Live-Cell Imaging Systems

“The great promise of live cell microscopy is to enable dynamic studies of cellular processes and responses,” says Philip Lee, director of research and development at CellASIC. “Nearly all the great techniques that have been developed for biology rely on static, endpoint measurements of activities,” he says, giving examples of gene expression arrays, protein blotting, immunostaining, and cellular metabolic studies. “Live cell microscopy currently offers the best route for scientists to observe in real-time how the ‘parts’ (i.e. DNA, RNA, protein, organelles) interact to create the response.”

To make this possible, live-cell imaging systems are emerging that are user-friendly, yet offer different strengths depending on what you are looking for. But they share some challenges too. “I think that our goal as makers of live cell imaging systems is to re-create the conditions of a typical cell-culture incubator on the microscope stage,” says Michael Ward, co-founder of In Vivo Scientific and a resident physician in the department of neurology at the University of California, San Francisco. Such a task is not as easy as it sounds, though he believes that they are nearing their goal. Here are some of the recent offerings in live-cell imaging systems.

“The reason for this choice is that the larger temperature-controlled chamber ensures that the specimen, the stage, and the objectives are all at the same temperature,” says Ward, noting that problems with focus drift can result if only the sample chamber is heated. “Humidity is controlled through the use of a very unique type of tubing that allows for water molecules to diffuse into the gas stream, but does not require the gas stream to actually bubble up through water, thus reducing the chance of contamination.” In Vivo Scientific offers three ways to control CO₂ levels depending on users’ needs. In their newest and most advanced system, the CO₂ levels are measured in the atmosphere directly surrounding the specimen, which they claim is the first tool for doing this. “All other live cell chambers measure CO₂ levels of the incoming gas stream prior to the gas entering the sample chamber, since in the past CO₂ probes were too bulky to place on the microscope stage,” says Ward. “While this sometimes worked, it did not guarantee that the CO₂ level that the sample actually sees is what the user had programmed into the controller. Any small leak or gap around the sample as it sits on the microscope stage can quite dramatically change the actual local CO₂ concentration of CO₂ at the sample, and thus effect media pH as ambient air enters the chamber from the outside.” To facilitate this, In Vivo Scientific has redesigned their stage top chamber to minimize the introduction of ambient air.

Another new release for climate control is Zeiss’s Incubation System for the Zeiss Axio Observer and Axiovert 200 inverted microscopes. This system is also aimed at precise monitoring and control of temperature, humidity, pH, CO₂, and O₂ concentrations. The system’s stackable modular design makes set-up, expansion, and upgrades easier. The climate parameters are controlled with Zeiss’s AxioVision software, and saved with the image files. The incubation system is better able to control the temperature near the specimen because Zeiss objectives were designed not to act as heat sinks, being thermally insulated or heated depending on what is required, such as for dynamic temperature experiments.

One important reason to have confidence in one’s ability to control the experimental conditions during live-cell imaging is to address the challenge of finding a standard set of conditions. According to Lee, “the biggest challenge right now for live cell imaging is standardizing the cell culture environment. Cells are notoriously non-uniform, and therefore it has been relatively difficult for cell biologists to use live cell data to the same extent as more traditional biochemical assays.” He believes that microfluidics technology—the precise manipulation of the movements of tiny volumes of fluids—promises a solution for live-cell imaging. “It is not unreasonable to imagine a fully self-contained microfluidic culture system that can sit on a microscope stage and execute precise experiment conditions with perfect repeatability. This will allow biologists to start sharing ‘cell response’ data in the same way gene expression data is currently shared between labs.”

CellASIC offers the ONIX™ Dynamic Cell Culture Platform for use with any standard inverted microscope to give computer-controlled medium exchange during live-cell imaging. They also offer a range of application-specific microfluidic cell culture plates, designed to enhance the culture environment for different cell types (such as bacteria, yeast, or cell lines) and optimize optics. “This is the first product that utilizes microfluidic cell culture technology with dynamic solution control for live cell microscopy,” says Lee. “It is also the only product that enables time-lapsed imaging of non-adherent cells during continuous flow, made possible by an innovative cell trapping design.”

Another contributor to microfluidics-based live-cell imaging is Nanopoint. Their cellTRAY Imaging System is designed to isolate cells, singularly or in small groups, into arrays of microwells connected by fluidic channels. The wells can be navigated automatically, and images of live cells captured over time, which makes this relatively inexpensive system advantageous for time-lapse experiments. The related cellTRAY Fluidics System uses a kind of “lab-on-a-chip” cellTRAY slide that enables up to 10 parallel experiments over multiple days. The cellTRAY slide is both a fluidics controller and a tiny incubator that fits on a microscope stage. CellTRAYs for the cellTRAY Imaging System are available with well diameters of 200 and 300 µm.

Another new 3D imaging system was recently unveiled by PerkinElmer in their UltraVIEW VoX live cell imaging system, which contains the new model of the Yokogawa CSU confocal scan head. This CSU-X spinning disc head is twice as efficient as the previous model and so requires the specimen to undergo less illumination, reducing both photobleaching and phototoxicity. The UltraVIEW VoX system is controlled by PerkinElmer’s award-winning Volocity software. This system is designed to do just about everything that can be done in live-cell imaging. Their strategic development leader in cellular imaging and analysis, Paul Orange, notes that, “Volocity is the only product that allows 3D imaging all the way from image acquisition through to analysis and preparing publication ready data.”

PerkinElmer also introduced the Opera LX High Content Screening (HCS) system a few months ago. Similarly based on the Yokogawa CSU scan head, this system is advantageous for live-cell imaging, too. “I see that live cell imaging and analysis is becoming more and more interesting to the HCS market,” says Orange. “The Opera HCS systems that we are selling now have a very high proportion of environmental control on them, a clear indication that our customers want to work with live cells on these systems.”

High content screening and higher-throughput experiments mean more information to be managed than ever before. PerkinElmer is just launching its new Volocity Imaging Computer Server. “This will allow our high-end users, who routinely do computationally-intensive tasks such as deconvolution, ray tracing, noise removal and certain measurement activities, to accelerate the speed of processing these data sets,” says Orange. PerkinElmer also just introduced their new Columbus Gallery for storing and managing images, imaging meta data, and HCS results. “The system can not only handle the complex data from Opera measurements—such as time series from live cell experiments—but can also be used to store and manage image data from microscopy sources throughout the laboratory,” says Orange. “The challenges are shifting from getting the high quality images required into analyzing those images. In the microscopy confocal market, we are seeing a greater emphasis being placed in getting quantitative information out of experiments, rather than ‘by-eye’ analysis of the images.”