Machine-Learning-Based Analysis in Genome-Edited Cells Reveals the Efficiency of Clathrin-Mediated Endocytosis.

Cell Rep

Department of Molecular and Cell Biology, University of California-Berkeley, Berkeley, CA 94720, USA. Electronic address:

Published: September 2015

AI Article Synopsis

  • Cells use clathrin-mediated endocytosis (CME) to internalize molecules, but previous studies indicated that it might be inefficient due to high termination rates of CME events.
  • Researchers utilized genome editing and machine learning to precisely identify and analyze genuine CME sites, avoiding confounding factors of prior methods.
  • Their findings revealed that authentic CME sites consistently contain both AP2 and clathrin, exhibit similar limited mobility, and are more stable over time, forming vesicles as indicated by dynamin2 recruitment.

Article Abstract

Cells 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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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4610353PMC
http://dx.doi.org/10.1016/j.celrep.2015.08.048DOI Listing

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