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Related Experiment Video

Updated: May 23, 2026

Simultaneous Assessment of Kinship, Division Number, and Phenotype via Flow Cytometry for Hematopoietic Stem and Progenitor Cells

Simultaneous Assessment of Kinship, Division Number, and Phenotype via Flow Cytometry for Hematopoietic Stem and Progenitor Cells

Published on: March 24, 2023

Method for physiologic phenotype characterization at the single-cell level in non-interacting and interacting cells.

Laimonas Kelbauskas¹, Shashanka P Ashili, Jeff Houkal

¹Arizona State University, Biodesign Institute, Tempe, Arizona, USA. lkelbaus@asu.edu

Journal of Biomedical Optics

|April 17, 2012

Summary

This study introduces a novel platform for measuring individual cell oxygen consumption rates (OCRs) under various conditions. The technology enables detailed analysis of cellular respiration and cell-to-cell interactions, advancing single-cell metabolic studies.

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A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Published on: October 25, 2018

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Last Updated: May 23, 2026

Simultaneous Assessment of Kinship, Division Number, and Phenotype via Flow Cytometry for Hematopoietic Stem and Progenitor Cells

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Published on: March 24, 2023

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A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

A Combinatorial Single-cell Approach to Characterize the Molecular and Immunophenotypic Heterogeneity of Human Stem and Progenitor Populations

Published on: October 25, 2018

Area of Science:

Cell Biology
Metabolic Engineering
Biomedical Engineering

Background:

Intercellular heterogeneity influences critical cellular processes like proliferation and drug resistance.
Studying cell-to-cell variability at the single-cell level is challenging due to experimental limitations.

Purpose of the Study:

To develop and present a measurement platform for quantifying single-cell oxygen consumption rates (OCRs).
To investigate the impact of cell-cell interactions on cellular respiration.
To enable ratiometric, intensity-based metabolic phenotyping at the single-cell level.

Main Methods:

Utilized extracellular optical sensors in subnanoliter microwells for real-time metabolite concentration measurements.
Quantified oxygen consumption rates (OCRs) of individual, non-interacting, and interacting human epithelial cells.
Assessed effects of cell-cell interactions by isolating two and three cells in single wells under normoxic and hypoxic conditions.

Main Results:

Successfully measured oxygen consumption rates (OCRs) of individual human epithelial cells.
Demonstrated the system's capability to study the effects of cell-cell interactions on respiration.
Validated a minimally invasive, ratiometric approach for single-cell metabolic characterization.

Conclusions:

The presented platform offers a minimally invasive method for studying single-cell metabolism and respiration.
This technology facilitates the investigation of intercellular heterogeneity and cell-cell interactions in cellular processes.
The system advances the study of metabolic phenotypes at the single-cell level, crucial for understanding disease and drug resistance.