ArticleClinical and translational medicine2025
Investigating alveolar macrophages in an human ex vivo precision-cut lung slice model of SARS-CoV-2 infection using Raman spectroscopy-A case study.
Article in Clinical and translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Dissecting Cell Death Pathways in Influenza A Virus Infection: Comparative Insights from Human Models.Viruses · 2026Review
- Investigating alveolar macrophages in an human ex vivo precision-cut lung slice model of SARS-CoV-2 infection using Raman spectroscopy-A case study.Clinical and translational medicine · 2025Article
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9 authors.
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Abstract
backgroundAlveolar macrophages (AMs) are crucial innate immune cells that play important roles during infection with severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2). Ex vivo human precision-cut lung slices (PCLSs) are well-suited models to study immune reactions and biochemical changes within host cells as well as to follow functional macrophage phenotype plasticity within complex tissue environment. Raman spectroscopy emerged in recent years as a powerful method for label-free cell characterization.
methodsHuman PCLSs from one donor were infected with either the SARS-CoV-2 delta or omicron variant. Immunofluorescence microscopy localized AMs and virus particles. Cytokine levels of interferon-gamma (IFN-γ) and interleukin 18 (IL-18) were quantified. The lung slice model was optimized for label-free Raman spectroscopic imaging and for the characterization of single AMs within the three-dimensional structure of the PCLS model.
resultsFluorescence microscopy confirmed the location of AMs and virus particles within the PCLS model. Raman spectroscopic imaging generated false-colour images, revealing distinct spectroscopic differences between AMs in the uninfected control PCLS model and those in PCLS models infected with SARS-CoV-2. These differences included variations in intracellular RNA, carotenoid, triacyl glyceride, and glucose levels, consistent in interpretation with cytokine quantification data. A linear discriminant analysis (LDA) classification model achieved an 83% accuracy in distinguishing cells from infected lung slices from those of the uninfected controls. The LDA loadings pointed to spectral bands that had been previously identified in an in vitro stimulation study of macrophages.
conclusionsRaman spectroscopy can characterize the cellular immune response and phenotype plasticity of AMs to infection with SARS-CoV-2 within a PCLS model in a label-free and non-invasive manner. The ability to distinguish cells from infected PCLSs from cells of the uninfected control PCLS based on intracellular biochemical changes highlights the potential of Raman spectroscopy as a powerful diagnostic tool in immunology and clinical diagnostics.
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