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Creating Rapid Oxygen Oscillations in Microbial Single-cell Growth Analysis using a Microfluidic Double-layer Device

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A microwell array device capable of measuring single-cell oxygen consumption rates.

Timothy W Molter¹, Sarah C McQuaide, Martin T Suchorolski

¹University of Washington, Benjamin Hall Research Building, 616 NE Northlake Pl. Rm. 440, Seattle, WA 98105.

Sensors and Actuators. B, Chemical

|January 20, 2010

Summary

Researchers developed a novel microwell array device for measuring single-cell oxygen consumption rates (OCR). This non-invasive technology offers high throughput and fmol/min resolution, advancing single-cell analysis.

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Area of Science:

Biotechnology
Cell Biology
Analytical Chemistry

Background:

Growing interest in cell population heterogeneity drives demand for advanced single-cell analysis technologies.
Current single-cell measurement systems aim for high throughput, comprehensive parameter measurement, and minimal cell disruption.

Purpose of the Study:

To develop and validate a novel microwell array device for quantitative, non-invasive measurement of single-cell oxygen consumption rates (OCR).
To enable high-throughput, high-resolution analysis of cellular metabolic activity at the single-cell level.

Main Methods:

Development of a glass microwell array device with integrated luminescent sensors for oxygen detection.
Diffusionally isolating individual cells within microwells for quantitative OCR measurements.
Testing the device with three distinct cell lines: RAW264.7, A549, and CP-D.

Main Results:

The device achieved fmol/min resolution for single-cell oxygen consumption rate (OCR) measurements.
Demonstrated non-invasive and relatively high-throughput quantitative OCR analysis.
Successfully measured OCR for small populations (12-18 cells) across three different cell lines.

Conclusions:

The developed microwell array device is a powerful tool for non-invasive, high-resolution single-cell metabolic analysis.
The platform's design allows for future integration of additional sensing capabilities for multi-parametric single-cell studies.
This technology advances the study of cell population heterogeneity by providing quantitative metabolic insights at the single-cell level.