Multiscale transport and 4D time-lapse imaging in precision-cut liver slices (PCLS)

Abstract

Background: Monitoring cellular processes across different levels of complexity, from the cellular to the tissue scale, is important for understanding tissue structure and function. However, it is challenging to monitor and estimate these structural and dynamic interactions within three-dimensional (3D) tissue models.

Objective: The aim of this study was to design a method for imaging, tracking, and quantifying 3D changes in cell morphology (shape and size) within liver tissue, specifically a precision-cut liver slice (PCLS). A PCLS is a 3D model of the liver that allows the study of the structure and function of liver cells in their native microenvironment.

Methods: Here, we present a method for imaging liver tissue during anisosmotic exposure in a multispectral four-dimensional manner. Three metrics of tissue morphology were measured to quantify the effects of osmotic stress on liver tissue. We estimated the changes in the volume of whole precision cut liver slices, quantified the changes in nuclei position, and calculated the changes in volumetric responses of tissue-embedded cells.

Results: During equilibration with cell-membrane-permeating and non-permeating solutes, the whole tissue experiences shrinkage and expansion. As nuclei showed a change in position and directional displacement under osmotic stress, we demonstrate that nuclei could be used as a probe to measure local osmotic and mechanical stress. Moreover, we demonstrate that cells change their volume within tissue slices as a result of osmotic perturbation and that this change in volume is dependent on the position of the cell within the tissue and the duration of the exposure.

Conclusion: The results of this study have implications for a better understanding of multiscale transport, mechanobiology, and triggered biological responses within complex biological structures.

Keywords: Cryopreservation; Hepatocyte; Image analysis; Mechanobiology; Multiscale modeling; Nuclear displacement; Osmotic stress; Permeating solute; Precision cut liver slices (PCLS); Three-dimensional imaging.

Figure 1. An illustration of the experimental procedure for imaging liver tissue.

(A) The process of acquiring liver tissue, followed by the preparation of PCLS, staining of the liver tissue, and the acquisition of 3D images. The blue well represents the line drawn by hand with a hydrophobic pen to hold tissue slices during imaging and dispensing liquid. (B) A two-dimensional representation of the size of the precision cut liver slice as well as the staining of the membrane and nuclei of the cells with CellMask (green) and Hoechst 33342 (blue; projected as red by Cellpose). A magnified and labelled image also shows the binucleated cells within the liver tissue. Note: The diffuse green color in the image represents cell membrane staining, while the projected red color, which comprise mostly solid disks, indicates nuclei staining. This distinction is also highlighted in the labeled image of the sample.

Figure 2. A microscopy image of mouse liver lobe.

An image of the left liver lobe of a mouse liver (300 µm thick), sectioned by vibratome for the purpose of imaging (A). Using the Imaris surface method, we rendered the volume data for liver slices, in which panel (B) shows the surface outlined by Imaris as a yellow-marked outline. The whole surface was shown with a white masked surface (C), demonstrating the surface masked tissue, which is used to render the area and volume of the tissue.

Figure 3. Volumetric responses of whole tissue slices.

A comparison of volumetric responses of whole tissue slices (n = 1 each treatment) from initial to final time, quantified through z-stack imaging of thick (∼300 µm) tissue sections, followed by 3D reconstruction and volume rendering.

Figure 4. Image analysis flow diagram.

The steps involved in acquiring nuclei tracking data from liver tissue can be seen in this flowchart. Nuclei tracking was done in four dimensions (x, y, z, and time), different colors represent the tracking IDs for the nuclei (n = 800).

Figure 5. Nuclei tracking within a 3D liver tissue model.

This figure illustrates nuclei tracking within a 3D liver tissue model after exposure to non-permeating anisosmotic media. Nuclei path are colored according to their positions change over time, while line (dots) length indicates how far nuclei have drifted from their original position. (A) Changes in nuclei position with hyposmotic media (80 mOsm) causing upward nuclear displacement (n = 620 in single tissue slice). (B) Changes in nuclei position with hyperosmotic solution (DMSO 1 mol/L) causing downward nuclear displacement (n = 565).

Figure 6. Nuclei tracking in a 3D tissue model is presented in the x and y (2D) directions upon exposure to permeating DMSO (1 mol/L).

(A) Using Imaris, nuclei tracks were constructed by tracking the position of the nuclei and displayed on top of the original image. Nuclei paths are colored according to their positions and change over time, while line length indicates how far nuclei have drifted from their original position. Nuclei drift is presented within an original image of the tissue with empty spaces showing a vasculature and portal vein. (B) The change in nuclear position over time is plotted. It indicates a diffusion-limited response of nuclei, with more nuclear drift at the periphery (boundary) of the tissue as compared to the core. This is a demonstration of time dependence of osmotic stress acting on the nuclei of the tissues in a thick tissue section comprising a variety of cells.

Figure 7. The mean volumetric responses of individual cells within 3D liver tissue after exposure to anisosmotic media.

(A) Hyposmotic media (80 mOsm) results in an increase in cell volume followed by a return towards initial volume. (B) Hyperosmotic media (1,215 mOsm) results in a decrease in volume followed by a return towards initial volume. (C) Media containing 30% DMSO (v/v) results in cells that first shrink due to the osmotic efflux of intracellular water, and then enlarge when CPA permeates, and the water is reabsorbed. The dots and error bars represent mean ± standard error of the mean measured from multiple different tissue slices. The black curved line represents the geom smoothing function, a local regression fitting method, applied to add a regression line to the scatter plot. This method is employed to add a regression line that captures the underlying trend in the data. The shaded gray region represents the 95% confidence interval for the fitted values. At least 530 cells were used for each data point.