Multistep Track Segmentation and Motion Classification for Transient Mobility Analysis

Anthony R. Vega, Spencer A. Freeman, Sergio Grinstein, Khuloud Jaqaman

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

Molecular interactions are often transient and might change within the window of observation, leading to changes in molecule movement. Therefore, accurate motion analysis often requires transient motion classification. Here we present an accurate and computationally efficient transient mobility analysis framework, termed “divide-and-conquer moment scaling spectrum” (DC-MSS). DC-MSS works in a multistep fashion: 1) it utilizes a local movement descriptor throughout a track to divide it into initial segments of putatively different motion classes; 2) it classifies these segments via moment scaling spectrum (MSS) analysis of molecule displacements; and 3) it uses the MSS analysis results to refine the track segmentation. This strategy uncouples the initial identification of motion switches from motion classification, allowing DC-MSS to circumvent the sensitivity-accuracy tradeoff of classic rolling window approaches for transient motion analysis, while at the same time harnessing the classification power of MSS analysis. Testing of DC-MSS demonstrates that it detects switches among free diffusion, confined diffusion, directed diffusion, and immobility with great sensitivity. To illustrate the utility of DC-MSS, we have applied it to single-particle tracks of the transmembrane protein CD44 on the surface of macrophages, revealing actin cortex-dependent transient mobility changes.

Original languageEnglish (US)
Pages (from-to)1018-1025
Number of pages8
JournalBiophysical Journal
Volume114
Issue number5
DOIs
Publication statusPublished - Mar 13 2018

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ASJC Scopus subject areas

  • Biophysics

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