits due to their pH sensitivity, which makes them unsuitable for long-term tracking of lysosomes in live cell imaging. In addition, viscosity probes are also responsive to polarity, which imposes considerable challenges in cellular imaging. Here, we report IQ-LVs, which can serve as viscosity sensors at the lysosomal pH. In contrast to the majority of current molecular rotors that exhibit blue and green emission, IQ-LVs showed red-shifted emission (∼95 nm) upon increasing the viscosity at pH 4.5. Among the synthesized viscosity sensors, IQ-LV57 and IQ-LV70 lacking an aromatic ring at R1 displayed 15-fold and 116-fold enhancement of red-shifted emission, respectively, upon changes in viscosity. They showed negligible polarity dependency, while the pH sensitivity was minimized by tuning R2 as we envisioned. Our 1D 1H-NMR titrations along with TCSPC analysis revealed that IQ-LVs exhibit two emissions in lysosomes, viscosity-insensitive green emission (+HA’-IQH+) and viscosity-sensitive red-shifted emission (A’-IQH+), which enabled live cell imaging for tracking lysosomes during the autophagy process. In fluorescence confocal imaging, the red emission was enhanced upon the increase in lysosomal viscosity in HeLa and MCF7 cells, and the observed emission from IQ-LV57 and IQ-LV70 had a longer duration than that of LysoTracker™ Deep Red in time-lapse images of live MCF7 cells. Furthermore, treatment of IQ-LV37 in MCF7 cells resulted in increased autophagosomes and autolysosomes during the autophagy process. Further western blot analysis revealed that IQ-LV37 and IQ-LV57 block the degradation of autophagosomes, serving as autophagy inhibitors.
|Journal||Sensors and Actuators, B: Chemical|
|Publication status||Published - 2020 Apr 15|
Bibliographical noteFunding Information:
This work was supported by the National Research Foundation of Korea (NRF) grants (NRF-2018R1A2B2005535 and 2018R1A4A1021703) funded by the Korean government (Ministry of Science and ICT). We acknowledge Ounyoung Lim for contribution in Operetta High-Content imaging data.
This work was supported by the National Research Foundation of Korea (NRF) grants ( NRF-2018R1A2B2005535 and 2018R1A4A1021703 ) funded by the Korean government ( Ministry of Science and ICT ). We acknowledge Ounyoung Lim for contribution in Operetta High-Content imaging data.
© 2020 Elsevier B.V.
All Science Journal Classification (ASJC) codes
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Surfaces, Coatings and Films
- Metals and Alloys
- Electrical and Electronic Engineering
- Materials Chemistry