Tissue-specific landscape of protein aggregation and quality control in an aging vertebrate

Yiwen R. Chen, Itamar Harel, Param Priya Singh, Inbal Ziv, Eitan Moses, Uri Goshtchevsky, Ben E. Machado, Anne Brunet*, Daniel F. Jarosz*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

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.

Original languageEnglish
Pages (from-to)1892-1911.e13
JournalDevelopmental Cell
Volume59
Issue number14
DOIs
StatePublished - 22 Jul 2024

Bibliographical note

Publisher Copyright:
© 2024 Elsevier Inc.

Keywords

  • aggregates
  • aging
  • multi-tissue
  • protein homeostasis
  • proteomics
  • systems biology

Fingerprint

Dive into the research topics of 'Tissue-specific landscape of protein aggregation and quality control in an aging vertebrate'. Together they form a unique fingerprint.

Cite this