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

NanoImpact 2023 12 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 50 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Jasmin Kniese, Sven Ritschar, Lina Bünger, Heike Feldhaar, Christian Laforsch, Andreas Römpp, Heinar Schmidt

Summary

Researchers developed a Raman spectroscopic imaging method to localize and identify polystyrene microplastic particles directly within tissue sections, enabling in-situ detection without fluorescent labeling and making environmental sample analysis feasible.

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.

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