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Aggregate Interactome Based on Protein Cross-linking Interfaces Predicts Drug Targets to Limit Aggregation in Neurodegenerative Diseases

Diagnosis of neurodegenerative diseases hinges on “seed” proteins detected in disease-specific aggregates. These inclusions contain diverse constituents, adhering through aberrant interactions that our prior data indicate are nonrandom. To define preferential protein-protein contacts mediating aggre...

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Autores principales: Balasubramaniam, Meenakshisundaram, Ayyadevara, Srinivas, Ganne, Akshatha, Kakraba, Samuel, Penthala, Narsimha Reddy, Du, Xiuxia, Crooks, Peter A., Griffin, Sue T., Shmookler Reis, Robert J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6817627/
https://www.ncbi.nlm.nih.gov/pubmed/31593839
http://dx.doi.org/10.1016/j.isci.2019.09.026
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author Balasubramaniam, Meenakshisundaram
Ayyadevara, Srinivas
Ganne, Akshatha
Kakraba, Samuel
Penthala, Narsimha Reddy
Du, Xiuxia
Crooks, Peter A.
Griffin, Sue T.
Shmookler Reis, Robert J.
author_facet Balasubramaniam, Meenakshisundaram
Ayyadevara, Srinivas
Ganne, Akshatha
Kakraba, Samuel
Penthala, Narsimha Reddy
Du, Xiuxia
Crooks, Peter A.
Griffin, Sue T.
Shmookler Reis, Robert J.
author_sort Balasubramaniam, Meenakshisundaram
collection PubMed
description Diagnosis of neurodegenerative diseases hinges on “seed” proteins detected in disease-specific aggregates. These inclusions contain diverse constituents, adhering through aberrant interactions that our prior data indicate are nonrandom. To define preferential protein-protein contacts mediating aggregate coalescence, we created click-chemistry reagents that cross-link neighboring proteins within human, APP(Sw)-driven, neuroblastoma-cell aggregates. These reagents incorporate a biotinyl group to efficiently recover linked tryptic-peptide pairs. Mass-spectroscopy outputs were screened for all possible peptide pairs in the aggregate proteome. These empirical linkages, ranked by abundance, implicate a protein-adherence network termed the “aggregate contactome.” Critical hubs and hub-hub interactions were assessed by RNAi-mediated rescue of chemotaxis in aging nematodes, and aggregation-driving properties were inferred by multivariate regression and neural-network approaches. Aspirin, while disrupting aggregation, greatly simplified the aggregate contactome. This approach, and the dynamic model of aggregate accrual it implies, reveals the architecture of insoluble-aggregate networks and may reveal targets susceptible to interventions to ameliorate protein-aggregation diseases.
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spelling pubmed-68176272019-10-31 Aggregate Interactome Based on Protein Cross-linking Interfaces Predicts Drug Targets to Limit Aggregation in Neurodegenerative Diseases Balasubramaniam, Meenakshisundaram Ayyadevara, Srinivas Ganne, Akshatha Kakraba, Samuel Penthala, Narsimha Reddy Du, Xiuxia Crooks, Peter A. Griffin, Sue T. Shmookler Reis, Robert J. iScience Article Diagnosis of neurodegenerative diseases hinges on “seed” proteins detected in disease-specific aggregates. These inclusions contain diverse constituents, adhering through aberrant interactions that our prior data indicate are nonrandom. To define preferential protein-protein contacts mediating aggregate coalescence, we created click-chemistry reagents that cross-link neighboring proteins within human, APP(Sw)-driven, neuroblastoma-cell aggregates. These reagents incorporate a biotinyl group to efficiently recover linked tryptic-peptide pairs. Mass-spectroscopy outputs were screened for all possible peptide pairs in the aggregate proteome. These empirical linkages, ranked by abundance, implicate a protein-adherence network termed the “aggregate contactome.” Critical hubs and hub-hub interactions were assessed by RNAi-mediated rescue of chemotaxis in aging nematodes, and aggregation-driving properties were inferred by multivariate regression and neural-network approaches. Aspirin, while disrupting aggregation, greatly simplified the aggregate contactome. This approach, and the dynamic model of aggregate accrual it implies, reveals the architecture of insoluble-aggregate networks and may reveal targets susceptible to interventions to ameliorate protein-aggregation diseases. Elsevier 2019-09-21 /pmc/articles/PMC6817627/ /pubmed/31593839 http://dx.doi.org/10.1016/j.isci.2019.09.026 Text en http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Balasubramaniam, Meenakshisundaram
Ayyadevara, Srinivas
Ganne, Akshatha
Kakraba, Samuel
Penthala, Narsimha Reddy
Du, Xiuxia
Crooks, Peter A.
Griffin, Sue T.
Shmookler Reis, Robert J.
Aggregate Interactome Based on Protein Cross-linking Interfaces Predicts Drug Targets to Limit Aggregation in Neurodegenerative Diseases
title Aggregate Interactome Based on Protein Cross-linking Interfaces Predicts Drug Targets to Limit Aggregation in Neurodegenerative Diseases
title_full Aggregate Interactome Based on Protein Cross-linking Interfaces Predicts Drug Targets to Limit Aggregation in Neurodegenerative Diseases
title_fullStr Aggregate Interactome Based on Protein Cross-linking Interfaces Predicts Drug Targets to Limit Aggregation in Neurodegenerative Diseases
title_full_unstemmed Aggregate Interactome Based on Protein Cross-linking Interfaces Predicts Drug Targets to Limit Aggregation in Neurodegenerative Diseases
title_short Aggregate Interactome Based on Protein Cross-linking Interfaces Predicts Drug Targets to Limit Aggregation in Neurodegenerative Diseases
title_sort aggregate interactome based on protein cross-linking interfaces predicts drug targets to limit aggregation in neurodegenerative diseases
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6817627/
https://www.ncbi.nlm.nih.gov/pubmed/31593839
http://dx.doi.org/10.1016/j.isci.2019.09.026
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