Project

Back to overview

Optofluidic single-cell analysis platform for systems immunology

English title Optofluidic single-cell analysis platform for systems immunology
Applicant Tay Savas
Number 141299
Funding scheme Project funding (Div. I-III)
Research institution Computational Systems Biology Department of Biosystems, D-BSSE ETH Zürich
Institution of higher education ETH Zurich - ETHZ
Main discipline Other disciplines of Engineering Sciences
Start/End 01.08.2012 - 31.07.2015
Approved amount 405'893.00
Show all

All Disciplines (7)

Discipline
Other disciplines of Engineering Sciences
Cellular Biology, Cytology
Microelectronics. Optoelectronics
Biophysics
Mechanical Engineering
Electrical Engineering
Immunology, Immunopathology

Keywords (9)

microfluidics; NF-kappaB; optical tweezers; immunology; signaling; cell culture; dynamics; systems biology; single-cell

Lay Summary (English)

Lead
Lay summary

   We propose to develop a high-throughput optofluidic single-cell analysis platform to culture, manipulate, monitor and analyze live cells with an unprecedented level of spatiotemporal control and accuracy, and to use this system to significantly improve the understanding of spatiotemporal characteristics of communication among immune cells via cell biological measurements and mathematical modeling. We will develop and integrate state-of-the-art microfluidics, optics, automation, and immune cells expressing fluorescent fusion proteins to investigate population level inter-cellular communication with single-cell resolution. Our optofluidic system will greatly improve the accuracy and throughput of cell biological measurements, generate an unprecedented data set on cell signaling under precisely controlled stimuli, and quantify cellular responses using live-cell imaging and genetic analysis.

    Our specific interest lies in the context of immunity and inflammation, to understand how cells communicate information about an inflammatory stimulus, such as a bacteria or other pathogen signal, particularly with respect to oscillatory and non-oscillatory activation of the transcription factor NF-κB.  We aim to achieve dynamic, quantitative understanding of tissue-like cellular systems through mathematical modeling.  Our models incorporate noise, heterogeneity, and stochasticity inherent in biological processes and are built from well-controlled, high-throughput experiments. Addressing questions about dynamic cell-cell communication and heterogeneity places high demands on the experimental platform.  We must be able to a) Culture adherent and non-adherent mammalian cells and bacteria under precisely controlled external and internal conditions in hundreds of parallel microfluidic chambers, b) Automate cell culture tasks such as surface treatments, cell loading and media exchange, and imaging, c) Create complex chemical stimuli by combining tens of ligands, make serial dilutions on chip, and create spatio-temporal gradients, and d) Stimulate cells with ligands in time-evolving patterns. We will use this system for time-lapse imaging of cells, transcription factors and downstream gene expression dynamics, and perform automated cell tracking and data extraction. We will be able to create shaped co-cultures using holographic optical tweezers where hundreds of cells and particles will be simultaneously picked and placed in predetermined positions to test various immune scenarios. With this, we will have absolute spatial and temporal control over chemical stimuli delivered to immune cells. Our optofluidic setup will also allow retrieval of any given cell for further genetic analysis out of the chip. Combination of these advances in a single optofluidic system represents a major advancement in cell culture experiments with a level of spatial and temporal control never seen before. Using this system, we will measure with single-cell resolution the dynamics of the transcription factor NF-κB under hundreds of different conditions relevant to immunology and systems biology.

   Ultimately, we will develop a computer model based on this data that will predict cellular behavior in various immunological scenarios and account for temporal and spatial dynamics with single-cell resolution, which will be revolutionary in understanding of NF-κB immune regulation and disease. The model will further serve as a rapid test-bed and guide our experimental studies. If successful, our work will lead to a significant advance in solving some of the most puzzling problems in cell biology and immunology, and result in a new set of competent technologies (comprising a “toolset”). These developments will impact a range of fundamental fields like systems immunology and cell biology, and applied fields like cancer and infection research. Our optofluidic system will address major shortcomings of the current technology used in live cell imaging and cell culture, and will posses potential for commercialization.

Direct link to Lay Summary Last update: 21.02.2013

Responsible applicant and co-applicants

Employees

Publications

Publication
High-content quantification of single-cell immune dynamics
M. Junkin A.J. Kaestli Z. Cheng C. Jordi C. Albayrak A. Hoffmann and S. Tay. (2016), High-content quantification of single-cell immune dynamics, in Cell Reports, 15, 411.
Automated co-culture system for spatiotemporal analysis of cell-to-cell communication
T. Frank S. Tay. (2015), Automated co-culture system for spatiotemporal analysis of cell-to-cell communication, in Lab Chip, 15, 2192.
Digital signaling decouples activation probability and population heterogeneity
R.A. Kellogg C. Tian T. Lipniacki S.R. Quake S. Tay. (2015), Digital signaling decouples activation probability and population heterogeneity, in eLife, 4, e08931.
Noise Facilitates Transcriptional Control Under Dynamic Inputs
R.A. Kellogg S. Tay. (2015), Noise Facilitates Transcriptional Control Under Dynamic Inputs, in Cell, 160, 381.
High-throughput microfluidic single-cell analysis pipeline for studies of signaling dynamics
R. Kellogg R. Gómez-Sjöberg A. A. Leyrat S. Tay. (2014), High-throughput microfluidic single-cell analysis pipeline for studies of signaling dynamics, in Nature Protocols, 9, 1713.
Real-time tracking, retrieval and gene expression analysis of migrating human T cells
M. Mehling T. Frank C. Albayrak S. Tay. (2014), Real-time tracking, retrieval and gene expression analysis of migrating human T cells, in Lab Chip, 15, 1276.
Flow-switching allows independently programmable, extremely stable, high-throughput diffusion-based gradients
T. Frank S. Tay (2013), Flow-switching allows independently programmable, extremely stable, high-throughput diffusion-based gradients, in Lab Chip, 13, 1273.

Collaboration

Group / person Country
Types of collaboration
Professor Tomasz Lipniacki, Polish Academy of Sciences Poland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication
Group of Ala Trusina Denmark (Europe)
- in-depth/constructive exchanges on approaches, methods or results

Abstract

We propose to develop a high-throughput optofluidic single-cell analysis platform to culture, manipulate, monitor and analyze live cells with an unprecedented level of spatiotemporal control and accuracy, and to use this system to significantly improve the understanding of spatiotemporal characteristics of communication among immune cells via cell biological measurements and mathematical modeling. We will develop and integrate state-of-the-art microfluidics, optics, automation, and immune cells expressing fluorescent fusion proteins to investigate population level inter-cellular communication with single-cell resolution. Our optofluidic system will greatly improve the accuracy and throughput of cell biological measurements, generate an unprecedented data set on cell signaling under precisely controlled stimuli, and quantify cellular responses using live-cell imaging and genetic analysis. Our specific interest lies in the context of immunity and inflammation, to understand how cells communicate information about an inflammatory stimulus, such as a bacteria or other pathogen signal, particularly with respect to oscillatory and non-oscillatory activation of the transcription factor NF-?B. We aim to achieve dynamic, quantitative understanding of tissue-like cellular systems through mathematical modeling. Our models incorporate noise, heterogeneity, and stochasticity inherent in biological processes and are built from well-controlled, high-throughput experiments. Addressing questions about dynamic cell-cell communication and heterogeneity places high demands on the experimental platform. We must be able to: A) Culture adherent and non-adherent mammalian cells and bacteria under precisely controlled external and internal conditions in hundreds of parallel microfluidic chambers, B) Automate cell culture tasks such as surface treatments, cell loading and media exchange, and imaging, C) Create complex chemical stimuli by combining tens of ligands, make serial dilutions on chip, and create spatio-temporal gradients, and D) Stimulate cells with ligands in time-evolving patterns. We will use this system for time-lapse imaging of cells, transcription factors and downstream gene expression dynamics, and perform automated cell tracking and data extraction. We will be able to create shaped co-cultures using holographic optical tweezers where hundreds of cells and particles will be simultaneously picked and placed in predetermined positions to test various immune scenarios. With this, we will have absolute spatial and temporal control over chemical stimuli delivered to immune cells. Our optofluidic setup will also allow retrieval of any given cell for further genetic analysis out of the chip. Combination of these advances in a single optofluidic system represents a major advancement in cell culture experiments with a level of spatial and temporal control never seen before. Using this system, we will measure with single-cell resolution the dynamics of the transcription factor NF-?B under hundreds of different conditions relevant to immunology and systems biology. Ultimately, we will develop a computer model based on this data that will predict cellular behavior in various immunological scenarios and account for temporal and spatial dynamics with single-cell resolution, which will be revolutionary in understanding of NF-?B immune regulation and disease. The model will further serve as a rapid test-bed and guide our experimental studies. If successful, our work will lead to a significant advance in solving some of the most puzzling problems in cell biology and immunology, and result in a new set of competent technologies (comprising a “toolset”). These developments will impact a range of fundamental fields like systems immunology and cell biology, and applied fields like cancer and infection research. Our optofluidic system will address major shortcomings of the current technology used in live cell imaging and cell culture, and will posses potential for commercialization.
-