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      Persistent Cell-Autonomous Circadian Oscillations in Fibroblasts Revealed by Six-Week Single-Cell Imaging of PER2::LUC Bioluminescence

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          Abstract

          Biological oscillators naturally exhibit stochastic fluctuations in period and amplitude due to the random nature of molecular reactions. Accurately measuring the precision of noisy oscillators and the heterogeneity in period and strength of rhythmicity across a population of cells requires single-cell recordings of sufficient length to fully represent the variability of oscillations. We found persistent, independent circadian oscillations of clock gene expression in 6-week-long bioluminescence recordings of 80 primary fibroblast cells dissociated from PER2::LUC mice and kept in vitro for 6 months. Due to the stochastic nature of rhythmicity, the proportion of cells appearing rhythmic increases with the length of interval examined, with 100% of cells found to be rhythmic when using 3-week windows. Mean period and amplitude are remarkably stable throughout the 6-week recordings, with precision improving over time. For individual cells, precision of period and amplitude are correlated with cell size and rhythm amplitude, but not with period, and period exhibits much less cycle-to-cycle variability (CV 7.3%) than does amplitude (CV 37%). The time series are long enough to distinguish stochastic fluctuations within each cell from differences among cells, and we conclude that the cells do exhibit significant heterogeneity in period and strength of rhythmicity, which we measure using a novel statistical metric. Furthermore, stochastic modeling suggests that these single-cell clocks operate near a Hopf bifurcation, such that intrinsic noise enhances the oscillations by minimizing period variability and sustaining amplitude.

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          Most cited references47

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          Nature, nurture, or chance: stochastic gene expression and its consequences.

          Gene expression is a fundamentally stochastic process, with randomness in transcription and translation leading to cell-to-cell variations in mRNA and protein levels. This variation appears in organisms ranging from microbes to metazoans, and its characteristics depend both on the biophysical parameters governing gene expression and on gene network structure. Stochastic gene expression has important consequences for cellular function, being beneficial in some contexts and harmful in others. These situations include the stress response, metabolism, development, the cell cycle, circadian rhythms, and aging.
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            The genetics of mammalian circadian order and disorder: implications for physiology and disease.

            Circadian cycles affect a variety of physiological processes, and disruptions of normal circadian biology therefore have the potential to influence a range of disease-related pathways. The genetic basis of circadian rhythms is well studied in model organisms and, more recently, studies of the genetic basis of circadian disorders has confirmed the conservation of key players in circadian biology from invertebrates to humans. In addition, important advances have been made in understanding how these molecules influence physiological functions in tissues throughout the body. Together, these studies set the scene for applying our knowledge of circadian biology to the understanding and treatment of a range of human diseases, including cancer and metabolic and behavioural disorders.
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              Suprachiasmatic nucleus: cell autonomy and network properties.

              The suprachiasmatic nucleus (SCN) is the primary circadian pacemaker in mammals. Individual SCN neurons in dispersed culture can generate independent circadian oscillations of clock gene expression and neuronal firing. However, SCN rhythmicity depends on sufficient membrane depolarization and levels of intracellular calcium and cAMP. In the intact SCN, cellular oscillations are synchronized and reinforced by rhythmic synaptic input from other cells, resulting in a reproducible topographic pattern of distinct phases and amplitudes specified by SCN circuit organization. The SCN network synchronizes its component cellular oscillators, reinforces their oscillations, responds to light input by altering their phase distribution, increases their robustness to genetic perturbations, and enhances their precision. Thus, even though individual SCN neurons can be cell-autonomous circadian oscillators, neuronal network properties are integral to normal function of the SCN.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                29 March 2012
                : 7
                : 3
                : e33334
                Affiliations
                [1 ]Department of Mathematics, Amherst College, Amherst, Massachusetts, United States of America
                [2 ]Department of Psychiatry and Center for Chronobiology, University of California San Diego, La Jolla, California, United States of America
                [3 ]Veterans Affairs San Diego Healthcare System, San Diego, California, United States of America
                Vanderbilt University, United States of America
                Author notes

                Conceived and designed the experiments: DKW. Performed the experiments: DKW. Analyzed the data: TLL CWW PJG DKW. Contributed reagents/materials/analysis tools: DKW TLL. Wrote the paper: TLL DKW.

                Article
                PONE-D-11-24458
                10.1371/journal.pone.0033334
                3315561
                22479387
                b2bd7371-9227-49a4-925e-6a179ab5f234
                Leise et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 5 December 2011
                : 7 February 2012
                Page count
                Pages: 10
                Categories
                Research Article
                Biology
                Anatomy and Physiology
                Physiological Processes
                Computational Biology
                Genetics
                Molecular Genetics
                Model Organisms
                Animal Models
                Molecular Cell Biology
                Mathematics
                Nonlinear Dynamics
                Statistics

                Uncategorized
                Uncategorized

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