Automated Microscopy for Faster and More Reliable Results

The use of automated microscopes has become commonplace in recent years—automating many of the laborious tasks associated with microscopy applications, and providing faster and more reliable results. But what do these advantages mean for research workflows, and how are these systems being used to advance scientific research?

Removing the manual burden

In traditional microscopy, the whole process is entirely manually operated. The user is responsible for everything from loading the samples, to choosing the light source and focusing, and finally capturing the image. But while this process works well for handling a small number of samples, larger sample sets or repetitious observations create considerable time and user burden.

In automated microscopy the user carries much less of a burden. Components such as motorized stages, shutters, filter wheels, light sources, and focus controls are replaced with electronic versions controlled by intelligent software systems. These allow for autofocusing, high-speed light and wavelength selection, and pre-set image acquisition. Pre-determined settings and sequences can automate whole workflows and allow multiple images to be captured or different experiments to be run with no user intervention. Indeed, the user is often only required once the images have been produced and the analysis begins.

Generating faster and more reliable results

”Automated microscopes offer significant advantages in research,” explains Bikram Chakraborty, Director of Strategic Marketing, Cell Analysis Division-BioTek, Agilent.

By automating labor-intensive operations and removing the need for user intervention, automated microscopes increase efficiency and allow faster image acquisition, in addition to freeing up considerable user time that can be turned to other tasks. This makes them particularly useful in applications that require repetitious observations, observations over long periods of time, or large sample sizes—examples include live-cell imaging and high-throughput analysis.

Increased reproducibly and accuracy is another major advantage. By employing robotic and intelligent software-controlled components, automated microscopes remove manual error and improve data confidence, giving fast and consistent results. This makes automated systems ideal for applications such as drug screening assays, disease diagnosis and parasite detection.

Advancing scientific research

”The most common cases for automation are instances where large number of images need to be taken across multiple dimensions,” explains Avi Smith, Global Product Marketing Manager at Evident, “such as in image stitching.” To create high-resolution images of large areas of tissues, multiple images are taken that are then combined to create a large panoramic view of your sample. However, there is still room for growth in automation for both efficiency and accuracy. Evident’s new IXplore IX85 microscope has new features that address both. “The field number of the microscope is expanded to increase efficiency,” explains Smith, “meaning that each image captures a larger area—reducing the number of images needed to stitch together large tissues or capture a certain number of cells for statistical analysis.”

”To improve accuracy, Evident has launched a new silicone gel pad immersion technology,” continues Smith. Many objectives use immersion media to match the refractive index of the samples being imaged, however this can be a barrier to automation as it can require the manual addition or cleaning of the immersion media during imaging. Users get around this by using dry objectives, but this can sacrifice the accuracy of data relative to immersion objectives. “Using silicone gel pad technology, the immersion media moves with your objective and doesn’t leave any residue, meaning users can screen multi-well plates and stitch together large sections with the high resolution enabled by immersion liquid but without any manual intervention.”

”Customers are utilizing the Agilent BioTek Lionheart and Cytation automated microscopes in diverse and innovative ways to advance their research,” explains Chakraborty. “High-throughput screening capabilities are crucial for drug discovery and large-scale studies of fixed-cell samples,” Chakraborty notes, with customers utilizing the systems’ ability to quickly automate imaging to rapidly generate results. The potential for automated environmental control can “maintain optimal conditions for cell viability and long-term live cell studies,” while the Gen5 imaging software’s tracking module is leveraged for detailed cell migration studies. Spinning disc confocal optics, available in the Cytation C10, are important for studying 3D cell models while dual reagent injectors facilitate rapid kinetic assays, allowing real-time observation and analysis of fast cellular reactions.

In other documented examples, the ZEISS Axioscan has been used in cancer profiling. Here researchers utilized the ability for fast automated scanning of up to 100 slides in a single run to identify circulating tumor cells (CTCs) from patient biopsies. Identified CTCs were then further characterized with the ultimate goal of improving the diagnosis and treatment of cancers.

Conclusion

By automating previously manual tasks, automated microscopy provides faster and more accurate results—freeing up user’s time to work on their science. And with future developments these advantages look set to expand. “One area I think automation will continue to grow is in AI-based acquisition,” says Smith. “Software will not only automatically capture images, but determine what images to capture, where to capture them, and when sufficient data has been acquired for measurable results.” Chakraborty agrees, noting that on top of this “advanced software capabilities will support complex assays and deeper insights, and remote and cloud-based data access will facilitate collaboration and efficient data sharing.” Together these developments will make automated microscopy even more important in the advancement of research.