Department of Medicine, University of Chicago
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Kim, A., Kilimnik, G., Hara, M. In situ Quantification of Pancreatic Beta-cell Mass in Mice. J. Vis. Exp. (40), e1970, doi:10.3791/1970 (2010).
Part 1: Preparation of Specimens
Part 2: Imaging and quantifying the beta-cell area in the intact pancreas
Figure 1A Virtual Slice image analysis of the entire distribution of beta-cells in an intact adult pancreas
Images of individual optical panels of a male mouse pancreas at 10-wk taken under a 2x objective. The images include the entire distribution of islets, even small clusters of beta-cells (<10 cells).
Figure 1B Virtual Slice image analysis of the entire distribution of beta-cells in an intact adult pancreas
A unified virtual slice with the dorsal pancreas on the right and the ventral pancreas on the left. Scale bar is 5 mm.
Proficient preparation of a pancreas for Virtual Slice imaging will allow for an effective quantification of all GFP-tagged beta-cells in an entire pancreas as a Virtual Slice image with clear and distinct islets. Successful Virtual Slice imaging of the whole pancreas in situ provides the means to examine and quantify the beta-cells, not only individual and total islet area, but also islet size distribution, regional analysis, and growth patterns as well. While ImageJ maintains the capacity to detect all beta-cells simultaneously in the analysis of Virtual Slice images, it can also control which beta-cells to quantify by restricting the analysis to certain islet sizes (by area or diameter), or by location. A standard analysis excludes artifacts e.g., debris smaller than one single beta-cell (<170 μm2) and records the area, perimeter (the distance surrounding an area), circularity (a degree of roundness, where 1.0 represents a perfect circle), and Feret's diameter (the longest distance within an area) for each islet detected. Virtual Slice analysis is capable of enhancing virtual slice images by employing Watershed segmentation, which distinguishes and separates overlapping islets into individual islets according to their shapes. The analysis further produces a series of detailed images; this includes masks of the images under both low and high intensity (Fig. 1C), an outline of all presumed islets, which are each individually numbered and listed in a table of corresponding information (Fig. 1D), and the original Virtual Slice image (Fig. 1B). Note that potential technical bias when choosing threshold values can skew the quantification of islets by including gratuitous light surrounding large structures, or by reducing the total number of islets, especially faint signals from small particles.
Figure 1C Virtual Slice image analysis of the entire distribution of beta-cells in an intact adult pancreas
A mask of the fluorescent particles in the virtual slice. Color codes:  blue: low intensity fluorescence;  green: intermediate intensity fluorescence; and  red: high intensity fluorescence.
Figure 1D Virtual Slice image analysis of the entire distribution of beta-cells in an intact adult pancreas
Quantification of individual islets/clusters of beta-cells. Note that each islet (including small clusters of beta-cells) is numbered, with its information detailed in a corresponding chart. Four parameters were taken for each structure: (1) area; (2) perimeter; (3) circularity: a degree of roundness where the number 1.0 represents a perfect circle; and (4) Feret's diameter: the longest distance within an area. Note that #706 displays the analyses resolution with an area of only a few beta-cells. Watershed segmentation detects groups of adjacent islets, such as the one shown, and appropriately distinguishes them as distinct islets (islets 1554, 1555, and 1556).
Figure 1E Virtual Slice image analysis of the entire distribution of beta-cells in an intact adult pancreas
3-dimensional plot of the virtual slice analysis, with axes of area, perimeter, and Feret's diameter. Each dot represents an islet.
The analysis of Virtual Slice images of islets and beta-cell clusters in the intact pancreas provides a large-scale view of the entire distribution of islets. Developments and changes in total islet distribution over time can thus be studied and compared. Such an example is demonstrated in our analysis of pancreatic islet formation (1). A comprehensive analysis of neonatal mice pancreata at various time points (P1-P21) has demonstrated that islets are formed by fission. While beta-cell proliferation fits with a lognormal probability density function in mice from P1-P10, islet distribution from P12 onward deviates leftward away from the lognormal pattern, suggesting a process of fission. A similar analysis was performed on progressive insulinoma development in mice, which fitted a lognormal function with the parameters of peak position and x-axis scale, and a power law distribution (2):
P(x) = axy. The data are effectively presented in three-dimensional plots of the area, perimeter and Feret's diameter (Fig. 1E). For our study, transgenic mice, in which pancreatic beta-cells were genetically tagged with green fluorescent protein (GFP; 3, 4) under the control of mouse insulin I promoter (MIP), were used. MIP-GFP can also be crossed with other specific transgenic mice in future studies.
No conflicts of interest declared.
The study is supported by US Public Health Service Grant DK-081527, DK-072473 and DK-20595 to the University of Chicago Diabetes Research and Training Center (Animal Models Core), and a gift from the Kovler Family Foundation.
|Large glass slide||Electron Microscopy Sciences||71862-01||75x51x1.2mm|
|Large cover glass||Ted Pella, Inc.||260462||50x75mm|
|Glass Slide||Fisher Scientific||12-550-15||25x75x1.0mm|
|Cover glass||Fisher Scientific||12-458-5M||75x25mm|
|Cover glass||Erie Scientific||25mm circle|
|Fluorescent microscope||Olympus Corporation|
|Dissection microscope||Olympus Corporation|
|Stereo Investigator||MBF Bioscience|
|MIP-GFP mice||Jackson Laboratory|