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A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations
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Integrating Population Heterogeneity Indices with Microfluidic Cell-Based Assays.

Thomas A Moore1, Alexander Li2, Edmond W K Young1

  • 11 Department of Mechanical & Industrial Engineering, Institute of Biomaterials & Biomedical Engineering, University of Toronto, Toronto, ON, Canada.

SLAS Discovery : Advancing Life Sciences R & D
|October 20, 2017
PubMed
Summary

Pittsburgh Heterogeneity Indices (PHIs) analyze cell population dynamics in microfluidic assays. This study demonstrates PHIs effectively track cellular heterogeneity and determine optimal microfluidic assay population sizes.

Keywords:
cancer and cancer drugscell-based assayschip technology and methodsmicrofluidicsstatistical analyses

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Area of Science:

  • Biotechnology
  • Cell Biology
  • Computational Biology

Background:

  • Single-cell analysis and microfluidics enable high-content, high-throughput cell-based assays.
  • Large datasets from these assays allow for studying cell population dynamics.
  • Statistical analysis of cell populations in microfluidic systems remains underexplored.

Purpose of the Study:

  • To apply Pittsburgh Heterogeneity Indices (PHIs) for statistical analysis of cell population heterogeneity.
  • To understand the evolution of cell population demographics in microfluidic single-cell assays.
  • To investigate the impact of population size on PHIs and traditional readouts in microfluidic systems.

Main Methods:

  • Utilized Pittsburgh Heterogeneity Indices (PHIs) on single-cell resolution data.
  • Applied PHIs to datasets from multiple myeloma cancer cells under drug response and signaling.
  • Examined the effect of varying microfluidic assay population sizes on PHIs and population-averaged metrics.

Main Results:

  • PHIs effectively reveal changing population distributions within microfluidic environments.
  • The study identified minimum population sizes for microfluidic assays without compromising heterogeneity indices.
  • PHIs offer a robust method for analyzing cellular heterogeneity in microfluidic assays.

Conclusions:

  • PHIs are valuable tools for characterizing cell population heterogeneity in microfluidic assays.
  • This research aids in optimizing microfluidic assay design by defining minimum population sizes.
  • The findings support the integration of microfluidics, cell-based assays, and advanced heterogeneity analyses.