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We are analyzing https://link.springer.com/article/10.1007/s00018-025-05708-7.

Title:
Proteomics-based characterization of ribosome heterogeneity in adult mouse organs | Cellular and Molecular Life Sciences
Description:
The translation process, leading to protein synthesis from mRNA, has been long thought to be invariable in all cellular organisms. Increasing evidence shows that it is finely regulated by variable features of the translation machinery. Notably, ribosomes, the functional units of protein synthesis, are suggested to display variations in their composition, depending on the developmental stage, cell type or physio-pathological context, thus hinting a new level of actionable regulation of gene expression. Yet, a comprehensive map of the heterogeneity of ribosome composition in ribosomal proteins (RPs) in different organs and tissues is not available. In this work, we explored tissue-specific ribosome heterogeneity using mass spectrometry-based quantitative proteomic characterization of ribosomal fractions purified from 14 adult mouse organs and tissues. We performed crossed clustering and statistical analyses of RP composition to highlight stable, variable and tissue-specific RPs across organs and tissues. Focusing on specific RPs, we validated their varying abundances using a targeted proteomic approach and western blot analyses, providing further insights into the tissue-specific ribosome RP signature. Finally, we investigated the origin of RP variations in ribosome fraction of the different tissues, by comparing RP relative amounts in our ribosomal proteomic dataset with their corresponding transcript abundances in three independent transcriptomic datasets. Interestingly, we found that, in some tissues, the RP abundance in purified ribosomes does not always correlate with the corresponding RP transcript level, arguing for a translational regulation of RP expression, and/or a regulated incorporation of RPs into ribosomes. Altogether, our data support the notion of a tissue-specific RP signature of ribosomes, which opens avenues to study how specific ribosomal composition provides an additional level of regulation to control gene expression in different tissues and organs. Graphical abstract
Website Age:
28 years and 1 months (reg. 1997-05-29).

Matching Content Categories {📚}

  • Education
  • Science
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Content Management System {📝}

What CMS is link.springer.com built with?

Custom-built

No common CMS systems were detected on Link.springer.com, and no known web development framework was identified.

Traffic Estimate {📈}

What is the average monthly size of link.springer.com audience?

🌠 Phenomenal Traffic: 5M - 10M visitors per month


Based on our best estimate, this website will receive around 7,642,828 visitors per month in the current month.

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How Does Link.springer.com Make Money? {💸}

We find it hard to spot revenue streams.

Earning money isn't the goal of every website; some are designed to offer support or promote social causes. People have different reasons for creating websites. This might be one such reason. Link.springer.com might be earning cash quietly, but we haven't detected the monetization method.

Keywords {🔍}

rps, ribosomal, pubmed, tissues, article, ribosome, google, scholar, protein, cas, fig, expression, fractions, rpl, ribosomes, central, proteins, specific, rpll, mouse, organs, analysis, composition, cell, tissue, fraction, peptides, relative, abundance, translation, test, mrna, regulation, detected, level, data, adult, testis, variable, heterogeneity, found, rplp, human, replicates, qvalue, normalized, proteomic, transcript, transcriptomic, analyzed,

Topics {✒️}

/science/article/pii/s1097276520307309 akirtava /profiproteomics/mzdb/tree/mzdb-processing_0 mono-charged y-type ions /trends/biochemical-sciences/abstract/s0968-0004 mass-spectrometry-based draft ms-based quantitative proteomics article download pdf discovery lc–ms/ms data reprosil-pur 120 c18-aq unidirectional flow “dna-mrna-protein” x-linked dyskeratosis congenita higher-energy collisional dissociation targeted proteomics-based quantification central nervous systems multiple unpaired t-tests bis–tris polyacrylamide gel cell type-specific control ms-based proteomic analysis based quantitative proteomics 60 min multi-linear gradient ultrapure ice-cold water tandem mass spectrometry user-friendly software suite nano-lc method consisted log10-transformed protein abundances quantitative discovery proteomics log-transformed protein abundance log-transformed relative abundances stroke-induced peripheral immunosuppression log-transformed relative expression rrna 2′-o-methylation plasticity identifying intra-cellular populations proteomics-based characterization intensity-based absolute quantification high energy-consuming process cell type-specific versus show organ-specific compensations c57bl/6j adult mice specific hox-coding mrnas mix male/female tissues heavy isotope-labeled peptides physio-pathological conditions revealed tissue-specific rp signature heavy isotope-labelled peptides full size image ires-mediated translation run limma t-test organ-specific rp signature malignant human cells home-made mus database

Questions {❓}

  • Fortelny N, Overall CM, Pavlidis P, Freue GVC (2017) Can we predict protein from mRNA levels?
  • Then the next key question is: what mechanisms are at play to control inter-organ variation in RP ribosomal composition?
  • Warner JR, McIntosh KB (2009) How common are extra-ribosomal functions of ribosomal proteins?

Schema {🗺️}

WebPage:
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         headline:Proteomics-based characterization of ribosome heterogeneity in adult mouse organs
         description:The translation process, leading to protein synthesis from mRNA, has been long thought to be invariable in all cellular organisms. Increasing evidence shows that it is finely regulated by variable features of the translation machinery. Notably, ribosomes, the functional units of protein synthesis, are suggested to display variations in their composition, depending on the developmental stage, cell type or physio-pathological context, thus hinting a new level of actionable regulation of gene expression. Yet, a comprehensive map of the heterogeneity of ribosome composition in ribosomal proteins (RPs) in different organs and tissues is not available. In this work, we explored tissue-specific ribosome heterogeneity using mass spectrometry-based quantitative proteomic characterization of ribosomal fractions purified from 14 adult mouse organs and tissues. We performed crossed clustering and statistical analyses of RP composition to highlight stable, variable and tissue-specific RPs across organs and tissues. Focusing on specific RPs, we validated their varying abundances using a targeted proteomic approach and western blot analyses, providing further insights into the tissue-specific ribosome RP signature. Finally, we investigated the origin of RP variations in ribosome fraction of the different tissues, by comparing RP relative amounts in our ribosomal proteomic dataset with their corresponding transcript abundances in three independent transcriptomic datasets. Interestingly, we found that, in some tissues, the RP abundance in purified ribosomes does not always correlate with the corresponding RP transcript level, arguing for a translational regulation of RP expression, and/or a regulated incorporation of RPs into ribosomes. Altogether, our data support the notion of a tissue-specific RP signature of ribosomes, which opens avenues to study how specific ribosomal composition provides an additional level of regulation to control gene expression in different tissues and organs.
         datePublished:2025-04-24T00:00:00Z
         dateModified:2025-04-24T00:00:00Z
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            Ribosome
            Ribosome heterogeneity
            Mass spectrometry
            Quantitative proteomic
            Translational control
            Transcriptomic analysis
            Cell Biology
            Biomedicine
            general
            Life Sciences
            Biochemistry
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                     address:
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                        name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
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      headline:Proteomics-based characterization of ribosome heterogeneity in adult mouse organs
      description:The translation process, leading to protein synthesis from mRNA, has been long thought to be invariable in all cellular organisms. Increasing evidence shows that it is finely regulated by variable features of the translation machinery. Notably, ribosomes, the functional units of protein synthesis, are suggested to display variations in their composition, depending on the developmental stage, cell type or physio-pathological context, thus hinting a new level of actionable regulation of gene expression. Yet, a comprehensive map of the heterogeneity of ribosome composition in ribosomal proteins (RPs) in different organs and tissues is not available. In this work, we explored tissue-specific ribosome heterogeneity using mass spectrometry-based quantitative proteomic characterization of ribosomal fractions purified from 14 adult mouse organs and tissues. We performed crossed clustering and statistical analyses of RP composition to highlight stable, variable and tissue-specific RPs across organs and tissues. Focusing on specific RPs, we validated their varying abundances using a targeted proteomic approach and western blot analyses, providing further insights into the tissue-specific ribosome RP signature. Finally, we investigated the origin of RP variations in ribosome fraction of the different tissues, by comparing RP relative amounts in our ribosomal proteomic dataset with their corresponding transcript abundances in three independent transcriptomic datasets. Interestingly, we found that, in some tissues, the RP abundance in purified ribosomes does not always correlate with the corresponding RP transcript level, arguing for a translational regulation of RP expression, and/or a regulated incorporation of RPs into ribosomes. Altogether, our data support the notion of a tissue-specific RP signature of ribosomes, which opens avenues to study how specific ribosomal composition provides an additional level of regulation to control gene expression in different tissues and organs.
      datePublished:2025-04-24T00:00:00Z
      dateModified:2025-04-24T00:00:00Z
      pageStart:1
      pageEnd:23
      license:http://creativecommons.org/licenses/by/4.0/
      sameAs:https://doi.org/10.1007/s00018-025-05708-7
      keywords:
         Ribosome
         Ribosome heterogeneity
         Mass spectrometry
         Quantitative proteomic
         Translational control
         Transcriptomic analysis
         Cell Biology
         Biomedicine
         general
         Life Sciences
         Biochemistry
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         name:Springer International Publishing
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            type:ImageObject
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      author:
            name:Marie R. Brunchault
            affiliation:
                  name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences
                  address:
                     name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
                     type:PostalAddress
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            type:Person
            name:Anne-Marie Hesse
            affiliation:
                  name:Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, CEA, FR2048
                  address:
                     name:Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, CEA, FR2048, Grenoble, France
                     type:PostalAddress
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            name:Julia Schaeffer
            affiliation:
                  name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences
                  address:
                     name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
                     type:PostalAddress
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                  name:IBDM, CNRS, UMR 7288, Aix-Marseille Université
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            name:Albrecht Fröhlich
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                  name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences
                  address:
                     name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
                     type:PostalAddress
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            name:Ana Saintpierre
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                  name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences
                  address:
                     name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Charlotte Decourt
            affiliation:
                  name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences
                  address:
                     name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
                     type:PostalAddress
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            name:Florence Combes
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                  name:Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, CEA, FR2048
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                     name:Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, CEA, FR2048, Grenoble, France
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            name:Homaira Nawabi
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                  address:
                     name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
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            name:Yohann Couté
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                     name:Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, CEA, FR2048, Grenoble, France
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            name:Stephane Belin
            url:http://orcid.org/0000-0001-7074-6885
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      name:Julia Schaeffer
      affiliation:
            name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences
            address:
               name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
               type:PostalAddress
            type:Organization
            name:IBDM, CNRS, UMR 7288, Aix-Marseille Université
            address:
               name:IBDM, CNRS, UMR 7288, Aix-Marseille Université, Marseille, France
               type:PostalAddress
            type:Organization
      name:Albrecht Fröhlich
      affiliation:
            name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences
            address:
               name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
               type:PostalAddress
            type:Organization
      name:Ana Saintpierre
      affiliation:
            name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences
            address:
               name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
               type:PostalAddress
            type:Organization
      name:Charlotte Decourt
      affiliation:
            name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences
            address:
               name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
               type:PostalAddress
            type:Organization
      name:Florence Combes
      affiliation:
            name:Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, CEA, FR2048
            address:
               name:Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, CEA, FR2048, Grenoble, France
               type:PostalAddress
            type:Organization
      name:Homaira Nawabi
      affiliation:
            name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences
            address:
               name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
               type:PostalAddress
            type:Organization
      name:Yohann Couté
      affiliation:
            name:Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, CEA, FR2048
            address:
               name:Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, CEA, FR2048, Grenoble, France
               type:PostalAddress
            type:Organization
      email:[email protected]
      name:Stephane Belin
      url:http://orcid.org/0000-0001-7074-6885
      affiliation:
            name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences
            address:
               name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
               type:PostalAddress
            type:Organization
      email:[email protected]
PostalAddress:
      name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
      name:Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, CEA, FR2048, Grenoble, France
      name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
      name:IBDM, CNRS, UMR 7288, Aix-Marseille Université, Marseille, France
      name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
      name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
      name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
      name:Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, CEA, FR2048, Grenoble, France
      name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
      name:Univ. Grenoble Alpes, INSERM, CEA, UA13 BGE, CNRS, CEA, FR2048, Grenoble, France
      name:Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France

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