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Time dynamics of protein complexes in the AD11 transgenic mouse model for Alzheimer’s disease like pathology

BACKGROUND: Many approaches exist to integrate protein-protein interaction data with other sources of information, most notably with gene co-expression data, to obtain information on network dynamics. It is of interest to look at groups of interacting gene products that form a protein complex. We we...

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Autores principales: Arisi, Ivan, D’Onofrio, Mara, Brandi, Rossella, Cattaneo, Antonino, Bertolazzi, Paola, Cumbo, Fabio, Felici, Giovanni, Guerra, Concettina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4436769/
https://www.ncbi.nlm.nih.gov/pubmed/25925689
http://dx.doi.org/10.1186/s12868-015-0155-5
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author Arisi, Ivan
D’Onofrio, Mara
Brandi, Rossella
Cattaneo, Antonino
Bertolazzi, Paola
Cumbo, Fabio
Felici, Giovanni
Guerra, Concettina
author_facet Arisi, Ivan
D’Onofrio, Mara
Brandi, Rossella
Cattaneo, Antonino
Bertolazzi, Paola
Cumbo, Fabio
Felici, Giovanni
Guerra, Concettina
author_sort Arisi, Ivan
collection PubMed
description BACKGROUND: Many approaches exist to integrate protein-protein interaction data with other sources of information, most notably with gene co-expression data, to obtain information on network dynamics. It is of interest to look at groups of interacting gene products that form a protein complex. We were interested in applying new tools to the characterization of pathogenesis and dynamic events of an Alzheimer’s-like neurodegenerative model, the AD11 mice, expressing an anti-NGF monoclonal antibody. The goal was to quantify the impact of neurodegeneration on protein complexes, by measuring the correlation between gene expression data by different metrics. RESULTS: Data were extracted from the gene expression profile of AD11 brain, obtained by Agilent microarray, at 1, 3, 6, 15 months of age. For genes coding proteins in complexes, the correlation matrix of pairwise expression was computed. The dynamics between correlation matrices at different time points was evaluated: paired T-test between average correlation levels and a normalized Euclidean distance with z-score. We unveiled a differential wiring of interactions in a set of complexes, whose network structure discriminates between transgenic and control mice. Furthermore, we analyzed the dynamics of gene expression values, by looking at changes in gene-to-gene correlation over time and identified those complexes that exhibit a different timedependent behaviour between transgenic and controls. The most significant changes in correlation dynamics are concentrated in the early stage of disease, with higher correlation in AD11 mice compared to controls. Many complexes go through dynamic changes over time, showing the role of the dysfunctional immunoproteasome, as early neurodegenerative disease event. Furthermore, this analysis shows key events in the neurodegeneration process of the AD11 model, by identifying significant differences in co-expression values of other complexes, such as parvulin complex, with a role in protein misfolding and proteostasis, and of complexes involved in transcriptional mechanisms. CONCLUSIONS: We have proposed a novel approach to analyze the network structure of protein complexes, by two different measures to evaluate the dynamics of gene-gene correlation matrices from gene expression profiles. The methodology was able to investigate the re-organization of interactions within protein complexes in the AD11 model of neurodegeneration.
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spelling pubmed-44367692015-05-20 Time dynamics of protein complexes in the AD11 transgenic mouse model for Alzheimer’s disease like pathology Arisi, Ivan D’Onofrio, Mara Brandi, Rossella Cattaneo, Antonino Bertolazzi, Paola Cumbo, Fabio Felici, Giovanni Guerra, Concettina BMC Neurosci Research Article BACKGROUND: Many approaches exist to integrate protein-protein interaction data with other sources of information, most notably with gene co-expression data, to obtain information on network dynamics. It is of interest to look at groups of interacting gene products that form a protein complex. We were interested in applying new tools to the characterization of pathogenesis and dynamic events of an Alzheimer’s-like neurodegenerative model, the AD11 mice, expressing an anti-NGF monoclonal antibody. The goal was to quantify the impact of neurodegeneration on protein complexes, by measuring the correlation between gene expression data by different metrics. RESULTS: Data were extracted from the gene expression profile of AD11 brain, obtained by Agilent microarray, at 1, 3, 6, 15 months of age. For genes coding proteins in complexes, the correlation matrix of pairwise expression was computed. The dynamics between correlation matrices at different time points was evaluated: paired T-test between average correlation levels and a normalized Euclidean distance with z-score. We unveiled a differential wiring of interactions in a set of complexes, whose network structure discriminates between transgenic and control mice. Furthermore, we analyzed the dynamics of gene expression values, by looking at changes in gene-to-gene correlation over time and identified those complexes that exhibit a different timedependent behaviour between transgenic and controls. The most significant changes in correlation dynamics are concentrated in the early stage of disease, with higher correlation in AD11 mice compared to controls. Many complexes go through dynamic changes over time, showing the role of the dysfunctional immunoproteasome, as early neurodegenerative disease event. Furthermore, this analysis shows key events in the neurodegeneration process of the AD11 model, by identifying significant differences in co-expression values of other complexes, such as parvulin complex, with a role in protein misfolding and proteostasis, and of complexes involved in transcriptional mechanisms. CONCLUSIONS: We have proposed a novel approach to analyze the network structure of protein complexes, by two different measures to evaluate the dynamics of gene-gene correlation matrices from gene expression profiles. The methodology was able to investigate the re-organization of interactions within protein complexes in the AD11 model of neurodegeneration. BioMed Central 2015-04-29 /pmc/articles/PMC4436769/ /pubmed/25925689 http://dx.doi.org/10.1186/s12868-015-0155-5 Text en © Arisi et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Arisi, Ivan
D’Onofrio, Mara
Brandi, Rossella
Cattaneo, Antonino
Bertolazzi, Paola
Cumbo, Fabio
Felici, Giovanni
Guerra, Concettina
Time dynamics of protein complexes in the AD11 transgenic mouse model for Alzheimer’s disease like pathology
title Time dynamics of protein complexes in the AD11 transgenic mouse model for Alzheimer’s disease like pathology
title_full Time dynamics of protein complexes in the AD11 transgenic mouse model for Alzheimer’s disease like pathology
title_fullStr Time dynamics of protein complexes in the AD11 transgenic mouse model for Alzheimer’s disease like pathology
title_full_unstemmed Time dynamics of protein complexes in the AD11 transgenic mouse model for Alzheimer’s disease like pathology
title_short Time dynamics of protein complexes in the AD11 transgenic mouse model for Alzheimer’s disease like pathology
title_sort time dynamics of protein complexes in the ad11 transgenic mouse model for alzheimer’s disease like pathology
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4436769/
https://www.ncbi.nlm.nih.gov/pubmed/25925689
http://dx.doi.org/10.1186/s12868-015-0155-5
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