4.8 Article

Three-Dimensional Plasmonic Trap Array for Ultrasensitive Surface-Enhanced Raman Scattering Analysis of Single Cells

期刊

ANALYTICAL CHEMISTRY
卷 90, 期 17, 页码 10394-10399

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.8b02252

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资金

  1. National Natural Science Foundation of China [21775028, 21575030, 31501555, 31600665, 21227805, 81772007, 21734003]
  2. National Key Research and Development Program [2017YFC0906700, 2016YFA0501300]
  3. STCSM [16391903900, 17JC1401900, 17JC1400200]

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Single-cell analysis provides an important strategy to evaluate cellular heterogeneity. Although surface-enhanced Raman scattering (SERS) has been considered as a promising label-free technique for single-cell, analysis, it remains at the early stage for characterizing the extracellular metabolites of single cells. Herein, we developed a convenient, flexible, and straightforward three-dimensional (3D) plasmonic trap array for simultaneously compartmentalizing and sensitively detecting single-cell metabolites. The 3D trap was spontaneously self-formed by an interfacial-energy-driven process when a liquid droplet was covered with an immiscible oil liquid (polydimethylsiloxane, PDMS). When a droplet of pure AgNO3 solution was immersed into PDMS, Ag+ ions were automatically reduced by the residual Si-H groups in PDMS. Snowflake-like nanoparticles of Ag could be formed Flunreaccm image on the inner surface of the 3D traps by tuning the concentration of Ag salt precursors and then assembled to flower-like microstructures, endowing the traps with remarkable plasmon enhancement. The established 3D traps exhibited considerably enhanced surface plasmon resonance signals for Raman reporting, and a low detection limit at the aM level was achieved for p-aminothiophenol. Moreover, these 3D traps can serve as an efficient tool for single-cell SERS measurement. As a proof-of-concept, dipicolinic acid, a common biomarker of bacterial spores, was successfully detected from a single cell. The presented approach provides a versatile tool for label-free and sensitive detection of single-cell environments.

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