A pH-Sensitive Double Chromophore Fluorescent Dye for Live-Tracking of Lipophagy.
Pascal M EngelhardtMatteo VeroneseAlpay A EryiğitAnushka DasAlexander T KaczmarekElena I RugarliHans-Günther SchmalzPublished in: Chemistry (Weinheim an der Bergstrasse, Germany) (2024)
Lipid droplet (LD) degradation provides metabolic energy and important building blocks for various cellular processes. The two major LD degradation pathways include autophagy (lipophagy), which involves delivery of LDs to autolysosomes, and lipolysis, which is mediated by lipases. While abnormalities in LD degradation are associated with various pathological disorders, our understanding of lipophagy is still rudimentary. In this study, we describe the development of a lipophilic dye containing two fluorophores, one of which is pH-sensitive and the other pH-stable. We further demonstrate that this "Lipo-Fluddy" can be used to visualize and quantify lipophagy in living cells, in an easily applicable and protein label-free approach. After estimating the ability of compound candidates to penetrate LDs, we synthesized several BODIPY and (pH-switchable) rhodol dyes, whose fluorescence properties (incl. their photophysical compatibility) were analyzed. Of three Lipo-Fluddy dyes synthesized, one exhibited the desired properties and allowed observation of lipophagy by fluorescence microscopy. Also, this dye proved to be non-toxic and suitable for the examination of various cell lines. Moreover, a method was developed to quantify the lipophagy process using flow cytometry, which could be applied in the future in the identification of lipophagy-related genes or in the screening of potential drugs against lipophagy-related diseases.
Keyphrases
- living cells
- single molecule
- label free
- fluorescent probe
- flow cytometry
- aqueous solution
- cell death
- highly efficient
- adipose tissue
- signaling pathway
- high resolution
- endoplasmic reticulum stress
- single cell
- current status
- risk assessment
- fatty acid
- climate change
- high speed
- oxide nanoparticles
- bioinformatics analysis