Comparative analysis of the intracellular responses to disease-related aggregation-prone proteins.

Amyloid Aβ42 FUS GFP HTT Neurodegenerative diseases Protein aggregation Quantitative proteomics TDP43 Yeast αSyn

Journal

Journal of proteomics
ISSN: 1876-7737
Titre abrégé: J Proteomics
Pays: Netherlands
ID NLM: 101475056

Informations de publication

Date de publication:
15 08 2020
Historique:
received: 16 01 2020
revised: 29 05 2020
accepted: 02 06 2020
pubmed: 15 6 2020
medline: 22 6 2021
entrez: 15 6 2020
Statut: ppublish

Résumé

Aggregation-prone proteins (APPs) have been implicated in numerous human diseases but the underlying mechanisms are incompletely understood. Here we comparatively analysed cellular responses to different APPs. Our study is based on a systematic proteomic and phosphoproteomic analysis of a set of yeast proteotoxicity models expressing different human disease-related APPs, which accumulate intracellular APP inclusions and exhibit impaired growth. Clustering and functional enrichment analyses of quantitative proteome-level data reveal that the cellular response to APP expression, including the chaperone response, is specific to the APP, and largely differs from the response to a more generalized proteotoxic insult such as heat shock. We further observe an intriguing association between the subcellular location of inclusions and the location of the cellular response, and provide a rich dataset for future mechanistic studies. Our data suggest that care should be taken when designing research models to study intracellular aggregation, since the cellular response depends markedly on the specific APP and the location of inclusions. Further, therapeutic approaches aimed at boosting protein quality control in protein aggregation diseases should be tailored to the subcellular location affected by inclusion formation. SIGNIFICANCE: We have examined the global cellular response, in terms of protein abundance and phosphorylation changes, to the expression of five human neurodegeneration-associated, aggregation-prone proteins (APPs) in a set of isogenic yeast models. Our results show that the cellular response to each APP is unique to that protein, is different from the response to thermal stress, and is associated with processes at the subcellular location of APP inclusion formation. These results further our understanding of how cells, in a model organism, respond to expression of APPs implicated in neurodegenerative diseases like Parkinson's, Alzheimer's, and ALS. They have implications for mechanisms of toxicity as well as of protective responses in the cell. The specificity of the response to each APP means that research models of these diseases should be tailored to the APP in question. The subcellular localization of the response suggest that therapeutic interventions should also be targeted within the cell.

Identifiants

pubmed: 32535145
pii: S1874-3919(20)30230-X
doi: 10.1016/j.jprot.2020.103862
pii:
doi:

Substances chimiques

Proteome 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

103862

Informations de copyright

Crown Copyright © 2020. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no competing interests.

Auteurs

Andre Melnik (A)

Institute of Biochemistry, Department of Biology, ETH Zurich, CH-8093 Zurich, Switzerland.

Valentina Cappelletti (V)

Institute of Biochemistry, Department of Biology, ETH Zurich, CH-8093 Zurich, Switzerland; Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, CH-8093 Zurich, Switzerland.

Federico Vaggi (F)

Amazon, Seattle, WA, USA.

Ilaria Piazza (I)

Institute of Biochemistry, Department of Biology, ETH Zurich, CH-8093 Zurich, Switzerland; Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, CH-8093 Zurich, Switzerland.

Marco Tognetti (M)

Institute of Biochemistry, Department of Biology, ETH Zurich, CH-8093 Zurich, Switzerland; Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, CH-8093 Zurich, Switzerland.

Carmen Schwarz (C)

Institute of Biochemistry, Department of Biology, ETH Zurich, CH-8093 Zurich, Switzerland.

Gea Cereghetti (G)

Institute of Biochemistry, Department of Biology, ETH Zurich, CH-8093 Zurich, Switzerland.

Mennat Allah Ahmed (MA)

Institute of Biochemistry, Department of Biology, ETH Zurich, CH-8093 Zurich, Switzerland.

Martin Soste (M)

Institute of Biochemistry, Department of Biology, ETH Zurich, CH-8093 Zurich, Switzerland.

Kent Matlack (K)

Whitehead Institute for Biomedical Research, MIT, 455 Main Street, Cambridge, MA 02142, USA.

Natalie de Souza (N)

Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, CH-8093 Zurich, Switzerland.

Attila Csikasz-Nagy (A)

Randall Division of Cell and Molecular Biophysics, King's College London, SE1 1UL London, United Kingdom; Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, 1083 Budapest, Hungary.

Paola Picotti (P)

Institute of Biochemistry, Department of Biology, ETH Zurich, CH-8093 Zurich, Switzerland; Institute of Molecular Systems Biology, Department of Biology, ETH Zurich, CH-8093 Zurich, Switzerland. Electronic address: picotti@imsb.biol.ethz.ch.

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Classifications MeSH