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      Identification of factors involved in ribosome assembly in the protozoan parasite Leishmania major

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      Acta Tropica
      Elsevier BV

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          The CRAPome: a Contaminant Repository for Affinity Purification Mass Spectrometry Data

          Affinity purification coupled with mass spectrometry (AP-MS) is now a widely used approach for the identification of protein-protein interactions. However, for any given protein of interest, determining which of the identified polypeptides represent bona fide interactors versus those that are background contaminants (e.g. proteins that interact with the solid-phase support, affinity reagent or epitope tag) is a challenging task. While the standard approach is to identify nonspecific interactions using one or more negative controls, most small-scale AP-MS studies do not capture a complete, accurate background protein set. Fortunately, negative controls are largely bait-independent. Hence, aggregating negative controls from multiple AP-MS studies can increase coverage and improve the characterization of background associated with a given experimental protocol. Here we present the Contaminant Repository for Affinity Purification (the CRAPome) and describe the use of this resource to score protein-protein interactions. The repository (currently available for Homo sapiens and Saccharomyces cerevisiae) and computational tools are freely available online at www.crapome.org.
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            The Nucleolus under Stress

            Cells typically respond quickly to stress, altering their metabolism to compensate. In mammalian cells, stress signaling usually leads to either cell-cycle arrest or apoptosis, depending on the severity of the insult and the ability of the cell to recover. Stress also often leads to reorganization of nuclear architecture, reflecting the simultaneous inhibition of major nuclear pathways (e.g., replication and transcription) and activation of specific stress responses (e.g., DNA repair). In this review, we focus on how two nuclear organelles, the nucleolus and the Cajal body, respond to stress. The nucleolus senses stress and is a central hub for coordinating the stress response. We review nucleolar function in the stress-induced regulation of p53 and the specific changes in nucleolar morphology and composition that occur upon stress. Crosstalk between nucleoli and CBs is also discussed in the context of stress responses.
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              The complexity of human ribosome biogenesis revealed by systematic nucleolar screening of Pre-rRNA processing factors.

              Mature ribosomal RNAs (rRNAs) are produced from polycistronic precursors following complex processing. Precursor (pre)-rRNA processing has been extensively characterized in yeast and was assumed to be conserved in humans. We functionally characterized 625 nucleolar proteins in HeLa cells and identified 286 required for processing, including 74 without a yeast homolog. For selected candidates, we demonstrated that pre-rRNA processing defects are conserved in different cell types (including primary cells), defects are not due to activation of a p53-dependent nucleolar tumor surveillance pathway, and they precede cell-cycle arrest and apoptosis. We also investigated the exosome's role in processing internal transcribed spacers (ITSs) and report that 3' end maturation of 18S rRNA involves EXOSC10/Rrp6, a yeast ITS2 processing factor. We conclude that human cells adopt unique strategies and recruit distinct trans-acting factors to carry out essential processing steps, posing fundamental implications for understanding ribosomopathies at the molecular level and developing effective therapeutic agents. Copyright © 2013 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                Acta Tropica
                Acta Tropica
                Elsevier BV
                0001706X
                April 2022
                April 2022
                : 228
                : 106315
                Article
                10.1016/j.actatropica.2022.106315
                f14cc1a9-3f6b-4bcf-a13b-e750d3308200
                © 2022

                https://www.elsevier.com/tdm/userlicense/1.0/

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