4.8 Article

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

Journal

ANALYTICAL CHEMISTRY
Volume 93, Issue 37, Pages 12504-12513

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.1c01284

Keywords

-

Funding

  1. ANR [ANR-15-CE32-0004]
  2. Chevreul Institute
  3. Ministere de l'Enseignement Superieur et de la Recherche
  4. Region Hauts-de-France (FEDER)
  5. Spanish government [PID 2019-1071586B-IOO]
  6. Agence Nationale de la Recherche (ANR) [ANR-15-CE32-0004] Funding Source: Agence Nationale de la Recherche (ANR)

Ask authors/readers for more resources

The study introduces a multivariate curve resolution method based on data slicing, allowing tailored and fit-free analysis of multiexponential fluorescence decay curves. This approach enables the recovery of individual components with decay profiles that are only partially describable by monoexponential functions, and can extract fluorescence lifetime information accurately.
Time-resolved fluorescence spectroscopy (TRFS), i.e., measurement of fluorescence decay curves for different excitation and/or emission wavelengths, provides specific and sensitive local information on molecules and on their environment. However, TRFS relies on multiexponential data fitting to derive fluorescence lifetimes from the measured decay curves and the time resolution of the technique is limited by the instrumental response function (IRF). We propose here a multivariate curve resolution (MCR) approach based on data slicing to perform tailored and fit-free analysis of multiexponential fluorescence decay curves. MCR slicing, taking as a basic framework the multivariate curve resolution-alternating least-squares (MCR-ALS) soft-modeling algorithm, relies on a hybrid bilinear/trilinear data decomposition. A key feature of the method is that it enables the recovery of individual components characterized by decay profiles that are only partially describable by monoexponential functions. For TRFS data, not only pure multiexponential tail information but also shorter time delay information can be decomposed, where the signal deviates from the ideal exponential behavior due to the limited time resolution. The accuracy of the proposed approach is validated by analyzing mixtures of three commercial dyes and characterizing the mixture composition, lifetimes, and associated contributions, even in situations where only ternary mixture samples are available. MCR slicing is also applied to the analysis of TRFS data obtained on a photoswitchable fluorescent protein (rsEGFP2). Three fluorescence lifetimes are extracted, along with the profile of the IRF, highlighting that decomposition of complex systems, for which individual isomers are characterized by different exponential decays, can also be achieved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available