Cells within the brain are highly organized and coordinate complex processes with each other. The ability to simultaneously visualize the organization and interactions of cells and molecules within brain tissue remains an important issue to understand the brain comprehensively. Stimulated Raman scattering (SRS) and fluorescence, two powerful imaging modalities, can provide complementary molecular contrasts within cells and tissue samples. Here, we present a high-speed super-multiplex imaging platform that combines SRS microscopy with confocal fluorescence microscopy to perform rapid 7-color brain imaging. We show simultaneous imaging of cellular components within the brain such as astrocytes, axons, and blood vessels while also showing organelles such as the nucleus and actin cytoskeleton. Also, we demonstrate the ability to take depth-resolved images that elucidate the three-dimensional organization of diverse components within brain tissue. This platform can be adapted to explore various processes within brain tissue that can reveal critical information about the brain and how it is affected by diseases, which leads toward a deeper understanding of disease progression and potentially the development of therapeutic options for brain diseases.
Worldwide, there has been an increase in the number of cases of non-Hodgkin lymphoma (NHL). Burkitt lymphoma comprises of 30-40% of pediatric NHL cases and is a rapidly growing tumor. Access to efficient diagnostic paradigms are therefore crucial for quick therapeutic intervention. Currently, the identification of Burkitt lymphoma and other NHL involves histologic and genetic testing which can be costly and slow. Also, the process of fixing tissue and staining biopsy samples can lead to inconsistent results. Recently, Raman spectroscopy has exposed potential biomarkers in B-cells that could be indicative of cancer. However, slow acquisition speed limits the viability of adapting Raman spectroscopy in a clinical setting. Here we demonstrate a high-speed method to visualize Burkitt lymphoma cells and non-malignant B-cells which does not involve chemical alteration or destruction of cells. Preliminary results indicate higher collection of lipid droplets in malignant B-cells compared to normal B-cells. Using a support-vector machine learning algorithm, we were able to exploit these chemical differences and classify malignant cells from non-malignant cells with a sensitivity of 80% and specificity of 81.2%. Further work into refining this process can lead towards faster identification of cells and could potentially provide deeper insights into the chemical processes that occur within malignant blood cells.
Among various optical methods, fluorescence imaging has been the most widely exploited thanks to its superior sensitivity and specificity, but the resolvable colors are restricted to 2-5 colors because of the intrinsically broad and featureless spectra. Recently, this fluorescent “color barrier” was broken and super-multiplex optical imaging became possible taking advantage of well-designed Raman probes. However, the acquisition of the super-multiplex images is still relatively slow which impedes wider applications. Here, we demonstrate fast super-multiplex organelle imaging with high-speed color switching and acquisition, which accelerates the imaging speed by 2 orders of magnitude. We applied it in imaging cytometry, tracing mitosis and fast organelle motions in live cells. We anticipate that high-speed supermultiplex optical imaging can expand to a much wider field of biological researches.
Simultaneous localization of multiple cellular components related to the cellular activities, e.g. metabolism of small molecules, is not well understood due to the intrinsic limitations of fluorescence imaging technologies. The broad fluorescence emission often limits the available color number to ~4. Additionally, staining of small metabolic precursors is still difficult using fluorophores because the relatively large size of fluorophores will affect the regular metabolism of small molecules. Here, we apply our newly developed high-speed multicolor stimulated Raman and fluorescence imaging platform to observe and investigate lipid metabolism in live HeLa cells. Metabolic products generated from the deuterated palmitic acid were imaged in the Raman silent region using stimulated Raman scattering microscopy; meanwhile four kinds of organelles were imaged using fast-tunable confocal fluorescence microscopy. By taking advantages of both stimulated Raman imaging and fluorescence imaging, it enables the localization of multiple components up to five during cellular metabolism in live cells, which can be a helpful method to research complex biomedical processes.
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