High-sensitivity hyperspectral vibrational imaging of heart tissues by mid-infrared photothermal microscopy

Cardiac multiscale bioimaging: from nano- through micro- to mesoscales

Cardiac multiscale bioimaging is an emerging field that aims to provide a comprehensive understanding of the heart and its functions at various levels, from the molecular to the entire organ. It combines both physiologically and clinically relevant dimensions: from nano- and micrometer resolution imaging based on vibrational spectroscopy and high-resolution microscopy to assess molecular processes in cardiac cells and myocardial tissue, to mesoscale structural investigations to improve the understanding of cardiac (patho)physiology. Tailored super-resolution deep microscopy with advanced proteomic methods and hands-on experience are thus strategically combined to improve the quality of cardiovascular research and support future medical decision-making by gaining additional biomolecular information for translational and diagnostic applications.

Probing Chemical Complexity of Amyloid Plaques in Alzheimer's Disease Mice using Hyperspectral Raman Imaging

One of the distinctive pathological features of Alzheimer's disease (AD) is the deposition of amyloid plaques within the brain of affected individuals. These plaques have traditionally been investigated using labeling techniques such as immunohistochemical imaging. However, the use of labeling can disrupt the structural integrity of the molecules being analyzed. Hence, it is imperative to employ label-free imaging methods for noninvasive examination of amyloid deposits in their native form, thereby providing more relevant information pertaining to AD. This study presents compelling evidence that label-free and nondestructive confocal Raman imaging is a highly effective approach for the identification and chemical characterization of amyloid plaques within cortical regions of an arcAβ mouse model of AD. Furthermore, this investigation elucidates how the spatial correlation of Raman signals can be exploited to identify robust Raman marker bands and discern proteins and lipids from amyloid plaques. Finally, this study uncovers the existence of distinct types of amyloid plaques in the arcAβ mouse brain, exhibiting significant disparities in terms of not only shape and size but also molecular composition.

Label-free visualization of photosynthetic microbial biofilms using mid-infrared photothermal and autofluorescence imaging

The formation of photosynthetic microbial biofilms comprising multispecies biomolecules, such as extracellular polymeric substances (EPSs), and microbial cells play pivotal roles in maintaining or stimulating their biological functions. Although there are numerous studies on photosynthetic microbial biofilms, the spatial distribution of EPS components that are vital for microbial biofilm formation, such as exopolysaccharides and proteins, is not well understood. Visualization of photosynthetic microbial biofilms requires label-free methods, because labelling EPSs results in structural changes or aggregation. Raman spectroscopy is useful for label-free visualization of biofilm constituents based on chemical contrast. However, interference resulting from the bright autofluorescence of photosynthetic molecules and the low detection efficiency of Raman scattering make visualization a challenge. Herein, we visualized photosynthetic microbial biofilms in a label-free manner using a super-resolution optical infrared absorption imaging technique, called mid-infrared photothermal (MIP) microscopy. By leveraging the advantages of MIP microscopy, such as its sub-micrometer spatial resolution, autofluorescence-free features, and high detection sensitivity, the distribution of cyanobacteria and their extracellular polysaccharides in the biofilm matrix were successfully visualized. This showed that cyanobacterial cells were aligned along acidic/sulfated polysaccharides in the extracellular environment. Furthermore, spectroscopic analyses elucidated that during formation of biofilms, sulfated polysaccharides initially form linear structures followed by entrapment of cyanobacterial cells. The present study provides the foundation for further studies on the formation, structure, and biological functions of microbial biofilms.

Single virus fingerprinting by widefield interferometric defocus-enhanced mid-infrared photothermal microscopy

Clinical identification and fundamental study of viruses rely on the detection of viral proteins or viral nucleic acids. Yet, amplification-based and antigen-based methods are not able to provide precise compositional information of individual virions due to small particle size and low-abundance chemical contents (e.g., ~ 5000 proteins in a vesicular stomatitis virus). Here, we report a widefield interferometric defocus-enhanced mid-infrared photothermal (WIDE-MIP) microscope for high-throughput fingerprinting of single viruses. With the identification of feature absorption peaks, WIDE-MIP reveals the contents of viral proteins and nucleic acids in single DNA vaccinia viruses and RNA vesicular stomatitis viruses. Different nucleic acid signatures of thymine and uracil residue vibrations are obtained to differentiate DNA and RNA viruses. WIDE-MIP imaging further reveals an enriched β sheet components in DNA varicella-zoster virus proteins. Together, these advances open a new avenue for compositional analysis of viral vectors and elucidating protein function in an assembled virion.

Digital Histopathology by Infrared Spectroscopic Imaging

Infrared (IR) spectroscopic imaging records spatially resolved molecular vibrational spectra, enabling a comprehensive measurement of the chemical makeup and heterogeneity of biological tissues. Combining this novel contrast mechanism in microscopy with the use of artificial intelligence can transform the practice of histopathology, which currently relies largely on human examination of morphologic patterns within stained tissue. First, this review summarizes IR imaging instrumentation especially suited to histopathology, analyses of its performance, and major trends. Second, an overview of data processing methods and application of machine learning is given, with an emphasis on the emerging use of deep learning. Third, a discussion on workflows in pathology is provided, with four categories proposed based on the complexity of methods and the analytical performance needed. Last, a set of guidelines, termed experimental and analytical specifications for spectroscopic imaging in histopathology, are proposed to help standardize the diversity of approaches in this emerging area.