Multi-parameter fluorescence lifetime imaging for high-noise neuroscience applications.

Area of Science:

• Biophysics
• Neuroscience
• Microscopy

Background:

• Fluorescence Lifetime Imaging Microscopy (FLIM) offers insights into molecular interactions and protein dynamics relevant to neurodegenerative diseases.
• Longitudinal FLIM studies in live samples are hindered by rapid acquisition needs, resulting in low signal-to-noise ratios and complex lifetime mixtures.
• Extracting accurate molecular interaction data from noisy FLIM images is challenging, potentially obscuring critical biological insights.

Purpose of the Study:

• To develop advanced methods for precise pixel-wise determination of fluorescence lifetime parameters in high-noise environments.
• To introduce a robust multi-exponential constrained fitting approach for reliable multiparameter extraction from noisy microscopy data.
• To validate the developed methods and demonstrate their application in neuronal imaging of alpha-synuclein aggregation.

Main Methods:

• A novel noise estimation method for accurate, pixel-wise fluorescence lifetime parameter determination.
• A multi-exponential constrained fitting approach for robust multiparameter extraction from noisy data.
• Validation using reference dyes and application to neuronal imaging of alpha-synuclein.

Main Results:

• Precise, pixel-wise determination of fluorescence lifetime parameters in high-noise environments.
• Robust multiparameter extraction from noisy neuronal imaging data.
• Successful validation and illustration in the context of Parkinson's disease-related protein aggregation.

Conclusions:

• The developed methods enable accurate fluorescence lifetime analysis in challenging, high-noise conditions typical of live neuronal studies.
• This advancement facilitates reliable studies of protein dynamics, crucial for understanding neurodegenerative disease etiology.
• The approach has broad applicability across diverse molecular systems and scientific disciplines.