High-content imaging systems enable researchers to measure more parameters and extract more data than is possible with conventional microscopy. High-content systems typically fall into one of two categories: those used for screening and those used for detailed analysis. High-content screening (HCS) systems offer sensitive measurements and high-throughput capabilities—and they examine as many samples as possible within an experiment. High-content analysis (HCA) systems may sacrifice some speed in the interest of obtaining even more complex, content-rich data.
Many systems offer combinations of brightfield, widefield, phase-contrast and confocal imaging and also make extensive use of fluorescent markers for multiplexing. Here we discuss some of the recent offerings from tool providers in high-content imaging systems as well as the wide array of applications that researchers are performing on them.
The luxury of more choices
Both HCS and HCA systems have seen throughputs rise recently, and virtually all are compatible with robotic systems, for walk-away automation that boosts productivity further.
With automation boosting throughput, the number of plates run per day is not always the top concern. “Live-cell imaging is where people are asking to go faster,” says Leanna Ferrand, global product support leader for cell analysis at GE Healthcare. GE’s systems can take one image per well in two colors, in a 96-well plate, in less than 2.5 minutes—which is fast for screening, but not fast enough to capture a dynamic process in a live-cell assay that occurs more quickly than 2.5 minutes. The company’s solution is to use rapid imaging internally within single wells—almost like a time lapse within each well. “If it’s an extremely dynamic process, we can remain within or re-visit a well, to capture fast events,” Ferrand explains.
With more high-content imaging systems available today, scientists have the luxury of choosing which model best fits their needs—even from within one company. For example, Thermo Fisher Scientific’s range of high-content imaging systems includes an entry-level model for screening the CellInsight™ CX5 High Content Screening Platform, a mid-level system the CellInsight™ CX7 High Content Platform and an advanced system, the ArrayScan™ High Content Platform for specialized applications, with modular options such as a live-cell chamber.
Tools like Thermo Fisher’s Invitrogen™ fluorescent markers also provide researchers with a wealth of multiplexing options. Indeed, the multiplexing power of high-content imaging systems is manifesting in new applications. “With increased use of genome editing using CRISPR, the ability to screen for multiple phenotypic effects quickly and easily provides rapid validation and feedback for a knockout or knock-in experiment,” says Stephen Oldfield, senior marketing development manager for cellular analysis at Thermo Fisher Scientific.
High-content imaging of 3D cultures
Increasingly, cancer researchers are adopting 3D cell cultures to study tumor biology, and high-content imaging has evolved to accommodate 3D samples.
Spheroids—clusters of cells derived from healthy or tumor tissues—are a common type of 3D cell culture. GE Healthcare offers an improved workflow for 3D imaging that refines the protocol used to form spheroids in imaging plates and also makes imaging easier. The company recently collaborated with Nano3D Biosciences to facilitate high-content 3D imaging of spheroids. Nano3D’s technology positions spheroids at the center of each well, for example, so they are easier to find when imaging.
Nano3D’s technology enables the printing of cells and spheroids in different 3D patterns and shapes, which is central to creating co-cultures with different cell types, says Glauco Souza, Nano3D’s president and chief science officer. For example, the company can create co-cultures for a scratch assay and follow a wound-healing assay in real time. “But then using the high-resolution imaging of [GE Healthcare’s] IN Cell Analyzer 6000, you can add a whole level of complexity by adding different cell types to the assay,” says Souza. “This opens the doors to a lot of new biology that hasn’t been studied yet.”
Revvity’s Opera Phenix™ HCS system is also used to study spheroids. The company’s Synchrony™ Optics design optimizes data acquisition of 3D cell cultures and improves sensitivity by “carefully controlling excitation to eliminate unwanted cross talk in the sample,” says Jacob Tesdorpf, Revvity’s director of high-content instrumentation and applications. Revvity recently expanded its range of HCS microplates for growing spheroids using the hanging drop method, including Revvity’s CellCarrier™ Spheroid ULA plate, and the GravityPLUS™ ULA plate and GravityPLUS™ Hanging Drop system from InSphero.
Easier-to-use software
Because high-content imaging generates large data files, software that samples, analyzes, displays and stores the data is crucial. Many tool providers are creating software that takes into consideration the researcher’s needs. GE Healthcare has emphasized making the software’s interface especially intuitive and easy to use, says Ferrand—for example, providing quick assessments of what certain parameters would look like on a subset of data, so that the user can preview the effects before analyzing all the data. GE Healthcare will launch new image analysis software at the end of October 2016.
Another key software feature is data linkage. The GE software’s built-in linkage between the data table and other displays means that if you click on a point of the scatterplot, for example, it will bring up that cell’s image, and it will highlight that cell on the data table. “You can also do this on a population level, by selecting a subpopulation of cells,” says Ferrand. “This gives researchers flexibility to look at cell-by-cell questions, as well as population-level questions.”
Revvity offers updated versions of its Columbus™ software (for high-volume image storage and analysis) and High Content Profiler™ software (for multiparametric hit selection). “These latest versions provide improved integration to enable browsing, searching, downloading and aggregation of content in Columbus directly within the High Content Profiler software,” says Tesdorpf. Users no longer need to import data, export data or merge with metadata manually—for the researcher, this means saving time and reducing data-transfer errors.
In addition, a new version of Revvity’s Harmony® high-content imaging and analysis software features PreciScan™ intelligent acquisition, which enables researchers to target objects of interest more accurately. “This leads to significantly reduced acquisition and analysis times, which is particularly valuable for 3D microtissue and rare-event studies,” says Tesdorpf.
Fighting Zika virus with high-content imaging
Researchers at the Institute of Biomedical Sciences at the Federal University of Rio de Janeiro and D'Or Institute for Research and Education are using Revvity’s Operetta® CLS™ high-content analysis system to study the Zika virus. This system, along with the company’s Opera Phenix™ HCS system, has “spinning-disk confocal optics, which help eliminate background to provide superior image data quality, and minimizes phototoxicity and bleaching of live cells,” says Tesdorpf.
“They’ve created what they call ‘mini-brains’ to simulate the brain function of fetuses at different stages of development,” he says. In addition, scientists at the University of Texas are using the Opera Phenix™ HCS system to identify FDA-approved drugs (20-plus so far) that may prevent or treat Zika virus infections, according to Tesdorpf.
The researchers use 3D cultures such as neurospheres and brain organoids to study the effects of Zika virus infection on neurogenesis and growth.
“They’ve created what they call ‘mini-brains’ to simulate the brain function of fetuses at different stages of development,” he says. In addition, scientists at the University of Texas are using the Opera Phenix™ HCS system to identify FDA-approved drugs (20-plus so far) that may prevent or treat Zika virus infections, according to Tesdorpf.
Given the continuing challenges that imaging 3D tissues presents, there is no doubt that more innovations will emerge in this area. However, it’s also clear that we don’t need to wait to reap the benefits of high-content imaging—it’s already happening, and it’s moving forward at a quick pace.
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