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Author Spotlight: Engineering Molecular Tools for Disease Detection and Imaging

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Metabolic Footprinting-Based DNA-AuNP Encoders for Extracellular Metabolic Response Profiling.

Guangpei Qi¹, Haixia Zou¹, Xiaohong Peng²

¹Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province and School of Biomedical Engineering, Sun Yat-Sen University, Shenzhen 518107, China.

Analytical Chemistry

|May 8, 2023

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This study introduces a novel DNA-AuNP encoder for non-invasive cell metabolomics, offering a powerful complement to metabolic footprinting for identifying tumor cell heterogeneity.

Area of Science:

Biochemistry
Nanotechnology
Cell Biology

Background:

Metabolic footprinting is a non-invasive cell metabolomics technique monitoring extracellular metabolism.
Current methods face limitations in universality due to cell medium pre-treatment and specialized equipment.

Purpose of the Study:

To develop a novel, broadly applicable method for quantifying extracellular metabolism.
To create a non-invasive strategy for profiling cellular metabolic responses.
To complement existing metabolic footprinting techniques.

Main Methods:

Design and application of fluorescently labeled single-stranded DNA (ssDNA)-AuNP encoders.
Detection of extracellular metabolites triggered by ssDNA-AuNP encoders.
Construction of metabolic response profiles using machine learning algorithms.

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Main Results:

The DNA-AuNP encoder strategy enables quantification of extracellular metabolism.
Demonstrated applicability in detecting metabolites from different tumor cells and drug-induced changes.
Machine learning analysis revealed distinct extracellular metabolism profiles.

Conclusions:

The DNA-AuNP encoder strategy offers a powerful, non-invasive complement to metabolic footprinting.
This approach facilitates the identification of tumor cell heterogeneity.
Potential for broad applications in non-invasive cell metabolomics and diagnostics.