Proteomics

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Proteomics of human tau-transgenic mice reveals protein modules associated with tau pathologies


ABSTRACT: Abnormally accumulated tau protein aggregates are one of the hallmarks of dementia, including Alzheimer’s disease (AD), and are believed to play a critical role in neurodegeneration. In order to investigate proteomic alteration driven by tau aggregates, we implemented quantitative proteomics to analyze disease model mice expressing human MAPTP301S transgene (hTau-Tg) and quantified more than 9,000 proteins in total. We applied the weighted gene co-expression analysis (WGCNA) algorithm to the datasets and explored protein co-expression modules that were associated with the accumulation of tau aggregates and were preserved in proteomes of AD brains. This led us to identify four modules with functions related to neuroinflammatory responses, mitochondrial energy production processes (including the tricarboxylic acid cycle and oxidative phosphorylation), cholesterol biosynthesis, and postsynaptic density. Furthermore, a phosphoproteomics study uncovered phosphorylation sites that were highly correlated with these modules. Our datasets represent resources for understanding the molecular basis of tau-induced neurodegeneration, including AD.

ORGANISM(S): Mus Musculus (mouse)

SUBMITTER: Junro Kuromitsu 

PROVIDER: PXD031129 | JPOST Repository | Tue Jul 05 00:00:00 BST 2022

REPOSITORIES: jPOST

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Co-expression network analysis of human tau-transgenic mice reveals protein modules associated with tau-induced pathologies.

Tsumagari Kazuya K   Sato Yoshiaki Y   Shimozawa Aki A   Aoyagi Hirofumi H   Okano Hideyuki H   Kuromitsu Junro J  

iScience 20220805 8


Abnormally accumulated tau protein aggregates are one of the hallmarks of neurodegenerative diseases, including Alzheimer's disease (AD). In order to investigate proteomic alteration driven by tau aggregates, we implemented quantitative proteomics to analyze disease model mice expressing human <i>MAPT</i> <sup>P301S</sup> transgene (hTau-Tg) and quantified more than 9,000 proteins in total. We applied the weighted gene co-expression analysis (WGCNA) algorithm to the datasets and explored protein  ...[more]