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Microfluidic Single-Cell Analysis of Cellular Information Processing

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When Oct 04, 2013
from 02:30 PM to 04:00 PM
Where 53-125 E4
Contact Name
Contact Phone 310-825-0915
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Visitor Seminar

Savas Tay
ETH Zurich, Switzerland

Abstract
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 understanding 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 here 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.
Biography
Savaş Tay is an assistant professor of Bioengineering at the Swiss Federal Institute of Technology, ETH Zurich, since 2011. He studied Physics and Education at Marmara University in Istanbul, Turkey and received his PhD in Optical Sciences from the University of Arizona, Tucson. His achievements in Nonlinear Optics include the development of world’s first updateable holographic 3D display, tunable photonic devices for optical communications, and narrow-band infrared thermal emitters. He became interested in biological research primarily to understand "how life works" from an engineer’s perspective. During his postdoctoral studies at Stanford University Bioengineering Department, he investigated mammalian signaling dynamics using high-throughout microfluidic live-cell imaging, quantitative gene expression techniques, and computational modeling. Tay Lab at ETH Zurich is an interdisciplinary group of physicists, biologists and engineers, and adopts a technology-driven systems approach to biological research that integrates high-throughput quantitative measurements, single-cell analysis and mathematical modeling (www.bsse.ethz.ch/microfluidics). Professor Tay has recently been awarded the European Research Commission Starting Grant on his work on microfluidic single-cell analysis of immune signaling and information processing.

Department Hosting: Electrical Engineering

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