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      The Efg1–Bud22 dimer associates with the U14 snoRNP contacting the 5′ rRNA domain of an early 90S pre-ribosomal particle

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          Abstract

          The DEAD-box helicase Dbp4 plays an essential role during the early assembly of the 40S ribosome, which is only poorly understood to date. By applying the yeast two-hybrid method and biochemical approaches, we discovered that Dbp4 interacts with the Efg1–Bud22 dimer. Both factors associate with early pre-90S particles and smaller complexes, each characterized by a high presence of the U14 snoRNA. A crosslink analysis of Bud22 revealed its contact to the U14 snoRNA and the 5′ domain of the nascent 18S rRNA, close to its U14 snoRNA hybridization site. Moreover, depletion of Bud22 or Efg1 specifically affects U14 snoRNA association with pre-ribosomal complexes. Accordingly, we concluded that the role of the Efg1–Bud22 dimer is linked to the U14 snoRNA function on early 90S ribosome intermediates chaperoning the 5′ domain of the nascent 18S rRNA. The successful rRNA folding of the 5′ domain and the release of Efg1, Bud22, Dpb4, U14 snoRNA and associated snoRNP factors allows the subsequent recruitment of the Kre33-Bfr2-Enp2-Lcp5 module towards the 90S pre-ribosome.

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          MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.

          Efficient analysis of very large amounts of raw data for peptide identification and protein quantification is a principal challenge in mass spectrometry (MS)-based proteomics. Here we describe MaxQuant, an integrated suite of algorithms specifically developed for high-resolution, quantitative MS data. Using correlation analysis and graph theory, MaxQuant detects peaks, isotope clusters and stable amino acid isotope-labeled (SILAC) peptide pairs as three-dimensional objects in m/z, elution time and signal intensity space. By integrating multiple mass measurements and correcting for linear and nonlinear mass offsets, we achieve mass accuracy in the p.p.b. range, a sixfold increase over standard techniques. We increase the proportion of identified fragmentation spectra to 73% for SILAC peptide pairs via unambiguous assignment of isotope and missed-cleavage state and individual mass precision. MaxQuant automatically quantifies several hundred thousand peptides per SILAC-proteome experiment and allows statistically robust identification and quantification of >4,000 proteins in mammalian cell lysates.
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            Gene Expression Omnibus: NCBI gene expression and hybridization array data repository.

            R. Edgar (2002)
            The Gene Expression Omnibus (GEO) project was initiated in response to the growing demand for a public repository for high-throughput gene expression data. GEO provides a flexible and open design that facilitates submission, storage and retrieval of heterogeneous data sets from high-throughput gene expression and genomic hybridization experiments. GEO is not intended to replace in house gene expression databases that benefit from coherent data sets, and which are constructed to facilitate a particular analytic method, but rather complement these by acting as a tertiary, central data distribution hub. The three central data entities of GEO are platforms, samples and series, and were designed with gene expression and genomic hybridization experiments in mind. A platform is, essentially, a list of probes that define what set of molecules may be detected. A sample describes the set of molecules that are being probed and references a single platform used to generate its molecular abundance data. A series organizes samples into the meaningful data sets which make up an experiment. The GEO repository is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.
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              The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidences

              The PRoteomics IDEntifications (PRIDE) database ( https://www.ebi.ac.uk/pride/ ) is the world's largest data repository of mass spectrometry-based proteomics data. PRIDE is one of the founding members of the global ProteomeXchange (PX) consortium and an ELIXIR core data resource. In this manuscript, we summarize the developments in PRIDE resources and related tools since the previous update manuscript was published in Nucleic Acids Research in 2019. The number of submitted datasets to PRIDE Archive (the archival component of PRIDE) has reached on average around 500 datasets per month during 2021. In addition to continuous improvements in PRIDE Archive data pipelines and infrastructure, the PRIDE Spectra Archive has been developed to provide direct access to the submitted mass spectra using Universal Spectrum Identifiers. As a key point, the file format MAGE-TAB for proteomics has been developed to enable the improvement of sample metadata annotation. Additionally, the resource PRIDE Peptidome provides access to aggregated peptide/protein evidences across PRIDE Archive. Furthermore, we will describe how PRIDE has increased its efforts to reuse and disseminate high-quality proteomics data into other added-value resources such as UniProt, Ensembl and Expression Atlas.
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                Author and article information

                Contributors
                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                11 January 2024
                24 November 2023
                24 November 2023
                : 52
                : 1
                : 431-447
                Affiliations
                Biochemie-Zentrum der Universität Heidelberg (BZH) , Im Neuenheimer Feld 328, 69120 Heidelberg, Germany
                Biochemie-Zentrum der Universität Heidelberg (BZH) , Im Neuenheimer Feld 328, 69120 Heidelberg, Germany
                Biochemie-Zentrum der Universität Heidelberg (BZH) , Im Neuenheimer Feld 328, 69120 Heidelberg, Germany
                Biochemie-Zentrum der Universität Heidelberg (BZH) , Im Neuenheimer Feld 328, 69120 Heidelberg, Germany
                Biochemie-Zentrum der Universität Heidelberg (BZH) , Im Neuenheimer Feld 328, 69120 Heidelberg, Germany
                Author notes
                To whom correspondence should be addressed. Tel: +49 6621 546757; Fax: +49 6621 544369; Email: jochen.bassler@ 123456bzh.uni-heidelberg.de
                Author information
                https://orcid.org/0000-0001-6852-5362
                https://orcid.org/0000-0002-7441-7867
                Article
                gkad1109
                10.1093/nar/gkad1109
                10783500
                38000371
                e9950a07-e04d-40fb-ba02-43005c8e5c8b
                © The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 02 November 2023
                : 27 October 2023
                : 21 November 2022
                Page count
                Pages: 17
                Funding
                Funded by: Deutsche Forschungsgemeinschaft, DOI 10.13039/501100001659;
                Award ID: BA 2316/2-1
                Award ID: INST 35/1314-1 FUGG
                Award ID: INST 35/1503-1 FUGG
                Funded by: European Research Council, DOI 10.13039/100010663;
                Award ID: ADG 741781 GLOWSOME
                Funded by: University of Heidelberg, DOI 10.13039/501100001661;
                Categories
                AcademicSubjects/SCI00010
                RNA and RNA-protein complexes

                Genetics
                Genetics

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