General Staining and Segmentation Procedures for High Content Imaging and Analysis

Abstract

Automated quantitative fluorescence microscopy, also known as high content imaging (HCI), is a rapidly growing analytical approach in cell biology. Because automated image analysis relies heavily on robust demarcation of cells and subcellular regions, reliable methods for labeling cells is a critical component of the HCI workflow. Labeling of cells for image segmentation is typically performed with fluorescent probes that bind DNA for nuclear-based cell demarcation or with those which react with proteins for image analysis based on whole cell staining. These reagents, along with instrument and software settings, play an important role in the successful segmentation of cells in a population for automated and quantitative image analysis. In this chapter, we describe standard procedures for labeling and image segmentation in both live and fixed cell samples. The chapter will also provide troubleshooting guidelines for some of the common problems associated with these aspects of HCI.

Monomeric Targeted Protein Degraders

“…20 A range of different automated fluorescence imaging systems acquire fluorescence images of the samples stained for the proteins of interest and use image analysis methods to quantify fluorescence intensities (and consequently the level of specific proteins) in different regions of the cells. 21,22 In the case of nonadherent cell types, flow cytometry is often a more suitable method than fluorescence imaging. Flow cytometry is a method that can be used to detect protein levels either on the cell surface or within the cell using intracellular staining procedures.…”

“…The most versatile and robust format is the secondary (indirect) immunofluorescence method in which a primary (unlabeled) antibody is bound to the protein of interest and then fluorescently labeled using a fluorophore conjugated secondary antibody that cross-links the primary antibodies in place . A range of different automated fluorescence imaging systems acquire fluorescence images of the samples stained for the proteins of interest and use image analysis methods to quantify fluorescence intensities (and consequently the level of specific proteins) in different regions of the cells. , In the case of nonadherent cell types, flow cytometry is often a more suitable method than fluorescence imaging. Flow cytometry is a method that can be used to detect protein levels either on the cell surface or within the cell using intracellular staining procedures. − Flow cytometry also uses the quantitation of fluorescence in individual cells as a means to measure protein levels and is potentially more sensitive than fluorescence imaging (although without subcellular localization information).…”

In‐cytoplasm mitochondrial transplantation for mesenchymal stem cells engineering and tissue regeneration

“…Non-autologous mitochondria isolated from donor Y40-ADSCs were labeled For quantitative analysis, image segmentation was performed by the GE Developer software (Chambers, Mandavilli, Dolman, & Janes, 2018). Briefly, using both the Hoechst blue channel and MitoTracker Green FM channel, cells were segmented using the Ǝ find nucleiƐ and Ǝ find cytoplasmƐ building blocks.…”

“…For quantitative analysis, image segmentation was performed by the GE Developer software. 58 Briefly, cells were segmented using the “find nuclei” by the Hoechst blue channel and “find cytoplasm” by MitoTracker Green FM channel. To exclude apoptotic or dividing cells, intensity, and morphological measurements were picked up from the segmented cells.…”

The anatomy of single cell mass cytometry data

“…Rather than requiring tissue dissociation, these allow the intact analysis of tissue sections like fine‐needle biopsies or archival paraffin blocks. This preserves additional relational information such as intercellular distances, but also raises new analysis challenges, such as image segmentation for cell determination that have been explored in light microscopy .…”