New developments and novel applications in high throughput and high content imaging

SINCE the first microscopes of Van Leeuwenhoek about 300 years ago, microscopy has continued to provide novel insights about the fundamental elements of life. Images are by nature rich in information and recent times have seen an increased effort to move beyond their descriptive value and to quantify this information. Over the past twenty-five years, significant advances in computational power, robotics and automation, and image detectors have made possible a huge increase in the throughput and content obtainable with light microscopy methods. Though the modalities that have been developed as platforms for high-content (HC) and high-throughput (HT) imaging vary somewhat, the resulting output is essentially the same: morphological data obtained from a large number of fields of cells. The term “high-throughput microscopy” first appeared in PubMed relatively recently (1) and in this case it referred to the use of an image-based screen of a cDNA library to identify genes that induced altered nuclear/cytoplasmic ratios of TORC1-eGFP. The following year, a chapter discussing the use of different screening strategies in RNAi based screens was the first use of the term “high-content microscopy” (2). In general, HC assays consider the morphological phenotypes of individual cells, rather than the average signals measured from all cells (3). Interestingly, the first example of imaging flow cytometry (IFC) appears much earlier, in 1979 (4). The authors developed a unit capable of detecting cellular particles, triggering a flashlamp if particles were in the preselected size range of interest, and feeding 16-mm film for acquisition, documentation, and image analysis. IFC has since been used to automate the analysis of many rare cellular events and those requiring data from large populations of cells, such as analysis of internalized bacteria (5), phagocytosis (6), nuclear–cytoplasmic translocation events (7), and yeast cell cycle analysis (8). Since this time the number of publications relying on HT/HC imaging methods has, predictably, grown exponentially (Fig. 1). This has led to a simultaneous explosion in the scale and content of image data and, most importantly, the type of scientific questions that can be asked when interrogating these datasets. These technological advances have brought imaging into the realm of “omics,” in which large datasets permit the quantification of molecular and morphological phenotypes that can inform as to the structure, function, and dynamics of a biological system. There are essentially four areas in which technological advances have had a significant impact on HT/HC imaging: (i) Reagents and assay tools, e.g. advanced fluorescent probes, genome-wide RNAi libraries, and gene editing techniques (e.g., TALENs and CRISPR/Cas9); (ii) Microscopy and optical advancements, e.g. high sensitivity detectors (sCMOS cameras and GaAsp detectors) and superresolution microscopy; (iii) Automation and robotics, such as the robotic microscope (9) and commercially available HT/HC platforms such as the Operetta (PerkinElmer) and the IN Cell Analyzer (GE Lifesciences); and (iv) Computational advancements, since one of the major bottlenecks for most HT/HC imaging platforms is how to handle storage, processing, and analysis of ever larger datasets. Improvements in the speed and capacity of desktop computing, tools for the rendering and analysis of three-dimensional image data, and platforms for archiving and analyzing large image databases (such as OMERO, Bisque, and Cell Profiler) have all facilitated this. In this special issue, we will provide a broad snapshot of