Enabling Fluorescence Lifetime Imaging Multiplexing Using UnaG through Its Modification with Canonical and
Valentina V Terekhova1, Daria V Bodunova1, Egor S Gorokhov1
1Faculty of Biology, Lomonosov Moscow State University, Moscow, Russian Federation 119991.
ACS Sensors
|September 4, 2025
Summary
Researchers engineered UnaG protein variants for multicolor imaging. These variants, using bilirubin, offer tunable fluorescence lifetimes for advanced microscopy techniques like FLIM.
Area of Science:
- Biochemistry
- Molecular Biology
- Microscopy
Background:
- Fluorogen-activating proteins are vital for microscopy and functional imaging, offering an oxygen-independent alternative to GFP-like proteins.
- Limitations in fluorophore selectivity and spectral channels hinder multicolor synthetic dye development.
- Poor cell permeability of synthetic dyes restricts their application in biological systems.
Purpose of the Study:
- To develop a palette of UnaG protein probes for fluorescence lifetime imaging microscopy (FLIM).
- To overcome limitations of synthetic dyes by utilizing bilirubin as a natural chromophore.
- To establish structure-lifetime relationships for UnaG-bilirubin complexes for in vivo applications.
Main Methods:
- Rational design and engineering of the UnaG protein.
- Utilizing point mutagenesis and noncanonical amino acid incorporation.
- Employing time-resolved spectroscopy and fluorescence lifetime imaging microscopy (FLIM).
Main Results:
- Generated UnaG variants with a wide range of fluorescence lifetimes (picoseconds to nanoseconds).
- Determined the limits of bilirubin lifetime variation based on protein structural changes.
- Demonstrated reliable distinction of minimal structural changes via in cellula lifetime analysis.
Conclusions:
- Engineered UnaG protein offers a versatile platform for multicolor FLIM probes.
- Bilirubin-based UnaG variants overcome limitations of traditional fluorescent proteins and synthetic dyes.
- Further modifications can optimize spectral and temporal characteristics for quantitative imaging.


