Surface-Enhanced Raman Spectroscopy in Cellular Applications

Surface-Enhanced Raman Spectroscopy (SERS) exploits the intense electromagnetic fields generated at metallic nanostructures to amplify weak molecular vibrations, enabling label-free detection of biochemical species within single cells. By harnessing plasmonic resonances of gold or silver nanostructures, SERS permits high-sensitivity interrogation of proteins, lipids, nucleic acids and small metabolites in situ. Integrating SERS with optical or electrochemical platforms yields spatially resolved maps of intracellular chemistry, while advances in nanofabrication have produced reproducible hot-spot architectures and multifunctional probes for targeted organelle imaging. Coupling real-time spectroscopy with multivariate analysis and machine-learning algorithms overcomes spectral complexity and facilitates the classification of cellular states, detection of stress responses and monitoring of drug uptake. Recent developments encompass three-dimensional live-cell imaging, controlled electroporation for intracellular sampling and single-molecule investigations in biomembranes. Together, these innovations position SERS as a versatile tool for fundamental cell biology, early disease diagnostics and high-throughput screening.

Research from Nature Portfolio

Recent studies have demonstrated a combined use of labelled and label-free SERS probes to achieve three-dimensional mapping of multiple organelles in live cells, revealing dynamic changes in nuclear chemistry and membrane receptor distributions during apoptosis. Advanced data-driven approaches have also been introduced, applying random forest algorithms to complex SERS datasets to identify informative spectral features, evaluate group relevance and uncover interrelations among biomolecular signatures without the need for added reporters. Complementing these efforts, single-molecule SERS investigations in supported lipid membranes have directly observed rapid conformational shifts of individual lipid molecules, illustrating the power of nanoparticle-on-mirror geometries to confine sampling volumes to a few cubic nanometres and enabling sustained measurements of native membrane dynamics.

Research from all publishers

A comprehensive tutorial review has outlined the critical factors governing SERS performance in complex biological samples, from nanoparticle design and selective targeting to the integration of multimodal microscopy and robust bioinformatic tools for spectral deconvolution. In parallel, three-dimensional plasmonic nanoelectrode arrays have been employed to probe cell membrane dynamics before, during and after electroporation, providing molecular time-traces of lipids, proteins and nucleic acids while enabling controlled intracellular access. Foundational work on purpose-built plasmonic nanoparticles for intracellular SERS has assessed synthesis methods, biocompatibility, cellular uptake pathways and multivariate spectral analysis, setting the stage for reproducible high-throughput assays and expanding our understanding of molecular processes at the nanoscale.

Surface-Enhanced Raman Spectroscopy in Cellular Applications publication trend

The graph below shows the total number of articles in surface-enhanced raman spectroscopy in cellular applications across all publications each year (not limited to Nature Index journals).

Technical terms

Surface-Enhanced Raman Spectroscopy (SERS): A vibrational spectroscopy technique that uses metal nanostructures to amplify Raman scattering signals from molecules in close proximity to their surfaces.

Localized Surface Plasmon Resonance (LSPR): The collective oscillation of conduction electrons at the surface of a metallic nanoparticle, excited by incident light, which generates intense local electromagnetic fields.

Plasmonic Hot Spot: A nanoscale region near a sharp feature or in the gap between metallic nanostructures where the electromagnetic field enhancement is maximised.

Label-Free Imaging: A detection approach that does not rely on fluorescent or colourimetric tags, instead using intrinsic molecular vibrations to provide chemical contrast.

Multivariate Analysis: Statistical methods, including machine learning, used to analyse complex spectral datasets by identifying patterns, classifying spectral groups and extracting key features.

References

1. SERS microscopy as a tool for comprehensive biochemical characterization in complex samples. Chemical Society Reviews (2024).
2. Nanoparticles and intracellular applications of surface-enhanced Raman spectroscopy. Analyst (2016).
3. 3D plasmonic nanoantennas integrated with MEA biosensors. Nanoscale (2015).
4. Application of random forest based approaches to surface-enhanced Raman scattering data. Scientific Reports (2020).
5. Watching individual molecules flex within lipid membranes using SERS. Scientific Reports (2014).
6. Combined Labelled and Label-free SERS Probes for Triplex Three-dimensional Cellular Imaging. Scientific Reports (2016).
7. Enhanced Raman Investigation of Cell Membrane and Intracellular Compounds by 3D Plasmonic Nanoelectrode Arrays. Advanced Science (2018).
8. Properties of in situ generated gold nanoparticles in the cellular context. Nanoscale (2017).
9. Biomolecular environment, quantification, and intracellular interaction of multifunctional magnetic SERS nanoprobes. Analyst (2016).