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Updated: Aug 1, 2025
Implementation of a Nonlinear Microscope Based on Stimulated Raman Scattering
Published on: July 6, 2019
Localisation and identification of polystyrene particles in tissue sections using Raman spectroscopic imaging
Jasmin Kniese1, Sven Ritschar2, Lina Bünger1
1Bioanalytical Sciences and Food Analysis, University of Bayreuth, Universitätsstraße 30, 95447 Bayreuth, Germany.
Abstract:
The uptake of microplastic particles (MPP) by organisms is frequently described and poses a potential risk for these organisms and ultimately for humans either through direct uptake or trophic transfer. Currently, the in-situ detection of MPP in organisms is typically based on histological examination of tissue sections after uptake of fluorescently-labelled MPP and is thus not feasible for environmental samples. The alternative approach is purification of MPP from whole organisms or organs by chemical digestion and subsequent spectroscopic detection (FT-IR or Raman). While this approach is feasible for un-labelled particles it goes along with loss of any spatial information related to the location in the tissue. In our study we aimed at providing a workflow for the localisation and identification of non-fluorescent and fluorescent polystyrene (PS) particles (fragments, size range 2-130 μm) in tissue sections of the model organism Eisenia fetida with Raman spectroscopic imaging (RSI). We provide methodological approaches for the preparation of the samples, technical parameters for the RSI measurements and data analysis for PS differentiation in tissue sections. The developed approaches were combined in a workflow for the in-situ analysis of MPP in tissue sections. The spectroscopic analysis requires differentiation of spectra of MPP and interfering compounds, which is challenging given the complexity of tissue. Therefore, a classification algorithm was developed to differentiate PS particles from haem, intestinal contents and surrounding tissue. It allows the differentiation of PS particles from protein in the tissue of E. fetida with an accuracy of 95%. The smallest PS particle detected in the tissue was 2 μm in diameter. We show that it is possible to localise and identify non-fluorescent and fluorescent ingested PS particles directly in tissue sections of E. fetida in the gut lumen and the adjacent tissue.
Insights
Researchers developed a new method to detect microplastic particles (MPP) in earthworm tissues. This workflow uses Raman spectroscopic imaging to locate and identify both fluorescent and non-fluorescent polystyrene particles within tissue sections.
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.
