Single-cell image analysis to explore cell-to-cell heterogeneity in isogenic populations
| Autor: | Mojca Mattiazzi Usaj, Brenda J. Andrews, Clarence Hue Lok Yeung, Helena Friesen, Charles Boone |
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| Rok vydání: | 2020 |
| Předmět: |
0303 health sciences
Histology Genetic heterogeneity Cell Cell Biology Computational biology Biology Phenotype Article Pathology and Forensic Medicine Image (mathematics) 03 medical and health sciences Multicellular organism 0302 clinical medicine medicine.anatomical_structure Biological Variation Population Microscopy Fluorescence High-content screening medicine Single-Cell Analysis 030217 neurology & neurosurgery Function (biology) 030304 developmental biology |
| Zdroj: | Cell Syst |
| ISSN: | 2405-4720 |
| Popis: | Single-cell image analysis provides a powerful approach for studying cell-to-cell heterogeneity, which is an important attribute of isogenic cell populations, from microbial cultures to individual cells in multicellular organisms. This phenotypic variability must be explained at a mechanistic level if biologists are to fully understand cellular function and address the genotype-to-phenotype relationship. Variability in single-cell phenotypes is obscured by bulk readouts or averaging of phenotypes from individual cells in a sample; thus, single-cell image analysis enables a higher resolution view of cellular function. Here, we consider examples of both small- and large-scale studies carried out with isogenic cell populations assessed by fluorescence microscopy, and we illustrate the advantages, challenges, and the promise of quantitative single-cell image analysis. |
| Databáze: | OpenAIRE |
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