Westley Van Zant

Fundamental studies of uncommon plasmonic materials expand their potential applications in nanoplasmonics. In this work, nanometers thin films of indium, a plasmonic yet rarely explored metal, were characterized for its surface plasmon polariton (SPP) properties and the performance in surface plasmon resonance (SPR) sensing and surface-enhanced Raman spectroscopy (SERS). Direct deposition of indium films on glass slides exhibited coalescence of discrete particles and generated no SPR response due to gaps disrupting SPP propagation. Addition of a 2-nm Cr base layer reduced the particle size and produced a resonance dip under the Kretschmann configuration. SPR sensing with a 2/40 nm Cr/In film was demonstrated for the first time and compared to the standard 2/50 nm Cr/Au film, revealing a sensitivity approximately 77% that of the gold film. The optical properties of the passivating In₂O₃ layer are investigated through analogous RF magnetron sputtered In₂O₃ films to allow for improved computational modeling and optimization of the substrates for plasmonic applications. Low extinction coefficient (k) at typical SPR wavelengths (~650 nm) found for the oxide layer indicates minimal effects on SPR response. However, finite-difference time-domain (FDTD) simulations revealed that the presence of the oxide layer resulted in a >50% increase in the SERS enhancement in the UV range, while exhibiting little effect with incident light in the visible range. This work provides insights into the plasmonic properties of thin indium films for optical sensing applications and highlights the critical role of the oxide layer in wavelength-specific performance.

The COVID-19 pandemic and recent viral outbreaks have highlighted the need for viral diagnostics that balance accuracy with accessibility. While traditional laboratory methods remain essential, point-of-care solutions are critical for decentralized testing at the population level. However, a gap persists between academic proof-of-concept studies and clinically viable tools, with novel technologies remaining inaccessible to clinics due to cost, complexity, training, and logistical constraints. Recent advances in surface functionalization, assay simplification, multiplexing, and performance in complex media have improved the feasibility of both optical and non-optical sensing techniques. These innovations, coupled with scalable manufacturing methods such as 3D printing and streamlined hardware production, pave the way for practical deployment in real-world settings. Additionally, software-assisted data interpretation, through simplified readouts, smartphone integration, and machine learning, enables the broader use of diagnostics once limited to experts. This review explores improvements in viral diagnostic approaches, including colorimetric, optical, and electrochemical assays, showcasing their potential for democratization efforts targeting the clinic. We also examine trends such as open-source hardware, modular assay design, and standardized reporting, which collectively reduce barriers to clinical adoption and the public dissemination of information. By analyzing these interdisciplinary advances, we demonstrate how emerging technologies can mature into accessible, low-cost diagnostic tools for widespread testing.

Alpha-synuclein is a presynaptic neuronal protein that is genetically and neuropathologically linked to Parkinson’s disease (PD), playing a critical role in the development of neurodegenerative disorders through its tendency to self-aggregate. However, its membrane-binding dynamics, especially in response to membrane curvature, remain poorly understood. Herein, we report the development and application of a tunable, curved membrane system built on an optical sensor platform for surface plasmon resonance (SPR) characterization of the protein-membrane interactions of alpha synuclein. Vesicles of varied size, lipid compositions, and charges were immobilized at the interface, enabling precise control of the interface with properties relevant to the effects on binding characteristics. Incorporation of cholesterol, sphingomyelin, and ganglioside (GM1) allowed the investigation of protein binding in a more biologically relevant membrane environment. Finally, the impact of a disaggregation agent on alpha synuclein binding was characterized to understand the disruption process. Our results demonstrate the capability of the optical biosensing system for studying complex protein-membrane interactions and facilitating the understanding of curvature-sensitive binding by alpha-synuclein.

The COVID-19 pandemic and recent viral outbreaks have underscored the urgent need for diagnostics that combine accuracy with widespread accessibility. While laboratory-based methods remain essential, point-of-care (POC) solutions are critical for quick, decentralized testing. Significant advancements in viral biosensors, from innovative technologies to enhancements of existing platforms, demonstrate the growing potential of new sensing technologies for clinical applications. However, a gap remains between academic proof-of-concept studies and viable, clinically deployable diagnostic tools. This review examines how recent advancements in sensing methodologies, including innovative analyte detection, simplified assay administration, and enhanced performance in complex media such as serum, collectively address barriers to adoption, including cost, usability, and scalability. We also explore broader trends, such as open-source hardware, modular assay design, and standardized reporting practices, that collectively work to reduce barriers to clinical implementation. By analyzing these converging innovations, we emphasize how interdisciplinary progress is transforming the landscape of viral diagnostics, bringing the field closer to practical, equitable, and scalable solutions for real-world settings through novel biosensing advancements.

Surface plasmon resonance (SPR) proves to be one of the most effective methods of label-free detection and has been integral for the study of biomolecular interactions and the development of biosensors. This trend delves into the latest SPR research and progress built upon the Kretschmann configuration, a pivotal platform, and highlights three key developments that have enhanced the capabilities of the technique. We will first cover a range of explorations of novel plasmonic materials that have shaped SPR performance. Innovative signal transduction and collection, which leverages traditional materials and emerging alternatives, will then be discussed. Finally, the evolving landscape of data analysis, including the integration of machine learning algorithms to navigate complex SPR datasets, will be reviewed. We will also discuss the implementation of these improvements that have enabled new biosensing functions. These advancements not only pave the way for enhanced biosensing in general but also open new avenues for the technique to play a more significant role in research concerning human health. Graphical Abstract

The continuing mutability of the SARS-CoV-2 virus can result in failures of diagnostic assays. To address this, we describe a generalizable bioinformatics-to-biology pipeline developed for the calibration and quality assurance of inactivated SARS-CoV-2 variant panels provided to Radical Acceleration of Diagnostics programs (RADx)-radical program awardees. A heuristic genetic analysis based on variant-defining mutations demonstrated the lowest genetic variance in the Nucleocapsid protein (Np)-C-terminal domain (CTD) across all SARS-CoV-2 variants. We then employed the Shannon entropy method on (Np) sequences collected from the major variants, verifying the CTD with lower entropy (less prone to mutations) than other Np regions. Polyclonal and monoclonal antibodies were raised against this target CTD antigen and used to develop an Enzyme-linked immunoassay (ELISA) test for SARS-CoV-2. Blinded Viral Quality Assurance (VQA) panels comprised of UV-inactivated SARS-CoV-2 variants (XBB.1.5, BF.7, BA.1, B.1.617.2, and WA1) and distractor respiratory viruses (CoV 229E, CoV OC43, RSV A2, RSV B, IAV H1N1, and IBV) were assembled by the RADx-rad Diagnostics core and tested using the ELISA described here. The assay tested positive for all variants with high sensitivity (limit of detection: 1.72–8.78 ng/mL) and negative for the distractor virus panel. Epitope mapping for the monoclonal antibodies identified a 20 amino acid antigenic peptide on the Np-CTD that an in-silico program also predicted for the highest antigenicity. This work provides a template for a bioinformatics pipeline to select genetic regions with a low propensity for mutation (low Shannon entropy) to develop robust ‘pan-variant’ antigen-based assays for viruses prone to high mutational rates.

The continuing mutability of the SARS-CoV-2 virus can result in failures of diagnostic assays. To address this, we describe a generalizable bioinformatics-to-biology pipeline developed for calibration and quality assurance of inactivated SARS-COV-2 variant panels provided to Radical Acceleration of Diagnostics programs (RADx)-radical program awardees. Heuristic genetic analysis based on variant-defining mutations demonstrated the lowest genetic variance in the Nucleocapsid protein (Np)- C-terminal domain (CTD) across all SARS-COV-2 variants. We then employed the Shannon entropy method on (Np) sequences collected from the major variants, verifying the CTD with lower entropy (less prone to mutations) than other Np regions. Polyclonal and monoclonal antibodies were raised against this target CTD antigen and used to develop an Enzyme-linked immunoassay (ELISA) test for SARS-CoV-2. Blinded Viral Quality Assurance (VQA) panels comprising of UV-inactivated SARS CoV-2 variants (XBB.1.5, BF.7, BA.1, B.1.617.2, and WA1) and distractor respiratory viruses (CoV 229E, CoV OC43, RSV A2, RSV B, IAV H1N1, and IBV) were assembled by the RADx-rad Diagnostics core and tested using the ELISA described here. The assay tested positive for all variants with high sensitivity (Limit of Detection: 1.72-8.78 ng/mL) and negative for the distractor virus panel. Epitope mapping for the monoclonal antibodies identified a twenty amino acid antigenic peptide on the Np-CTD that an in-silico program also predicted for the highest antigenicity. This work provides a template for a bioinformatics pipeline to select genetic regions with a low propensity for mutation (low Shannon entropy) to develop robust ‘pan-variant’ antigen-based assays for viruses prone to high mutational rates.

The recent development and mass administration of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) vaccines allowed for disease control, reducing hospitalizations and mortality. Most of these vaccines target the SARS-CoV-2 Spike (S) protein antigens, culminating with the production of neutralizing antibodies (NAbs) that disrupt the attachment of the virus to ACE2 receptors on the host cells. However, several studies demonstrated that the NAbs typically rise within a few weeks after vaccination but quickly reduce months later. Thus, multiple booster administration is recommended, leading to vaccination hesitancy in many populations. Detecting serum anti-SARS-CoV-2 NAbs can instruct patients and healthcare providers on correct booster strategies. Several in vitro diagnostics kits are available; however, their high cost impairs the mass NAbs diagnostic testing. Recently, we engineered an ACE2 mimetic that interacts with the Receptor Binding Domain (RBD) of the SARS-2 S protein. Here we present the use of this engineered mini-protein (p-deface2 mut) to develop a detection assay to measure NAbs in patient sera using a competitive ELISA assay. Serum samples from twenty-one patients were tested. Nine samples (42.8%) tested positive, and twelve (57.1%) tested negative for neutralizing sera. The data correlated with the result from the standard commercial assay that uses human ACE2 protein. This confirmed that p-deface2 mut could replace human ACE2 in ELISA assays. Using bacterially expressed p-deface2 mut protein is cost-effective and may allow mass SARS-CoV-2 NAbs detection, especially in low-income countries where economical diagnostic testing is crucial. Such information will help providers decide when a booster is required, reducing risks of reinfection and preventing the administration before it is medically necessary.