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      Optogenetic perturbation and bioluminescence imaging to analyze cell-to-cell transfer of oscillatory information

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          Single cell RNA Seq reveals dynamic paracrine control of cellular variation

          High-throughput single-cell transcriptomics offers an unbiased approach for understanding the extent, basis, and function of gene expression variation between seemingly identical cells. Here, we sequence single-cell RNA-Seq libraries prepared from over 1,700 primary mouse bone marrow derived dendritic cells (DCs) spanning several experimental conditions. We find substantial variation between identically stimulated DCs, in both the fraction of cells detectably expressing a given mRNA and the transcript’s level within expressing cells. Distinct gene modules are characterized by different temporal heterogeneity profiles. In particular, a “core” module of antiviral genes is expressed very early by a few “precocious” cells, but is later activated in all cells. By stimulating cells individually in sealed microfluidic chambers, analyzing DCs from knockout mice, and modulating secretion and extracellular signaling, we show that this response is coordinated via interferon-mediated paracrine signaling. Surprisingly, preventing cell-to-cell communication also substantially reduces variability in the expression of an early-induced “peaked” inflammatory module, suggesting that paracrine signaling additionally represses part of the inflammatory program. Our study highlights the importance of cell-to-cell communication in controlling cellular heterogeneity and reveals general strategies that multicellular populations use to establish complex dynamic responses.
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            Encoding and decoding cellular information through signaling dynamics.

            A growing number of studies are revealing that cells can send and receive information by controlling the temporal behavior (dynamics) of their signaling molecules. In this Review, we discuss what is known about the dynamics of various signaling networks and their role in controlling cellular responses. We identify general principles that are emerging in the field, focusing specifically on how the identity and quantity of a stimulus is encoded in temporal patterns, how signaling dynamics influence cellular outcomes, and how specific dynamical patterns are both shaped and interpreted by the structure of molecular networks. We conclude by discussing potential functional roles for transmitting cellular information through the dynamics of signaling molecules and possible applications for the treatment of disease. Copyright © 2013 Elsevier Inc. All rights reserved.
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              Detection ofn:mPhase Locking from Noisy Data: Application to Magnetoencephalography

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                Author and article information

                Journal
                Genes & Development
                Genes Dev.
                Cold Spring Harbor Laboratory
                0890-9369
                1549-5477
                April 06 2017
                March 01 2017
                : 31
                : 5
                : 524-535
                Article
                10.1101/gad.294546.116
                acfd9373-a7df-4c76-85f3-f07144d93701
                © 2017
                History

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