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Pseudophosphorylation of tau at S422 enhances SDS-stable dimer formation and impairs both anterograde and retrograde fast axonal transport. 1.0.0

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charles.hoyt@scai.fraunhofer.de at 2019-02-27 16:23:20.909760
Authors
Rana Aldisi
Contact
charles.hoyt@scai.fraunhofer.de
License
CC BY 4.0
Copyright
Copyright © 2018 Fraunhofer Institute SCAI, All rights reserved.
Number Nodes
15
Number Edges
31
Number Components
1
Network Density
0.147619047619048
Average Degree
2.06666666666667
Number Citations
1
Number BEL Errors
0

Content Statistics

Network Overlap

The node-based overlap between this network and other networks is calculated as the Szymkiewicz-Simpson coefficient of their respective nodes. Up to the top 10 are shown below.

Network Overlap
Tau oligomers and tau toxicity in neurodegenerative disease v1.0.0 40%
Alzheimer’s disease and the autophagic-lysosomal system v1.0.0 40%
Tau oligomers-Cytotoxicity, propagation, and mitochondrial damage v1.0.0 40%
Inert and seed-competent tau monomers suggest structural origins of aggregation v1.0.0 38%
Tau Trimers Are the Minimal Propagation Unit Spontaneously Internalized to Seed Intracellular Aggregation v1.0.0 36%
Tau in physiology and pathology v1.0.0 33%
Tau Modifications v1.9.5 33%
Caenorhabditis elegans models of tauopathy v1.0.0 33%
Estrogen receptor-α is localized to neurofibrillary tangles in Alzheimer's disease v1.0.0 33%
Tau clearance mechanisms and their possible role in the pathogenesis of Alzheimer disease v1.0.0 33%

Sample Edges

p(HGNC:MAPT) hasVariant p(HGNC:MAPT, pmod(Ph)) View Subject | View Object

a(HBP:"Tau aggregates") positiveCorrelation path(MESH:"Alzheimer Disease") View Subject | View Object

The amount of total tau captured with pS422 (detected with the pan-tau antibody, Tau5) was significantly higher in AD compared to control (Fig. 7E; t10 = 6.07, p = 0.0001). The level of pS422 tau that also contained PAD exposed tau (i.e., TNT1 reactive) was significantly higher in AD compared to control (Fig. 7F; t10 = 2.31, p = 0.0435). Similarly, the level of pS422 tau that also contained an oligomeric conformation (i.e., TOC1 reactive) was significantly higher in AD compared to control (Fig. 7G; t10 = 1.51, p = 0.0029). PubMed:27373205

composite(a(HBP:"Tau aggregates"), p(HGNC:MAPT)) hasComponent a(HBP:"Tau aggregates") View Subject | View Object

composite(a(HBP:"Tau aggregates"), p(HGNC:MAPT)) hasComponent p(HGNC:MAPT) View Subject | View Object

composite(a(HBP:"Tau aggregates"), p(HGNC:MAPT)) increases a(HBP:"Tau oligomers") View Subject | View Object

Compared to monomers, aggregation significantly increased PAD exposure for both hT40 and S422E samples (Fig. 3B; F(1,12) = 685.8, p b 0.0001), as indicated by increased TNT1 reactivity. Aggregation also significantly increased oligomer formation (TOC1 reactivity) compared to monomers in both hT40 and S422E samples (Fig. 3C; F(1,12) = 109.3, p b 0.0001). PubMed:27373205

Sample Nodes

path(MESH:"Alzheimer Disease")

In-Edges: 536 | Out-Edges: 704 | Classes: 5 | Explore Neighborhood | Download JSON

p(HGNC:MAPT)

In-Edges: 477 | Out-Edges: 480 | Classes: 11 | Children: 27 | Explore Neighborhood | Download JSON

p(HGNC:MAPT, pmod(Ph))

In-Edges: 201 | Out-Edges: 71 | Classes: 1 | Children: 4 | Explore Neighborhood | Download JSON

bp(GO:"anterograde axonal protein transport")

In-Edges: 26 | Out-Edges: 2 | Explore Neighborhood | Download JSON

a(HBP:"Tau aggregates")

In-Edges: 224 | Out-Edges: 71 | Children: 3 | Explore Neighborhood | Download JSON

About

BEL Commons is developed and maintained in an academic capacity by Charles Tapley Hoyt and Daniel Domingo-Fernández at the Fraunhofer SCAI Department of Bioinformatics with support from the IMI project, AETIONOMY. It is built on top of PyBEL, an open source project. Please feel free to contact us here to give us feedback or report any issues. Also, see our Publishing Notes and Data Protection information.

If you find BEL Commons useful in your work, please consider citing: Hoyt, C. T., Domingo-Fernández, D., & Hofmann-Apitius, M. (2018). BEL Commons: an environment for exploration and analysis of networks encoded in Biological Expression Language. Database, 2018(3), 1–11.