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Super-resolution microscopy reveals majorly mono- and dimeric presenilin1/γ-secretase at the cell surface
eLife ( IF 6.4 ) Pub Date : 2020-07-07 , DOI: 10.7554/elife.56679
Abril Angélica Escamilla-Ayala 1, 2 , Ragna Sannerud 1, 2 , Magali Mondin 3 , Karin Poersch 4 , Wendy Vermeire 1, 2 , Laura Paparelli 1, 2, 5 , Caroline Berlage 6 , Marcelle Koenig 7 , Lucia Chavez-Gutierrez 2, 8 , Maximilian H Ulbrich 9, 10 , Sebastian Munck 2, 5 , Hideaki Mizuno 11 , Wim Annaert 1, 2
Affiliation  

γ-Secretase is a multi-subunit enzyme whose aberrant activity is associated with Alzheimer’s disease and cancer. While its structure is atomically resolved, γ-secretase localization in the membrane in situ relies mostly on biochemical data. Here, we combined fluorescent tagging of γ-secretase subunits with super-resolution microscopy in fibroblasts. Structured illumination microscopy revealed single γ-secretase complexes with a monodisperse distribution and in a 1:1 stoichiometry of PSEN1 and nicastrin subunits. In living cells, sptPALM revealed PSEN1/γ-secretase mainly with directed motility and frequenting ‘hotspots’ or high track-density areas that are sensitive to γ-secretase inhibitors. We visualized γ-secretase association with substrates like amyloid precursor protein and N-cadherin, but not with its sheddases ADAM10 or BACE1 at the cell surface, arguing against pre-formed megadalton complexes. Nonetheless, in living cells PSEN1/γ-secretase transiently visits ADAM10 hotspots. Our results highlight the power of super-resolution microscopy for the study of γ-secretase distribution and dynamics in the membrane.

中文翻译:

超分辨率显微镜显示细胞表面主要是单聚体和二聚体早老素1/γ-分泌酶

γ-分泌酶是一种多亚基酶,其异常活性与阿尔茨海默病和癌症有关。虽然它的结构是原子解析的,但原位膜中的γ-分泌酶定位主要依赖于生化数据。在这里,我们将γ-分泌酶亚基的荧光标记与成纤维细胞中的超分辨率显微镜相结合。结构照明显微镜显示单个 γ-分泌酶复合物具有单分散分布,并且 PSEN1 和 nicastrin 亚基的化学计量比为 1:1。在活细胞中,sptPALM 显示 PSEN1/γ-分泌酶主要具有定向运动性和频繁出现的“热点”或对 γ-分泌酶抑制剂敏感的高轨道密度区域。我们观察了 γ-分泌酶与淀粉样前体蛋白和 N-钙粘蛋白等底物的关联,但不是在细胞表面的 sheddases ADAM10 或 BACE1,反对预先形成的兆道尔顿复合物。尽管如此,在活细胞中,PSEN1/γ-分泌酶会短暂访问 ADAM10 热点。我们的结果突出了超分辨率显微镜在研究膜中 γ-分泌酶分布和动力学方面的能力。
更新日期:2020-07-07
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