ATR8800 rapid test for respiratory diseases with high incidence in winter

Introduction

Winter is a period of high incidence of respiratory tract infections. Currently, respiratory diseases prevalent in my country are caused by a variety of pathogens, including bacteria, mycoplasma, influenza viruses, and the new coronavirus that has caused a global pandemic. Given that respiratory diseases are highly contagious and spread quickly, and respiratory infections caused by different pathogens have significant differences in symptoms and treatments, early detection and diagnosis are important means to effectively curb the spread of respiratory diseases. Although traditional isolation and culture methods have significant advantages in terms of accuracy and authority, they are no longer able to meet the actual needs of current clinical testing due to their cumbersome operations, long time consumption, and biosafety risks. Currently, the main detection methods used include nucleic acid detection and immunological detection. However, these methods require professional laboratory equipment, operators need to receive professional training, the cost is relatively high, and the detection cycle is also relatively lengthy, which cannot meet the rapidly increasing number of respiratory tract infections. There is an urgent need for large-scale on-site detection of disease samples, and therefore there is an urgent need to develop new respiratory virus detection technologies.

When light strikes a substance and scatters, the scattered light that changes wavelength is called Raman scattering. The reason for the change in wavelength is that after the energy transfer occurs between the photon and the molecules of the irradiated material, the vibrational energy level of the molecule changes. The energy transferred when the photon is Raman scattered on different materials is different, and the irradiated material can be specifically identified. type. Surface-enhanced Raman spectroscopy (SERS) technology is based on ordinary Raman scattering, which adsorbs or connects the irradiated substance to the rough noble metal surface, greatly improving the Raman signal intensity. On the basis of the inherent non-destructive analysis of ordinary Raman scattering, which is not affected by water components, does not require complicated sample processing, has fast detection speed, and can be used for on-site analysis using portable instruments, SERS technology has higher sensitivity and can be used under certain conditions. It can reach single molecule detection level. By analyzing biological samples from patients, this technology can quickly detect specific molecular markers that can identify the specific causative agent of respiratory disease. It helps medical professionals make accurate diagnoses earlier and provide patients with more timely and personalized treatment plans. By shortening diagnosis time and reducing the tedious process of traditional examinations, rapid testing methods are expected to play a key role in preventing and controlling infectious diseases, improving medical efficiency, and reducing medical burden, and provide more effective support for the treatment of respiratory diseases.

Application of SERS technology in COVID-19 detection

The new coronavirus is the seventh coronavirus that can infect humans and is extremely contagious. Therefore, it is particularly urgent to develop a new ultra-fast and highly sensitive detection method. LEONG et al. designed a handheld new coronavirus detector based on SERS technology. The instrument integrates three types of chips, each equipped with three sets of SERS probe molecules: 2-mercaptobenzoic acid, 4-mercaptopyridine and adenosine triphosphate. These SERS probe molecules are immobilized on the surface of silver nanoparticles. During the detection process, the subject exhales into the device for about 10 seconds. Since the new coronavirus biomarkers in the breath react chemically with the sensor, the reacted compounds can be characterized through changes in the SERS signal. Regarding the on-site testing of 501 people for the new coronavirus in hospitals and airports, the research results of LEONG et al. showed that the false negative rate of this testing method was 3.8% and the false positive rate was 0.1%. This is comparable in accuracy to polymerase chain reaction testing and is less expensive, with the test taking only 5 minutes. It is worth noting that this instrument is not only capable of detecting changes in the types of biogenic volatile organic compounds, but can also be used to screen for other types of respiratory viral infections.

Figure 1 Scheme design for identifying COVID-19 positive individuals based on respiratory volatile organic compounds

Application of SERS technology in influenza virus detection

Influenza viruses have high infectivity and mutation rates, which may trigger seasonal epidemics or even lead to global pandemics, posing a serious burden to public health. Therefore, there is an urgent need to develop an accurate and rapid influenza virus detection method to curb the spread of influenza through timely and precise detection before it breaks out. Chen et al. developed an aptasensor based on dual-mode surface-enhanced Raman scattering (SERS), which can accurately diagnose and distinguish the new coronavirus and influenza A H1N1 at the same time. In this technology, DNA aptamers that selectively bind SARS-CoV-2 and influenza A (H1N1) are co-immobilized on a popcorn-shaped gold nanosubstrate. Raman reporter genes (Cy3 and RRX), connected to the ends of DNA aptamers, can generate strong SERS signals in the nanogaps of gold nanosubstrates. At the same time, the internal standard Raman reporter gene (4-MBA) was fixed on the gold nanosubstrate together with the aptamer DNA to reduce errors caused by changes in the measurement environment. When SARS-CoV-2 or influenza A virus approaches a gold nanosubstrate, the relevant DNA aptamer is selectively detached from the substrate due to the significant binding affinity between the corresponding DNA aptamer and the virus. Therefore, as the target virus concentration increases, the corresponding SERS intensity gradually decreases. This SERS-based DNA aptamer sensor can quickly determine whether a suspected patient is infected with SARS-CoV-2 or influenza A, while quantitatively assessing the target virus concentration with high sensitivity without being affected by cross-reactivity.

Figure 2 (a) Symptoms that occur when infected with SARS-CoV-2 or influenza A, and RT-PCR and rapid antigen kits for diagnosis; (b) Photographs and SEM images of popcorn-shaped gold nanosubstrates; ( c) Working principle of dual-aptamer-immobilized popcorn-like gold nanosubstrates for virus detection

Application of SERS technology in bacterial infection detection

Bacterial infections are the leading cause of death, claiming 6.7 million lives each year in developed and developing countries. These infections are also expensive to treat, accounting for 8.7%, or $33 billion, of annual healthcare spending in the United States alone. Current diagnostic methods require sample culture to detect and identify bacteria and their antibiotic sensitivities, a slow process that can take days even in the most advanced laboratories. Broad-spectrum antibiotics are often prescribed while awaiting culture results, and more than 30 percent of patients receive unnecessary treatment, according to the Centers for Disease Control and Prevention. New methods for rapid, culture-free diagnosis of bacterial infections are therefore needed to enable the prescribing of targeted antibiotics earlier and help mitigate antimicrobial resistance. Raman spectroscopy has the potential to identify bacterial species and antibiotic resistance and, when combined with confocal spectroscopy, enables the analysis of individual bacterial cells. Different bacterial phenotypes have unique molecular compositions, resulting in subtle differences in their corresponding Raman spectra. However, due to the low efficiency of Raman scattering (~10−8 scattering probability), these subtle spectral differences are easily masked by background noise. Therefore, a high signal-to-noise ratio is required to achieve high identification accuracy, often requiring long measurement times, which hinders the development of high-throughput single-cell technologies.Furthermore, the large number of clinically relevant species, strains, and antibiotic resistance patterns requires comprehensive data sets that have not been collected in studies focused on distinguishing species isolates or antibiotic susceptibilities. Ho et al. addressed this challenge by combining SERS technology with convolutional neural network training to classify bacterial SERS spectra by isolation, empirical treatment, and antibiotic resistance.

Figure 3 Convolutional neural network used to identify bacteria from SERS spectra

Conclusion

With the advancement of SERS technology, there are currently three main application ideas in the field of detection: (1) attaching specific nucleic acid sequences and antibodies to the surface of nanoparticles to construct SERS tags, thereby achieving accurate detection of respiratory viruses in complex body fluids; (2) Use new enhanced substrate preparation technology to make the size of the "hot spots" between nanoparticles more suitable for virus particles, improve detection efficiency, reduce costs, and effectively avoid the interference of biological backgrounds such as saliva and blood on the detection results; (3) ) is used in conjunction with other detection technologies, such as SERS-chromatography combined technology, which assembles a SERS-enhanced substrate onto an optical fiber to serve as a highly sensitive detection sensor. Furthermore, combining SERS and plasmonic sensing can be used for highly sensitive quantitative detection of biomolecular interactions. SERS technology overcomes the shortcomings of weak signals in ordinary Raman spectroscopy and provides structural information that is difficult to obtain.

SERS technology has made significant progress in the detection of respiratory disease pathogens. However, in order to more comprehensively and in-depth study and diagnosis of respiratory viruses, researchers usually choose to use confocal micro-Raman spectroscopy. This instrument combines the features of confocal laser microscopy and Raman spectroscopy to provide unique advantages for SERS detection of respiratory disease pathogens:

High spatial resolution: The confocal Raman microscope has high-resolution imaging capabilities and can observe the structure and organization of samples at the microscopic scale. In the detection of respiratory disease pathogens, this high spatial resolution can help researchers accurately locate and observe tiny virus particles or cellular structures.

Depth information acquisition: The confocal Raman microscope can realize three-dimensional imaging and provide researchers with depth information inside the sample. This is crucial for understanding the distribution and interactions of pathogens at different cellular levels, helping to provide a more comprehensive understanding of the development of respiratory diseases.

Real-time monitoring: The confocal Raman microscope has a real-time monitoring function and can track the dynamic changes of pathogens in samples. In the study of respiratory diseases, real-time monitoring helps researchers understand the life cycle of the virus, the infection process, and the effectiveness of therapeutic interventions.

Reduce background interference: The confocal Raman microscope can reduce background signal interference by precisely controlling the focus. This is particularly important for highly sensitive SERS detection in complex biological samples to ensure the accuracy and reliability of detection results.

Optosky ATR8800 series micro-Raman spectrometer integrates up to 4 lasers and combines the advantages of both microscopes and Raman spectrometers. The micro-Raman detection platform makes it possible to "what you see is what you measure", visualization The precise positioning Raman detection platform allows observers to detect Raman signals of different surface states on the sample, and can simultaneously display the micro-area morphology at the detected location on the computer, which greatly facilitates Raman micro-area detection.

The entire series of ATR8800 can perform fully automatic focusing, fully automatic scanning, and one-click operation. It can perform batch experiments, uniformity scanning, etc. without waiting, and can obtain highly reliable scanning imaging Raman data;

The ATR8800 is equipped with spectrometers of different focal lengths to meet different resolution requirements. The ATR8800 is also equipped with an objective lens specially designed for the Raman system, which makes the laser spot close to the diffraction limit. The focus information is accurately and intuitively displayed on the computer through a 5-megapixel camera. It overcomes the problem in ordinary Raman systems that the focal plane for collecting Raman signals is slightly higher or slightly lower than the actual optimal focal plane, thereby improving the quality of the Raman spectrum.

ATR8800 perfectly solves the loss of optical path for camera imaging and realizes the separation of camera imaging and Raman signal collection, thereby obtaining the best signal strength. At the same time, ATR8800 uses high-performance Raman specially optimized for micro-Raman systems. It is industry-leading in terms of sensitivity, signal-to-noise ratio, stability, etc., providing a strong guarantee for Raman research.