PUBLICATION

Automated time-lapse data segmentation reveals in vivo cell state dynamics

Authors
Genuth, M.A., Kojima, Y., Jülich, D., Kiryu, H., Holley, S.A.
ID
ZDB-PUB-230603-31
Date
2023
Source
Science advances   9: eadf1814eadf1814 (Journal)
Registered Authors
Holley, Scott, Jülich, Dörthe
Keywords
none
Datasets
GEO:GSE173894
MeSH Terms
  • Animals
  • Cell Tracking/methods
  • Embryonic Development
  • Time-Lapse Imaging
  • Zebrafish*/metabolism
  • Zebrafish Proteins*/metabolism
PubMed
37267354 Full text @ Sci Adv
Abstract
Embryonic development proceeds as a series of orderly cell state transitions built upon noisy molecular processes. We defined gene expression and cell motion states using single-cell RNA sequencing data and in vivo time-lapse cell tracking data of the zebrafish tailbud. We performed a parallel identification of these states using dimensional reduction methods and a change point detection algorithm. Both types of cell states were quantitatively mapped onto embryos, and we used the cell motion states to study the dynamics of biological state transitions over time. The time average pattern of cell motion states is reproducible among embryos. However, individual embryos exhibit transient deviations from the time average forming left-right asymmetries in collective cell motion. Thus, the reproducible pattern of cell states and bilateral symmetry arise from temporal averaging. In addition, collective cell behavior can be a source of asymmetry rather than a buffer against noisy individual cell behavior.
Genes / Markers
Figures
Show all Figures
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Antibodies
Orthology
Engineered Foreign Genes
Mapping