Preparation and epitope mapping of monoclonal antibodies against African swine fever virus p22 protein.

African swine fever (ASF), caused by the African swine fever virus (ASFV), is now widespread in many countries and severely affects the commercial rearing of swine. Rapid and early diagnosis is crucial for the prevention of ASF. ASFV mature virions comprise the inner envelope protein, p22, making it an excellent candidate for the serological diagnosis and surveillance of ASF. In this study, the prokaryotic-expressed p22 recombinant protein was prepared and purified for immunization in mice. Four monoclonal antibodies (mAbs) were identified using hybridoma cell fusion, clone purification, and immunological assays. The epitopes of mAbs 14G1 and 22D8 were further defined by alanine-scanning mutagenesis. Our results showed that amino acids C39, K40, V41, D42, C45, G48, E49, and C51 directly bound to 14G1, while the key amino acid epitope for 22D8 included K161, Y162, G163, D165, H166, I167, and I168. Homologous and structural analysis revealed that these sites were highly conserved across Asian and European ASFV strains, and the amino acids identified were located on the surface of p22. Thus, our study contributes to a better understanding of the antigenicity of the ASFV p22 protein, and the results could facilitate the prevention and control of ASF.

Development and application of a low-priced duplex quantitative PCR assay based on SYBR Green I for the simultaneous detection of porcine deltacoronavirus and porcine sapelovirus.

Porcine deltacoronavirus (PDCoV) and porcine sapelovirus (PSV) are two viruses that can cause diarrhoea in pigs and bring great economic loss to the pig industry. In this research, a duplex real-time quantitative polymerase chain reaction (qPCR) assay based on SYBR Green I was developed to simultaneously detect PDCoV and PSV. No specific melting peaks were found in other porcine diarrhoea-associated viruses, indicating that the method developed in this study had good specificity. The detection limits of PDCoV and PSV were 1.0 × 101 copies µl-1 and 1.0 × 102 copies µl-1, respectively. The duplex real-time qPCR assay tested two hundred and three (203) intestinal and faecal samples collected from diarrhoeal and asymptomatic pigs. The positive rates of PDCoV and PSV were 20.2% and 23.2%, respectively. The co-infection rate of PDCoV and PSV was 13.8%. To evaluate the accuracy of the developed method, conventional PCR and singular TaqMan real-time qPCR assays for PDCoV/PSV were also used to detect the samples. The results showed that the duplex real-time qPCR assay was consistent with the singular assays, but its sensitivity was higher than conventional PCR methods. This duplex real-time qPCR assay provides a rapid, sensitive and reliable method in a clinic to simultaneously detect PDCoV and PSV.

An improved faster R-CNN algorithm for assisted detection of lung nodules.

The morbidity and mortality of lung cancer are increasing rapidly in every country in the world, and pulmonary nodules are the main symptoms of lung cancer in the early stage. If we can diagnose pulmonary nodules in time at the early stage and follow up and treat suspicious patients, we can effectively reduce the incidence of lung cancer. CT (Computed Tomography) has been applied to the screening of many diseases because of its high resolution. Pulmonary nodules show white round shadows in CT images. With the popularity of CT equipment, doctors need to review a large number of imaging results every day. Doctors will misjudge and miss the lesions because of reviewing CT scanning results for a long time. At this time, the method of automatic detection of pulmonary nodules by computer can relieve the pressure of doctors in reviewing CT scan results. Traditional lung nodule detection methods, such as gray threshold method and region growing method, divide the detection process into two steps: extracting candidate regions and eliminating false regions. In addition, the traditional detection method can only operate on a single image, which leads to the inability of this method to detect the batch scanning results in real time. With the continuous development of computer equipment performance and artificial intelligence, the relationship between medical image processing and deep learning is getting closer and closer. In deep learning, object detection methods such as Faster R-CNN、YOLO can complete parallel detection of batch images, and deep structure can fully extract the features of input images. Compared with traditional lung nodule detection methods, it has the characteristics of high efficiency and high precision. Faster R-CNN is a classical and high-precision two-stage object detection method. In this paper, an improved Faster R-CNN model is proposed. On the basis of Faster R-CNN, multi-scale training strategy is used to fully mine the features of different scale spaces and perform path augmentation on lower-dimensional features, which improves the small object detection ability of the model. Through Online Hard Example Mining (OHEM), the loss value is used to quantify the difficulty of candidate region detection, and the training times of the region to be detected are adaptively adjusted. Make full use of prior information to customize the size and proportion of preset boundary anchor boxes. Using deformable convolution to improve the visual field to enhance the global features and enhance the ability to extract the feature information of pulmonary nodules in the same scale space. The new model was tested on LUNA16 (Lung Nodule Analysis 2016) dataset. The detection precision of the improved Faster R-CNN model for pulmonary nodules increased from 76.4% to 90.7%, and the recall rate increased from 40.1% to 56.8% Compared with the mainstream object detection algorithms YOLOv3 and Cascade R-CNN, the improved model is superior to the above models in every index.

Preparation of monoclonal antibody and identification of two novel B cell epitopes to VP1 protein of porcine sapelovirus.

Porcine sapelovirus (PSV) is an important emerging swine pathogen that causes diarrhoea, respiratory distress, severe reproductive system and neurological disorders in pigs, posing huge threat to swine industry. However, there are no effective serological diagnostic products and the epitope characterization of PSV VP1 protein is still largely unknown. In current study, we successfully expressed recombinant His-VP1 protein by prokaryotic expression system and the recombinant VP1 protein had good immunogenicity. BALB/C mice were then selected and immunized with purified recombinant VP1 protein, and two monoclonal antibodies (Mabs) 9F10 and 15E4 against VP1 were successfully prepared by hybrioma technology. The isotype of these two Mabs were identified and showed that Mab 9F10 with the heavy chain subtype was IgG1 and the light chain subtype was kappa. Mab 15E4 was identified as IgG2 for the heavy chain subtype and Kappa for the light chain subtype. The antigen epitopes of prepared two VP1 Mabs were clearly identified. The minimal unit of B cell specific epitope recognized by Mab 15E4 was 203YDGDG207 and conserved in different strain genotypes of PSV, indicating this epitope may be a good target for serological detection of PSV. However, the epitope recognized by Mab 9F10 was 8QAIVNRT14 and varied greatly among different PSV strains. Structural modeling analysis showed that the identified two novel B cell epitopes were located on the surface of VP1. Our study provides useful tool for the establishment the serological detection methods of PSV and may support the study of VP1 protein function.

Preparation of a Single-Chain Antibody against Nucleocapsid Protein of Porcine Deltacoronavirus by Phage Display Technology.

Porcine deltacoronavirus (PDCoV) mainly causes severe diarrhea and intestinal pathological damage in piglets and poses a serious threat to pig farms. Currently, no effective reagents or vaccines are available to control PDCoV infection. Single-chain fragment variable (scFv) antibodies can effectively inhibit virus infection and may be a potential therapeutic reagent for PDCoV treatment. In this study, a porcine phage display antibody library from the peripheral blood lymphocytes of piglets infected with PDCoV was constructed and used to select PDCoV-specific scFv. The library was screened with four rounds of biopanning using the PDCoV N protein, and the colony with the highest affinity to the PDCoV N protein was obtained (namely, N53). Then, the N53-scFv gene fragment was cloned into plasmid pFUSE-hIgG-Fc2 and expressed in HEK-293T cells. The scFv-Fc antibody N53 (namely, scFv N53) was purified using Protein A-sepharose. The reactive activity of the purified antibody with the PDCoV N protein was confirmed by indirect enzyme-linked immunosorbent assay (ELISA), western blot and indirect immunofluorescence assay (IFA). Finally, the antigenic epitopes that the scFv N53 recognized were identified by a series of truncated PDCoV N proteins. The amino acid residues 82GELPPNDTPATTRVT96 of the PDCoV N protein were verified as the minimal epitope that can be recognized by the scFv-Fc antibody N53. In addition, the interaction between the scFv-Fc antibody N53 and the PDCoV N protein was further analyzed by molecule docking. In conclusion, our research provides some references for the treatment and prevention of PDCoV.

Expression of porcine interferon-α and its bioactivity analysis in vitro and in vivo.

Interferon α (IFN-α) plays a crucial role in the host's immune response. In this study, the amino acid sequence of porcine interferon α (PoIFN-α) was analyzed. Seven substitutions, S38F, H40Q, F43L, N78D, Y86C, S151A, and R156T, were mutated and obtained by aligning the sequences of PoIFN-α subtypes. The PoIFN-α mutants were designed, expressed, and purified in E. coli. The antiviral activities of these PoIFN-αs were measured in Vero and swine testis cells against vesicular stomatitis virus (VSV). Their inhibitory abilities on pseudorabies virus (PRV) were also examined. Commercial PoIFN-α was used as a control. We found the ideal inducer concentration of isopropyl ß-D-thiogalactoside was 1 mM, and the best time-point for induction was 8 h. The PoIFN-α mutant named PoIFN-α-156s had the highest antiviral activity, which was about 200-fold more than that of PoIFN-α. PoIFN-α-156s could inhibit VSV and PRV replication in a dose-dependent manner in vitro. The half-life of PoIFN-α-156s was longer than that of PoIFN-α in mice, and the effective antiviral action was higher than PoIFN-α. Animal experiments showed that PoIFN-α-156s could decrease the viral load after infection with VSV. Overall, these results suggest that recombinant PoIFN-α-156s has the ability of antivirus, and is feasible for veterinary clinical applications and fundamental research.