An Analytical Tool that Quantifies Cellular Morphology Changes from Three-dimensional Fluorescence Images

Summary

We developed a software platform that utilizes Imaris Neuroscience, ImarisXT and MATLAB to measure the changes in morphology of an undefined shape taken from three-dimensional confocal fluorescence of single cells. This novel approach can be used to quantify changes in cell shape following receptor activation and therefore represents a possible additional tool for drug discovery.

Abstract

The most common software analysis tools available for measuring fluorescence images are for two-dimensional (2D) data that rely on manual settings for inclusion and exclusion of data points, and computer-aided pattern recognition to support the interpretation and findings of the analysis. It has become increasingly important to be able to measure fluorescence images constructed from three-dimensional (3D) datasets in order to be able to capture the complexity of cellular dynamics and understand the basis of cellular plasticity within biological systems. Sophisticated microscopy instruments have permitted the visualization of 3D fluorescence images through the acquisition of multispectral fluorescence images and powerful analytical software that reconstructs the images from confocal stacks that then provide a 3D representation of the collected 2D images. Advanced design-based stereology methods have progressed from the approximation and assumptions of the original model-based stereology¹ even in complex tissue sections². Despite these scientific advances in microscopy, a need remains for an automated analytic method that fully exploits the intrinsic 3D data to allow for the analysis and quantification of the complex changes in cell morphology, protein localization and receptor trafficking.

Current techniques available to quantify fluorescence images include Meta-Morph (Molecular Devices, Sunnyvale, CA) and Image J (NIH) which provide manual analysis. Imaris (Andor Technology, Belfast, Northern Ireland) software provides the feature MeasurementPro, which allows the manual creation of measurement points that can be placed in a volume image or drawn on a series of 2D slices to create a 3D object. This method is useful for single-click point measurements to measure a line distance between two objects or to create a polygon that encloses a region of interest, but it is difficult to apply to complex cellular network structures. Filament Tracer (Andor) allows automatic detection of the 3D neuronal filament-like however, this module has been developed to measure defined structures such as neurons, which are comprised of dendrites, axons and spines (tree-like structure). This module has been ingeniously utilized to make morphological measurements to non-neuronal cells³, however, the output data provide information of an extended cellular network by using a software that depends on a defined cell shape rather than being an amorphous-shaped cellular model. To overcome the issue of analyzing amorphous-shaped cells and making the software more suitable to a biological application, Imaris developed Imaris Cell. This was a scientific project with the Eidgenössische Technische Hochschule, which has been developed to calculate the relationship between cells and organelles. While the software enables the detection of biological constraints, by forcing one nucleus per cell and using cell membranes to segment cells, it cannot be utilized to analyze fluorescence data that are not continuous because ideally it builds cell surface without void spaces. To our knowledge, at present no user-modifiable automated approach that provides morphometric information from 3D fluorescence images has been developed that achieves cellular spatial information of an undefined shape (Figure 1).

We have developed an analytical platform using the Imaris core software module and Imaris XT interfaced to MATLAB (Mat Works, Inc.). These tools allow the 3D measurement of cells without a pre-defined shape and with inconsistent fluorescence network components. Furthermore, this method will allow researchers who have extended expertise in biological systems, but not familiarity to computer applications, to perform quantification of morphological changes in cell dynamics.

Protocol

1. Three-dimensional Morphometric Analysis of Single-cell Phenotypic Changes

1. Human embryonic Kidney (HEK293) cells were transfected with hemagglutinin (HA)-tagged corticotropin releasing factor receptor-2 (CRF-R2), a G protein-coupled receptor (GPCR) as described previously^{4, 5}.
2. The cells were left untreated (no treatment, NT), stimulated with the CRF-R2 endogenous ligand, corticotropin releasing factor, CRF (1 μM, 30 min), or pretreated with a selective CRF-R2 antagonist, anti-sauvagine 30 (AS-30, 1 μM, 30 min) prior to agonist treatment.
3. The cells were then fixed, permeabilized and treated with anti-HA. CRF-R2 was visualize....

Discussion

We showed that CRF treatment induced a significant change in the morphology and location of CRF-R2. The change in CRF-R2 was inhibited by selective antagonist treatment. We showed that receptor modifications were not detected and cannot be measured using the standard 2D multispectral techniques. The ability to study complex 3D images is critical to incorporate the complexity of biological parameters for morphometric analysis. We were able to make 3D measurements of cells without a pre-defined shape with inconsistent fluo.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Human Embryonic Kidney (HEK293)	American Type Culture Collection	CRL-1573
Dulbecco's Modified Eagle Medium (DMEM)	Invitrogen	11965118
Fetal Bovine Serum (FBS)	Invitrogen	SH30070.03
AlexaFluor-488 (IgG2b)	Invitrogen	A-11001
monoclonal anti-HA.11 (IgG1)	Covance	16B12
DAPI	Vector Laboratories	H-1200
CRF	Sigma	C2917
Antisauvagine-30 (AS-30)	Sigma	A4727