Raman spectroscopy for viral diagnostics

Unraveling the Nanomechanical and Vibrational Properties of the Mayaro Virus

Mayaro virus (MAYV) is an emerging mosquito-borne viral pathogen whose infection results in arthritogenic disease. Despite ongoing research efforts, MAYV biology is largely unknown. Physical virology can assess MAYV nanoparticle metastability, assembly/disassembly, and polymorphism, allowing us to understand virion architecture and dynamics. Here, we employ atomic force microscopy (AFM) and surface enhancement Raman spectroscopy (SERS) to assess MAYV nanomechanical properties, including maps of adhesion force and Young's modulus on individual viral particles. We established topographic maps of MAYV in two and three dimensions, revealing the three-dimensional arrangement and distribution of charges on viral spikes at the virus surface. Furthermore, the organization of the densely packaged RNA, which affords the viral particle exceptional mechanical resistance compared to chikungunya (CHIKV), was observed using MAYV adsorption patterns. The vibrational signature of MAYV particles differs from CHIKV, with more intense protein modes matching the distribution of E1/E2 dimers and the nucleocapsid, which are well structured and suggestive of mechanical strength.

Studying on the in vivo pathological evolution of spinal cord injury with the rat model by the method of integrated multispectral imaging and Raman spectroscopy

Spinal cord injury (SCI) is a debilitating neurological and pathological condition that results in significant impairments in motor, sensory, and autonomic functions. By integrating multispectral imaging (MSI) with Raman spectroscopy, a label-free optical methodology was developed for achieving a non-invasive in vivo understanding on the pathological features of SCI evolution. Under the guidance of captured the spectral imaging data cube with a rigid endoscope based MSI system, a special designed fiber probe passed through the instrumental channel for acquiring the finger-print spectral information from compression rat SCI models. After identifying the main visual features of injured spinal cord tissue in all Sham, 0-, 3- and 7-days post injury (0 DPI, 3 DPI, and 7 DPI) groups, the blood volume and oxygen content were visualized to describe hemorrhage, hypoxia and inflammatory state after acute injury. The averaged reflectance spectra, which were deduced from MSI data cubes, were utilized for describing oxygen saturation and hemoglobin concentration in living tissue. The results of Raman spectroscopy addressed complex compositional and conformational phenomena during SCI progression, correlated with the well-known event like neuronal apoptosis, hemorrhage, demyelination, and even the upregulation of chondroitin sulfate proteoglycans (CSPGs). A principal component analysis and linear discriminate algorithm (PCA-LDA) based discriminate model was introduced for categorizing spectral features in different injury stages, which was applicable for intraoperative interpretations on the complex pathological courses of SCI and therapeutic outcomes.

Machine Learning and Hyperspectral Imaging for Analysis of Human Papillomaviruses (HPV) Vaccine Self-Healing Particles

Human papillomaviruses (HPV) are known to cause a variety of diseases, including cervical cancer and genital warts. HPV is a highly prevalent virus and is considered the most common sexually transmitted disease. Because of the risks associated with HPV, Gardasil, a quadrivalent recombinant vaccine, was developed by Merck & Co., Inc., Rahway, NJ, USA, and approved by the Food and Drug Administration (FDA) in 2006. The second generation of the vaccine, Gardasil9, was subsequently approved by the FDA in 2014, providing significant protection against HPV. The HPV vaccine may be given as 2 or 3 doses; however, vaccine administration as a single dose with a sustained release mechanism may potentially offer benefits to meet emerging health needs. To explore this, HPV vaccines were formulated within microporous self-healing particles (SHPs) to enable potential controlled release of HPV virus-like particle (VLP) antigen. Machine learning, in the form of multivariate curve resolution-alternating least-squares (MCR-ALS), with Raman hyperspectral imaging was used to determine the molecular identity and spatial distribution of all relevant species within this HPV vaccine formulation. The results indicate that machine learning with Raman hyperspectral imaging was able to spatially resolve HPV VLP antigens within SHP vaccines for the first time, providing crucial information necessary for vaccine development.

SERS-based microdevices for use as in vitro diagnostic biosensors

Advances in surface-enhanced Raman scattering (SERS) detection have helped to overcome the limitations of traditional in vitro diagnostic methods, such as fluorescence and chemiluminescence, owing to its high sensitivity and multiplex detection capability. However, for the implementation of SERS detection technology in disease diagnosis, a SERS-based assay platform capable of analyzing clinical samples is essential. Moreover, infectious diseases like COVID-19 require the development of point-of-care (POC) diagnostic technologies that can rapidly and accurately determine infection status. As an effective assay platform, SERS-based bioassays utilize SERS nanotags labeled with protein or DNA receptors on Au or Ag nanoparticles, serving as highly sensitive optical probes. Additionally, a microdevice is necessary as an interface between the target biomolecules and SERS nanotags. This review aims to introduce various microdevices developed for SERS detection, available for POC diagnostics, including LFA strips, microfluidic chips, and microarray chips. Furthermore, the article presents research findings reported in the last 20 years for the SERS-based bioassay of various diseases, such as cancer, cardiovascular diseases, and infectious diseases. Finally, the prospects of SERS bioassays are discussed concerning the integration of SERS-based microdevices and portable Raman readers into POC systems, along with the utilization of artificial intelligence technology.

Multimodal Biosensing of Foodborne Pathogens

Microbial foodborne pathogens present significant challenges to public health and the food industry, requiring rapid and accurate detection methods to prevent infections and ensure food safety. Conventional single biosensing techniques often exhibit limitations in terms of sensitivity, specificity, and rapidity. In response, there has been a growing interest in multimodal biosensing approaches that combine multiple sensing techniques to enhance the efficacy, accuracy, and precision in detecting these pathogens. This review investigates the current state of multimodal biosensing technologies and their potential applications within the food industry. Various multimodal biosensing platforms, such as opto-electrochemical, optical nanomaterial, multiple nanomaterial-based systems, hybrid biosensing microfluidics, and microfabrication techniques are discussed. The review provides an in-depth analysis of the advantages, challenges, and future prospects of multimodal biosensing for foodborne pathogens, emphasizing its transformative potential for food safety and public health. This comprehensive analysis aims to contribute to the development of innovative strategies for combating foodborne infections and ensuring the reliability of the global food supply chain.

Mosaic quadrivalent influenza vaccine single nanoparticle characterization

Recent work by our laboratory and others indicates that co-display of multiple antigens on protein-based nanoparticles may be key to induce cross-reactive antibodies that provide broad protection against disease. To reach the ultimate goal of a universal vaccine for seasonal influenza, a mosaic influenza nanoparticle vaccine (FluMos-v1) was developed for clinical trial (NCT04896086). FluMos-v1 is unique in that it is designed to co-display four recently circulating haemagglutinin (HA) strains; however, current vaccine analysis techniques are limited to nanoparticle population analysis, thus, are unable to determine the valency of an individual nanoparticle. For the first time, we demonstrate by total internal reflection fluorescence microscopy and supportive physical-chemical methods that the co-display of four antigens is indeed achieved in single nanoparticles. Additionally, we have determined percentages of multivalent (mosaic) nanoparticles with four, three, or two HA proteins. The integrated imaging and physicochemical methods we have developed for single nanoparticle multivalency will serve to further understand immunogenicity data from our current FluMos-v1 clinical trial.

Preparation of arsenic(III) monoclonal antibodies and preliminary evaluation of a novel silver-coated gold nanorod SERS immunoassay strip construction

Heavy metal pollution has become a growing concern in industrial, agricultural, and manufacturing processes, posing a significant threat to human health. Among these heavy metals, arsenic (As) is highly toxic and shares similar chemical properties and environmental behavior with other heavy metals. As(III) is particularly toxic compared to other forms of arsenic. Therefore, it is essential to develop a real-time, rapid, and sensitive method for the determination of As(III). In this study, we employed a unique bifunctional chelator, 1-(4-isothiocyanobenzyl)-ethylenediamine N,N,N',N'-tetraacetic acid (ITCBE), to prepare a complete antigen. Through a series of tests including balb/c mouse immunization, cell fusion (mouse L2041 spleen cells with mouse myeloma cells SP2/0), and subcloning, we generated four monoclonal cell lines (1C1, 2C2, 3A9, and 4A11). These cell lines demonstrated high purity, high affinity, and IC50 values of less than 50 μg mL-1. Monoclonal antibody 4A11, which exhibited a strong Raman signal, was selected as the probe, and Au@Ag 200 was utilized as the surface-enhanced Raman scattering (SERS) substrate for the preliminary establishment of SERS immunochromatographic test strips. The sensitivity of the SERS immunochromatographic test strips, measured through Raman signal detection, showed a significant improvement compared to the SERS immunochromatographic test strips analyzed by colorimetry (LOD = 49.43 μg mL-1 and LDR = 5.32-81.31 μg mL-1). The SERS immunochromatographic test strips achieved a LOD of 7.62 μg mL-1 and an LDR of 12.66-71.84 μg mL-1. This study presents innovative methodologies for the rapid detection of As(III) using SERS immunochromatographic test strips.

A Review on Photonic Sensing Technologies: Status and Outlook

In contemporary science and technology, photonic sensors are essential. They may be made to be extremely resistant to some physical parameters while also being extremely sensitive to other physical variables. Most photonic sensors may be incorporated on chips and operate with CMOS technology, making them suitable for use as extremely sensitive, compact, and affordable sensors. Photonic sensors can detect electromagnetic (EM) wave changes and convert them into an electric signal due to the photoelectric effect. Depending on the requirements, scientists have found ways to develop photonic sensors based on several interesting platforms. In this work, we extensively review the most generally utilized photonic sensors for detecting vital environmental parameters and personal health care. These sensing systems include optical waveguides, optical fibers, plasmonics, metasurfaces, and photonic crystals. Various aspects of light are used to investigate the transmission or reflection spectra of photonic sensors. In general, resonant cavity or grating-based sensor configurations that work on wavelength interrogation methods are preferred, so these sensor types are mostly presented. We believe that this paper will provide insight into the novel types of available photonic sensors.

Biophysical Reviews: And the winner is …

This Editorial (Vol. 15 Issue 2-Regular Issue) first announces the winner of the 2023 Michèle Auger Award for Young Scientists' Independent Research before then going on to describe the contents of the current Issue. The Editorial closes with a discussion of the pros and cons of writing in the formulation of scientific ideas.