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

ABSTRACT: 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 MAPT ^P301S 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.

SUBMITTER: Tsumagari K

PROVIDER: S-EPMC9382322 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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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]

PMID: 35992067

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Project description:BACKGROUND: Biological networks characterize the interactions of biomolecules at a systems-level. One important property of biological networks is the modular structure, in which nodes are densely connected with each other, but between which there are only sparse connections. In this report, we attempted to find the relationship between the network topology and formation of modular structure by comparing gene co-expression networks with random networks. The organization of gene functional modules was also investigated. RESULTS: We constructed a genome-wide Arabidopsis gene co-expression network (AGCN) by using 1094 microarrays. We then analyzed the topological properties of AGCN and partitioned the network into modules by using an efficient graph clustering algorithm. In the AGCN, 382 hub genes formed a clique, and they were densely connected only to a small subset of the network. At the module level, the network clustering results provide a systems-level understanding of the gene modules that coordinate multiple biological processes to carry out specific biological functions. For instance, the photosynthesis module in AGCN involves a very large number (> 1000) of genes which participate in various biological processes including photosynthesis, electron transport, pigment metabolism, chloroplast organization and biogenesis, cofactor metabolism, protein biosynthesis, and vitamin metabolism. The cell cycle module orchestrated the coordinated expression of hundreds of genes involved in cell cycle, DNA metabolism, and cytoskeleton organization and biogenesis. We also compared the AGCN constructed in this study with a graphical Gaussian model (GGM) based Arabidopsis gene network. The photosynthesis, protein biosynthesis, and cell cycle modules identified from the GGM network had much smaller module sizes compared with the modules found in the AGCN, respectively. CONCLUSION: This study reveals new insight into the topological properties of biological networks. The preferential hub-hub connections might be necessary for the formation of modular structure in gene co-expression networks. The study also reveals new insight into the organization of gene functional modules.

Project description:Considering the complicated pathogenesis of Alzheimer's disease (AD), multi-targets have become a focus in the discovery of drugs for treatment of this disease. In the current work, we established a multi-target strategy for discovering active reagents capable of suppressing both Aβ level and Tau hyperphosphorylation from natural products, and found that the ethanol extract of Thamnolia vermicularis (THA) was able to improve learning ability in APP/PS1 transgenic mice by inhibiting both Aβ levels and Tau hyperphosphorylation. SH-SY5Y and CHO-APP/BACE1 cells and primary astrocytes were used in cell-based assays. APP/PS1 transgenic mice [B6C3-Tg(APPswe, PS1dE9)] were administered THA (300 mg·kg-1·d-1, ig) for 100 d. After the administration was completed, the learning ability of the mice was detected using a Morris water maze (MWM) assay; immunofluorescence staining, Congo red staining and Thioflavine S staining were used to detect the senile plaques in the brains of the mice. ELISA was used to evaluate Aβ and sAPPβ contents, and Western blotting and RT-PCR were used to investigate the relevant signaling pathway regulation in response to THA treatment. In SH-SY5Y cells, THΑ (1, 10, 20 μg/mL) significantly stimulated PI3K/AKT/mTOR and AMPK/raptor/mTOR signaling-mediated autophagy in the promotion of Aβ clearance as both a PI3K inhibitor and an AMPK indirect activator, and restrained Aβ production as a suppressor against PERK/eIF2α-mediated BACE1 expression. Additionally, THA functioned as a GSK3β inhibitor with an IC50 of 1.32±0.85 μg/mL, repressing Tau hyperphosphorylation. Similar effects on Aβ accumulation and Tau hyperphosphorylation were observed in APP/PS1 transgenic mice treated with THA. Furthermore, administration of THA effectively improved the learning ability of APP/PS1 transgenic mice, and markedly reduced the number of senile plaques in their hippocampus and cortex. The results highlight the potential of the natural product THA for the treatment of AD.

Dataset Information

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

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

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