Cargando…

Time-Series Clustering of Single-Cell Trajectories in Collective Cell Migration

SIMPLE SUMMARY: In this study, we normalized trajectories containing both mesenchymal and epithelial cells to remove the effect of cell location on clustering, and performed a dimensionality reduction on the time series data before clustering. When the clustering results were superimposed on the tra...

Descripción completa

Detalles Bibliográficos
Autores principales: Xin, Zhuohan, Kajita, Masashi K., Deguchi, Keiko, Suye, Shin-ichiro, Fujita, Satoshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9559181/
https://www.ncbi.nlm.nih.gov/pubmed/36230509
http://dx.doi.org/10.3390/cancers14194587
_version_ 1784807599832563712
author Xin, Zhuohan
Kajita, Masashi K.
Deguchi, Keiko
Suye, Shin-ichiro
Fujita, Satoshi
author_facet Xin, Zhuohan
Kajita, Masashi K.
Deguchi, Keiko
Suye, Shin-ichiro
Fujita, Satoshi
author_sort Xin, Zhuohan
collection PubMed
description SIMPLE SUMMARY: In this study, we normalized trajectories containing both mesenchymal and epithelial cells to remove the effect of cell location on clustering, and performed a dimensionality reduction on the time series data before clustering. When the clustering results were superimposed on the trajectories prior to normalization, the results still showed similarities in location, indicating that this method can find cells with similar migration patterns. These data highlight the reliability of this method in identifying consistent migration patterns in collective cell migration. ABSTRACT: Collective invasion drives multicellular cancer cells to spread to surrounding normal tissues. To fully comprehend metastasis, the methodology of analysis of individual cell migration in tissue should be well developed. Extracting and classifying cells with similar migratory characteristics in a colony would facilitate an understanding of complex cell migration patterns. Here, we used electrospun fibers as the extracellular matrix for the in vitro modeling of collective cell migration, clustering of mesenchymal and epithelial cells based on trajectories, and analysis of collective migration patterns based on trajectory similarity. We normalized the trajectories to eliminate the effect of cell location on clustering and used uniform manifold approximation and projection to perform dimensionality reduction on the time-series data before clustering. When the clustering results were superimposed on the trajectories before normalization, the results still exhibited positional similarity, thereby demonstrating that this method can identify cells with similar migration patterns. The same cluster contained both mesenchymal and epithelial cells, and this result was related to cell location and cell division. These data highlight the reliability of this method in identifying consistent migration patterns during collective cell migration. This provides new insights into the epithelial–mesenchymal interactions that affect migration patterns.
format Online
Article
Text
id pubmed-9559181
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-95591812022-10-14 Time-Series Clustering of Single-Cell Trajectories in Collective Cell Migration Xin, Zhuohan Kajita, Masashi K. Deguchi, Keiko Suye, Shin-ichiro Fujita, Satoshi Cancers (Basel) Article SIMPLE SUMMARY: In this study, we normalized trajectories containing both mesenchymal and epithelial cells to remove the effect of cell location on clustering, and performed a dimensionality reduction on the time series data before clustering. When the clustering results were superimposed on the trajectories prior to normalization, the results still showed similarities in location, indicating that this method can find cells with similar migration patterns. These data highlight the reliability of this method in identifying consistent migration patterns in collective cell migration. ABSTRACT: Collective invasion drives multicellular cancer cells to spread to surrounding normal tissues. To fully comprehend metastasis, the methodology of analysis of individual cell migration in tissue should be well developed. Extracting and classifying cells with similar migratory characteristics in a colony would facilitate an understanding of complex cell migration patterns. Here, we used electrospun fibers as the extracellular matrix for the in vitro modeling of collective cell migration, clustering of mesenchymal and epithelial cells based on trajectories, and analysis of collective migration patterns based on trajectory similarity. We normalized the trajectories to eliminate the effect of cell location on clustering and used uniform manifold approximation and projection to perform dimensionality reduction on the time-series data before clustering. When the clustering results were superimposed on the trajectories before normalization, the results still exhibited positional similarity, thereby demonstrating that this method can identify cells with similar migration patterns. The same cluster contained both mesenchymal and epithelial cells, and this result was related to cell location and cell division. These data highlight the reliability of this method in identifying consistent migration patterns during collective cell migration. This provides new insights into the epithelial–mesenchymal interactions that affect migration patterns. MDPI 2022-09-22 /pmc/articles/PMC9559181/ /pubmed/36230509 http://dx.doi.org/10.3390/cancers14194587 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Xin, Zhuohan
Kajita, Masashi K.
Deguchi, Keiko
Suye, Shin-ichiro
Fujita, Satoshi
Time-Series Clustering of Single-Cell Trajectories in Collective Cell Migration
title Time-Series Clustering of Single-Cell Trajectories in Collective Cell Migration
title_full Time-Series Clustering of Single-Cell Trajectories in Collective Cell Migration
title_fullStr Time-Series Clustering of Single-Cell Trajectories in Collective Cell Migration
title_full_unstemmed Time-Series Clustering of Single-Cell Trajectories in Collective Cell Migration
title_short Time-Series Clustering of Single-Cell Trajectories in Collective Cell Migration
title_sort time-series clustering of single-cell trajectories in collective cell migration
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9559181/
https://www.ncbi.nlm.nih.gov/pubmed/36230509
http://dx.doi.org/10.3390/cancers14194587
work_keys_str_mv AT xinzhuohan timeseriesclusteringofsinglecelltrajectoriesincollectivecellmigration
AT kajitamasashik timeseriesclusteringofsinglecelltrajectoriesincollectivecellmigration
AT deguchikeiko timeseriesclusteringofsinglecelltrajectoriesincollectivecellmigration
AT suyeshinichiro timeseriesclusteringofsinglecelltrajectoriesincollectivecellmigration
AT fujitasatoshi timeseriesclusteringofsinglecelltrajectoriesincollectivecellmigration