Establishment of a Simple, Sensitive, and Specific Salmonella Detection Method Based on Recombinase-Aided Amplification Combined with dsDNA-Specific Nucleases.

Salmonella is a common foodborne pathogen that can cause food poisoning, posing a serious threat to human health. Therefore, quickly, sensitively, and accurately detecting Salmonella is crucial to ensuring food safety. For the Salmonella hilA gene, we designed Recombinase-aided amplification (RAA) primers and dsDNA-specific nuclease (DNase) probes. The ideal primer and probe combination was found when conditions were optimized. Under UV light, a visual Salmonella detection technique (RAA-dsDNase) was developed. Additionally, the RAA-dsDNase was modified to further reduce pollution hazards and simplify operations. One-pot RAA-dsDNase-UV or one-pot RAA-dsDNase-LFD was developed as a Salmonella detection method, using UV or a lateral flow dipstick (LFD) for result observation. Among them, one-pot RAA-dsDNase and one-pot RAA-dsDNase-LFD had detection times of 50 min and 60 min, respectively, for detecting Salmonella genomic DNA. One-pot RAA-dsDNase-UV had a detection limit of 101 copies/µL and 101 CFU/mL, while one-pot RAA-dsDNase-LFD had a sensitivity of 102 copies/µL and 102 CFU/mL. One-pot RAA-dsDNase-UV and one-pot RAA-dsDNase-LFD assays may identify 17 specific Salmonella serovars witho ut causing a cross-reaction with the remaining 8 bacteria, which include E. coli. Furthermore, Salmonella in tissue and milk samples has been reliably detected using both approaches. Overall, the detection method developed in this study can quickly, sensitively, and accurately detect Salmonella, and it is expected to become an important detection tool for the prevention and control of Salmonella in the future.

Pyrococcus furiosus Argonaute Based Detection Assays for Porcine Deltacoronavirus.

Porcine deltacoronavirus (PDCoV) is a major cause of diarrhea and diarrhea-related deaths among piglets and results in massive losses to the overall porcine industry. The clinical manifestations of porcine diarrhea brought on by the porcine epidemic diarrhea virus (PEDV), porcine transmissible gastroenteritis virus (TGEV), and PDCoV are oddly similar to each other. Hence, the identification of different pathogens through molecular diagnosis and serological techniques is crucial. Three novel detection methods for identifying PDCoV have been developed utilizing recombinase-aided amplification (RAA) or reverse transcription recombinase-aided amplification (RT-RAA) in conjunction with Pyrococcus furiosus Argonaute (PfAgo): RAA-PfAgo, one-pot RT-RAA-PfAgo, and one-pot RT-RAA-PfAgo-LFD. The indicated approaches have a detection limit of around 60 copies/µL of PDCoV and do not cross-react with other viruses including PEDV, TGEV, RVA, PRV, PCV2, or PCV3. The applicability of one-pot RT-RAA-PfAgo and one-pot RT-RAA-PfAgo-LFD were examined using clinical samples and showed a positive rate comparable to the qPCR method. These techniques offer cutting-edge technical assistance for identifying, stopping, and managing PDCoV.

Establishment of a simple, sensitive, and specific ASFV detection method based on Pyrococcus furiosus argonaute.

African swine fever (ASF), which is casued by African swine fever virus (ASFV), is a fatal infectious disease of pigs that results in significant losses to the breeding industry. Therefore, screening and detection are crucial for the control and prevention of the ASFV. Argonaute is a new detection tool that is being extensively used due to its high specificity and programmability. This study reports on a new nucleic acid assay method, termed REPD, which uses recombinase-aided amplification and restriction endonuclease-assisted Pyrococcus furiosus argonaute (PfAgo) detection. One-pot REPD was developed for the detection of ASFV. The one-pot REPD could detect a single copy of ASFV nucleic acid and showed no cross-reactivity with other pathogens. Detection in clinical samples was 100% consistent with the results of real-time PCR analysis. The results showed that the one-pot REPD assay is convenient, sensitive, specific, and potentially adaptable to the detection of ASFV. In summary, this study highlights a novel method that can be employed for the detection of pathogens.

Pyrococcus furiosus Argonaute-mediated porcine epidemic diarrhea virus detection.

Porcine epidemic diarrhea virus (PEDV), an enteric coronavirus, induces severe vomiting and acute watery diarrhea in unweaned piglets. The pig industry has suffered tremendous financial losses due to the high mortality rate of piglets caused by PEDV. Consequently, a simple and rapid on-site diagnostic technology is crucial for preventing and controlling PEDV. This study established a detection method for PEDV using recombinase-aided amplification (RAA) and Pyrococcus furiosus Argonaute (PfAgo), which can detect 100 copies of PEDV without cross-reactivity with other pathogens. The entire reaction of RAA and PfAgo to detect PEDV does not require sophisticated instruments, and the reaction results can be observed with the naked eye. Overall, this integrated RAA-PfAgo cleavage assay is a practical tool for accurately and quickly detecting PEDV. KEY POINTS: • PfAgo has the potential to serve as a viable molecular diagnostic tool for the detection and diagnosis of viral genomes • The RAA-PfAgo detection technique has a remarkable level of sensitivity and specificity • The RAA-PfAgo detection system can identify PEDV without needing advanced equipment.

Non-local generative machine learning-based inverse design for scattering properties.

Metamaterials are created by arranging small scatterers in a regular array throughout a space to manipulate electromagnetic waves. However, current design methods view metasurfaces as independent meta-atoms, which limits the range of geometrical structures and materials used, and prevents the generation of arbitrary electric field distributions. To address this issue, we propose an inverse design method based on generative adversarial networks (GANs), which includes both a forward model and an inverse algorithm. The forward model utilizes dyadic Green's function to interpret the expression of non-local response, realizing the mapping from scattering properties to generated electric fields. The inverse algorithm innovatively transforms the scattering properties and electric fields into images and generates datasets with methods in computer vision (CV), proposing an architecture of GAN with ResBlock to achieve the design for the target electric field pattern. Our algorithm improves upon traditional methods, as it achieves greater time efficiency and generates higher quality electric fields. From a metamaterial perspective, our method can find optimal scattering properties for specific generated electric fields. Training results and extensive experiments demonstrate the algorithm's validity.

Sensitive detection of viable salmonella bacteria based on tertiary cascade signal amplification via splintR ligase ligation-PCR amplification-CRISPR/Cas12a cleavage.

Several viable Salmonella bacteria are capable of causing severe human diseases and huge economic losses. In this regard, viable Salmonella bacteria detection techniques that can identify small numbers of microbial cells are highly valuable. Here, we present a detection method (referred to as SPC) based on the amplification of tertiary signals using splintR ligase ligation, PCR amplification and CRISPR/Cas12a cleavage. The detection limit of the SPC assay was 6 copies (HilA RNA) and 10 CFU (cell). Based on Intracellular HilA RNA detection, this assay can be used to distinguish between viable and dead Salmonella. In addition, it is able to detect multiple serotypes of Salmonella and has been successfully used to detect Salmonella in milk or isolated from farms. Overall, this assay is a promising test for viable pathogens detection and biosafety control.