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      Nuclear Proteomics Uncovers Diurnal Regulatory Landscapes in Mouse Liver

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          Summary

          Diurnal oscillations of gene expression controlled by the circadian clock and its connected feeding rhythm enable organisms to coordinate their physiologies with daily environmental cycles. While available techniques yielded crucial insights into regulation at the transcriptional level, much less is known about temporally controlled functions within the nucleus and their regulation at the protein level. Here, we quantified the temporal nuclear accumulation of proteins and phosphoproteins from mouse liver by SILAC proteomics. We identified around 5,000 nuclear proteins, over 500 of which showed a diurnal accumulation. Parallel analysis of the nuclear phosphoproteome enabled the inference of the temporal activity of kinases accounting for rhythmic phosphorylation. Many identified rhythmic proteins were parts of nuclear complexes involved in transcriptional regulation, ribosome biogenesis, DNA repair, and the cell cycle and its potentially associated diurnal rhythm of hepatocyte polyploidy. Taken together, these findings provide unprecedented insights into the diurnal regulatory landscape of the mouse liver nucleus.

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          Most cited references77

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          Transcriptional architecture and chromatin landscape of the core circadian clock in mammals.

          The mammalian circadian clock involves a transcriptional feed back loop in which CLOCK and BMAL1 activate the Period and Cryptochrome genes, which then feedback and repress their own transcription. We have interrogated the transcriptional architecture of the circadian transcriptional regulatory loop on a genome scale in mouse liver and find a stereotyped, time-dependent pattern of transcription factor binding, RNA polymerase II (RNAPII) recruitment, RNA expression, and chromatin states. We find that the circadian transcriptional cycle of the clock consists of three distinct phases: a poised state, a coordinated de novo transcriptional activation state, and a repressed state. Only 22% of messenger RNA (mRNA) cycling genes are driven by de novo transcription, suggesting that both transcriptional and posttranscriptional mechanisms underlie the mammalian circadian clock. We also find that circadian modulation of RNAPII recruitment and chromatin remodeling occurs on a genome-wide scale far greater than that seen previously by gene expression profiling.
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            Proteomic characterization of the human centrosome by protein correlation profiling.

            The centrosome is the major microtubule-organizing centre of animal cells and through its influence on the cytoskeleton is involved in cell shape, polarity and motility. It also has a crucial function in cell division because it determines the poles of the mitotic spindle that segregates duplicated chromosomes between dividing cells. Despite the importance of this organelle to cell biology and more than 100 years of study, many aspects of its function remain enigmatic and its structure and composition are still largely unknown. We performed a mass-spectrometry-based proteomic analysis of human centrosomes in the interphase of the cell cycle by quantitatively profiling hundreds of proteins across several centrifugation fractions. True centrosomal proteins were revealed by both correlation with already known centrosomal proteins and in vivo localization. We identified and validated 23 novel components and identified 41 likely candidates as well as the vast majority of the known centrosomal proteins in a large background of nonspecific proteins. Protein correlation profiling permits the analysis of any multiprotein complex that can be enriched by fractionation but not purified to homogeneity.
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              COMPARTMENTS: unification and visualization of protein subcellular localization evidence

              Information on protein subcellular localization is important to understand the cellular functions of proteins. Currently, such information is manually curated from the literature, obtained from high-throughput microscopy-based screens and predicted from primary sequence. To get a comprehensive view of the localization of a protein, it is thus necessary to consult multiple databases and prediction tools. To address this, we present the COMPARTMENTS resource, which integrates all sources listed above as well as the results of automatic text mining. The resource is automatically kept up to date with source databases, and all localization evidence is mapped onto common protein identifiers and Gene Ontology terms. We further assign confidence scores to the localization evidence to facilitate comparison of different types and sources of evidence. To further improve the comparability, we assign confidence scores based on the type and source of the localization evidence. Finally, we visualize the unified localization evidence for a protein on a schematic cell to provide a simple overview. Database URL: http://compartments.jensenlab.org
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                Author and article information

                Journal
                101233170
                32527
                Cell Metab
                Cell Metab.
                Cell metabolism
                1550-4131
                1932-7420
                13 January 2017
                03 November 2016
                10 January 2017
                19 January 2017
                : 25
                : 1
                : 102-117
                Affiliations
                [1 ]Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
                [2 ]Department of Diabetes and Circadian Rhythms, Nestlé Institute of Health Sciences, CH-1015 Lausanne, Switzerland
                [3 ]Department of Pharmacology and Toxicology, University of Lausanne, CH-1015 Lausanne, Switzerland
                [4 ]Systems Nutrition, Metabonomics, and Proteomics, Nestlé Institute of Health Sciences, CH-1015 Lausanne, Switzerland
                [5 ]Department of Cell Biology, Nestlé Institute of Health Sciences, CH-1015 Lausanne, Switzerland
                [6 ]Protein Analysis Facility, University of Lausanne, CH-1015 Lausanne, Switzerland
                [7 ]CNRS, UMR 5535, Institut de Génétique Moléculaire de Montpellier, 34090 Montpellier, France
                [8 ]School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
                Author notes
                [9]

                Co-first author

                [10]

                Present address: Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland

                [11]

                Lead Contact

                Article
                EMS70424
                10.1016/j.cmet.2016.10.003
                5241201
                27818260
                4228be15-7384-442c-af2c-344e3b292f55

                This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/).

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                Cell biology
                Cell biology

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