کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
2039449 1073057 2015 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Machine-Learning-Based Analysis in Genome-Edited Cells Reveals the Efficiency of Clathrin-Mediated Endocytosis
ترجمه فارسی عنوان
تجزیه و تحلیل مبتنی بر ماشین های یادگیری در سلول های اصلاح ژن نشان دهنده کارایی اندوسیتوز شده توسط کلاتین
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک علوم کشاورزی و بیولوژیک (عمومی)
چکیده انگلیسی


• Authentic endocytic sites were identified by genome editing and machine learning
• Authentic endocytic sites (clathrin and AP2 positive) almost always form vesicles
• Authentic endocytic sites mature steadily and have limited mobility
• False endocytic sites have a dynamic signature distinct from authentic sites

SummaryCells internalize various molecules through clathrin-mediated endocytosis (CME). Previous live-cell imaging studies suggested that CME is inefficient, with about half of the events terminated. These CME efficiency estimates may have been confounded by overexpression of fluorescently tagged proteins and inability to filter out false CME sites. Here, we employed genome editing and machine learning to identify and analyze authentic CME sites. We examined CME dynamics in cells that express fluorescent fusions of two defining CME proteins, AP2 and clathrin. Support vector machine classifiers were built to identify and analyze authentic CME sites. From inception until disappearance, authentic CME sites contain both AP2 and clathrin, have the same degree of limited mobility, continue to accumulate AP2 and clathrin over lifetimes >∼20 s, and almost always form vesicles as assessed by dynamin2 recruitment. Sites that contain only clathrin or AP2 show distinct dynamics, suggesting they are not part of the CME pathway.

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ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: - Volume 12, Issue 12, 29 September 2015, Pages 2121–2130
نویسندگان
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