Functional Plasmonic Microscope: Characterizing the Metabolic Activity of Single Cells via Sub-nm Membrane Fluctuations.

Metabolic abnormalities are at the center of many diseases, and the capability to film and quantify the metabolic activities of a single cell is important for understanding the heterogeneities in these abnormalities. In this paper, a functional plasmonic microscope (FPM) is used to image and measure metabolic activities without fluorescent labels at a single-cell level. The FPM can accurately image and quantify the subnanometer membrane fluctuations with a spatial resolution of 0.5 µm in real time. These active cell membrane fluctuations are caused by metabolic activities across the cell membrane. A three-dimensional (3D) morphology of the bottom cell membrane was imaged and reconstructed with FPM to illustrate the capability of the microscope for cell membrane characterization. Then, the subnanometer cell membrane fluctuations of single cells were imaged and quantified with the FPM using HeLa cells. Cell metabolic heterogeneity is analyzed based on membrane fluctuations of each individual cell that is exposed to similar environmental conditions. In addition, we demonstrated that the FPM could be used to evaluate the therapeutic responses of metabolic inhibitors (glycolysis pathway inhibitor STF 31) on a single-cell level. The result showed that the metabolic activities significantly decrease over time, but the nature of this response varies, depicting cell heterogeneity. A low-concentration dose showed a reduced fluctuation frequency with consistent fluctuation amplitudes, while the high-concentration dose showcased a decreasing trend in both cases. These results have demonstrated the capabilities of the functional plasmonic microscope to measure and quantify metabolic activities for drug discovery.

Integrated Cytometry With Machine Learning Applied to High-Content Imaging of Human Kidney Tissue for In Situ Cell Classification and Neighborhood Analysis.

The human kidney is a complex organ with various cell types that are intricately organized to perform key physiological functions and maintain homeostasis. New imaging modalities, such as mesoscale and highly multiplexed fluorescence microscopy, are increasingly being applied to human kidney tissue to create single-cell resolution data sets that are both spatially large and multidimensional. These single-cell resolution high-content imaging data sets have great potential to uncover the complex spatial organization and cellular makeup of the human kidney. Tissue cytometry is a novel approach used for the quantitative analysis of imaging data; however, the scale and complexity of such data sets pose unique challenges for processing and analysis. We have developed the Volumetric Tissue Exploration and Analysis (VTEA) software, a unique tool that integrates image processing, segmentation, and interactive cytometry analysis into a single framework on desktop computers. Supported by an extensible and open-source framework, VTEA's integrated pipeline now includes enhanced analytical tools, such as machine learning, data visualization, and neighborhood analyses, for hyperdimensional large-scale imaging data sets. These novel capabilities enable the analysis of mesoscale 2- and 3-dimensional multiplexed human kidney imaging data sets (such as co-detection by indexing and 3-dimensional confocal multiplexed fluorescence imaging). We demonstrate the utility of this approach in identifying cell subtypes in the kidney on the basis of labels, spatial association, and their microenvironment or neighborhood membership. VTEA provides an integrated and intuitive approach to decipher the cellular and spatial complexity of the human kidney and complements other transcriptomics and epigenetic efforts to define the landscape of kidney cell types.

Quantitative 3-dimensional imaging and tissue cytometry reveals lymphatic expansion in acute kidney injury.

The lymphatic system plays an integral role in physiology and has recently been identified as a key player in disease progression. Tissue injury stimulates lymphatic expansion, or lymphangiogenesis (LA), though its precise role in disease processes remains unclear. LA is associated with inflammation, which is a key component of acute kidney injury (AKI), for which there are no approved therapies. While LA research has gained traction in the last decade, there exists a significant lack of understanding of this process in the kidney. Though innovative studies have elucidated markers and models with which to study LA, the field is still evolving with ways to visualize lymphatics in vivo. Prospero-related homeobox-1 (Prox-1) is the master regulator of LA and determines lymphatic cell fate through its action on vascular endothelial growth factor receptor expression. Here, we investigate the consequences of AKI on the abundance and distribution of lymphatic endothelial cells using Prox1-tdTomato reporter mice (ProxTom) coupled with large-scale three-dimensional quantitative imaging and tissue cytometry (3DTC). Using these technologies, we describe the spatial dynamics of lymphatic vasculature in quiescence and post-AKI. We also describe the use of lymphatic vessel endothelial hyaluronan receptor-1 (LYVE-1) as a marker of lymphatic vessels using 3DTC in the absence of the ProxTom reporter mice as an alternative approach. The use of 3DTC for lymphatic research presents a new avenue with which to study the origin and distribution of renal lymphatic vessels. These findings will enhance our understanding of renal lymphatic function during injury and could inform the development of novel therapeutics for intervention in AKI.

Large-scale, three-dimensional tissue cytometry of the human kidney: a complete and accessible pipeline.

The advent of personalized medicine has driven the development of novel approaches for obtaining detailed cellular and molecular information from clinical tissue samples. Tissue cytometry is a promising new technique that can be used to enumerate and characterize each cell in a tissue and, unlike flow cytometry and other single-cell techniques, does so in the context of the intact tissue, preserving spatial information that is frequently crucial to understanding a cell's physiology, function, and behavior. However, the wide-scale adoption of tissue cytometry as a research tool has been limited by the fact that published examples utilize specialized techniques that are beyond the capabilities of most laboratories. Here we describe a complete and accessible pipeline, including methods of sample preparation, microscopy, image analysis, and data analysis for large-scale three-dimensional tissue cytometry of human kidney tissues. In this workflow, multiphoton microscopy of unlabeled tissue is first conducted to collect autofluorescence and second-harmonic images. The tissue is then labeled with eight fluorescent probes, and imaged using spectral confocal microscopy. The raw 16-channel images are spectrally deconvolved into 8-channel images, and analyzed using the Volumetric Tissue Exploration and Analysis (VTEA) software developed by our group. We applied this workflow to analyze millimeter-scale tissue samples obtained from human nephrectomies and from renal biopsies from individuals diagnosed with diabetic nephropathy, generating a quantitative census of tens of thousands of cells in each. Such analyses can provide useful insights that can be linked to the biology or pathology of kidney disease. The approach utilizes common laboratory techniques, is compatible with most commercially-available confocal microscope systems and all image and data analysis is conducted using the VTEA image analysis software, which is available as a plug-in for ImageJ.

In Situ Classification of Cell Types in Human Kidney Tissue Using 3D Nuclear Staining.

To understand the physiology and pathology of disease, capturing the heterogeneity of cell types within their tissue environment is fundamental. In such an endeavor, the human kidney presents a formidable challenge because its complex organizational structure is tightly linked to key physiological functions. Advances in imaging-based cell classification may be limited by the need to incorporate specific markers that can link classification to function. Multiplex imaging can mitigate these limitations, but requires cumulative incorporation of markers, which may lead to tissue exhaustion. Furthermore, the application of such strategies in large scale 3-dimensional (3D) imaging is challenging. Here, we propose that 3D nuclear signatures from a DNA stain, DAPI, which could be incorporated in most experimental imaging, can be used for classifying cells in intact human kidney tissue. We developed an unsupervised approach that uses 3D tissue cytometry to generate a large training dataset of nuclei images (NephNuc), where each nucleus is associated with a cell type label. We then devised various supervised machine learning approaches for kidney cell classification and demonstrated that a deep learning approach outperforms classical machine learning or shape-based classifiers. Specifically, a custom 3D convolutional neural network (NephNet3D) trained on nuclei image volumes achieved a balanced accuracy of 80.26%. Importantly, integrating NephNet3D classification with tissue cytometry allowed in situ visualization of cell type classifications in kidney tissue. In conclusion, we present a tissue cytometry and deep learning approach for in situ classification of cell types in human kidney tissue using only a DNA stain. This methodology is generalizable to other tissues and has potential advantages on tissue economy and non-exhaustive classification of different cell types.

Imaging the Electrochemical Impedance of Single Cells via Conductive Polymer Thin Film.

Many fundamentally important biological phenomena involve the cells to establish and break down the adhesive interactions with the substrate. Here, we report a novel optical method that could directly image the electrochemical impedance of cell-substrate interactions at the single cell level with conventional microscopes and cameras. A thin conductive polymer layer on top of the ITO substrate (poly(3,4-ethylenedioxythiophene) poly(styrenesulfonate), PEDOT:PSS) is used as the impedance imaging and sensing layer. A sinusoidal electrochemical potential is applied to the conductive polymer film, and the ion intercalation and transportation in the PEDOT:PSS layer will change the absorption spectrum of the polymer film. The attachment of the cells to the substrate will block and affect the ion doping and dedoping process, and therefore change the color of the polymer film. This process can be captured by any upright or inverted microscope with a simple camera. Utilizing this method, we have successfully imaged the impedance of single-cell attachment, observed the variations of cell-substrate interactions, and measured the impedance changes at different stages of the attachment process. This paper has proposed and successfully demonstrated a new strategy that translates the electrochemical impedance information to an optical signal that could be imaged and used to quantify the local responses. In addition, this method does not need any specially designed optical setup, which may lead to its broad applications in the clinics and biological research laboratories.

A Precision Medicine Approach Uncovers a Unique Signature of Neutrophils in Patients With Brushite Kidney Stones.

INTRODUCTION: We have previously found that papillary histopathology differs greatly between calcium oxalate and brushite stone formers (SF); the latter have much more papillary mineral deposition, tubular cell injury, and tissue fibrosis. METHODS: In this study, we applied unbiased orthogonal omics approaches on biopsied renal papillae and extracted stones from patients with brushite or calcium oxalate (CaOx) stones. Our goal was to discover stone type-specific molecular signatures to advance our understanding of the underlying pathogenesis. RESULTS: Brushite SF did not differ from CaOx SF with respect to metabolic risk factors for stones but did exhibit increased tubule plugging in their papillae. Brushite SF had upregulation of inflammatory pathways in papillary tissue and increased neutrophil markers in stone matrix compared with those with CaOx stones. Large-scale 3-dimensional tissue cytometry on renal papillary biopsies showed an increase in the number and density of neutrophils in the papillae of patients with brushite versus CaOx, thereby linking the observed inflammatory signatures to the neutrophils in the tissue. To explain how neutrophil proteins appear in the stone matrix, we measured neutrophil extracellular trap (NET) formation-NETosis-and found it significantly increased in the papillae of patients with brushite stones compared with CaOx stones. CONCLUSION: We show that increased neutrophil infiltration and NETosis is an unrecognized factor that differentiates brushite and CaOx SF and may explain the markedly increased scarring and inflammation seen in the papillae of patients with brushite stones. Given the increasing prevalence of brushite stones, the role of neutrophil activation in brushite stone formation requires further study.