Methodologies for label free Raman microspectroscopic monitoring of viral replication processes in vitro

Abstract

This study demonstrates the use of Raman Spectroscopy, integrated with multivariate statistical analysis, to monitor the process of viral infection in cells, in-vitro, using the model example of Sendai Virus (SeV) infection in LLC-MK2 monkey kidney cells. A comprehensive methodology is described for determining a precise multiplicity of infection, 48 h post infection, tailored for analysis of viral-host interactions using Raman Microspectroscopy. SeV infected LLC-MK2 cells were fixed on a gold-coated glass slide for Raman spectroscopic analysis. 30-point spectra of uninfected control and 30-point spectra of SeV-infected cells were acquired, focusing randomly on the individual cells. Mean Raman spectra of the control and SeV-infected LLC-MK2 cells revealed spectral differences of peaks corresponding to nucleic acids (485 cm⁻¹, 785 cm⁻¹), lipids (1445 cm⁻¹) and proteins (1600 cm⁻¹, 1655 cm⁻¹). These changes in the relative intensities of Raman peaks indicate modifications in the biochemical content, potentially due to viral entry and replication inside the cells. Principal Components Analysis distinguished between control and SeV-infected LLC-MK2 cells, indicating significant biochemical alterations in response to the SeV infection. Partial Least Squares Discriminant Analysis can be employed to quantify the differentiation of the spectral datasets of the infected/noninfected cells, classifying them with 100 % sensitivity and specificity. The detailed methodology described in the study is potentially a powerful tool for tracking viral replication and detecting viral infections and has the potential to impact future research on host-virus interactions and viral diagnostics. Further research on these spectral differences can contribute to developing more efficient viral screening techniques and a better understanding of viral infections.