Prof. Savas Tay
Department of Biosystems Science and Engineering, ETH Zürich
October 1, 2013 | 12:30 to 01:30 | 540 Cory Hall
Host: Luke Lee
Immune cells constantly receive signaling inputs such as pathogen-emitted molecules, use gene regulatory pathways to process these signals, and generate outputs by secreting signaling molecules. Characterizing the input-output relationship of a biological system helps to understand its regulatory mechanisms and allows building models to predict how the system will operate in complex physiological scenarios - a primary goal for Systems Immunology. A major obstacle has been the so-called “biological noise,” or significant variability in molecular parameters between cells. Each cell contains its own time-dependent composition of pathway components (e.g., RNA and proteins) generating distinct, time-varying outputs for the exact same inputs. Such variability makes time-dependent single-cell analysis crucial in understanding how biological systems operate. Single-cell dynamical analysis, however, has been a low-throughput, and at best, semi-quantitative method due to technical challenges in isolating, manipulating and measuring individual cells. I will talk about how we address these limitations by developing automated, high-throughput, microfluidic/optofluidic single-cell analysis systems with unprecedented capabilities and measurement accuracy, and how we use them in understanding immune cell coordination during response to infection. Our recent efforts have resulted in a new set of technologies, helping solve some of the most puzzling problems in Systems Immunology and Cell Signaling. These include microfluidic systems to measure cytokine secretion dynamics from single-cells under complex time-varying signaling inputs, a high-throughput cell culture system that creates programmable diffusion-based chemical gradients, a chip to measure cell-cell communication via secreted factors, and a new method for digital quantification of proteins and nucleic acids (mRNA and DNA) in the same cell. In addition to new technologies, I will also talk about newly obtained biological insight from our measurements and modeling efforts on how single-cells detect and encode dose and frequency information using the immune pathway NF-κB, and how they create dynamic cytokine outputs under inflammatory stimuli. A primary goal in this combined technology/cell biology effort is to develop a computer model of tissue-level immune response through the NF-κB pathway, with particular focus on cytokine signal propagation mechanism (e.g., diffusion vs. waves), speed, range and duration.
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