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      A unique surface on Pat1 C-terminal domain directly interacts with Dcp2 decapping enzyme and Xrn1 5′–3′ mRNA exonuclease in yeast

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          Abstract

          <p id="d13065485e254">Control of mRNA synthesis and decay is crucial for cells to adapt to their environment and for proper development. The 5′ end of eukaryotic mRNAs is modified by a structure called cap that protects them from rapid and uncontrolled decay. During mRNA decay, this cap is removed by a specialized and finely regulated multiprotein factory called decapping complex. Our results support a model in which the two major enzymes responsible for mRNA decapping (Dcp2) and decay (Xrn1) are sequentially recruited to mRNAs by the same surface from Pat1, a scaffolding protein central for decapping. As this Pat1 region is important for growth and specific to fungi, this is a potential target for the development of drugs against pathogenic yeasts. </p><p class="first" id="d13065485e257">The Pat1 protein is a central player of eukaryotic mRNA decay that has also been implicated in translational control. It is commonly considered a central platform responsible for the recruitment of several RNA decay factors. We demonstrate here that a yeast-specific C-terminal region from Pat1 interacts with several short motifs, named helical leucine-rich motifs (HLMs), spread in the long C-terminal region of yeast Dcp2 decapping enzyme. Structures of Pat1–HLM complexes reveal the basis for HLM recognition by Pat1. We also identify a HLM present in yeast Xrn1, the main 5′–3′ exonuclease involved in mRNA decay. We show further that the ability of yeast Pat1 to bind HLMs is required for efficient growth and normal mRNA decay. Overall, our analyses indicate that yeast Pat1 uses a single binding surface to successively recruit several mRNA decay factors and show that interaction between those factors is highly polymorphic between species. </p>

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          Most cited references45

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          Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise.

          A major goal of biology is to provide a quantitative description of cellular behaviour. This task, however, has been hampered by the difficulty in measuring protein abundances and their variation. Here we present a strategy that pairs high-throughput flow cytometry and a library of GFP-tagged yeast strains to monitor rapidly and precisely protein levels at single-cell resolution. Bulk protein abundance measurements of >2,500 proteins in rich and minimal media provide a detailed view of the cellular response to these conditions, and capture many changes not observed by DNA microarray analyses. Our single-cell data argue that noise in protein expression is dominated by the stochastic production/destruction of messenger RNAs. Beyond this global trend, there are dramatic protein-specific differences in noise that are strongly correlated with a protein's mode of transcription and its function. For example, proteins that respond to environmental changes are noisy whereas those involved in protein synthesis are quiet. Thus, these studies reveal a remarkable structure to biological noise and suggest that protein noise levels have been selected to reflect the costs and potential benefits of this variation.
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            ESPript/ENDscript: Extracting and rendering sequence and 3D information from atomic structures of proteins.

            The fortran program ESPript was created in 1993, to display on a PostScript figure multiple sequence alignments adorned with secondary structure elements. A web server was made available in 1999 and ESPript has been linked to three major web tools: ProDom which identifies protein domains, PredictProtein which predicts secondary structure elements and NPS@ which runs sequence alignment programs. A web server named ENDscript was created in 2002 to facilitate the generation of ESPript figures containing a large amount of information. ENDscript uses programs such as BLAST, Clustal and PHYLODENDRON to work on protein sequences and such as DSSP, CNS and MOLSCRIPT to work on protein coordinates. It enables the creation, from a single Protein Data Bank identifier, of a multiple sequence alignment figure adorned with secondary structure elements of each sequence of known 3D structure. Similar 3D structures are superimposed in turn with the program PROFIT and a final figure is drawn with BOBSCRIPT, which shows sequence and structure conservation along the Calpha trace of the query. ESPript and ENDscript are available at http://genopole.toulouse.inra.fr/ESPript.
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              General translational repression by activators of mRNA decapping.

              Translation and mRNA degradation are affected by a key transition where eukaryotic mRNAs exit translation and assemble an mRNP state that accumulates into processing bodies (P bodies), cytoplasmic sites of mRNA degradation containing non-translating mRNAs, and mRNA degradation machinery. We identify the decapping activators Dhh1p and Pat1p as functioning as translational repressors and facilitators of P body formation. Strains lacking both Dhh1p and Pat1p show strong defects in mRNA decapping and P body formation and are blocked in translational repression. Contrastingly, overexpression of Dhh1p or Pat1p causes translational repression, P body formation, and arrests cell growth. Dhh1p, and its human homolog, RCK/p54, repress translation in vitro, and Dhh1p function is bypassed in vivo by inhibition of translational initiation. These results identify a broadly acting mechanism of translational repression that targets mRNAs for decapping and functions in translational control. We propose this mechanism is competitively balanced with translation, and shifting this balance is an important basis of translational control.
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                Author and article information

                Journal
                Proceedings of the National Academy of Sciences
                Proc Natl Acad Sci USA
                Proceedings of the National Academy of Sciences
                0027-8424
                1091-6490
                November 07 2017
                November 07 2017
                November 07 2017
                October 24 2017
                : 114
                : 45
                : E9493-E9501
                Article
                10.1073/pnas.1711680114
                5692570
                29078363
                45a05fee-e12e-4a48-897d-f820da93e295
                © 2017

                Free to read

                http://www.pnas.org/site/misc/userlicense.xhtml

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