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Updated: Jan 3, 2026

Fluorescence detection methods for microfluidic droplet platforms
Published on: December 10, 2011
Label-Free Detection of Multiplexed Metabolites at Single-Cell Level via a SERS-Microfluidic Droplet Platform
Dan Sun1, Fanghao Cao1,2, Yu Tian1
1State Key Laboratory of Supramolecular Structure and Materials, Institute of Theoretical Chemistry , Jilin University , Changchun 130012 , P.R. China.
Abstract:
Single-cell metabolomics could be used to discover the chemical strategies of cells for coping with chemical or environmental stress because metabolomics provides a more immediate and dynamic picture of cell functionality. However, these small-molecule metabolites are the most difficult to measure because they characterize rapid metabolic dynamics, structural diversity, and incapacity to achieve signal amplification or labeling. In order to solve above problems, we presented a surface-enhanced Raman scattering (SERS)-microfluidic droplet platform to realize the label-free simultaneous analysis of multiplexed metabolites at the single-cell level via a versatile magnetic SERS substrate composed by silver nanoparticles (AgNPs, 30 nm)-decorated 400 nm Fe3O4 magnetic microspheres. This metal-magnetic composite substrate is beneficial to efficient adsorption of single cell metabolites, fast separation from complex matrixes, and high SERS sensitivity. Also, the endocytosis effect can be fully prohibited due to its relatively large size. This work achieves label-free, nondestructive, simultaneous determination of three single-cell metabolites, pyruvate, adenosine triphosphate (ATP), and lactate, owing to their intrinsic SERS fingerprints. The "hotspots" effect induced by the magnetic aggregation of Fe3O4@AgNPs allows highly sensitive SERS detection. Encapsulating metabolites in such a limited and isolated droplet accelerates the process of diffusion and adsorption equilibriums. Activation with saponin for metabolites was assessed on different cell lines. The SERS-microdroplet platform is a powerful tool for exploring single-cell heterogeneity at the metabolic level.
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