Honeycomb-inspired SERS nano-bowls for rapid capture and analysis of extracellular vesicles and liposomes in suspension

Nanoscale carriers such as liposomes and extracellular vesicles (EVs) are readily being explored for personalized medicine or disease prediction and diagnostics, respectively. Owing to their small size, such nanocarriers can undergo endocytosis or exocytosis, providing means to either transport cargo to the cells (liposomes) or to serve as a biomarker (EVs). When looking at current analysis methods, there is a growing need for detailed characterization of the content and composition of such nanocarriers in their natural state in aqueous media. This can be achieved through surface-enhanced Raman spectroscopy (SERS), which provides a molecular fingerprint of the analytes while reducing the detection limit. In this paper, we utilize a nano-structured SERS substrate to study different bio-nanoparticles such as liposomes, EVs and DNA nanogel in suspension. A silver-coated polydimethylsiloxane (PDMS) film-based honeycomb shaped nano-bowl surface passively traps and reduces the mobility of the nanosized bio-particles, improving the intensity and the reproducibility of the SERS signal. FDTD simulations are used for substrate geometry optimization, and a detection limit of 10-15 M is demonstrated for Rhodamine 6G (R6G). The potential of the proposed SERS nano-bowl is shown through distinct spectral features following surface-(polyethylene glycol) and bilayer-(cholesterol) modification of empty liposomes. For DNA nanogels, the characterization of highly crosslinked DNA specimens exhibits enhanced peaks for nitrogenous bases, sugar, and phosphate groups. EVs isolated from various cells provided spectral signatures of specific protein content, lipid components, and nucleic acids. Concluding, the findings of the spectral signatures of a wide range of molecular complexes and chemical morphology of bio-membranes in their natural state highlight the possibilities of using SERS as a sensitive and instantaneous characterization alternative.