CytoMAP, By the Gerner Lab

I am a research scientist in the Department of Immunology within the University of Washington, School of Medicine. At my core I am an experimentalist, I love trying to figure out how things work and if I can make them better. This has led to research in nonlinear optics and fluorescent protein evolution in the Physics department at Montana State University, building microscopic optical filters at Spectrum Lab, and currently to developing new ways of understanding how immune cells interact and organize in tissues. I am particularly interested in pushing the limits of optical technologies, like lasers and microscopes, and I am working on turning this hobby into a career. In 2016 I graduated with a PhD in Physics from Montana State University, where I spent my time playing with lasers and building imaging systems in the Rebane lab. I look forward to seeing what breakthroughs the future of science holds, and hope that I can be a part of them.

How do you describe your research to colleagues?

I am working in Michael Gerner’s Lab on an interdisciplinary research project attempting to elucidate how the spatial organization of immune cells in tissue microenvironments influence disease progression and treatment outcomes. Specifically, I am utilizing multi-dimensional spectrally resolved confocal microscopy to image the local environments of immune cells, and developing a software tool, CytoMAP, to extract information from these imaging datasets and interrogate cellular composition, tissue architecture, and locations of cell-cell interactions.

How do you describe your current research to non-scientists?

I am trying to create 3D schematics of tissues, with cellular resolution positional information, much like the schematics that come with Ikea furniture. In addition to the numbers and types of cells in tissues, the position of cells within tissues affects both how individual cells interact, and how whole organs function. Unlike Ikea furniture, even small tissues have millions of component parts, meaning I must develop software tools, which use images of tissues, and machine learning to create my schematics. These tools simultaneously look at millions of cells and distill their information down to a few key, understandable relationships. This helps us understand where different types of cells are, how they are interacting with each other, and what the structure of their host tissue is.

What public benefit do you hope will come from your work?

A better understanding of how the spatial organization of immune cells influences disease will provide significant benefit, yielding advances on both the basic research and clinical levels. Developing analysis tools directly in an immunology lab has yielded user friendly software, which places powerful quantitative analysis techniques in the hands of biologists who direct and shape the forefront of immunological drug discovery, tissue exploration, and diagnostics.