Optofluidic toolkit for characterizing single-cell.. (SINGLECELLDYNAMICS)
Optofluidic toolkit for characterizing single-cell dynamics in systems immunology
Start date: Oct 1, 2013,
End date: Sep 30, 2018
Immune cells constantly receive signalling inputs such as pathogen-emitted molecules, use gene regulatory pathways to process these signals, and generate outputs by secreting signalling molecules like cytokines. 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, such as population tissue response to infection. A major obstacle in this endeavor has been the so-called “biological noise”, or significant variability in measured molecular parameters between cells. Such variability makes time-dependent single-cell analysis crucial to understand how biological systems operate. Development of new analytical tools with improved functionality, accuracy, and throughput is needed to realize the full potential of single-cell analysis. We propose to develop automated, high-throughput, Optofluidic single-cell analysis systems with unprecedented capabilities, and to use them in understanding how immune cells organize in tissue during response to infection. Microfluidic membrane-valves, nanodroplets, optics, and automation will be integrated to achieve an unparalleled degree of control over single immune cells. Multi-functional lab-on-chip devices will simultaneously measure: a) The activity of immune regulatory proteins such as NF-κB, and b) Inflammatory cytokines secreted from single immune cells in a time-dependent manner, under precisely defined biochemical inputs. Characterizing macrophage cytokine secretion dynamics under combinatorial regiments of bacterial and apoptotic-cell signals will allow dissecting the signalling mechanism responsible from the resolution of inflammation. We will identify the role of the NF-κB pathway in regulation of cytokine dynamics. We will use our data to develop a computer model of tissue-level immune response to pathogens through the NF-κB pathway and cytokine signaling.
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