When surface-enhanced Raman spectroscopy meets complex biofluids: A new representation strategy for reliable and...

Area of Science:

• Analytical Chemistry
• Spectroscopy
• Biomolecular Analysis

Background:

• Surface-enhanced Raman spectroscopy (SERS) offers high specificity and sensitivity for molecular detection.
• Characterizing complex biofluids like cell lysates and serums is challenging due to numerous biomolecules and concentration variations.
• Conventional SERS methods using single or averaged spectra fail to capture the full molecular information of complex biofluids.

Purpose of the Study:

• To develop a novel representation strategy for characterizing full molecular information in complex biofluids using SERS.
• To introduce Wasserstein distance (WD) as a robust method for assessing SERS spectral sets, overcoming limitations of traditional chemometrics.

Main Methods:

• Constructing a spectral set from unordered multiple SERS spectra to represent complex biofluid samples.
• Utilizing Wasserstein distance (WD) for quantitative assessment of SERS spectral sets, independent of spectral ordering.
• Experimental validation using cell lysates and human serums to verify reproducibility, uniformity, repeatability, and cardinality effects.

Main Results:

• The SERS spectral set successfully captures detailed molecular information and spatial/temporal distribution characteristics.
• Wasserstein distance demonstrated superiority in quantitatively assessing spectral sets and their properties.
• Experiments confirmed the reproducibility, uniformity, and repeatability of the SERS spectral set approach.
• The SERS spectral sets effectively distinguished different human serum classes and improved prostate cancer classification accuracy.

Conclusions:

• The proposed SERS spectral set is a robust representation for accessing comprehensive information from biological samples.
• This approach offers significant advantages over single or averaged spectra in terms of reproducibility, uniformity, and repeatability.
• The integration of Wasserstein distance enhances the characterization of complex biofluids, solidifying the role of SERS in biological analysis.