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Raman spectroscopy of large extracellular vesicles derived from human microvascular endothelial cells to detect benzoapyrene exposure
Raman spectroscopy of large extracellular vesicles derived from human microvascular endothelial cells to detect benzoapyrene exposure
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Raman spectroscopy of large extracellular vesicles derived from human microvascular endothelial cells to detect benzoapyrene exposure
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Raman spectroscopy of large extracellular vesicles derived from human microvascular endothelial cells to detect benzoapyrene exposure
Raman spectroscopy of large extracellular vesicles derived from human microvascular endothelial cells to detect benzoapyrene exposure

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Raman spectroscopy of large extracellular vesicles derived from human microvascular endothelial cells to detect benzoapyrene exposure
Raman spectroscopy of large extracellular vesicles derived from human microvascular endothelial cells to detect benzoapyrene exposure
Journal Article

Raman spectroscopy of large extracellular vesicles derived from human microvascular endothelial cells to detect benzoapyrene exposure

2024
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Overview
Extracellular vesicles (EVs) have shown great potential as biomarkers since they reflect the physio-pathological status of the producing cell. In the context of cytotoxicity, it has been found that exposing cells to toxicants leads to changes in protein expression and the cargo of the EVs they produce. Here, we studied large extracellular vesicles (lEVs) derived from human microvascular endothelial cells (HMEC-1) to detect the modifications induced by cell exposure to benzo[a]pyrene (B[a]P). We used a custom CaF2-based biochip which allowed hyphenated techniques of investigation: surface plasmon resonance imaging (SPRi) to monitor the adsorption of objects, atomic force microscopy (AFM) to characterise EVs’ size and morphology, and Raman spectroscopy to detect molecular modifications. Results obtained on EVs by Raman microscopy and tip-enhanced Raman spectroscopy (TERS) showed significant differences induced by B[a]P in the high wavenumber region of Raman spectra (2800 to 3000 cm−1), corresponding mainly to lipid modifications. Two types of spectra were detected in the control sample. A support vector machine (SVM) model was trained on the pre-processed spectral data to differentiate between EVs from cells exposed or not to B[a]P at the spectrum level; this model could achieve a sensitivity of 88% and a specificity of 99.5%. Thus, this experimental setup facilitated the distinction between EVs originating from two cell culture conditions and enabled the discrimination of EV subsets within one cell culture condition.