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Kristiana, Kandere-Grzybowska
첨단연성물질 연구단
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Protocol and Software for Automated Detection of Lysosome Active “Runs” and “Flights” with Wavelet Transform Approach

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Title
Protocol and Software for Automated Detection of Lysosome Active “Runs” and “Flights” with Wavelet Transform Approach
Author(s)
Kristiana, Kandere-Grzybowska; Konstantin Polev; Diana KOLYGINA; Bartosz Andrzej Grzybowski
Publication Date
2022-12
Journal
Methods in Molecular Biology, Springer Protocols, pp.171 - 195
Publisher
Springer Protocols
Abstract
Lysosomes are highly dynamic degradation/recycling organelles that harbor sophisticated molecular sensors and signal transduction machinery through which they control cell adaptation to environmental cues and nutrients. The movements of these signaling hubs comprise persistent, directional runs—active, ATP-dependent transport along the microtubule tracks—interspersed by short, passive movements and pauses imposed by cytoplasmic constraints. The trajectories of individual lysosomes are usually obtained by time-lapse imaging of the acidic organelles labeled with LysoTracker dyes or fluorescently-tagged lysosomal-associated membrane proteins LAMP1 and LAMP2. Subsequent particle tracking generates large data sets comprising thousands of lysosome trajectories and hundreds of thousands of data points. Analyzing such data sets requires unbiased, automated methods to handle large data sets while capturing the temporal heterogeneity of lysosome trajectory data. This chapter describes integrated and largely automated workflow from live cell imaging to lysosome trajectories to computing the parameters of lysosome dynamics. We describe an open-source code for implementing the continuous wavelet transform (CWT) to distinguish trajectory segments corresponding to active transport (i.e., “runs” and “flights”) versus passive lysosome movements. Complementary cumulative distribution functions (CDFs) of the “runs/flights” are generated, and Akaike weight comparisons with several competing models (lognormal, power law, truncated power law, stretched exponential, exponential) are performed automatically. Such high-throughput analyses yield useful aggregate/ensemble metrics for lysosome active transport.
URI
https://pr.ibs.re.kr/handle/8788114/13283
ISBN
978-1-0716-2810-2
Appears in Collections:
Center for Soft and Living Matter(첨단연성물질 연구단) > 2. Books & Book Chapters (저역서)
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