CYTO 2023: Beyond Cytometry Frontier

Gotthold Fläschner, PhD 
PostDoc, ETH Zürich

Rohit Bhargava, PhD
Founder Professor of Bioengineering, Faculty Affiliate in Chemistry, Director, Cancer Center, University of Illinois, Urbana-Champaign

Gotthold Fläschner, PhD: Staying in touch: interrogating single cell mass and mechanics with micro-oscillators
The ancient and tremendously successful study of motion and deformation has reached the microscopic universe: mechanobiology studies how cells sense mechanical cues from their environment and how they regulate both their mechanical properties and a wide range of biological activities in response. To facilitate an in-depth understanding of cellular behaviour, we developed different techniques to measure the most important cell-mechanical properties, mass, elasticity, and viscosity with high precision. These advances have been made possible by rigorously controlled micro-mechanical oscillators, that are brought in contact with single cells. Using this technology platform, we measured how virus infection can impede cellular growth and characterized how budding yeast increase their mass during G2 phase. Moreover, we quantified the cell resonance frequency and characterized cellular viscoelasticity up to tens of kilohertz. While the technologies are being transferred to industry, the insights gained from this line of research are expected to contribute significantly to biology, tissue engineering and regenerative medicine, where the understanding of the complex material properties of cells and tissue are key.

Rohit Bhargava, PhD: Infrared chemical imaging: an emerging technology for understanding chemical-structural composition of cells and tissues
Infrared spectroscopic imaging combines the ability to record molecular content with the ability to visualize chemistry in its spatial diversity. Recent advances in instrumentation make it possible to record high fidelity data in reasonable times, with insights ranging from cells in tissues to sub-cellular domains. We first describe a new microscope design for increased speed and rapid coverage that is useful for biomedical and clinical tissue imaging. Next, we describe a configuration to measure chirality in samples that promises higher spectral information that present methods. Finally, we present a new approach to nanoscale IR imaging that provides greater fidelity and speed at unprecedented levels of signal to noise ratio. Finally, we show how emerging machine learning approaches can further augment these advances. For each instrumentation advance, examples of use cases will be presented. We also discuss the merits of various techniques, trade-offs and potential directions. 

CMLE Credit: 1.0