What is the benefit of having this technology at Stowers?

At Stowers we often work with research organisms that are understudied and therefore lack the tools established for more commonly used systems such as mice or human cell lines. The ImageStream captures large numbers of images of cells without the need for fluorescent probes in order to study those cells using machine and deep learning algorithms. This workflow facilitates the study of uncommon research organisms and empowers our scientists to work with a more representative array of species to answer fundamental questions about immunity, genetics, development, and regeneration.

What are some of the most exciting discoveries made so far with this technology? Both at Stowers and elsewhere.

We recently published a machine and deep learning-based analysis method called Image3C that featured novel insights into the immune systems of cavefish and apple snails, two of the species studied at the Institute to better understand metabolic dysregulation and soft tissue regeneration, respectively.

Other areas of research that the ImageStream has had a large impact on are small-particle biology as well as the study of rare circulating leukemia cells, aging, and immune cell interactions. The most important impact of image cytometry to me personally has been the push to develop cell sorters powered by this technology. Various inroads to a mature instrument have been made by research labs and companies alike for several years now and access to image cytometry cell sorting would revolutionize the way we study both well-studied and understudied organisms here at Stowers and around the world.