Image-Based Tracking of Heterogeneous Single-Cell Phenotypes
| Autor: | Daniel Ruderman, Katherin Patsch, Shannon M. Mumenthaler |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Cell signaling Computer science Cell Gene Expression Mitosis Computational biology Tracking (particle physics) Article Cell Line 03 medical and health sciences Genes Reporter Live cell imaging Image Processing Computer-Assisted medicine Humans Segmentation Computational Biology Filter (signal processing) Phenotype Pipeline (software) 030104 developmental biology medicine.anatomical_structure Microscopy Fluorescence Nuclear receptor Cell Tracking Cell culture Single-Cell Analysis Biomarkers |
| Zdroj: | Cellular Heterogeneity ISBN: 9781493976799 Methods Mol Biol |
| Popis: | Cells display broad heterogeneity across multiple phenotypic features, including motility, morphology, and cell signaling. Live-cell imaging techniques are beginning to capture the importance and interdependence of these phenomena. However, existing image analysis pipelines often fail to capture the intricate changes that occur in small subpopulations, either due to poor segmentation protocols or cell tracking errors. Here we report a pipeline designed to image and track single-cell dynamic phenotypes in heterogeneous cell populations. We provide step-by-step instructions for three phenotypically different cell lines across two time scales as well as recommendations for adaptation to custom data sets. Our protocols include steps for quality control that can be used to filter out erroneous tracks and improve assessment of heterogeneity. We demonstrate possible phenotypic readouts including motility, nuclear receptor translocation, and mitosis. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|