Multivariate Curve Resolution Slicing of Multiexponential Time-Resolved Spectroscopy Fluorescence Data

Area of Science:

• Analytical Chemistry
• Spectroscopy
• Physical Chemistry

Background:

• Time-resolved fluorescence spectroscopy (TRFS) provides molecular insights but relies on complex multiexponential fitting.
• The instrumental response function (IRF) limits TRFS time resolution and complicates data analysis.
• Extracting accurate fluorescence lifetimes from decay curves is challenging due to instrumental limitations and sample complexity.

Purpose of the Study:

• To develop a novel, fit-free method for analyzing multiexponential fluorescence decay curves in TRFS.
• To enhance the accuracy and applicability of TRFS by overcoming limitations imposed by the IRF.
• To enable detailed characterization of complex molecular systems and mixtures using TRFS data.

Main Methods:

• A multivariate curve resolution (MCR) approach based on data slicing was developed.
• The method utilizes a hybrid bilinear/trilinear data decomposition within the MCR-ALS framework.
• The approach is designed to handle decay profiles deviating from ideal monoexponential behavior.

Main Results:

• The MCR slicing method accurately determined composition, lifetimes, and contributions for ternary dye mixtures.
• The technique successfully recovered individual component decay profiles, even those not purely monoexponential.
• Analysis of a photoswitchable fluorescent protein (rsEGFP2) yielded three distinct fluorescence lifetimes and the IRF profile.

Conclusions:

• MCR slicing offers a robust, fit-free alternative for analyzing complex TRFS data.
• The method accurately decomposes multiexponential decays and characterizes components in intricate systems.
• This approach advances the capabilities of TRFS for detailed molecular analysis.