The demand for understanding cells on a microscopic level continues to fuel development for new imaging platforms and analysis software. This is being further buoyed by high-content and high-throughput protocols. Optical imaging is an emerging field that holds promise to help make drug discovery and development faster and more efficient.
Speakers at the Informa Global Imaging Summit, which will be held in December in Cologne, Germany, will illustrate how technologies in this field are rapidly evolving and making their way into the clinic to assess disease progression and monitor drug efficacy.
For example, scientists from PerkinElmer plan to address some of the major challenges of high-content screening (HCS) for cellular imaging with new image analysis software and platforms.
“Two of the biggest bottlenecks include setting up the high-content screening assays and then dealing with vast amounts of data,” explains Gabriele Gradl, Ph.D., global product leader, high content screening at PE Cellular Technology Germany. In addition, as HCS becomes more accepted, researchers are pushing the boundaries of its possibilities.
“People are trying to use their instruments to their fullest potential. So, the ability to do data analysis in two and three dimensions along with high-content screening, is something that has driven us to set up a cellular imaging business,” states Paul Orange, Ph.D., strategic development leader, cellular imaging and analysis at Improvision.
Opera™ is a confocal microplate imaging reader that provides automated simultaneous high-speed and high-resolution screening. Assay applications include: whole cell fluorescence, cell signaling, gene expression, membrane receptor, translocation, and morphology. The accompanying image analysis software, Acapella™, provides high-speed, two-dimensional, and high-content image analysis.
“This software enables you to look at different aspects of data in different ways,” says Dr. Orange. It comes with a set of ready-made application solutions or “scripts,” and is also flexible for new algorithm development via an open architecture.
Columbus™ Gallery is a database system that allows HCS multichannel images to be stored and accessed by multiple users. It can import, export, and manage images from a wide variety of sources. A system to enable reanalysis of data images, called Columbus Conductor, will be available sometime this fall.
Another platform, Volocity Visualisation software, helps during assay development and provides 3-D imaging solutions. Data is acquired from high-speed image capture and archived on a hard drive. It provides parallel processing and video streaming, and visualizes and analyzes structure and function of biological samples. Algorithms eliminate noise and blur.
Model Tumor Cell Invasion
Researchers at AstraZeneca have developed more predictive in vitro, in vivo, and in silico models to improve efficacy of potential drugs at an early stage.
“We do advanced image analysis on assays to obtain information on how drugs are affecting the cells’ phenotype. Some of the challenges with 2-D assays are throughput and large amounts of data generated from image analysis. When we try to translate that into a 3-D cell system, we have a whole host of new challenges,” explains Neil Carragher, Ph.D., associate principal scientist at AstraZeneca.
“This includes developing 3-D gels of the cells,” Dr. Carragher says, “which has to be done manually since most of the automated equipment can’t handle the 3-D gels; making it especially challenging for large target validation studies or large compound screens.”
Dr. Carragher’s group has also developed a number of image analysis algorithms to capture a drug’s physiological effect on the cell, rather than looking at a single target enzyme, called phenotype profiling. In order to look at different depths, his group has revised its image analysis approaches to account for an extra dimension—the Z focal plane.
The Z-series is a collection of images taken on a sample at different focal planes to construct a Z-stack, which provides the necessary spatial resolution to fully examine 3-D samples. To determine whether their 3-D assays are more predictive than 2-D samples, Dr. Carragher says, they are conducting in vivo imaging studies with real-time image analysis and comparing those results to 3-D data obtained from in vitro assays.
“We’ve seen several cases where our assay is not replicating what we see in vivo, so we’ve begun to re-engineer those assays,” Dr. Carragher notes. “The final endpoint is a multiparametric signature; we’re almost getting a fingerprint for every compound.” This information is used to identify how the compound is affecting the phenotype of the cells.
Dr. Carragher says that one of the active areas in cellular imaging is the development of new optical imaging instruments for in vivo assays. His group uses multiphoton confocal microscopy for deep tissue imaging in animals to monitor fluorescently labeled proteins or cells.