Spectroscopic Identification of Charge Transfer of Thiolated Molecules on Gold Nanoparticles via Gold Nanoclusters.

Investigation of charge transfer needs analytical tools that could reveal this phenomenon, and enables understanding of its effect at the molecular level. Here, we show how the combination of using gold nanoclusters (AuNCs) and different spectroscopic techniques could be employed to investigate the charge transfer of thiolated molecules on gold nanoparticles (AuNP@Mol). It was found that the charge transfer effect in the thiolated molecule could be affected by AuNCs, evidenced by the amplification of surface-enhanced Raman scattering (SERS) signal of the molecule and changes in fluorescence lifetime of AuNCs. Density functional theory (DFT) calculations further revealed that AuNCs could amplify the charge transfer process at the molecular level by pumping electrons to the surface of AuNPs. Finite element method (FEM) simulations also showed that the electromagnetic enhancement mechanism along with chemical enhancement determines the SERS improvement in the thiolated molecule. This study provides a mechanistic insight into the investigation of charge transfer at the molecular level between organic and inorganic compounds, which is of great importance in designing new nanocomposite systems. Additionally, this work demonstrates the potential of SERS as a powerful analytical tool that could be used in nanochemistry, material science, energy, and biomedical fields.

Shape-Induced Variations in Aromatic Thiols Adsorption on Gold Nanoparticle: A Novel Method for Accurate Evaluation of Adsorbed Molecules.

Nonspherical gold nanoparticles (GNPs) are increasingly used to enhance sensitivity and selectivity in analytical methods such as surface-enhanced Raman spectroscopy (SERS) for detecting trace biomarkers. However, there is limited research on the adsorption properties of aromatic thiols onto gold nanoparticles of different morphologies, where surface curvature varies significantly at the molecular level. In this study, we investigated the adsorption kinetics of 4-mercaptobenzoic acid, an aromatic molecule, on GNPs with different shapes using SERS. Our findings revealed significant differences in the adsorption behavior and binding site preferences of aromatic thiols on GNPs with distinct morphologies. While thiol molecules consider any surface site on nanospheres equally appealing, nanostars exhibit variations in curvature and surface energy, leading to initial binding with further repositioning from the tips of the nanostar after plasmon activation. To address these differences, we proposed a universal method to evaluate the quantity of tightly bound adsorbed molecules on GNPs independently of the particle size, shape, or concentration.

Microfluidic-SERS Technologies for CTC: A Perspective on Clinical Translation.

Enumeration and phenotypic profiling of circulating tumor cells (CTCs) provide critical information for clinical diagnosis and treatment monitoring in cancer. To achieve this goal, an integrated system is needed to efficiently isolate CTCs from patient samples and sensitively evaluate their phenotypes. Such integration would comprise a high-throughput single-cell processing unit for the isolation and manipulation of CTCs and a sensitive and multiplexed quantitation unit to detect clinically relevant signals from these cells. Surface-enhanced Raman scattering (SERS) has been used as an analytical method for molecular profiling and in vitro cancer diagnosis. More recently, its multiplexing capability and power to create distinct molecular signatures against their targets have garnered attention. Here, we share our insights into the combined power of microfluidics and SERS in realizing CTC isolation, enumeration, and detection from a clinical translation perspective. We highlight the key operational factors in CTC microfluidic processing and SERS detection from patient samples. We further discuss microfluidic-SERS integration and its clinical utility as a paradigm shift in clinical CTC-based cancer diagnosis and prognostication. Finally, we summarize the challenges and attempt to look forward to what lies ahead of us in potentially translating the technique into real clinical applications.

Nanosupernova: a new anisotropic nanostructure for SERS.

Gold and/or silver nanostars are interesting anisotropic nanoparticles that have been used in surface-enhanced Raman scattering (SERS). In particular SERS nanotags consisting of gold nanostars and Raman reporter molecules have been widely utilised in biosensing and bioimaging. To improve the SERS activity of gold/silver nanostars, this paper details the development of a simple synthesis method that results in the formation of quasi-spherical SERS nanotags and larger highly anisotropic nanoparticles with a novel structure, which we have designated nanosupernova. The resulting SERS nanotags and nanosupernova contain gold/silver nanostars at their core, a self-assembled monolayer of Raman reporter molecules, and a final silver coating. The silver coating is the essential step responsible for the formation of the two types of particles, with incubation time, and type of Raman reporter molecule, the defining factor as to which forms. We discovered that the Raman reporter molecule, 5,5'-dithiobis-(2-nitrobenzoic acid) (DTNB), plays a crucial role in controlling the morphology of nanosupernova. We believe the larger highly anisotropic nanoparticles will open new applications in material sciences and in optical and electronic devices in the future.

Emerging integrated SERS-microfluidic devices for analysis of cancer-derived small extracellular vesicles.

Cancer-derived small extracellular vesicles (sEVs) are specific subgroups of lipid bilayer vesicles secreted from cancer cells to the extracellular environment. They carry distinct biomolecules (e.g., proteins, lipids and nucleic acids) from their parent cancer cells. Therefore, the analysis of cancer-derived sEVs can provide valuable information for cancer diagnosis. However, the use of cancer-derived sEVs in clinics is still limited due to their small size, low amounts in circulating fluids, and heterogeneous molecular features, making their isolation and analysis challenging. Recently, microfluidic technology has gained great attention for its ability to isolate sEVs in minimal volume. In addition, microfluidics allows the isolation and detection of sEVs to be integrated into a single device, offering new opportunities for clinical application. Among various detection techniques, surface-enhanced Raman scattering (SERS) has emerged as a promising candidate for integrating with microfluidic devices due to its ultra-sensitivity, stability, rapid readout, and multiplexing capability. In this tutorial review, we start with the design of microfluidics devices for isolation of sEVs and introduce the key factors to be considered for the design, and then discuss the integration of SERS and microfluidic devices by providing descriptive examples of the currently developed platforms. Lastly, we discuss the current limitations and provide our insights for utilising integrated SERS-microfluidics to isolate and analyse cancer-derived sEVs in clinical settings.

Emerging SERS biosensors for the analysis of cells and extracellular vesicles.

Cells and their derived extracellular vesicles (EVs) or exosomes contain unique molecular signatures that could be used as biomarkers for the detection of severe diseases such as cancer, as well as monitoring the treatment response. Revealing these molecular signatures requires developing non-invasive ultrasensitive tools to enable single molecule/cell-level detection using a small volume of sample with low signal-to-noise ratio background and multiplex capability. Surface-enhanced Raman scattering (SERS) can address the current limitations in studying cells and EVs through two main mechanisms: plasmon-enhanced electric field (the so-called electromagnetic mechanism (EM)), and chemical mechanism (CM). In this review, we first highlight these two SERS mechanisms and then discuss the nanomaterials that have been used to develop SERS biosensors based on each of the aforementioned mechanisms as well as the combination of these two mechanisms in order to take advantage of the synergic effect between electromagnetic enhancement and chemical enhancement. Then, we review the recent advances in designing label-aided and label-free SERS biosensors in both colloidal and planar systems to investigate the surface biomarkers on cancer cells and their derived EVs. Finally, we discuss perspectives of emerging SERS biosensors in future biomedical applications. We believe this review article will thus appeal to researchers in the field of nanobiotechnology including material sciences, biosensors, and biomedical fields.

Spectroscopy of model-membrane liposome-protein systems: complementarity of linear dichroism, circular dichroism, fluorescence and SERS.

A range of membrane models have been developed to study components of cellular systems. Lipid vesicles or liposomes are one such artificial membrane model which mimics many properties of the biological system: they are lipid bilayers composed of one or more lipids to which other molecules can associate. Liposomes are thus ideal to study the roles of cellular lipids and their interactions with other membrane components to understand a wide range of cellular processes including membrane disruption, membrane transport and catalytic activity. Although liposomes are much simpler than cellular membranes, they are still challenging to study and a variety of complementary techniques are needed. In this review article, we consider several currently used analytical methods for spectroscopic measurements of unilamellar liposomes and their interaction with proteins and peptides. Among the variety of spectroscopic techniques seeing increasing application, we have chosen to discuss: fluorescence based techniques such as FRET (fluorescence resonance energy transfer) and FRAP (fluorescence recovery after photobleaching), that are used to identify localisation and dynamics of molecules in the membrane; circular dichroism (CD) and linear dichroism (LD) for conformational and orientation changes of proteins on membrane binding; and SERS (Surface Enhanced Raman Spectroscopy) as a rapidly developing ultrasensitive technique for site-selective molecular characterisation. The review contains brief theoretical basics of the listed techniques and recent examples of their successful applications for membrane studies.

Gold Nanostars with Reduced Fouling Facilitate Small Molecule Detection in the Presence of Protein.

Gold nanoparticles have the potential to be used in biomedical applications from diagnostics to drug delivery. However, interactions of gold nanoparticles with different biomolecules in the cellular environment result in the formation of a "protein corona"-a layer of protein formed around a nanoparticle, which induces changes in the properties of nanoparticles. In this work we developed methods to reproducibly synthesize spheroidal and star-shaped gold nanoparticles, and carried out a physico-chemical characterization of synthesized anionic gold nanospheroids and gold nanostars through transmission electron microscopy (TEM), dynamic light scattering (DLS), zeta potential (ZP), nanoparticles tracking analysis (NTA), ultraviolet-visible (UV-Vis) spectroscopy and estimates of surface-enhanced Raman spectroscopy (SERS) signal enhancement ability. We analyzed how they interact with proteins after pre-incubation with bovine serum albumin (BSA) via UV-Vis, DLS, ZP, NTA, SERS, cryogenic TEM (cryo-TEM) and circular dichroism (CD) spectroscopy. The tests demonstrated that the protein adsorption on the particles' surfaces was different for spheroidal and star shaped particles. In our experiments, star shaped particles limited the protein corona formation at SERS "hot spots". This benefits the small-molecule sensing of nanostars in biological media. This work adds more understanding about protein corona formation on gold nanoparticles of different shapes in biological media, and therefore guides design of particles for studies in vitro and in vivo.

SOMSpec as a General Purpose Validated Self-Organising Map Tool for Rapid Protein Secondary Structure Prediction From Infrared Absorbance Data.

A protein's structure is the key to its function. As protein structure can vary with environment, it is important to be able to determine it over a wide range of concentrations, temperatures, formulation vehicles, and states. Robust reproducible validated methods are required for applications including batch-batch comparisons of biopharmaceutical products. Circular dichroism is widely used for this purpose, but an alternative is required for concentrations above 10 mg/mL or for solutions with chiral buffer components that absorb far UV light. Infrared (IR) protein absorbance spectra of the Amide I region (1,600-1700 cm-1) contain information about secondary structure and require higher concentrations than circular dichroism often with complementary spectral windows. In this paper, we consider a number of approaches to extract structural information from a protein infrared spectrum and determine their reliability for regulatory and research purpose. In particular, we compare direct and second derivative band-fitting with a self-organising map (SOM) approach applied to a number of different reference sets. The self-organising map (SOM) approach proved significantly more accurate than the band-fitting approaches for solution spectra. As there is no validated benchmark method available for infrared structure fitting, SOMSpec was implemented in a leave-one-out validation (LOOV) approach for solid-state transmission and thin-film attenuated total reflectance (ATR) reference sets. We then tested SOMSpec and the thin-film ATR reference set against 68 solution spectra and found the average prediction error for helix (α + 310) and ß-sheet was less than 6% for proteins with less than 40% helix. This is quantitatively better than other available approaches. The visual output format of SOMSpec aids identification of poor predictions. We also demonstrated how to convert aqueous ATR spectra to and from transmission spectra for structure fitting. Fourier self-deconvolution did not improve the average structure predictions.