Description

Driven by an increasing number of studies demonstrating its relevance to a broad variety of disease states, the bioenergy production phenotype has been widely characterized at the bulk sample level. Its cell-to-cell variability, a key player associated with cancer cell

Driven by an increasing number of studies demonstrating its relevance to a broad variety of disease states, the bioenergy production phenotype has been widely characterized at the bulk sample level. Its cell-to-cell variability, a key player associated with cancer cell survival and recurrence, however, remains poorly understood due to ensemble averaging of the current approaches. We present a technology platform for performing oxygen consumption and extracellular acidification measurements of several hundreds to 1,000 individual cells per assay, while offering simultaneous analysis of cellular communication effects on the energy production phenotype. The platform comprises two major components: a tandem optical sensor for combined oxygen and pH detection, and a microwell device for isolation and analysis of single and few cells in hermetically sealed sub-nanoliter chambers. Our approach revealed subpopulations of cells with aberrant energy production profiles and enables determination of cellular response variability to electron transfer chain inhibitors and ion uncouplers.

Reuse Permissions
  • Downloads
    PDF (1.8 MB)

    Details

    Title
    • A Platform for High-Throughput Bioenergy Production Phenotype Characterization in Single Cells
    Contributors
    Date Created
    2017-03-28
    Resource Type
  • Text
  • Collections this item is in
    Identifier
    • Digital object identifier: 10.1038/srep45399
    • Identifier Type
      International standard serial number
      Identifier Value
      2045-2322
    Note
    • The final version of this article, as published in Scientific Reports, can be viewed online at: https://www.nature.com/articles/srep45399

    Citation and reuse

    Cite this item

    This is a suggested citation. Consult the appropriate style guide for specific citation guidelines.

    Kelbauskas, L., Glenn, H., Anderson, C., Messner, J., Lee, K. B., Song, G., . . . Meldrum, D. R. (2017). A platform for high-throughput bioenergy production phenotype characterization in single cells. Scientific Reports, 7, 45399. doi:10.1038/srep45399

    Machine-readable links