Abstract
The ability to simultaneously image multiple biomolecules in biologically relevant three-dimensional (3D) cell culture environments would contribute greatly to the understanding of complex cellular mechanisms and cell–material interactions. Here, we present a computational framework for label-free quantitative volumetric Raman imaging (qVRI). We apply qVRI to a selection of biological systems: human pluripotent stem cells with their cardiac derivatives, monocytes and monocyte-derived macrophages in conventional cell culture systems and mesenchymal stem cells inside biomimetic hydrogels that supplied a 3D cell culture environment. We demonstrate visualization and quantification of fine details in cell shape, cytoplasm, nucleus, lipid bodies and cytoskeletal structures in 3D with unprecedented biomolecular specificity for vibrational microspectroscopy.
Highlights
The ability to simultaneously image multiple biomolecules in biologically relevant three-dimensional (3D) cell culture environments would contribute greatly to the understanding of complex cellular mechanisms and cell–material interactions
By taking advantage of this, we demonstrate the visualization of fine details in 3D cell shape, cytoplasm, nucleus, protein rich clusters, intracellular lipid bodies, membrane lipids and submicron-sized cytoskeletal structures with unprecedented biomolecular specificity for vibrational microspectroscopy
We demonstrate for the first time a volumetric quantification of endogenous biomolecules using 3D Raman imaging datasets that allows us to spatially monitor complex biological processes like differentiation within a 3D cell culture system
Summary
The ability to simultaneously image multiple biomolecules in biologically relevant three-dimensional (3D) cell culture environments would contribute greatly to the understanding of complex cellular mechanisms and cell–material interactions. We demonstrate visualization and quantification of fine details in cell shape, cytoplasm, nucleus, lipid bodies and cytoskeletal structures in 3D with unprecedented biomolecular specificity for vibrational microspectroscopy. Raman spectroscopy-based imaging studies on cellular systems have been mostly applied using non-confocal settings associated with challenges arising from substrate background signals and poor z-axis resolution giving rise to overlapping spectral signatures. This naturally compromises the biomolecular specificity achievable using multivariate analysis. We introduce a comprehensive computational framework, namely quantitative volumetric Raman imaging (qVRI) to visualize, identify and quantify biomolecules in 2D and 3D cell culture systems. We demonstrate for the first time a volumetric quantification of endogenous biomolecules using 3D Raman imaging datasets that allows us to spatially monitor complex biological processes like differentiation within a 3D cell culture system
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