Mitochondrial apoptosis imaged by high-throughput confocal microscopy.

IF 7.2 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Lina Hellwig, Felix J Meigel, Harald Stachelscheid, Steffen Rulands, Philipp Mergenthaler
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引用次数: 0

Abstract

Mitochondrial programmed cell death (i.e. intrinsic apoptosis) is regulated through the formation of pro-apoptotic protein complexes at the mitochondrial outer membrane (MOM), which permeabilize the MOM and commit the cell to die. This step is modulated by mitochondrial dynamics. To capture this, we treated cells with the mitochondrial dynamics inhibitor M1 before inducing apoptosis with actinomycin D (ActD), and imaged them by high-throughput spinning-disk confocal microscopy. In mouse embryonic fibroblasts (MEFs) we followed apoptosis by long-term live-cell imaging, and in human induced pluripotent stem cells (hiPSCs) we stained fixed cells for the pro-apoptotc protein BAX at mitochondria. Here, we provide a description of these two large-scale microscopy datasets. Dataset 1 contains 637,632 images of MEFs imaged as time series after labelling of mitochondrial morphology and integrity with the mitochondrial membrane potential-sensitive dye tetramethylrhodamine-ethylester (TMRE) and apoptosis with Annexin V-FITC. The dataset also contains a digital phase contrast channel which can be useful to track cells. Dataset 2 contains 9,504 images of hiPSCs with immunofluorescence labelling of BAX and COX IV. The datasets are made available through the BioImage Archive repository.

高通量共聚焦显微镜成像的线粒体凋亡。
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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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