Localisation and identification of polystyrene particles in tissue sections using Raman spectroscopic imaging

Area of Science:

• Environmental Science
• Toxicology
• Analytical Chemistry

Background:

• Microplastic particles (MPP) pose risks to organisms and humans via direct uptake or trophic transfer.
• Current in-situ detection methods for MPP in organisms are limited, often requiring fluorescent labeling or chemical digestion, which sacrifices spatial information.
• Accurate detection and localization of MPP in environmental samples are crucial for risk assessment.

Purpose of the Study:

• To develop and validate a workflow for the in-situ localization and identification of non-fluorescent and fluorescent polystyrene (PS) particles in tissue sections.
• To establish methodological approaches for sample preparation, Raman spectroscopic imaging (RSI) parameter optimization, and data analysis for PS differentiation.
• To create a classification algorithm for distinguishing PS particles from biological matrix components in complex tissues.

Main Methods:

• Utilized Raman spectroscopic imaging (RSI) for the analysis of microplastic particles (MPP) in tissue sections of the model organism Eisenia fetida.
• Developed specific sample preparation techniques and optimized RSI parameters for differentiating polystyrene (PS) particles (2-130 μm).
• Implemented a classification algorithm to accurately distinguish PS particle spectra from interfering compounds like haem and intestinal contents, achieving 95% accuracy.

Main Results:

• Successfully localized and identified both non-fluorescent and fluorescent PS particles within the gut lumen and adjacent tissues of Eisenia fetida.
• Demonstrated the capability to detect PS particles as small as 2 μm in diameter using the developed workflow.
• Validated a classification algorithm that effectively differentiates PS particles from biological matrix components with high accuracy.

Conclusions:

• The developed workflow enables the in-situ localization and identification of ingested microplastic particles in organism tissues without prior fluorescent labeling.
• Raman spectroscopic imaging combined with a classification algorithm provides a powerful tool for analyzing microplastic contamination in environmental samples.
• This method overcomes limitations of existing techniques, offering precise spatial information on microplastic distribution within organisms.