bioRxivNeurosciencePreprint
The Alzheimer’s disease associated bacterial protease RgpB from P. gingivalis activates the alternative β-secretase meprin β thereby increasing Aβ generation
Fred ArmbrustiD, Cynthia Colmorgen, Claus U. PietrzikiD, Christoph Becker‐PaulyiD
Abstract
Alzheimers disease (AD) is the most common type of dementia and characterized by tau hyperphosphorylation, oxidative stress, reactive microglia and amyloid-{beta} (A{beta}) deposits. A recent study revealed that Porphyromonas gingivalis infection is associated with amyloid {beta} generation in Alzheimers disease. Increased A{beta} levels, tau degradation and neuronal toxicity were observed as a consequence of ginigipain R (RgpB) activity, a cysteine protease constitutively secreted by P. gingivalis. Of note, we previously identified RgpB as a potent activator of the metalloproteinase meprin {beta}. Interestingly, meprin {beta} is an alternative {beta}-secretase of the amyloid precursor protein (APP), which together with the {gamma}-secretase leads to the generation of aggregation-prone N-terminally truncated A{beta}2-x peptides. Importantly, identification of a risk gene variant of meprin {beta} (rs173032) for Alzheimers disease using whole-exome sequencing of the BDR cohort further supports the impact of this alternative {beta}-secretase. Thus, we wondered if increased A{beta} levels as a consequence of P. gingivalis colonization into the brain might be due to meprin {beta} activation by RgpB. Here, we demonstrate that i) upon incubation with RgpB the proteolytic activity of meprin {beta} at the cell surface of transfected HEK cells or of endogenously expressed enzyme in SH-SY5Y neuroblastoma cells was significantly increased, and that ii) RgpB-mediated increase in meprin {beta} activity leads to massive generation of A{beta}-peptides. In conclusion, our findings would further explain the pathogenesis of P. gingivalis in AD brain.
- organism: human
- assay: proteomics
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: variant effect prediction
- research focus: protein structure prediction
- approach: statistical model
- Citations
- 7
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