High-content imaging-based screening of microenvironment-induced changes to stem cells

Sebastián L. Vega, Er Liu, Parth J. Patel, Anthony B. Kulesa, Aaron L. Carlson, Yanrui Ma, Matthew L. Becker, Prabhas V. Moghe

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Effective screening methodologies for cells are challenged by the divergent and heterogeneous nature of phenotypes inherent to stem cell cultures, particularly on engineered biomaterial surfaces. In this study, we showcase a high-content, confocal imaging-based methodology to parse single-cell phenotypes by quantifying organizational signatures of specific subcellular reporter proteins and applied this profiling approach to three human stem cell types (embryonic-human embryonic stem cell [hESC], induced pluripotent-induced pluripotent stem cell [iPSC], and mesenchymal-human mesenchymal stem cell [hMSC]). We demonstrate that this method could distinguish self-renewing subpopulations of hESCs and iPSCs from heterogeneous populations. This technique can also provide insights into how incremental changes in biomaterial properties, both physiochemical and mechanical, influence stem cell fates by parsing the organization of stem cell proteins. For example, hMSCs cultured on polymeric films with varying degrees of poly(ethylene glycol) to modulate osteogenic differentiation were parsed using high-content organization of the cytoskeletal protein F-actin. In addition, hMSCs cultured on a self-assembled monolayer platform featuring compositional gradients were screened and descriptors obtained to correlate substrate variations with adipogenic lineage commitment. Taken together, high-content imaging of structurally sensitive proteins can be used as a tool to identify stem cell phenotypes at the single-cell level across a diverse range of culture conditions and microenvironments.

Original languageEnglish (US)
Pages (from-to)1151-1162
Number of pages12
JournalJournal of Biomolecular Screening
Volume17
Issue number9
DOIs
StatePublished - Oct 2012
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Analytical Chemistry
  • Biotechnology
  • Biochemistry
  • Molecular Medicine
  • Pharmacology
  • Drug Discovery

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