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An innovative spectroscopic method that allows to chemically and structurally characterize viruses directly in suspension within few minutes was developed. A library of five different plant viruses was obtained combining dielectrophoresis (DEP), performed with a device specifically designed to capture and agglomerate virus particles, and Raman spectroscopy to provide a chemical fingerprint of virions. The tested viruses, purified from infected plants, were chosen for their economic impact on horticultural crops and for their different morphological and structural features. Using the Raman-DEP device, specific profiles for each virus were successfully obtained, relying on chemical differences occurring even with genetically similar viruses belonging to the same taxonomic species and morphologically indiscernible by transmission electron microscopy (TEM). Moreover, we investigated the potentiality of Raman-DEP to follow dynamic changes occurring upon heat treatment of tobacco mosaic virus (TMV) particles. Raman peak deviations linked to TMV coat protein conformation were observed upon treatment at temperatures equal or higher than 85°C, substantiating the rod-to-spherical shape transitions observed by TEM and the concomitant drastic loss of infectivity following plant inoculation. Overall, the Raman-DEP method can be useful for the characterization of virus (nano)particles, setting the basis to create a database suitable for the study of viruses or virus derived-nanoparticles relevant for the agricultural, medical, or biotechnological fields.

In this work, biomolecules, such as membrane proteins, lipids, and DNA, were identified and their spatial distribution was mapped within a single Escherichia coli cell by Raman hyperspectral imaging. Raman spectroscopy allows direct, nondestructive, rapid, and cost-effective analysis of biological samples, minimizing the sample preparation and without the need of chemical label or immunological staining. Firstly, a comparison between an air-dried and a freeze-dried cell was made, and the principal vibrational modes associated to the membrane and nucleic acids were identified by the bacterium’s Raman chemical fingerprint. Then, analyzing the Raman hyperspectral images by multivariate statistical analysis, the bacterium biological status was investigated at a subcellular level. Principal components analysis (PCA) was applied for dimensionality reduction of the spectral data, then spectral unmixing was performed by multivariate curve resolution–alternating least squares (MCR-ALS). Thanks to multivariate data analysis, the DNA segregation and the Z-ring formation of a replicating bacterial cell were detected at a sub-micrometer level, opening the way to real-time molecular analysis that could be easily applied on in vivo or ex vivo biological samples, avoiding long preparation and analysis process.