Journal
JOURNAL OF BIOMOLECULAR SCREENING
Volume 21, Issue 9, Pages 887-896Publisher
SAGE PUBLICATIONS INC
DOI: 10.1177/1087057116652064
Keywords
live imaging; CellProfiler; HipDynamics; iPSC; high-content screening
Funding
- Wellcome Trust
- Medical Research Council
- National Institute for Health Research (NIHR) Biomedical Research studentship from the NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London
- Arthritis Research UK
- British Heart Foundation
- Cancer Research UK
- Chief Scientist Office
- Economic and Social Research Council
- Engineering and Physical Sciences Research Council
- National Institute for Health Research
- National Institute for Social Care and Health Research
- Wellcome Trust [MR/K006584/1]
- MRC [MC_PC_12026, MR/K026666/1] Funding Source: UKRI
- Medical Research Council [MR/K006584/1, MC_PC_12026, MR/K026666/1, MR/L022699/1] Funding Source: researchfish
Ask authors/readers for more resources
Most image analysis pipelines rely on multiple channels per image with subcellular reference points for cell segmentation. Single-channel phase-contrast images are often problematic, especially for cells with unfavorable morphology, such as induced pluripotent stem cells (iPSCs). Live imaging poses a further challenge, because of the introduction of the dimension of time. Evaluations cannot be easily integrated with other biological data sets including analysis of endpoint images. Here, we present a workflow that incorporates a novel CellProfiler-based image analysis pipeline enabling segmentation of single-channel images with a robust R-based software solution to reduce the dimension of time to a single data point. These two packages combined allow robust segmentation of iPSCs solely on phase-contrast single-channel images and enable live imaging data to be easily integrated to endpoint data sets while retaining the dynamics of cellular responses. The described workflow facilitates characterization of the response of live-imaged iPSCs to external stimuli and definition of cell line-specific, phenotypic signatures. We present an efficient tool set for automated high-content analysis suitable for cells with challenging morphology. This approach has potentially widespread applications for human pluripotent stem cells and other cell types.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available