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charles.hoyt@scai.fraunhofer.de at 2019-02-27 16:23:13.246067
Authors
Rana Aldisi
Contact
charles.hoyt@scai.fraunhofer.de
Description
This file encodes the article Tau Antibody Targeting Pathological Species Blocks Neuronal Uptake and Interneuron Propagation of Tau in Vitro by Nobuhara et. al. 2017
License
CC BY 4.0
Copyright
Copyright © 2018 Fraunhofer Institute SCAI, All rights reserved.
Number Nodes
11
Number Edges
34
Number Components
1
Network Density
0.309090909090909
Average Degree
3.09090909090909
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 Modifications v1.9.5 36%
Tau interactome mapping based identification of Otub1 as Tau deubiquitinase involved in accumulation of pathological Tau forms in vitro and in vivo v1.0.0 36%
Tau clearance mechanisms and their possible role in the pathogenesis of Alzheimer disease v1.0.0 36%
Tau in physiology and pathology v1.0.0 27%
Tau oligomers-Cytotoxicity, propagation, and mitochondrial damage v1.0.0 27%
Imbalances in the Hsp90 Chaperone Machinery: Implications for Tauopathies v1.0.0 27%
Pseudophosphorylation of tau at S422 enhances SDS-stable dimer formation and impairs both anterograde and retrograde fast axonal transport. v1.0.0 27%
Tau oligomers and tau toxicity in neurodegenerative disease v1.0.0 27%
Clearance of Amyloid Beta and Tau in Alzheimer’s Disease:from Mechanisms to Therapy v1.0.1 27%
TAU and Interaction Partners v1.2.5 27%

Sample Edges

a(HBP:"Tau antibody, 40E8") decreases p(MGI:Mapt, loc(GO:cell)) View Subject | View Object

Among the seven antibodies, Tau13 and 6C5 most efficiently removed tau (>85% reduction) from rTg4510 brain extracts on immunodepletion (Figure 2A). HT7 showed an intermediate effect (72% reduction), whereas the other four antibodies (40E8, 4E4, p396, and Tau46) removed only a small fraction of tau (5.6%, 16.6%, 8.4%, and 18% reductions, respectively) (Figure 2A). PubMed:28408124

Annotations
MeSH
Brain
MeSH
Tauopathies
Text Location
Results

a(HBP:"Tau antibody, 40E8") decreases tloc(p(MGI:Mapt), fromLoc(GO:"extracellular region"), toLoc(GO:intracellular)) View Subject | View Object

The 40E8, 4E4, and p396 antibodies also reduced neuronal tau uptake by 40% to 80%, despite their low-immunodepletion efficiency (Figure 2). This finding suggests that they interacted with tau species that are prone to cellular uptake, which account for only a small fraction of all soluble tau species in the brain extract. Notably, Tau46 had little effect on tau uptake (Figure 2, B and C). PubMed:28408124

Annotations
MeSH
Brain
MeSH
Tauopathies
Text Location
Results

a(HBP:"Tau antibody, 40E8") decreases p(HGNC:MAPT, loc(GO:cell)) View Subject | View Object

Tau13, 6C5, and HT7 efficiently depleted tau from the AD HMW fraction (97%, 82%, and 72%, respectively), whereas the other four antibodies (40E8, 4E4, p396, and Tau46) removed only a small fraction of tau (33%, 4.7%, 22%, and 21% reductions, respectively) (Figure 4A). PubMed:28408124

Annotations
MeSH
Alzheimer Disease
Text Location
Results

a(HBP:"Tau antibody, 40E8") decreases tloc(p(HGNC:MAPT), fromLoc(GO:"extracellular region"), toLoc(GO:intracellular)) View Subject | View Object

In the tau uptake assay, 6C5 most effectively reduced tau uptake by immunodepletion (75% reduction) (Figure 4, B and C). Tau13 and HT7 showed intermediate effects (55% and 47% reductions, respectively) (Figure 4, B and C). The 40E8, p396, and 4E4 antibodies also reduced neuronal tau uptake (65%, 53%, and 47% reductions, respectively), despite their low immunodepletion efficiency (Figure 4). PubMed:28408124

Annotations
MeSH
Neurons
MeSH
Alzheimer Disease
Text Location
Results

Sample Nodes

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

a(HBP:"Tau aggregates")

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

p(MGI:Mapt)

In-Edges: 57 | Out-Edges: 59 | Explore Neighborhood | Download JSON

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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.