This research was supported by Natural Science Foundation of Zhejiang Province grants (Z23H290001, LY19H280001); National Natural Science Foundation of China grants (82274364, 81673607, and 81774011); as well as the Public Welfare Research Project of Huzhou Science and Technology Grant (2021GY49, 2018GZ24). We appreciate the great help, technical support, and experimental support from the Public Platform of Medical Research Center, Academy of Chinese Medical Science, Zhejiang Chinese Medical University.

1. Material preparation
<ol>
	<li>Culture 2 x 106 Panc02 cells in 12 mL of DMEM medium (10% fetal bovine serum and 100 U/mL of penicillin-streptomycin), and maintain at 37 &#176;C and 95% humidity in an atmosphere of 5% carbon dioxide and 95% air for 48 h.</li>
	<li>Collect Panc02 cells, centrifuge at 28 x g for 2 min, and then discard the supernatant. Ensure that the sample is of an appropriate size (1 x 107 cells), as otherwise, the following fixation and dehydration steps will not work well.</li>
	<li>Add 1 mL of 2.5% glutaraldehyde as a fixative to fix the fresh Panc02 cells in the 1.5 mL micro-centrifuge tubes overnight at 4 &#176;C. 
	NOTE: The samples need to be centrifuged at 1,006 x g for 5 min in each of the following steps (steps 1.3-1.11).</li>
	<li>Aspirate the fixative, and rinse the samples twice with 0.1 M phosphate-buffered saline (PBS), and then rinse twice with double-distilled water (ddH2O) at room temperature for 10 min each.</li>
	<li>Add 50 &#181;L of a solution containing 1% osmium tetroxide (OsO4) and 1.5% potassium ferrocyanide at a ratio of 1:1 at 4 &#176;C for 1 h. Then, rinse twice with 0.1 M PBS for 10 min each time, and rinse with ddH2O for another 10 min.</li>
	<li>Add 1 mL of 1% thiocarbohydrazide (TCH), incubate at room temperature for 30 min to 1 h, and then rinse with ddH2O four times for 10 min each time.</li>
	<li>Add 50 &#181;L of 1% OsO4, fix at room temperature for 1 h, and then rinse with ddH2O four times for 10 min each time.</li>
	<li>Add 1 mL of 2% uranyl acetate at 4 &#176;C overnight, and then rinse with ddH2O four times for 10 min each time.</li>
	<li>Add 1 mL of Walton solution (0.066 g of lead nitrate dissolved in 10 mL of 0.03 mol/L aspartic acid stock solution) at 60 &#176;C for an additional 1 h of incubation.</li>
	<li>Rinse with ddH2O four times for 10 min each time, and then dehydrate in a graded alcohol series for 10 min each time: 50% alcohol, 70% alcohol, 80% alcohol, and 90% alcohol 1x, and 100% alcohol 2x. Then, dehydrate in 100% acetone twice for 10 min each time. Use 1 mL of each solution for the dehydration.</li>
	<li>Mix 200 &#181;L of acetone with Pon 812 epoxy resin at a ratio of 3:1, 1:1, and 1:3. Soak the sample in resin at room temperature for 2 h, 4 h, and 4 h, respectively, and then take the 100% Pon 812 epoxy resin to impregnate overnight. 
	NOTE: When performing the staining and resin embedding steps, it is important to operate in a fume hood as these are toxic substances. Additionally, lab coats and solvent-resistant gloves must be worn during the experiment.</li>
	<li>Put the specimens into an embedding mold, and then place in an oven at 60 &#176;C for 48 h to polymerize. Use flat embedding29 to reduce the appearance of resin around the sample. This simplifies the specimen installation and decreases the impact of charging artifacts on the subsequent image segmentation. 
	NOTE: To subsequently generate a horizontal cutting surface, a small amount of resin can be added into the mold hole, taking care not to overfill it.</li>
	<li>Prepare silicon wafers by first washing them and then hydrophilizing with a concentrated H2SO4/H2O2 solution for 30 min. Collect serially slice strips with a thickness of 70 nm on the hydrophilized silicon wafers by using an ultramicrotome, and dry them in a 60 &#176;C oven for 10 min. 
	NOTE: Slowly capture the slice as the slice floats to the surface of the wafers to prevent slice loss or deformation.</li>
</ol>
2. Image acquisition and three-dimensional reconstruction
<ol>
	<li>Before mounting a silicon wafer on the stage, wash the sections with distilled water three times, and air-dry them. Cut a conductive carbon tape with the size of 1 cm x 0.5 cm, and stick this between the silicon wafer and SEM specimen stage to complete the sample setup (Figure 2E).</li>
	<li>Set the FE-SEM accelerating voltage parameter to 2 kV with a working distance of 4 mm (Figure 3B and Table 1). 
	NOTE: In order to improve the signal-to-noise ratio and reduce the noise in the image, observe at low magnifications whenever possible.As the multiple increases, the scanning range of the SEM decreases, leading to an increase in charge accumulation on the images.</li>
	<li>Click on the H/L icon in the top menu bar. First, at low magnification, orient the first section of the target slice strips, and then click again on the H/L option (Figure 3A) to switch to high-magnification mode; collect an appropriate image for the structure of interest by adjusting the image brightness, contrast, and magnification.</li>
	<li>Select Project View &#62; Open Data, and import the image files to be analyzed into the software.</li>
	<li>Align the pictures by clicking on Align Slices &#62; Edit (Figure 4B), and adjust the Intensity Range value in the lower-left menu bar by modifying the image transparency. Here, use a semi-automatic alignment strategy; specifically, through automatic alignment, make the pictures overlap with a previous picture, and then perform manual fine-tuning. 
	NOTE: In this work, during the process of alignment, the previous image was used as a reference, and the move and rotate operations were utilized to maximally overlap the target structure of the two images. Clicking on Align Current Slice Pair can help to align the images automatically, but misplacement may occur.</li>
	<li>Select the Extract Subvolume module, and clip the aligned data sets to fit the size of the overlapping portion of the whole stack.</li>
	<li>Under the Segmentation subsection (Figure 4C), select Resample &#62; Segmentation &#62; Save. Choose the threshold of the Magic Wand and the size of Brush tool to select the correct range. Here again, adopt a semi-automatic segmentation method by first using the Magic Wand to automatically select a suitable large area, and then use the Brush to accurately describe the details. 
	NOTE: The Magic Wand can be applied to segment images based on the obvious differences in the pixel intensity existing between the structure of interest and the surrounding structures by altering the Masking value and using the Draw Limit Line. It is incapable of distinguishing the charging artifacts generated during image acquisition. Therefore, it may result in incorrect segmentation for the target regions. The Brush tool can be used to segment manually to accurately reconstruct the biological structures.</li>
	<li>Under Segmentation &#62; Selection, click on the + icon to add the selected area (Figure 4C).</li>
	<li>Repeat the above step (2.8) to select the same target structure in different images until the selection is complete for reconstructing the microstructures of interest. 
	NOTE: During the mitochondrial remodeling processes, the selection of the target object must be performed from the picture in the middle of a group of sequential images. If the required area is selected from the first or last picture, the reconstruction result will not be able to present a complete 3D visualization.</li>
	<li>After completing the regional segmentation, generate the image file according to the best results for the size of the object and the picture resolution. Click on Crop Editor, and then enter the number 6 in the Virtual Slider box (Figure 4C).</li>
	<li>In the drop-down menu on the left, right-click on the gray area under the Project subsection, and select Generate Surface &#62; Create &#62; Apply. In the generated file, use the Surface View module to create the surface structure and 3D representation.</li>
</ol>
3. Quantification
<ol>
	<li>Click on Remove Small Spots &#62; Apply (Figure 4D). Under the Project subsection, right-click on the gray area, and select Label Analysis &#62; Apply (Figure 4D).</li>
	<li>Customize the name of the column, and choose a measure group. Select Volume3d and Length3d from the Native Measurements box.</li>
	<li>Click on the Apply button in the lower-left corner of the screen. Copy the data, and graph in the statistical software, such as GraphPad.</li>
</ol>

3D Technique to Visualize Mitochondrial Cristae in Pancreatic Cancer Cells

The authors declare no conflicts of interest.

The method presented here is a useful step-by-step guide for applying the 3D reconstruction technique, which involves applying electron microscopy and image processing technology to the stacking and segmentation of 2D tomographic images generated from serial ultrathin sections. This protocol highlights a limitation of 2D images that can be addressed by 3D visualization of the organelle ultrastructure, which has the advantages of strong reproducibility of the structures at a high-resolution level and higher accuracy. More...

Mitochondria are one of the most important organelles in the cell. They serve as the central hub of cellular bioenergetics and metabolism1,2 and play a critical role in cancer3. Pancreatic cancer (PC) is one of the most difficult cancers4 to treat due to its rapid spread and high mortality rate. Mitochondrial dysfunction, which is mainly caused by changes in the mitochondrial morphology3,5,6,7, has been linked to the disease mechanisms underlying PC8. Mitochondria are also highly dynamic, which is reflected by the frequent and dynamic changes in their network connectivity and cristae structure9. The reshaping of the cristae structure can directly impact the mitochondrial function and cellular state10,11, which are significantly altered during tumor cell growth, metastasis, and tumor microenvironment changes12,13.
In recent years, scientists have studied this organelle using EM observation14,15,16,17; for example, researchers have analyzed the mitochondrial dynamics using 3D reconstruction techniques6,7,18,19. The general concept and method for the 3D reconstruction of electron microscopy images were formally established as early as 196820 and involved combining electron microscopy, electron diffraction, and computer image processing to reconstruct the T4 phage tail. Up until now, electron microscopy 3D imaging technology has made significant advancements in terms of the image resolution21, degree of automation22, and processing volume23 and has been used on an increasingly broad scale in biological research, from the tissue level to the organelle ultrastructure level at the nanometer scale24. In recent years, electron microscopy 3D imaging has also become a promising technology for a wide range of applications25,26,27.
The growing attention on mitochondrial cristae particularly illustrates the essential requirements for ultrastructural volume imaging. Transmission electron microscopy (TEM) has been used to visualize samples collected on a copper grid (400 mesh)28, with the electron beam passing through the section. However, due to the limited range of the copper grid, it is impossible to fully image continuous slices of the same sample29. This complicates the study of target structures during TEM imaging. Additionally, TEM relies on time-consuming and error-prone manual tasks, including cutting and collecting multiple slices and imaging them sequentially21, so it is not adapted for ultrastructural reconstructions of large-volume samples23. At present, the high-resolution reconstruction of large-volume sample imaging is achieved through the use of specialized equipment, such as the TEM camera array (TEMCA)30 or two second-generation TEMCA systems (TEMCA2)31, which enable automated high-throughput imaging in a short time. However, this type of imaging does not have the advantage of being easy to obtain and universal due to the requirement for customized equipment.
Compared with TEM, the method for automatically generating thousands of serial volumetric images for large areas based on SEM32,33 enhances the efficiency and reliability of serial imaging and delivers higher z-resolutions34. For example, serial block-face scanning electron microscopy (SBF-SEM) and focused ion beam scanning electron microscopy (FIB-SEM) have both made it possible to achieve the 3D reconstruction of ultrastructure with high speed, efficiency, and resolution35,36. However, it is inevitable that the block surface is mechanically shaved off by the diamond knife of the SBF-SEM or by milling with the focused ion beam of FIB-SEM33,37. Due to the destructiveness of the two methods to the samples, it is not possible to reconstruct the same target structure again for further analysis38,39,40. In addition, few studies have attempted to reconstruct the 3D organelle ultrastructure of cancer cells using EM to observe pathological changes12. For these reasons, in order to further elucidate the pathological mechanisms of cancer cells, such as pancreatic cancer cells, we propose a novel technology for the 3D reconstruction of serial section images using an ultramicrotome and a field emission scanning electron microscope (FE-SEM) to analyze the mitochondrial ultrastructure at the cristae level; with this technology, high-resolution data can be acquired using an efficient and accessible method. The serial ultrathin sections made using an ultramicrotome can be semi-permanently stored in a grid case and reimaged multiple times, even after several years41. FE-SEM is highly valued as a tool in various research fields due to its ability to provide high-resolution imaging, high magnification, and versatility42. In an attempt to display the fine structure of organelles in 3D, the technique for producing serial 2D image stacks with useful resolution using back-scattered electrons produced by FE-SEM43,44 can also be used to achieve high-throughput and multi-scale imaging of target regions or their associated structures without special equipment45. The generation of charge artifacts directly affects the quality of the acquired images, so it is particularly important to keep the dwell time short.
Thus, the present study elaborates on the experimental procedures employed in this SEM technique to reconstruct the 3D structure of mitochondrial cristae46. Specifically, we show the process developed to achieve the semi-automatic segmentation of mitochondrial regions and digitize the 3D reconstruction using Amira software, which also involves making slice samples using the conventional OTO specimen preparation method44,47, completing the section collection using ultramicrotome slicing, and acquiring sequential 2D data by FE-SEM.

<table><tbody><tr><td>(1S,3R)-RSL3</td><td>MCE</td><td>HY-100218A</td><td></td></tr><tr><td>Acetone</td><td>SIGMA</td><td>179124</td><td></td></tr><tr><td>Amira</td><td>Visage Imaging</td><td></td><td>2020.2</td></tr><tr><td>Aspartic acid</td><td>MCE</td><td>HY-42068</td><td></td></tr><tr><td>Dulbecco&#039;s modified Eagle&amp;rsquo;s medium</td><td>Gibco</td><td>11995115</td><td></td></tr><tr><td>Ethanol</td><td>Merck</td><td>100983</td><td></td></tr><tr><td>Ferrostatin-1</td><td>MCE</td><td>HY-100579</td><td></td></tr><tr><td>Fetal bovine serum</td><td>Gibco</td><td>10437010</td><td></td></tr><tr><td>Field emission scanning electron microscope</td><td>HITACHI</td><td>SU8010</td><td></td></tr><tr><td>Glutaraldehyde</td><td>Alfa Aesar</td><td>A10500.22</td><td></td></tr><tr><td>Lead nitrate</td><td>SANTA CRUZ</td><td>sc-211724</td><td></td></tr><tr><td>Osmium Tetroxide</td><td>SANTA CRUZ</td><td>sc-206008B</td><td></td></tr><tr><td>Panc02</td><td>European Collection of Authenticated Cell Cultures&amp;nbsp;</td><td>98102213</td><td></td></tr><tr><td>Penicillin-streptomycin</td><td>Biosharp</td><td>BL505A</td><td></td></tr><tr><td>Phosphate Buffered Saline</td><td>Biosharp</td><td>BL302A</td><td></td></tr><tr><td>Pon 812 Epoxy resin</td><td>SPI CHEM</td><td>GS02660</td><td></td></tr><tr><td>Potassium ferrocyanide</td><td>Macklin</td><td>P816416</td><td></td></tr><tr><td>Thiocarbohydrazide</td><td>Merck</td><td>223220</td><td></td></tr><tr><td>Ultramicrotome</td><td>LEICA</td><td>EMUC7</td><td></td></tr><tr><td>Uranyl Acetate</td><td>RHAWN</td><td>R032929</td><td></td></tr></tbody></table>

a three-dimensional technique for the visualization of mitochondrial ultrastructural changes in pancreatic cancer cells

Understanding the dynamic features of the cell organelle ultrastructure, which is not only rich in unknown information but also sophisticated from a three-dimensional (3D) perspective, is critical for mechanistic studies. Electron microscopy (EM) offers good imaging depth and allows for the reconstruction of high-resolution image stacks to investigate the ultrastructural morphology of cellular organelles even at the nanometer scale; therefore, 3D reconstruction is gaining importance due to its incomparable advantages. Scanning electron microscopy (SEM) provides a high-throughput image acquisition technology that allows for reconstructing large structures in 3D from the same region of interest in consecutive slices. Therefore, the application of SEM in large-scale 3D reconstruction to restore the true 3D ultrastructure of organelles is becoming increasingly common. In this protocol, we suggest a combination of serial ultrathin section and 3D reconstruction techniques to study mitochondrial cristae in pancreatic cancer cells. The details of how these techniques are performed are described in this protocol in a step-by-step manner, including the osmium-thiocarbohydrazide-osmium (OTO) method, the serial ultrathin section imaging, and the visualization display.

During cell culture (Figure 1A), we first divided the pancreatic cancer cells into a control group cultured with complete culture medium, a (1S,3R)-RSL348 (RSL3, a ferroptosis activator, 100 nM) group, and an RSL3 (100 nM) plus ferrostatin-149 (Fer-1, a ferroptosis inhibitor, 100 nM) group. Through the above experimental steps, the scanning electron microscope acquired 38 (Supplementary&#160;Figure 1), 43 (Supplementary...

Watch this Scientific Journal Video about A Three-Dimensional Technique for the Visualization of Mitochondrial Ultrastructural Changes in Pancreatic Cancer Cells at JoVE.com

Author Spotlight: A Three-Dimensional Technique for the Visualization of Mitochondrial Ultrastructural Changes in Pancreatic Cancer Cells  

This protocol describes how to reconstruct mitochondrial cristae to achieve 3D imaging with high accuracy, high resolution, and high throughput.

A Three-Dimensional Technique for the Visualization of Mitochondrial Ultrastructural Changes in Pancreatic Cancer Cells

Understanding the dynamic features of the cell organelle ultrastructure, which is not only rich in unknown information but also sophisticated from a ...

a-three-dimensional-technique-for-visualization-mitochondrial

Universidad de Cartagena UDEC

Research

JoVE Journal

Cancer Research

1.5K Views.  School of Pharmaceutical Science of Zhejiang Chinese Medical University. This protocol describes how to reconstruct mitochondrial cristae to achieve 3D imaging with high accuracy, high resolution, and high throughput.

Video: Author Spotlight: A Three-Dimensional Technique for the Visualization of Mitochondrial Ultrastructural Changes in Pancreatic Cancer Cells  

Preparation and Metabolic Assay of 3-dimensional Spheroid Co-cultures of Pancreatic Cancer Cells and Fibroblasts

Many cancer types, including pancreatic cancer, have a dense fibrotic stroma that plays an important role in tumor progression and invasion. Activated cancer associated fibroblasts are a key component of the tumor stroma that interact with cancer cells and support their growth and survival. Models that recapitulate the interaction of cancer cells and activated fibroblasts are important tools for studying the stromal biology and for development of antitumor agents. Here, a method is described for the rapid generation of robust 3-dimensional (3D) spheroid co-culture of pancreatic cancer cells and activated pancreatic fibroblasts that can be used for subsequent biological studies. Additionally, described is the use of 3D spheroids in carrying out functional metabolic assays to probe cellular bioenergetics pathways using an extracellular flux analyzer paired with a spheroid microplate. Pancreatic cancer cells (Patu8902) and activated pancreatic fibroblast cells (PS1) were co-cultured and magnetized using a biocompatible nanoparticle assembly. Magnetized cells were rapidly bioprinted using magnetic drives in a 96 well format, in growth media to generate spheroids with a diameter ranging between 400-600 &#181;m within 5-7 days of culture. Functional metabolic assays using Patu8902-PS1 spheroids were then carried out using the extracellular flux technology to probe cellular energetic pathways. The method herein is simple, allows consistent generation of cancer cell-fibroblast spheroid co-cultures and can be potentially adapted to other cancer cell types upon optimization of the current described methodology.

Here, a method is described for the preparation of 3-dimensional (3D) spheroid co-culture of pancreatic cancer cells and fibroblasts, followed by measurement of metabolic functions using an extracellular flux analyzer.

Many cancer types, including pancreatic cancer, have a dense fibrotic stroma that plays an important role in tumor progression and invasion. Activated ...

Murine Pancreatic Imaging Using Implanted Stabilized Window

Stabilized Window for Intravital Imaging of the Murine Pancreas

The physiology and pathophysiology of the pancreas are complex. Diseases of the pancreas, such as pancreatitis and pancreatic adenocarcinoma (PDAC) have high morbidity and mortality. Intravital imaging (IVI) is a powerful technique enabling the high-resolution imaging of tissues in both healthy and diseased states, allowing for real-time observation of cell dynamics. IVI of the murine pancreas presents significant challenges due to the deep visceral and compliant nature of the organ, which make it highly prone to damage and motion artifacts. 
Described here is the process of implantation of the Stabilized Window for Intravital imaging of the murine Pancreas (SWIP). The SWIP allows IVI of the murine pancreas in normal healthy states, during the transformation from the healthy pancreas to acute pancreatitis induced by cerulein, and in malignant states such as pancreatic tumors. In conjunction with genetically labeled cells or the administration of fluorescent dyes, the SWIP enables the measurement of single-cell and subcellular dynamics (including single-cell and collective migration) as well as serial imaging of the same region of interest over multiple days. 
The ability to capture tumor cell migration is of particular importance as the primary cause of cancer-related mortality in PDAC is the overwhelming metastatic burden. Understanding the physiological dynamics of metastasis in PDAC is a critical unmet need and crucial for improving patient prognosis. Overall, the SWIP provides improved imaging stability and expands the application of IVI in the healthy pancreas and malignant pancreas diseases.

Author Spotlight: Revolutionizing Pancreatic Disease Understanding Through Advanced Intravital Imaging 

We present a protocol for the surgical implantation of a stabilized indwelling optical window for subcellular-resolution imaging of the murine pancreas, allowing serial and longitudinal studies of the healthy and diseased pancreas.

The physiology and pathophysiology of the pancreas are complex. Diseases of the pancreas, such as pancreatitis and pancreatic adenocarcinoma (PDAC) have ...

High Resolution 3D Imaging of the Human Pancreas Neuro-insular Network

Using traditional histological methods, researchers are hampered in their ability to image whole tissues or organs in large-scale 3D. Histological sections are generally limited to &#60;20 &#181;m as formalin fixed paraffin section on glass slides or &#60;500 &#181;m for free-floating fixed sections. Therefore, extensive efforts are required for serial sectioning and large-scale image reconstruction methods to recreate 3D for samples &#62;500 &#181;m using traditional methods. In addition, light scatters from macromolecules within tissues, particularly lipids, prevents imaging to a depth &#62;150 &#181;m with most confocal microscopes. To reduce light scatter and to allow for deep tissue imaging using simple confocal microscopy, various optical clearing methods have been developed that are relevant for rodent and human tissue samples fixed by immersion. Several methods are related and use protein crosslinking with acrylamide and tissue clearing with sodium dodecyl sulfate (SDS). Other optical clearing techniques used various solvents though each modification had various advantages and disadvantages. Here, an optimized passive optical clearing method is described for studies of the human pancreas innervation and specifically for interrogation of the innervation of human islets.

Here, we present a protocol to image human pancreas sections in three dimensions (3D) using optimized passive clearing methods. This manuscript demonstrates these procedures for passive optical clearing followed by multiple immunofluorescence staining to identify key elements of the autonomic and sensory neural networks innervating human islets.

Using traditional histological methods, researchers are hampered in their ability to image whole tissues or organs in large-scale 3D. Histological ...

Bioengineering

Three-dimensional Imaging and Analysis of Mitochondria within Human Intraepidermal Nerve Fibers

The goal of this protocol is to study mitochondria within intraepidermal nerve fibers. Therefore, 3D imaging and analysis techniques were developed to isolate nerve-specific mitochondria and evaluate disease-induced alterations of mitochondria in the distal tip of sensory nerves. The protocol combines fluorescence immunohistochemistry, confocal microscopy and 3D image analysis techniques to visualize and quantify nerve-specific mitochondria. Detailed parameters are defined throughout the procedures in order to provide a concrete example of how to use these techniques to isolate nerve-specific mitochondria. Antibodies were used to label nerve and mitochondrial signals within tissue sections of skin punch biopsies, which was followed by indirect immunofluorescence to visualize nerves and mitochondria with a green and red fluorescent signal respectively. Z-series images were acquired with confocal microscopy and 3D analysis software was used to process and analyze the signals. It is not necessary to follow the exact parameters described within, but it is important to be consistent with the ones chosen throughout the staining, acquisition and analysis steps. The strength of this protocol is that it is applicable to a wide variety of circumstances where one fluorescent signal is used to isolate other signals that would otherwise be impossible to study alone.

This protocol uses three-dimensional (3D) imaging and analysis techniques to visualize and quantify nerve-specific mitochondria. The techniques are applicable to other situations where one fluorescent signal is used to isolate a subset of data from another fluorescent signal.

The goal of this protocol is to study mitochondria within intraepidermal nerve fibers. Therefore, 3D imaging and analysis techniques were developed to ...

Neuroscience

Computer-assisted Large-scale Visualization and Quantification of Pancreatic Islet Mass, Size Distribution and Architecture

The pancreatic islet is a unique micro-organ composed of several hormone secreting endocrine cells such as beta-cells (insulin), alpha-cells (glucagon), and delta-cells (somatostatin) that are embedded in the exocrine tissues and comprise 1-2% of the entire pancreas. There is a close correlation between body and pancreas weight. Total beta-cell mass also increases proportionately to compensate for the demand for insulin in the body. What escapes this proportionate expansion is the size distribution of islets. Large animals such as humans share similar islet size distributions with mice, suggesting that this micro-organ has a certain size limit to be functional. The inability of large animal pancreata to generate proportionately larger islets is compensated for by an increase in the number of islets and by an increase in the proportion of larger islets in their overall islet size distribution. Furthermore, islets exhibit a striking plasticity in cellular composition and architecture among different species and also within the same species under various pathophysiological conditions. In the present study, we describe novel approaches for the analysis of biological image data in order to facilitate the automation of analytic processes, which allow for the analysis of large and heterogeneous data collections in the study of such dynamic biological processes and complex structures. Such studies have been hampered due to technical difficulties of unbiased sampling and generating large-scale data sets to precisely capture the complexity of biological processes of islet biology. Here we show methods to collect unbiased "representative" data within the limited availability of samples (or to minimize the sample collection) and the standard experimental settings, and to precisely analyze the complex three-dimensional structure of the islet. Computer-assisted automation allows for the collection and analysis of large-scale data sets and also assures unbiased interpretation of the data. Furthermore, the precise quantification of islet size distribution and spatial coordinates (i.e. X, Y, Z-positions) not only leads to an accurate visualization of pancreatic islet structure and composition, but also allows us to identify patterns during development and adaptation to altering conditions through mathematical modeling. The methods developed in this study are applicable to studies of many other systems and organisms as well.

Novel computer-assisted methods of large-scale procurement and analysis of immunohistochemically stained pancreatic specimens are described: (1) Virtual Slice capture of the entire section; (2) Mass analysis of large-scale data; (3) Reconstruction of 2D Virtual Slices; (4) 3D islet mapping; and (5) Mathematical analysis.

The pancreatic islet is a unique micro-organ composed of several hormone secreting endocrine cells such as beta-cells (insulin), alpha-cells (glucagon), ...

Biology

Visualization of Endogenous Mitophagy Complexes In Situ in Human Pancreatic Beta Cells Utilizing Proximity Ligation Assay

Mitophagy is an essential mitochondrial quality control pathway, which is crucial for pancreatic islet beta cell bioenergetics to fuel glucose-stimulated insulin release. Assessment of mitophagy is challenging and often requires genetic reporters or multiple complementary techniques not easily utilized in tissue samples, such as primary human pancreatic islets. Here we demonstrate a robust approach to visualize and quantify formation of key endogenous mitophagy complexes in primary human pancreatic islets. Utilizing the sensitive proximity ligation assay technique to detect interaction of the mitophagy regulators NRDP1 and USP8, we are able to specifically quantify formation of essential mitophagy complexes in situ. By coupling this approach to counterstaining for the transcription factor PDX1, we can quantify mitophagy complexes, and the factors that can impair mitophagy, specifically within beta cells. The methodology we describe overcomes the need for large quantities of cellular extracts required for other protein-protein interaction studies, such as immunoprecipitation (IP) or mass spectrometry, and is ideal for precious human islet&#160;samples generally not available in sufficient quantities for these approaches. Further, this methodology obviates the need for flow sorting techniques to purify beta cells from a heterogeneous islet population for downstream protein applications. Thus, we describe a valuable protocol for visualization of mitophagy highly compatible for use in heterogeneous and limited cell populations.

This protocol outlines a method for quantitative analysis of mitophagy protein complex formation specifically in beta cells from primary human islet samples. This technique thus allows analysis of mitophagy from limited biological material, which are crucial in precious human pancreatic beta cell samples.

Mitophagy is an essential mitochondrial quality control pathway, which is crucial for pancreatic islet beta cell bioenergetics to fuel glucose-stimulated ...

Medicine

Stabilized Longitudinal In Vivo Cellular-Level Visualization of the Pancreas in a Murine Model with a Pancreatic Intravital Imaging Window

Direct in vivo cellular-resolution imaging of the pancreas in a live small animal model has been technically challenging. A recent intravital imaging study, with an abdominal imaging window, enabled visualization of the cellular dynamics in abdominal organs in vivo. However, due to the soft sheet-like architecture of the mouse pancreas that can be easily influenced by physiologic movement (e.g., peristalsis and respiration), it was difficult to perform stabilized longitudinal in vivo imaging over several weeks at the cellular level to identify, track, and quantify islets or cancer cells in the mouse pancreas. Herein, we describe a method for implanting a novel supporting base, an integrated pancreatic intravital imaging window, that can spatially separate the pancreas from the bowel for longitudinal time-lapse intravital imaging of the pancreas microstructure. Longitudinal in vivo imaging with the imaging window enables stable visualization, allowing for the tracking of islets over a period of 3 weeks and high-resolution three-dimensional imaging of the microstructure, as evidenced here in an orthotopic pancreatic cancer model. With our method, further intravital imaging studies can elucidate the pathophysiology of various diseases involving the pancreas at the cellular level.

Stabilized Longitudinal In Vivo Cellular-Level Visualization of the Pancreas in a Murine Model with a Pancreatic Intravital Imaging Window

In vivo high-resolution imaging of the pancreas was facilitated with the pancreatic intravital imaging window.

Direct in vivo cellular-resolution imaging of the pancreas in a live small animal model has been technically challenging. A recent intravital imaging ...

Organotypic Slice Cultures as Preclinical Models of Tumor Microenvironment in Primary Pancreatic Cancer and Metastasis

Realistic preclinical models of primary pancreatic cancer and metastasis are urgently needed to test the therapy response ex vivo and facilitate personalized patient treatment. However, the absence of tumor-specific microenvironment in currently used models, e.g., patient-derived cell lines and xenografts, only allows limited predictive insights. Organotypic slice cultures (OTSCs) comprise intact multicellular tissue, which can be rapidly used for the spatially resolved drug response testing.
This protocol describes the generation and cultivation of viable tumor slices of pancreatic cancer and its metastasis. Briefly, tissue is casted in low melt agarose and stored in cold isotonic buffer. Next, tissue slices of 300 &#181;m thickness are generated with a vibratome. After preparation, slices are cultured at an air-liquid interface using cell culture inserts and an appropriate cultivation medium. During cultivation, changes in cell differentiation and viability can be monitored. Additionally, this technique enables the application of treatment to viable human tumor tissue ex vivo and subsequent downstream analyses, such as transcriptome and proteome profiling.
OTSCs provide a unique opportunity to test the individual treatment response ex vivo and identify individual transcriptomic and proteomic profiles associated with the respective response of distinct slices of a tumor. OTSCs can be further explored to identify therapeutic strategies to personalize treatment of primary pancreatic cancer and metastasis.

This protocol describes the preparation of organotypic slice cultures (OTSCs). This technique facilitates the ex vivo cultivation of intact multicellular tissue. OTSCs can be used immediately to test for their respective response to drugs in a multicellular environment.

Realistic preclinical models of primary pancreatic cancer and metastasis are urgently needed to test the therapy response ex vivo and facilitate ...

An In Situ Immunostaining Protocol for Parkinson's Disease Study

Histological Examination of Mitochondrial Morphology in a Parkinson's Disease Model

Mitochondria play a central role in the energy metabolism of cells, and their function is especially important for neurons due to their high energy demand. Therefore, mitochondrial dysfunction is a pathological hallmark of various neurological disorders, including Parkinson's disease. The shape and organization of the mitochondrial network is highly plastic, which allows the cell to respond to environmental cues and needs, and the structure of mitochondria is also tightly linked to their health. Here, we present a protocol to study mitochondrial morphology in situ based on immunostaining of the mitochondrial protein VDAC1 and subsequent image analysis. This tool could be particularly useful for the study of neurodegenerative disorders because it can detect subtle differences in mitochondrial counts and shape induced by aggregates of &#945;-synuclein, an aggregation-prone protein heavily involved in the pathology of Parkinson's disease. This method allows one to report that substantia nigra pars compacta dopaminergic neurons harboring pS129 lesions show mitochondrial fragmentation (as suggested by their reduced Aspect Ratio, AR) compared to their healthy neighboring neurons in a pre-formed fibril intracranial injection Parkinson model.

Author Spotlight: Establishing a New Fluorescence-Based Protocol for In Vivo Mitochondrial Morphology Analysis in Parkinson's Disease

This study presents a method to analyze the morphology of mitochondria based on immunostaining and image analysis in mouse brain tissue in situ. It also describes how this allows one to detect changes in mitochondrial morphology induced by protein aggregation in Parkinson's disease models.

Mitochondria play a central role in the energy metabolism of cells, and their function is especially important for neurons due to their high energy ...

3D Mitochondrial Ultrastructure of Drosophila Indirect Flight Muscle Revealed by Serial-section Electron Tomography

Mitochondria are cellular powerhouses that produce ATP, lipids, and metabolites, as well as regulate calcium homeostasis and cell death. The unique cristae-rich double membrane ultrastructure of this organelle is elegantly arranged to carry out multiple functions by partitioning biomolecules. Mitochondrial ultrastructure is intimately linked with various functions; however, the fine details of these structure-function relationships are only beginning to be described. Here, we demonstrate the application of serial-section electron tomography to elucidate mitochondrial structure in Drosophila indirect flight muscle. Serial-section electron tomography may be adapted to study any cellular structure in three-dimensions.

3D Mitochondrial Ultrastructure of Drosophila Indirect Flight Muscle Revealed by Serial-section Electron Tomography

In this protocol, we demonstrate the application of serial-section electron tomography to elucidate mitochondrial structure in Drosophila indirect flight muscle.

Mitochondria are cellular powerhouses that produce ATP, lipids, and metabolites, as well as regulate calcium homeostasis and cell death. The unique ...

A Three-Dimensional Technique for the Visualization of Mitochondrial Ultrastructural Changes in Pancreatic Cancer Cells

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Stabilized Longitudinal In Vivo Cellular-Level Visualization of the Pancreas in a Murine Model with a Pancreatic Intravital Imaging Window

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Histological Examination of Mitochondrial Morphology in a Parkinson's Disease Model

3D Mitochondrial Ultrastructure of Drosophila Indirect Flight Muscle Revealed by Serial-section Electron Tomography