Quantification of vesicles in differentiating human SH-SY5Y neuroblastoma cells by automated image analysis

Quantitative Phenotypic Image Analysis of Three-Dimensional Organotypic Cultures

Glandular epithelial cells differentiate into three-dimensional (3D) multicellular or acinar structures, particularly when embedded in laminin-rich extracellular matrix (ECM). The spectrum of different multicellular morphologies formed in 3D is a reliable indicator for the differentiation potential of normal, non-transformed cells compared to different stages of malignant progression. Motile cancer cells may actively invade the matrix, utilizing epithelial, mesenchymal, or mixed modes of motility. Dynamic phenotypic changes involved in 3D tumor cell invasion are also very sensitive to small-molecule inhibitors that, e.g., target the actin cytoskeleton. Our strategy is to recapitulate the formation and the histology of complex solid cancer tissues in vitro, based on cell culture technologies that promote the intrinsic differentiation potential of normal and transformed epithelial cells, and also including stromal fibroblasts and other key components of the tumor microenvironment. We have developed a streamlined stand-alone software solution that supports the detailed quantitative phenotypic analysis of organotypic 3D cultures. This approach utilizes the power of automated image analysis as a phenotypic readout in cell-based assays. AMIDA (Automated Morphometric Image Data Analysis) allows quantitative measurements of a large number of multicellular structures, which can form a multitude of different organoid shapes, sizes, and textures according to their capacity to engage in epithelial differentiation programs or not. At the far end of this spectrum of tumor-relevant differentiation properties, there are highly invasive tumor cells or multicellular structures that may rapidly invade the surrounding ECM, but fail to form higher-order epithelial tissue structures. Furthermore, this system allows us to monitor dynamic changes that can result from the extraordinary plasticity of tumor cells, e.g., epithelial-to-mesenchymal transition in live cell settings. Furthermore, AMIDA supports an automated workflow, and can be combined with quality control and statistical tools for data interpretation and visualization. Our approach supports the growing needs for user-friendly, straightforward solutions that facilitate cell-based organotypic 3D assays in basic research, drug discovery, and target validation.

Quantification of dynamic morphological drug responses in 3D organotypic cell cultures by automated image analysis

Glandular epithelial cells differentiate into complex multicellular or acinar structures, when embedded in three-dimensional (3D) extracellular matrix. The spectrum of different multicellular morphologies formed in 3D is a sensitive indicator for the differentiation potential of normal, non-transformed cells compared to different stages of malignant progression. In addition, single cells or cell aggregates may actively invade the matrix, utilizing epithelial, mesenchymal or mixed modes of motility. Dynamic phenotypic changes involved in 3D tumor cell invasion are sensitive to specific small-molecule inhibitors that target the actin cytoskeleton. We have used a panel of inhibitors to demonstrate the power of automated image analysis as a phenotypic or morphometric readout in cell-based assays. We introduce a streamlined stand-alone software solution that supports large-scale high-content screens, based on complex and organotypic cultures. AMIDA (Automated Morphometric Image Data Analysis) allows quantitative measurements of large numbers of images and structures, with a multitude of different spheroid shapes, sizes, and textures. AMIDA supports an automated workflow, and can be combined with quality control and statistical tools for data interpretation and visualization. We have used a representative panel of 12 prostate and breast cancer lines that display a broad spectrum of different spheroid morphologies and modes of invasion, challenged by a library of 19 direct or indirect modulators of the actin cytoskeleton which induce systematic changes in spheroid morphology and differentiation versus invasion. These results were independently validated by 2D proliferation, apoptosis and cell motility assays. We identified three drugs that primarily attenuated the invasion and formation of invasive processes in 3D, without affecting proliferation or apoptosis. Two of these compounds block Rac signalling, one affects cellular cAMP/cGMP accumulation. Our approach supports the growing needs for user-friendly, straightforward solutions that facilitate large-scale, cell-based 3D assays in basic research, drug discovery, and target validation.

Cholesterol supports the retinoic acid-induced synaptic vesicle formation in differentiating human SH-SY5Y neuroblastoma cells

Synaptic vesicle formation, vesicle activation and exo/endocytosis in the pre-synaptic area are central steps in neuronal communication. The formation and localization of synaptic vesicles in human SH-SY5Y neuroblastoma cells, differentiated with 12-o-tetradecanoyl-phorbol-13-acetate, dibutyryl cyclic AMP, all-trans-retinoic acid (RA) and cholesterol, was studied by fluorescence microscopy and immunocytochemical methods. RA alone or together with cholesterol, produced significant neurite extension and formation of cell-to-cell contacts. Synaptic vesicle formation was followed by anti-synaptophysin (SypI) and AM1-43 staining. SypI was only weakly detected, mainly in cell somata, before 7 days in vitro, after which it was found in neurites. Depolarization of the differentiated cells with high potassium solution increased the number of fluorescent puncta, as well as SypI and AM1-43 co-localization. In addition to increase in the number of synaptic vesicles, RA and cholesterol also increased the number and distribution of lysosome-associated membrane protein 2 labeled lysosomes. RA-induced Golgi apparatus fragmentation was partly avoided by co-treatment with cholesterol. The SH-SY5Y neuroblastoma cell line, differentiated by RA and cholesterol and with good viability in culture, is a valuable tool for basic studies of neuronal metabolism, specifically as a model for dopaminergic neurons.

Deconvolving single-molecule intensity distributions for quantitative microscopy measurements

In fluorescence microscopy, images often contain puncta in which the fluorescent molecules are spatially clustered. This article describes a method that uses single-molecule intensity distributions to deconvolve the number of fluorophores present in fluorescent puncta as a way to "count" protein number. This method requires a determination of the correct statistical relationship between the single-molecule and single-puncta intensity distributions. Once the correct relationship has been determined, basis histograms can be generated from the single-molecule intensity distribution to fit the puncta distribution. Simulated data were used to demonstrate procedures to determine this relationship, and to test the methodology. This method has the advantages of single-molecule measurements, providing both the mean and variation in molecules per puncta. This methodology has been tested with the avidin-biocytin binding system for which the best-fit distribution of biocytins in the sample puncta was in good agreement with a bulk determination of the avidin-biocytin binding ratio.