Plasmonic Metasurfaces for Specific SERS Detection of Shiga Toxins

Pathogenic Factors and Recent Study on the Rapid Detection of Shiga Toxin-Producing Escherichia coli (STEC)

This comprehensive review delves into the pathogenicity and detection of Shiga Toxin-Producing Escherichia coli (STEC), shedding light on its various genetic and clinical manifestations. STEC originating from E. coli acquires pathogenicity through mobility and genetic elements. The pathogenicity of STEC is explored in terms of clinical progression, complications, and key toxins such as Shiga toxin (Stx). Stx1 and Stx2 are two distinct Stx types exhibiting different toxicities, with Stx2 often associated with severe diseases. This review also delves into Subtilase cytotoxin, an additional cytotoxin produced by some STEC strains. Pathogenic mechanisms of STEC, such as attaching and effacing intestinal lesions, are discussed, with a focus on roles of genetic factors. Plasmids in STEC can confer unique pathogenicity. Hybridization with other pathogenic E. coli can create more lethal pathogens. This review covers a range of detection methods, ranging from DNA amplification to antigen detection techniques, emphasizing the need for innovative approaches to improve the sensitivity and speed of STEC diagnosis. In conclusion, understanding diverse aspects of STEC pathogenicity and exploring enhanced diagnostic methods are critical to addressing this foodborne pathogen effectively. Pathology of Shiga toxin toxicity. STEC-derived Shiga toxin consists of one A subunit and five B subunits. Pathological symptoms of the disease can progress to HUS within two weeks after the onset of diarrhea. Shiga toxin intoxication is also associated with many complications, such as neurological and cardiac complications. This figure was reconstructed based on data from Bruyand et al.

The Label-Free Detection and Identification of SARS-CoV-2 Using Surface-Enhanced Raman Spectroscopy and Principal Component Analysis

The World Health Organization (WHO) declared in a May 2023 announcement that the COVID-19 illness is no longer categorized as a Public Health Emergency of International Concern (PHEIC); nevertheless, it is still considered an actual threat to world health, social welfare and economic stability. Consequently, the development of a convenient, reliable and affordable approach for detecting and identifying SARS-CoV-2 and its emerging new variants is crucial. The fingerprint and signal amplification characteristics of surface-enhanced Raman spectroscopy (SERS) could serve as an assay scheme for SARS-CoV-2. Here, we report a machine learning-based label-free SERS technique for the rapid and accurate detection and identification of SARS-CoV-2. The SERS spectra collected from samples of four types of coronaviruses on gold nanoparticles film, fabricated using a Langmuir-Blodgett self-assembly, can provide more spectroscopic signatures of the viruses and exhibit low limits of detection (<100 TCID50/mL or even <10 TCID50/mL). Furthermore, the key Raman bands of the SERS spectra were systematically captured by principal component analysis (PCA), which effectively distinguished SARS-CoV-2 and its variant from other coronaviruses. These results demonstrate that the combined use of SERS technology and PCA analysis has great potential for the rapid analysis and discrimination of multiple viruses and even newly emerging viruses without the need for a virus-specific probe.

Self-Assembly of Silver Nanowire Films for Surface-Enhanced Raman Scattering Applications

The development of SERS detection technology is challenged by the difficulty in obtaining SERS active substrates that are easily prepared, highly sensitive, and reliable. Many high-quality hotspot structures exist in aligned Ag nanowires (NWs) arrays. This study used a simple self-assembly method with a liquid surface to prepare a highly aligned AgNW array film to form a sensitive and reliable SERS substrate. To estimate the signal reproducibility of the AgNW substrate, the RSD of SERS intensity of 1.0 × 10^-10 M Rhodamine 6G (R6G) in an aqueous solution at 1364 cm^-1 was calculated to be as low as 4.7%. The detection ability of the AgNW substrate was close to the single molecule level, and even the R6G signal of 1.0 × 10^-16 M R6G could be detected with a resonance enhancement factor (EF) as high as 6.12 × 10¹¹ under 532 nm laser excitation. The EF without the resonance effect was 2.35 × 10⁶ using 633 nm laser excitation. FDTD simulations have confirmed that the uniform distribution of hot spots inside the aligned AgNW substrate amplifies the SERS signal.

Latest Advances in Metasurfaces for SERS and SEIRA Sensors as Well as Photocatalysis

Metasurfaces can enable the confinement of electromagnetic fields on huge surfaces and zones, and they can thus be applied to biochemical sensing by using surface-enhanced Raman scattering (SERS) and surface-enhanced infrared absorption (SEIRA). Indeed, these metasurfaces have been examined for SERS and SEIRA sensing thanks to the presence of a wide density of hotspots and confined optical modes within their structures. Moreover, some metasurfaces allow an accurate enhancement of the excitation and emission processes for the SERS effect by supporting resonances at frequencies of these processes. Finally, the metasurfaces allow the enhancement of the absorption capacity of the solar light and the generation of a great number of catalytic active sites in order to more quickly produce the surface reactions. Here, we outline the latest advances in metasurfaces for SERS and SEIRA sensors as well as photocatalysis.

Transcription Factor-Based Biosensors for Detecting Pathogens

Microorganisms are omnipresent and inseparable from our life. Many of them are beneficial to humans, while some are not. Importantly, foods and beverages are susceptible to microbial contamination, with their toxins causing illnesses and even death in some cases. Therefore, monitoring and detecting harmful microorganisms are critical to ensuring human health and safety. For several decades, many methods have been developed to detect and monitor microorganisms and their toxicants. Conventionally, nucleic acid analysis and antibody-based analysis were used to detect pathogens. Additionally, diverse chromatographic methods were employed to detect toxins based on their chemical and structural properties. However, conventional techniques have several disadvantages concerning analysis time, sensitivity, and expense. With the advances in biotechnology, new approaches to detect pathogens and toxins have been reported to compensate for the disadvantages of conventional analysis from different research fields, including electrochemistry, nanotechnology, and molecular biology. Among them, we focused on the recent studies of transcription factor (TF)-based biosensors to detect microorganisms and discuss their perspectives and applications. Additionally, the other biosensors for detecting microorganisms reported in recent studies were also introduced in this review.