A high content imaging-based approach for classifying cellular phenotypes

Joseph J. Kim, Sebastian Vega Fuentes, Prabhas V. Moghe

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Scopus citations

Abstract

Current methods to characterize cell-biomaterial interactions are population-based and rely on imaging or biochemical analysis of end-point biological markers. The analysis of stem cells in cultures is further challenged by the heterogeneous nature and divergent fates of stem cells, especially in complex, engineered microenvironments. Here, we describe a high content imaging-based platform capable of identifying cell subpopulations based on cell phenotype-specific morphological descriptors. This method can be utilized to identify microenvironment-responsive morphological descriptors, which can be used to parse cells from a heterogeneous cell population based on emergent phenotypes at the single-cell level and has been successfully deployed to forecast long-term cell lineage fates and screen regenerative phenotype-prescriptive biomaterials.

Original languageEnglish (US)
Title of host publicationImaging and Tracking Stem Cells
Subtitle of host publicationMethods and Protocols
Pages41-48
Number of pages8
DOIs
StatePublished - Sep 4 2013

Publication series

NameMethods in Molecular Biology
Volume1052
ISSN (Print)1064-3745

All Science Journal Classification (ASJC) codes

  • Molecular Biology
  • Genetics

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