Identifying infectiousness of SARS-CoV-2 by ultra-sensitive SnS2 SERS biosensors with capillary effect

Single-molecule detection and imaging are of great value in chemical analysis, biomarker identification and other trace detection fields. However, the localization and visualization of single molecule are still quite a challenge. Here, we report a special-engineered nanostructure of Ag nanoparticles embedded in multi-layer black phosphorus nanosheets (Ag/BP-NS) synthesized by a unique photoreduction method as a surface-enhanced Raman scattering (SERS) sensor. Such a SERS substrate features the lowest detection limit of 10–20 mol L−1 for R6G, which is due to the three synergistic resonance enhancement of molecular resonance, photo-induced charge transfer resonance and electromagnetic resonance. We propose a polarization-mapping strategy to realize the detection and visualization of single molecule. In addition, combined with machine learning, Ag/BP-NS substrates are capable of recognition of different tumor exosomes, which is meaningful for monitoring and early warning of the cancer. This work provides a reliable strategy for the detection of single molecule and a potential candidate for the practical bio-application of SERS technology. 

/pdf/visualized-sers-imaging-of-single-molecule-by-ag-black-302au6ou.pdf

Visualized SERS Imaging of Single Molecule by Ag/Black Phosphorus Nanosheets

During the COVID-19 pandemic, the development of sensitive and rapid techniques for detection of viruses have become vital. Surface-enhanced Raman scattering (SERS) is an appropriate tool for new techniques due to its high sensitivity. SERS materials modified with short-structured oligonucleotides (DNA aptamers) provide specificity for SERS biosensors. Existing SERS-based aptasensors for rapid virus detection are either inapplicable for quantitative determination or have sophisticated and expensive construction and implementation. In this paper, we provide a SERS-aptasensor based on colloidal solutions which combines rapidity and specificity in quantitative determination of SARS-CoV-2 virus, discriminating it from the other respiratory viruses.

https://www.mdpi.com/2079-4991/11/6/1394/pdf

SERS-Based Aptasensor for Rapid Quantitative Detection of SARS-CoV-2.

The world today is witnessing the significant role and huge demand for molecular detection and screening in healthcare and medical diagnosis, especially during the outbreak of COVID-19. Surface-enhanced spectroscopy techniques, including Surface-Enhanced Raman Scattering (SERS) and Infrared Absorption (SEIRA), provide lattice and molecular vibrational fingerprint information which is directly linked to the molecular constituents, chemical bonds, and configuration. These properties make them an unambiguous, nondestructive, and label-free toolkit for molecular diagnostics and screening. However, new issues in molecular diagnostics, such as increasing molecular species, faster spread of viruses, and higher requirements for detection accuracy and sensitivity, have brought great challenges to detection technology. Advancements in artificial intelligence and machine learning (ML) techniques show promising potential in empowering SERS and SEIRA with rapid analysis and automatic data processing to jointly tackle the challenge. This review introduces the combination of ML and SERS/SEIRA by investigating how ML algorithms can be beneficial to SERS/SEIRA, discussing the general process of combining ML and SEIRA/SERS, highlighting the molecular diagnostics and screening applications based on ML-combined SEIRA/SERS, and providing perspectives on the future development of ML-integrated SEIRA/SERS. In general, this review offers comprehensive knowledge about the recent advances and the future outlook regarding ML-integrated SEIRA/SERS for molecular diagnostics and screening.

/pdf/machine-learning-augmented-surface-enhanced-spectroscopy-16tbd1e8.pdf

Machine learning-augmented surface-enhanced spectroscopy toward next-generation molecular diagnostics

Abstract Coronavirus disease 2019 (COVID-19) is a highly contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The gold standard method for the diagnosis of SARS-CoV-2 depends on quantitative reverse transcription-polymerase chain reaction till now, which is time-consuming and requires expensive instrumentation, and the confirmation of variants relies on further sequencing techniques. Herein, we first proposed a robust technique-methodology of electrochemical CRISPR sensing with the advantages of rapid, highly sensitivity and specificity for the detection of SARS-CoV-2 variant. To enhance the sensing capability, gold electrodes are uniformly decorated with electro-deposited gold nanoparticles. Using DNA template identical to SARS-CoV-2 Delta spike gene sequence as model, our biosensor exhibits excellent analytical detection limit (50 fM) and high linearity ( R 2 = 0.987) over six orders of magnitude dynamic range from 100 fM to 10 nM without any nucleic-acid-amplification assays. The detection can be completed within 1 h with high stability and specificity which benefits from the CRISPR-Cas system. Furthermore, based on the wireless micro-electrochemical platform, the proposed biosensor reveals promising application ability in point-of-care testing. 

/pdf/crispr-cas12a-empowered-electrochemical-biosensor-for-rapid-2e467wcr.pdf

CRISPR-Cas12a-Empowered Electrochemical Biosensor for Rapid and Ultrasensitive Detection of SARS-CoV-2 Delta Variant

The current COVID-19 pandemic urges the extremely sensitive and prompt detection of SARS-CoV-2 virus. Here, we present a Human Angiotensin-converting-enzyme 2 (ACE2)-functionalized gold "virus traps" nanostructure as an extremely sensitive SERS biosensor, to selectively capture and rapidly detect S-protein expressed coronavirus, such as the current SARS-CoV-2 in the contaminated water, down to the single-virus level. Such a SERS sensor features extraordinary 106-fold virus enrichment originating from high-affinity of ACE2 with S protein as well as "virus-traps" composed of oblique gold nanoneedles, and 109-fold enhancement of Raman signals originating from multi-component SERS effects. Furthermore, the identification standard of virus signals is established by machine-learning and identification techniques, resulting in an especially low detection limit of 80 copies mL-1 for the simulated contaminated water by SARS-CoV-2 virus with complex circumstance as short as 5 min, which is of great significance for achieving real-time monitoring and early warning of coronavirus. Moreover, here-developed method can be used to establish the identification standard for future unknown coronavirus, and immediately enable extremely sensitive and rapid detection of novel virus.

/pdf/human-ace2-functionalized-gold-virus-trap-nanostructures-for-hg6ysfs3sk.pdf

Human ACE2-Functionalized Gold “Virus-Trap” Nanostructures for Accurate Capture of SARS-CoV-2 and Single-Virus SERS Detection

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Human ACE2-Functionalized Gold “Virus-Trap” Nanostructures for Accurate Capture of SARS-CoV-2 and Single-Virus SERS Detection