Fabrication and characterization of a multiwell array SERS chip with biological applications.

Uniform, large surface area substrates for surface-enhanced Raman spectroscopy (SERS) are fabricated by oblique angle deposition. The SERS-active substrates are patterned by a polymer-molding technique to provide a uniform array for high throughput biosensing and multiplexing. Using a conventional SERS-active molecule, 1,2-di(4-pyridyl)ethylene (BPE) >or=98%, we show that this device provides a uniform Raman signal enhancement from well to well with a detection limit of at least 10(-8)M of the BPE solution or 10(-18)mol of BPE. The SERS intensity is also demonstrated to vary logarithmically with the log of BPE concentration and the apparent sensitivity of the patterned substrate is compared to previous reports from our group on non-patterned substrates. Avian influenza is analyzed to demonstrate the utility of SERS multiwell patterned substrates for biosensing. The spectra acquired from patterned substrates show better reproducibility and less variation compared to the unpatterned substrates according to multivariate analysis. Our results highlight potential advantages of the patterned substrate.

Rapid microRNA (miRNA) detection and classification via surface-enhanced Raman spectroscopy (SERS).

microRNAs (miRNA) are recognized as regulators of gene expression during development and cell differentiation as well as biomarkers of disease. Development of rapid and sensitive miRNA profiling methods is essential for evaluating the pattern of miRNA expression that varies across normal and diseased states. The ability to identify miRNA expression patterns is limited to cumbersome assays that often lack sensitivity and specificity to distinguish between different miRNA families and members. We evaluated a surface-enhanced Raman scattering (SERS) platform for detection and classification of miRNAs. The strength of the SERS-based sensor is its sensitivity to detect extremely low levels of analyte and specificity to provide the molecular fingerprint of the analyte. We show that the SERS spectra of related and unrelated miRNAs can be detected in near-real time, that detection is sequence dependent, and that SERS spectra can be used to classify miRNA patterns with high accuracy.

Identification and classification of respiratory syncytial virus (RSV) strains by surface-enhanced Raman spectroscopy and multivariate statistical techniques.

There is a critical need for a rapid and sensitive means of detecting viruses. Recent reports from our laboratory have shown that surface-enhanced Raman spectroscopy (SERS) can meet these needs. In this study, SERS was used to obtain the Raman spectra of respiratory syncytial virus (RSV) strains A/Long, B1, and A2. SERS-active substrates composed of silver nanorods were fabricated using an oblique angle vapor deposition method. The SERS spectra obtained for each virus were shown to possess a high degree of reproducibility. Based on their intrinsic SERS spectra, the four virus strains were readily detected and classified using the multivariate statistical methods principal component analysis (PCA) and hierarchical cluster analysis (HCA). The chemometric results show that PCA is able to separate the three virus strains unambiguously, whereas the HCA method was able to readily distinguish an A2 strain-related G gene mutant virus (DeltaG) from the A2 strain. The results described here demonstrate that SERS, in combination with multivariate statistical methods, can be utilized as a highly sensitive and rapid viral identification and classification method.

Detection of viruses: atomic force microscopy and surface enhanced Raman spectroscopy.

This paper demonstrates the capability of atomic force microscopy (AFM) and surface enhanced Raman spectroscopy (SERS) to function effectively as ultra-sensitive readout tools for chip-scale platforms designed for pathogen detection in complex biological media. AFM allows direct (i.e., label-free) visualization and quantification of nanometer-sized viruses captured on a smooth, selective surface. AFM readout led to optimization of a capture substrate for feline calicivirus (FCV), and yielded a limit of detection of 3 x 10(6) FCV/mL. SERS-based detection of FCV, carried out in a sandwich-type assay, requires labelling of the substrate-bound FCV with a selective extrinsic Raman label (ERL). These studies yielded a limit of detection of 1 x 10(6) FCV/mL. The prospects of these two readout methods as additions to the arsenal of tools in bioterrorism prevention are briefly discussed.