<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Chen YR</submitter><funding>NIA NIH HHS</funding><funding>NIGMS NIH HHS</funding><pagination>1892-1911.e13</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11265985</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>59(14)</volume><pubmed_abstract>Protein aggregation is a hallmark of age-related neurodegeneration. Yet, aggregation during normal aging and in tissues other than the brain is poorly understood. Here, we leverage the African turquoise killifish to systematically profile protein aggregates in seven tissues of an aging vertebrate. Age-dependent aggregation is strikingly tissue specific and not simply driven by protein expression differences. Experimental interrogation in killifish and yeast, combined with machine learning, indicates that this specificity is linked to protein-autonomous biophysical features and tissue-selective alterations in protein quality control. Co-aggregation of protein quality control machinery during aging may further reduce proteostasis capacity, exacerbating aggregate burden. A segmental progeria model with accelerated aging in specific tissues exhibits selectively increased aggregation in these same tissues. Intriguingly, many age-related protein aggregates arise in wild-type proteins that, when mutated, drive human diseases. Our data chart a comprehensive landscape of protein aggregation during vertebrate aging and identify strong, tissue-specific associations with dysfunction and disease.</pubmed_abstract><journal>Developmental cell</journal><pubmed_title>Tissue-specific landscape of protein aggregation and quality control in an aging vertebrate.</pubmed_title><pmcid>PMC11265985</pmcid><funding_grant_id>R01 AG063418</funding_grant_id><funding_grant_id>RF1 AG057334</funding_grant_id><funding_grant_id>R21 AG063739</funding_grant_id><funding_grant_id>DP2 GM119140</funding_grant_id><pubmed_authors>Chen YR</pubmed_authors><pubmed_authors>Goshtchevsky U</pubmed_authors><pubmed_authors>Brunet A</pubmed_authors><pubmed_authors>Jarosz DF</pubmed_authors><pubmed_authors>Harel I</pubmed_authors><pubmed_authors>Ziv I</pubmed_authors><pubmed_authors>Singh PP</pubmed_authors><pubmed_authors>Moses E</pubmed_authors><pubmed_authors>Machado BE</pubmed_authors></additional><is_claimable>false</is_claimable><name>Tissue-specific landscape of protein aggregation and quality control in an aging vertebrate.</name><description>Protein aggregation is a hallmark of age-related neurodegeneration. Yet, aggregation during normal aging and in tissues other than the brain is poorly understood. Here, we leverage the African turquoise killifish to systematically profile protein aggregates in seven tissues of an aging vertebrate. Age-dependent aggregation is strikingly tissue specific and not simply driven by protein expression differences. Experimental interrogation in killifish and yeast, combined with machine learning, indicates that this specificity is linked to protein-autonomous biophysical features and tissue-selective alterations in protein quality control. Co-aggregation of protein quality control machinery during aging may further reduce proteostasis capacity, exacerbating aggregate burden. A segmental progeria model with accelerated aging in specific tissues exhibits selectively increased aggregation in these same tissues. Intriguingly, many age-related protein aggregates arise in wild-type proteins that, when mutated, drive human diseases. Our data chart a comprehensive landscape of protein aggregation during vertebrate aging and identify strong, tissue-specific associations with dysfunction and disease.</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Jul</publication><modification>2026-03-31T10:34:08.653Z</modification><creation>2025-08-24T03:07:37.207Z</creation></dates><accession>S-EPMC11265985</accession><cross_references><pubmed>38810654</pubmed><doi>10.1016/j.devcel.2024.04.014</doi></cross_references></HashMap>