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Multiple and simultaneous fluorophore detection using fluorescence spectrometry and partial least-squares regression
Michael L Griffiths1, Romina P Barbagallo, Jacquie T Keer
1Analytical Technology Division, LGC, Queens Road, Teddington, UK, TW11 0LY. michael.griffiths@lgc.co.uk
Analytical Chemistry
|January 18, 2006
Summary
This study introduces a new method for analyzing complex fluorescent signals without needing to resolve individual spectral peaks. This approach accurately identifies multiple fluorophores in multiplexed analyses, improving data interpretation.
Area of Science:
- Analytical Chemistry
- Biotechnology
- Spectroscopy
Background:
- Multiplexed fluorescent analyses are crucial for high-throughput biological and chemical studies.
- Current methods struggle with signal deconvolution, limiting multiplexing capabilities.
- Advanced data interpretation is needed to identify individual components in complex spectral signals.
Purpose of the Study:
- To investigate a novel approach for signal deconvolution in multiplexed fluorescent analysis.
- To develop a method that does not rely on traditional multivariate curve resolution.
- To enable accurate identification of individual fluorophores within complex spectral data.
Main Methods:
- Application of partial least-squares regression (PLSR) for multivariate prediction.
- Calculation of sample-specific confidence intervals for PLSR predictions.
- Utilizing total spectral signals for fluorophore presence/absence estimation.
Main Results:
- Successfully obtained concentrations for up to eight dye-labeled oligonucleotides (0.6-5.3 x 10^-6 M).
- Demonstrated good discrimination for the presence/absence of seven out of eight labeled oligonucleotides.
- Achieved high efficiencies, ranging from approximately 91% to 100%, in identifying fluorophores.
Conclusions:
- The developed approach offers a robust alternative for signal deconvolution in multiplexed measurements.
- This method bypasses the need for spectral peak resolution, simplifying complex data analysis.
- The technique shows significant potential for application across various multiplexed analytical systems.