Literature DB >> 31602624

Advanced Yeast Models of Familial Alzheimer Disease Expressing FAD-Linked Presenilin to Screen Mutations and γ-Secretase Modulators.

Eugene Futai1.   

Abstract

γ-Secretase is a multisubunit membrane protein complex containing catalytic presenilin (PS1 or PS2) and cofactors such as nicastrin, Aph-1, and Pen2. γ-Secretase hydrolyzes the transmembrane domains of type-I membrane proteins, which include the amyloid precursor protein (APP). APP is cleaved by γ-secretase to produce amyloid β peptide (Aβ), which is deposited in the brains of Alzheimer disease patients. However, the mechanism of this unusual proteolytic process within the lipid bilayer remains unknown. We have established a yeast transcriptional activator Gal4p system with artificial γ-secretase substrates containing APP or Notch fragments to examine the enzymatic properties of γ-secretase. The γ-secretase activities were evaluated by transcriptional activation of reporter genes upon Gal4 release from the membrane bound substrates as assessed by growth of yeast or β-galactosidase assay. We also established an in vitro yeast microsome assay system which identified different Aβ species produced by trimming. The yeast system allows for the screening of mutations and chemicals that inhibit or modulate γ-secretase activity. Herein we describe the genetic and biochemical methods used to analyze γ-secretase activity using the yeast reconstitution system. By studying the loss-of-function properties of PS1 mutants, it is possible to successfully screen FAD suppressor mutations and identify γ-secretase modulators (GSMs), which are promising Alzheimer disease therapeutic agents.

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Keywords:  Alzheimer disease; Amyloid β; Budding yeast; Intramembrane proteolysis; Saccharomyces cerevisiae; γ-Secretase

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Year:  2019        PMID: 31602624     DOI: 10.1007/978-1-4939-9736-7_23

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  1 in total

1.  Specific Mutations in Aph1 Cause γ-Secretase Activation.

Authors:  Hikari Watanabe; Chika Yoshida; Masafumi Hidaka; Tomohisa Ogawa; Taisuke Tomita; Eugene Futai
Journal:  Int J Mol Sci       Date:  2022-01-03       Impact factor: 5.923

  1 in total

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