Faculty Opinions recommendation of Live cell imaging of telomerase RNA dynamics reveals cell cycle-dependent clustering of telomerase at elongating telomeres.

2015 ◽  
Author(s):  
Lea Harrington
Keyword(s):  
Cell Cycle ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
Live Cell ◽  
Telomerase Rna ◽  
Rna Dynamics ◽  
Cycle Dependent

scholarly journals Live Cell Imaging of Telomerase RNA Dynamics Reveals Cell Cycle-Dependent Clustering of Telomerase at Elongating Telomeres

2011 ◽  
Vol 44 (5) ◽  
pp. 819-827 ◽  
Author(s):  
Franck Gallardo ◽  
Nancy Laterreur ◽  
Emilio Cusanelli ◽  
Faissal Ouenzar ◽  
Emmanuelle Querido ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
Live Cell ◽  
Telomerase Rna ◽  
Rna Dynamics ◽  
Cycle Dependent

scholarly journals Cell Cycle-dependent Binding of HMGN Proteins to Chromatin

2008 ◽  
Vol 19 (5) ◽  
pp. 1816-1824 ◽  
Author(s):  
Srujana Cherukuri ◽  
Robert Hock ◽  
Tetsuya Ueda ◽  
Frédéric Catez ◽  
Mark Rochman ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
Live Cell ◽  
Bimolecular Fluorescence Complementation ◽  
Chromatin Interaction ◽  
Mitotic Chromosomes ◽  
Mobility Shift ◽  
Immunofluorescence Studies ◽  
Cycle Dependent

Throughout the cell cycle, the histones remain associated with DNA, but the repertoire of proteins associated with the chromatin fiber continuously changes. The chromatin interaction of HMGNs, a family of nucleosome binding proteins that modulates the structure and activity of chromatin, during the cell cycle is controversial. Immunofluorescence studies demonstrated that HMGNs are not associated with chromatin, whereas live cell imaging indicated that they are present in mitotic chromosomes. To resolve this controversy, we examined the organization of wild-type and mutated HMGN1 and HMGN2 proteins in the cell nucleus by using immunofluorescence studies, live cell imaging, gel mobility shift assays, and bimolecular fluorescence complementation (BiFC). We find that during interphase, HMGNs bind specifically to nucleosomes and form homodimeric complexes that yield distinct BiFC signals. In metaphase, the nucleosomal binding domain of the protein is inactivated, and the proteins associate with chromatin with low affinity as monomers, and they do not form specific complexes. Our studies demonstrate that the mode of binding of HMGNs to chromatin is cell cycle dependent.

Cell cycle dependent TN-C promoter activity determined by live cell imaging

2011 ◽  
Vol 79A (3) ◽  
pp. 192-202 ◽  
Author(s):  
Michael Halter ◽  
Daniel R. Sisan ◽  
Joe Chalfoun ◽  
Benjamin L. Stottrup ◽  
Antonio Cardone ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Live Cell Imaging ◽  
Promoter Activity ◽  
Cell Imaging ◽  
Live Cell ◽  
Cycle Dependent

scholarly journals Live-cell imaging to detect phosphatidylserine externalization in brain endothelial cells exposed to ionizing radiation: implications for the treatment of brain arteriovenous malformations

2016 ◽  
Vol 124 (6) ◽  
pp. 1780-1787 ◽  
Author(s):  
Zhenjun Zhao ◽  
Michael S. Johnson ◽  
Biyi Chen ◽  
Michael Grace ◽  
Jaysree Ukath ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Endothelial Cells ◽  
Ionizing Radiation ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
Live Cell ◽  
Vascular Targeting ◽  
Radiation Doses ◽  
Radiation Induced ◽  
Polarity Sensitive

OBJECT Stereotactic radiosurgery (SRS) is an established intervention for brain arteriovenous malformations (AVMs). The processes of AVM vessel occlusion after SRS are poorly understood. To improve SRS efficacy, it is important to understand the cellular response of blood vessels to radiation. The molecular changes on the surface of AVM endothelial cells after irradiation may also be used for vascular targeting. This study investigates radiation-induced externalization of phosphatidylserine (PS) on endothelial cells using live-cell imaging. METHODS An immortalized cell line generated from mouse brain endothelium, bEnd.3 cells, was cultured and irradiated at different radiation doses using a linear accelerator. PS externalization in the cells was subsequently visualized using polarity-sensitive indicator of viability and apoptosis (pSIVA)-IANBD, a polarity-sensitive probe. Live-cell imaging was used to monitor PS externalization in real time. The effects of radiation on the cell cycle of bEnd.3 cells were also examined by flow cytometry. RESULTS Ionizing radiation effects are dose dependent. Reduction in the cell proliferation rate was observed after exposure to 5 Gy radiation, whereas higher radiation doses (15 Gy and 25 Gy) totally inhibited proliferation. In comparison with cells treated with sham radiation, the irradiated cells showed distinct pseudopodial elongation with little or no spreading of the cell body. The percentages of pSIVA-positive cells were significantly higher (p = 0.04) 24 hours after treatment in the cultures that received 25- and 15-Gy doses of radiation. This effect was sustained until the end of the experiment (3 days). Radiation at 5 Gy did not induce significant PS externalization compared with the sham-radiation controls at any time points (p > 0.15). Flow cytometric analysis data indicate that irradiation induced growth arrest of bEnd.3 cells, with cells accumulating in the G2 phase of the cell cycle. CONCLUSIONS Ionizing radiation causes remarkable cellular changes in endothelial cells. Significant PS externalization is induced by radiation at doses of 15 Gy or higher, concomitant with a block in the cell cycle. Radiation-induced markers/targets may have high discriminating power to be harnessed in vascular targeting for AVM treatment.

Live-cell imaging of budding yeast telomerase RNA and TERRA

Methods ◽  
2017 ◽  
Vol 114 ◽  
pp. 46-53 ◽  
Author(s):  
Hadrien Laprade ◽  
Maxime Lalonde ◽  
David Guérit ◽  
Pascal Chartrand
Keyword(s):  
Live Cell Imaging ◽  
Cell Imaging ◽  
Budding Yeast ◽  
Live Cell ◽  
Telomerase Rna ◽  
Yeast Telomerase

scholarly journals Long-term fate of etoposide-induced micronuclei and micronucleated cells in Hela-H2B-GFP cells

2020 ◽  
Vol 94 (10) ◽  
pp. 3553-3561
Author(s):  
Hauke Reimann ◽  
Helga Stopper ◽  
Henning Hintzsche
Keyword(s):  
Cell Cycle ◽  
Cell Death ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
Live Cell ◽  
Cellular Structures ◽  
Death Rates ◽  
Daughter Cells

Abstract Micronuclei are small nuclear cellular structures containing whole chromosomes or chromosomal fragments. While there is a lot of information available about the origin and formation of micronuclei, less is known about the fate of micronuclei and micronucleated cells. Possible fates include extrusion, degradation, reincorporation and persistence. Live cell imaging was performed to quantitatively analyse the fates of micronuclei and micronucleated cells occurring in vitro. Imaging was conducted for up to 96 h in HeLa-H2B-GFP cells treated with 0.5, 1 and 2 µg/ml etoposide. While a minority of micronuclei was reincorporated into the main nucleus during mitosis, the majority of micronuclei persisted without any alterations. Degradation and extrusion were observed rarely or never. The presence of micronuclei affected the proliferation of the daughter cells and also had an influence on cell death rates. Mitotic errors were found to be clearly increased in micronucleus-containing cells. The results show that micronuclei and micronucleated cells can, although delayed in cell cycle, sustain for multiple divisions.

scholarly journals Cell-ACDC: a user-friendly toolset embedding state-of-the-art neural networks for segmentation, tracking and cell cycle annotations of live-cell imaging data

2021 ◽  
Author(s):  
Francesco Padovani ◽  
Benedikt Mairhoermann ◽  
Pascal Falter-Braun ◽  
Jette Lengefeld ◽  
Kurt M Schmoller
Keyword(s):  
Cell Cycle ◽  
Image Analysis ◽  
Deep Learning ◽  
Live Cell Imaging ◽  
Cell Imaging ◽  
State Of The Art ◽  
Single Cells ◽  
Live Cell ◽  
Cell Segmentation ◽  
User Friendly

Live-cell imaging is a powerful tool to study dynamic cellular processes on the level of single cells with quantitative detail. Microfluidics enables parallel high-throughput imaging, creating a downstream bottleneck at the stage of data analysis. Recent progress on deep learning image analysis dramatically improved cell segmentation and tracking. Nevertheless, manual data validation and correction is typically still required and broadly used tools spanning the complete range of live-cell imaging analysis, from cell segmentation to pedigree analysis and signal quantification, are still needed. Here, we present Cell-ACDC, a user-friendly graphical user-interface (GUI)-based framework written in Python, for segmentation, tracking and cell cycle annotation. We included two state-of-the-art and high-accuracy deep learning models for single-cell segmentation of yeast and mammalian cells implemented in the most used deep learning frameworks TensorFlow and PyTorch. Additionally, we developed and implemented a cell tracking method and embedded it into an intuitive, semi-automated workflow for label-free cell cycle annotation of single cells. The open-source and modularized nature of Cell-ACDC will enable simple and fast integration of new deep learning-based and traditional methods for cell segmentation or downstream image analysis. Source code: https://github.com/SchmollerLab/Cell_ACDC

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