Detection of biomarkers is of vital importance in disease detection, management, and monitoring of therapeutic efficacy. Extensive efforts have been devoted to the development of novel diagnostic methods that detect and quantify biomarkers with higher sensitivity and reliability, contributing to better disease diagnosis and prognosis. When it comes to such devastating diseases as cancer, these novel powerful methods allow for disease staging as well as detection of cancer at very early stages. Over the past decade, there have been some advances in the development of platforms for biomarker detection of diseases. The main focus has recently shifted to the development of simple and reliable diagnostic tests that are inexpensive, accurate, and can follow a patient’s disease progression and therapy response. The individualized approach in biomarker detection has been also emphasized with detection of multiple biomarkers in body fluids such as blood and urine. This review article covers the developments in Surface-Enhanced Raman Scattering (SERS) and related technologies with the primary focus on immunoassays. Limitations and advantages of the SERS-based immunoassay platform are discussed. The article thoroughly describes all components of the SERS immunoassay and highlights the superior capabilities of SERS readout strategy such as high sensitivity and simultaneous detection of a multitude of biomarkers. Finally, it introduces recently developed strategies for in vivo biomarker detection using SERS.

Tip-enhanced Raman Scattering (TERS) is an advanced technique allowing to measure Raman signals with high spatial resolution. By utilizing SERS effect in a probe coupled with Scanning Probe Microscopy the resolution reaches only a few nanometers breaking diffraction limit of optical microscopy. We have used TERS to study conformational features of amyloid aggregates formed by a peptide (CGNNQQNY) from the yeast prion protein Sup35. TERS results allowed us to identify a set of conformations that composes surfaces of morphologically different amyloid fibrils. Analysis of characteristic Raman bands in the amide III region showed that fibrils formed at pH 5.6 are composed of a mixture of peptide conformations (b-sheets, unordered and a-helix) while fibrils formed at pH 2 have primarily b-sheets. Additionally, by correlating the Raman peak positions corresponding to b-sheet structure in the amide III region with J dihedral angle obtained from Molecular Dynamics simulations of 16-mer fibrils, we proposed that peptides have parallel arrangement of b-sheets for pH 2 fibrils and antiparallel arrangement for fibrils formed at pH 5.6. We developed a methodology for detailed analysis of the peptide secondary structure that enabled us to correlate intensity changes in TERS spectra. Extensive cross correlation analysis of Raman peak intensities corresponding to a-helix, b-sheet and unordered secondary structures in amide III region and amide I region indicated that both regions provide adequate representation of structural characteristics of amyloid surfaces. Furthermore, 2D correlation with the band corresponding to Ca-H in plane bending suggested high localization of structural properties and large contribution of unordered non-helical secondary structures. Here we also discuss various ways to prepare TERS active probes, their longevity and enhancement capabilities suitable for protein aggregation studies.

No abstract

Nanoparticle technology has been a growing field in biomedical research. This is in part due to potential applications in drug delivery, biosensing, diagnostics, and imaging. Our long-term goal is to use protein functionalized AuNPs as a general tool for molecular sensing and drug delivery. The ability to use nanomaterials as biosensors and drug delivery methods in cellular uptake is directly dependent on the amount of protein that is able to bind to the surface of any given nanoparticle. It is hypothesized that electrostatic interactions play a significant role in protein-AuNP interactions, since citrate-stabilized AuNPs carry a net negative charge. Our group has developed an NMR-based approach to rapidly quantify bound protein to AuNP. To understand the above phenomenon, GB3 was chosen as our model protein and it contains seven lysine residues. These positively-charged lysine residues are involved in protein-AuNP binding, and a potential binding site was identified using APBS calculations which contain lysine residues. This hypothesis was tested by mutating the lysine residues to alanine one at a time using site-directed mutagenesis. NMR experiments were carried out to observe how the binding capacities of each of these variants change relative to wild type GB3. Notably K4A, K13A and K50A variants has significantly reduced binding, while the binding capacity of other lysine to alanine variants was on par with wild-type GB3. To obtain better understanding, GB3 variants were competed with wild type GB3 in the same solution with AuNP to observe how the binding capacities vary with wild type GB3. As predicted, the binding capacity ratio was lower for lysine residues in the proposed binding site were changed to alanine. A reduced binding capacity ratio was not observed for other lysine variants. The results reported are significant in establishing our original hypothesis, and suggest that GB3 adopts a specific orientation on the AuNP surface.