Optical diffraction tomography and Raman spectroscopy reveal distinct cellular phenotypes during white and brown adipocyte differentiation

Uncovering Astrocyte Morphological Dynamics Using Optical Diffraction Tomography and Shape-Based Trajectory Inference

Astrocytes, integral components of the central nervous system, are increasingly recognized for their multifaceted roles beyond support cells. Despite their acknowledged importance, understanding the intricacies of astrocyte morphological dynamics remains limited. Our study marks the first exploration of astrocytes using optical diffraction tomography (ODT), establishing a label-free, quantitative method to observe morphological changes in astrocytes over a 7-day in-vitro period. ODT offers quantitative insights into cell volume, dry mass, and area through label-free, real-time measurements-capabilities that are challenging to achieve with conventional imaging techniques. Through comprehensive analysis of 3D refractive index maps and shape characterization techniques, we capture the developmental trajectory and dynamic morphological transformations of astrocytes. Specifically, our observations reveal increased area and a transition to larger, flattened shapes, with alterations in cell volume and density, indicating shifts in cellular composition. By employing unsupervised clustering and pseudotime trajectory analysis, we introduce a novel morphological trajectory inference for neural cells, tracking the morphological evolution of astrocytes from elongated to evenly spread shapes. This analysis marks the first use of trajectory inference based solely on morphology for neural cell types, laying a foundation for future studies employing ODT to examine astrocyte dynamics and neural cell interactions across diverse substrates.

Imaging of perivascular adipose tissue in cardiometabolic diseases by Raman spectroscopy: Towards single-cell analysis

Perivascular adipose tissue (PVAT) has emerged as a dynamic organ influencing vascular function and cardiovascular health. In this brief review, an overview of the recent research in the investigation of PVAT is presented, ranging from in vivo studies to single-cell methodologies, in particular those based on Raman spectroscopy. The strengths and limitations of each, emphasizing their contributions to the current understanding of PVAT biology were discussed. Ultimately, the integration of these diverse methodologies promises to uncover new therapeutic targets and diagnostic biomarkers, including those emerging from simple Raman spectroscopy-based measurements of alterations in lipid unsaturation degree, invariably associated with PVAT dysfunction.

Label-Free Visualization and Morphological Profiling of Neuronal Differentiation and Axonal Degeneration through Quantitative Phase Imaging

Understanding the intricate processes of neuronal growth, degeneration, and neurotoxicity is paramount for unraveling nervous system function and holds significant promise in improving patient outcomes, especially in the context of chemotherapy-induced peripheral neuropathy (CIPN). These processes are influenced by a broad range of entwined events facilitated by chemical, electrical, and mechanical signals. The progress of each process is inherently linked to phenotypic changes in cells. Currently, the primary means of demonstrating morphological changes rely on measurements of neurite outgrowth and axon length. However, conventional techniques for monitoring these processes often require extensive preparation to enable manual or semi-automated measurements. Here, a label-free and non-invasive approach is employed for monitoring neuronal differentiation and degeneration using quantitative phase imaging (QPI). Operating on unlabeled specimens and offering little to no phototoxicity and photobleaching, QPI delivers quantitative maps of optical path length delays that provide an objective measure of cellular morphology and dynamics. This approach enables the visualization and quantification of axon length and other physical properties of dorsal root ganglion (DRG) neuronal cells, allowing greater understanding of neuronal responses to stimuli simulating CIPN conditions. This research paves new avenues for the development of more effective strategies in the clinical management of neurotoxicity.

Cell-TIMP: Cellular Trajectory Inference based on Morphological Parameter

Cellular morphology, shaped by various genetic and environmental influences, is pivotal to studying experimental cell biology, necessitating precise measurement and analysis techniques. Traditional approaches, which rely on geometric metrics derived from stained images, encounter obstacles stemming from both the imaging and analytical domains. Staining processes can disrupt the cell's natural state and diminish accuracy due to photobleaching, while conventional analysis techniques, which categorize cells based on shape to discern pathophysiological conditions, often fail to capture the continuous and asynchronous nature of biological processes such as cell differentiation, immune responses, and cancer progression. In this work, we propose the use of quantitative phase imaging for morphological assessment due to its label-free nature. For analysis, we repurposed the genomic analysis toolbox to perform trajectory inference analysis purely based on morphology information. We applied the developed framework to study the progression of leukemia and breast cancer metastasis. Our approach revealed a clear pattern of morphological evolution tied to the diseases' advancement, highlighting the efficacy of our method in identifying functionally significant shape changes where conventional techniques falter. This advancement offers a fresh perspective on analyzing cellular morphology and holds significant potential for the broader research community, enabling a deeper understanding of complex biological dynamics.