Unknown

Dataset Information

0

CycleTrak: a novel system for the semi-automated analysis of cell cycle dynamics.


ABSTRACT: Cell proliferation is crucial to tissue growth and form during embryogenesis, yet dynamic tracking of cell cycle progression and cell position presents a challenging roadblock. We have developed a fluorescent cell cycle indicator and single cell analysis method, called CycleTrak, which allows for better spatiotemporal resolution and quantification of cell cycle phase and cell position than current methods. Our method was developed on the basis of the existing Fucci method. CycleTrak uses a single lentiviral vector that integrates mKO2-hCdt1 (30/120), and a nuclear-localized eGFP reporter. The single vector and nuclear localized fluorescence signals simplify delivery into cells and allow for rapid, automated cell tracking and cell cycle phase readout in single and subpopulations of cells. We validated CycleTrak performance in metastatic melanoma cells and identified novel cell cycle dynamics in vitro and in vivo after transplantation and 3D confocal time-lapse imaging in a living chick embryo.

SUBMITTER: Ridenour DA 

PROVIDER: S-EPMC3322266 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature

altmetric image

Publications

CycleTrak: a novel system for the semi-automated analysis of cell cycle dynamics.

Ridenour Dennis A DA   McKinney Mary Cathleen MC   Bailey Caleb M CM   Kulesa Paul M PM  

Developmental biology 20120225 1


Cell proliferation is crucial to tissue growth and form during embryogenesis, yet dynamic tracking of cell cycle progression and cell position presents a challenging roadblock. We have developed a fluorescent cell cycle indicator and single cell analysis method, called CycleTrak, which allows for better spatiotemporal resolution and quantification of cell cycle phase and cell position than current methods. Our method was developed on the basis of the existing Fucci method. CycleTrak uses a singl  ...[more]

Similar Datasets

| S-EPMC6928233 | biostudies-literature
2022-12-01 | GSE205417 | GEO
| S-EPMC9316907 | biostudies-literature
| S-EPMC9360406 | biostudies-literature
| S-EPMC3478691 | biostudies-literature
| S-EPMC9277997 | biostudies-literature
2024-10-18 | MSV000096132 | MassIVE
| S-EPMC5800540 | biostudies-literature
| S-EPMC3696430 | biostudies-literature
| S-EPMC3840952 | biostudies-literature