Quantitative Imaging

We research, develop, and utilize advanced microscopy techniques and computational image analysis software to study biological processes in single cells.

We work collaboratively with other reseachers to use the techniques we develop to capture movies of growing cells. By fluorescently labeling subcellular components such as proteins and organelles, we can track their position and quantify their function. This results in rich data containing information about cellular populations at multiple resolution levels - from subcellular processes, single cell biology, to cell-cell interactions from whole colonies or tissue.

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We have developed techniques to film, identify, and track individual bacterial cells in a time-lapse video.

This approach allows us to study cells more accurately by quantifying its context - the variation in genotype, biological state, environmental conditions, or even the interaction with other cells and viruses - that can affect its behavior. Our recent findings suggest that individual, genetically-identical cells can exhibit remarkably distinct behavior compared to the population average. We currently have projects studying this behavior during photoinhibition of cyanobacteria and phage infection in E. coli.

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Cyanobacteria cells in a genetically-identical colony show different behaviors when exposed to photodamaging conditions. Figure reproduced from Tay and Cameron, Photosynth. Res. 155, 289-297 (2022).

Computational image analysis tools

A large part of our work involves the development of software for biological image analysis. We have developed toolboxes to identify and track cells and other objects over time, as well as developing data analysis and visualization pipelines. Our software tools are available here.

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Quantitative data from single-cells extracted from microscopy imaging datasets.

Advancing learning with technology

We are also working on reimagining research education for the next generation by using technology to increase accessibility and learning opportunities for students.

Research experiences increase the participation and retention of undergraduate students in academic and professional STEM careers by providing students with an opportunity to gain hands-on experience designing and conducting experiments. However, this training takes time, is costly, and finding sufficient faculty mentors can be challenging. This has resulted in many students initially participating in unpaid internships. However, this practice greatly disadvantages under-resourced students who may need to financially support themselves.

We recently received a CU ASSETT grant to tackle this challenge by developing virtual laboratories to provide new researchers with authentic research experiences. Our simulations will provide more open-ended experiences, allowing students more freedom to explore and learn through experience, compared to recipe-based laboratories. This project will be spearheaded by a team of undergraduate developers, artists, and researchers.