Identification of B-cell epitope on the N protein of type 1 Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) using monoclonal antibody and construction of epitope-mutated virus.

The escalating epidemic of PRRSV-1 in China has prompted widespread concern regarding the evolution of strains, disparities in pathogenicity to herds, and immunological detection of emerging strains. The nucleocapsid (N) protein, as a highly conserved protein with immunogenic properties in PRRSV, is a subject of intensive study. In this research, the recombinant His-N protein was expressed based on the N gene of PRRSV-1 using a prokaryotic expression system and then administered to BALB/c mice. A cell fusion protocol was implemented between SP2/0 cells and splenocytes, resulting in the successful screening of a monoclonal antibody against the N protein, designated as mAb 2D7, by indirect ELISA. Western Blot analysis and Indirect Immunofluorescence Assay (IFA) confirmed that mAb 2D7 positively responded to PRRSV-1. By constructing and expressing a series of truncated His-fused N proteins, a B-cell epitope of N protein, 59-AAEDDIR-65, was identified. A sequence alignment of two genotypes of PRRSV revealed that this epitope is relatively conserved in PRRSV, yet more so in genotype 1. Cross-reactivity analysis by Western blot analysis demonstrated that the B-cell epitope containing D62Y mutation could not be recognized by mAb 2D7. The inability of mAb 2D7 to recognize the epitope carrying the D62Y mutation was further determined using an infectious clone of PRRSV. This research may shed light on the biological significance of the N protein of PRRSV, paving the way for the advancement of immunological detection and development of future recombinant marker vaccine.

Construction and characterization of recombinant senecavirus A expressing secreted luciferase for antiviral screening.

Senecavirus A (SVA) is a newly identified picornavirus associated with swine vesicular disease and neonatal mortality. The development of an SVA incorporating an exogenous reporter gene provides a powerful tool for viral research. In this study, we successfully constructed a recombinant SVA expressing Gaussia Luciferase (Gluc), termed rSVA-Gluc. The growth kinetics of rSVA-Gluc in BHK-21 cells were found to be comparable to those of the parental virus, and Gluc activity paralleled the virus growth curve. Genetic analysis revealed stable inheritance of the inserted reporter protein genes for at least six generations. We evaluated the utility of rSVA-Gluc in antiviral drug screening, and the results highlighted its potential as an effective tool for such purposes against SVA. DATA AVAILABILITY STATEMENT: The data that support the findings of this study are available on request from the corresponding author.

Development of a monoclonal antibody specifically recognizing a linear epitope on the capsid protein of the emerging Group III Getah virus.

Getah virus (GETV) is an emerging mosquito-borne alphavirus that can infect horses, pigs and other animals. Given the public health threat posed by GETV, research on its pathogenesis, diagnosis and prevention is urgently needed. In the current study, prokaryotic expression systems were used to express the capsid protein of GETV. This protein was then used to immunize BALB/c mice in order to generate monoclonal antibodies (mAbs). Subsequently, hybridoma cells secreting a mAb (2B11-4) against the capsid protein were obtained using the hybridoma technique. A B cell linear epitope, 18-PAYRPWR-24, located at the capsid protein's N-terminal region was identified using western blotting analysis with the produced mAb, 2B11-4. Sequence alignment indicated that this epitope was highly conserved in group III (GIII) strains of GETV, but varied among the other genotypes. Western blotting showed that mAb 2B11-4 could discriminate Group III GETVs from other genotypes. This study describes the preparation of a mAb against the GETV capsid protein and the identification of the specific localization of B-cell epitopes, and will contribute towards a better understanding of the biological importance of the GETV capsid protein. It will also pave the way for developing immunological detection methods and genotype diagnosis for GETVs.

Construction and characterization of a full-length infectious clone of an emerging senecavirus A strain.

Senecavirus A (SVA) is an emerging virus that causes vesicular disease in pigs. Construction of a full-length SVA cDNA clone is crucial for understanding its replication and pathogenesis. Here, we successfully constructed a CMV-promoter-driven infectious cDNA clone of the SVA isolate SVA/GX/CH/2018, which we named rSVA GX01. Sequence comparison between the pSVA GX01 and the parental isolate (SVA/GX/CH/2018) revealed three single-nucleotide differences. Four-week-old piglets were experimentally infected with either the parental virus or the cloned virus. The results showed that the cloned rSVA GX01 displayed weak pathogenicity in 4-week-old pigs compared to the parental virus SVA CH-GX-01-2018. The infectious clone of SVA will serve as a valuable tool for studying the viral replication cycle and for functional analysis of the viral genome.

Molecular epidemiological and genetic characterization of pseudorabies virus in Guangxi, China.

Pseudorabies virus (PRV) is an important pathogen that can cause harm to the pig population. Since 2011, there have been a number of large-scale outbreaks of pseudorabies on Chinese farms where animals had been vaccinated with the Bartha-K61 vaccine. In order to understand the epidemiological trend and genetic variations of PRV in Guangxi province, China, 819 tissue samples were collected from swine farms where PRV infection was suspected from 2013 to 2019, and these were tested for infectious wild strains of PRV. The results showed a positive rate of PRV in Guangxi province of 28.21% (231/819). Thirty-six wild-type PRV strains were successfully isolated from PRV-positive tissue samples, and a genetic evolutionary analysis was performed based on the gB, gC, gD, gE, and TK genes. Thirty of the PRV strains were found to be closely related to the Chinese variant strains HeN1-China-2012 and HLJ8-China-2013. In addition, five PRV strains were genetically related to Chinese classical strains, and one isolate was a recombinant of the PRV variant and the vaccine strain Bartha-K61. Amino acid sequence analysis showed that all 36 PRV strains had characteristic variant sites in the amino acid sequences of the gB, gC, gD, and gE proteins. Pathogenicity analysis showed that, compared to classical PRV strains, the PRV variant strains were more pathogenic in mice and had a lower LD50. Taken together, our results show that wild-type PRV infections are common on pig farms in Guangxi province of China and that the dominant prevalent strains were those of the PRV variants. The PRV variant strains also had increased pathogenicity in mice. Our data will provide a useful reference for understanding the prevalence and genetic evolution of PRV in China.

Evaluation of packaging capacity at the genomic 2C/3A junction region in Porcine enterovirus G.

Porcine enterovirus G (EV-G) is endogenous to most pig farming countries worldwide. Reports that a papain-like protease (PLP) gene has been naturally inserted into the 2C/3A junction region of the EV-G genome, has increased the potential public health threats from this virus. We constructed a full-length infectious cDNA clone of EV-G, CH/17GXQZ/2017, in order to determine the packaging capacity at the 2C/3A insertion site. Subsequently, recombinants viruses containing the coding tags, GFP, iLOV and His at the 2C/3A junction region, were synthesized. The infectious virus was successfully rescued only with the insertion of the His-tag, which displayed similar virological and molecular properties to its parental strain. This study determined the packaging capacity of the 2C/3A insertion site, and it provides a practical tool for studying the functions and pathogenic mechanisms of EV-G in pigs.

Clinical Characteristics Profile of COVID-19 Patients with Omicron Variant Admitted in a Tertiary Hospital, Central China.

Purpose: Omicron, a variant of COVID-19, is becoming a major issue of global concern. Its high transmissibility may bring challenges to the distribution of health care in a large population country like China. Investigating the behavior of the virus in the Chinese population will certainly help to plan for the upcoming surge of Omicron. Therefore, we made a preliminary analysis of the clinical and epidemiological characteristics of suspected cases of Omicron at the early stage of the surge. Patients and Methods: The study was conducted in Nanyang Central Hospital, a tertiary hospital, from 21st December, 2022 to 8th January, 2023. A total of 210 patients underwent demographic characteristics and clinical symptom collection from their medical records. Moreover, sputum culture was also conducted to explore the types of bacterial or fungal infections. Results: Our results showed that 5 patients (4.1%) were aged 16-49, 40 patients (32.5%) were aged 50-70, and 78 patients (63.4%) were aged 70 or more in the severe group. The proportion of male patients with severe diseases infected with Omicron is higher than that of female patients and the proportion of severe cases increases with age. The main symptoms of patients infected with Omicron are cough (91, 74.0%), fever (90, 73.2%), and asthma (73, 59.3%). The pathogens Streptococcus pneumoniae (71, 31.0%), Staphylococcus aureus (46, 20.1%), Mycoplasma pneumoniae (26, 11.4%), Klebsiella pneumoniae (18, 7.9%), Acinetobacter baumannii (13, 5.7%), and Haemophilus influenzae were detected in lower respiratory tract. Conclusion: This study suggests that age >70 is a risk factor for severe COVID-19 and that patients often have bacterial or fungal infections. Our research results may help to provide effective treatment for patients with Omicron infection and also contribute to health economic analysis and research to assist future public health decision-making.

Development of a recombinant reporter Getah virus for antiviral drug screening assays.

Getah virus (GETV), is an often neglected and re-emerging mosquito-borne RNA virus. GETV can cause illness accompanied with high fever, rash, incapacitating arthralgia and chronic arthritis or encephalitic disease in affected animals. Currently, there is no specific treatment or vaccine against GETV infection. In this study, we developed three recombinant viruses by inserting different reporter protein genes between the Cap and pE2 genes. The reporter viruses exhibited high replication capacity similar to the parental virus. The rGECiLOV and rGECGFP viruses were genetically stable within at least ten rounds of passages in BHK-21 cells. We confirmed that the reporter virus, rGECGFP, facilitated the antiviral assays against GETV by testing it with the known inhibitor, ribavirin. It was also found that the compound, doxycycline, showed an inhibitory effect on GETV replication. In addition, rGECGFP was found to be an authentic mimic of the parental virus infection in 3-day-old mice, but with milder pathogenicity. The reporter viruses will contribute to the assessment of viral replication and proliferation, tracking and elucidating of alphavirus-host interactions. In addition, they will help in the screening of potential antiviral compounds.

The Emergence and Pathogenesis of Recombinant Viruses Associated with NADC34-like Strains and the Predominant Circulating Strains of Porcine Reproductive and Respiratory Syndrome Virus in Southern China.

Since its recent appearance in China, the NADC30-like strains of porcine reproductive and respiratory syndrome virus 2 (PRRSV-2) have caused an expanding epidemic, and this has further expanded the genetic diversity of PRRSV. In this study, three NADC30-like strains-GXFCG20210401, GXQZ20210403 and GXNN20210506-were isolated from pig serum samples obtained in Guangxi, and their genomes were sequenced. A comparative analysis of the whole genomes showed that the three strains were most similar to NADC30 (88.3-88.7%). In particular, the non-structural protein coding regions (nsp1, nsp4-5, nsp7-8 and nsp9) showed the highest similarities to JXA1, and the ORF2a-ORF5 regions showed the highest similarities to NADC34. The three strains had same discontinuous deletions of 111+1+19 amino acids in the nsp2 region, which were similar to the NADC30-like strains. Phylogenetic tree analysis based on the ORF5 gene showed that the three PRRSV isolates were divided into lineage 1.5 along with the representative NADC34-like strains, but they were classified as NADC30-like strains with respect to the whole genome and nsp2 evolutionary trees. Recombinant analysis revealed complex recombination patterns in the genomes of the three strains, which likely originated from multiple recombination events among JXA1-like, NADC30-like and NADC34-like strains. The results from animal experiments showed that the GXQZ20210403 strain was 20% lethal to piglets and caused more severe clinical reactions than GXFCG20210401, and both recombinant strains were similar in terms of pathogenicity to the previously reported NADC34 strains. This study demonstrates that NADC34-like strains of PRRSV have been circulating in the southern provinces of China and have exchanged genomes with several other indigenous strains. In addition, differences in recombination patterns may cause different clinical pathogenicity and indicate the importance of the surveillance and preventive control of recombinant strains.

Construction and characterization of a full-length infectious clone of Getah virus in vivo.

Getah virus (GETV) is a mosquito-borne virus of the genus Alphavirus in the family Togaviridae and, in recent years, it has caused several outbreaks in animals. The molecular basis for GETV pathogenicity is not well understood. Therefore, a reverse genetic system of GETV is needed to produce genetically modified viruses for the study of the viral replication and its pathogenic mechanism. Here, we generated a CMV-driven infectious cDNA clone based on a previously isolated GETV strain, GX201808 (pGETV-GX). Transfection of pGETV-GX into BHK-21 â€‹cells resulted in the recovery of a recombinant virus (rGETV-GX) which showed similar growth characteristics to its parental virus. Then three-day-old mice were experimentally infected with either the parental or recombinant virus. The recombinant virus showed milder pathogenicity than the parental virus in the mice. Based on the established CMV-driven cDNA clone, subgenomic promoter and two restriction enzyme sites (BamHI and EcoRI) were introduced into the region between E1 protein and 3'UTR. Then the green fluorescent protein (GFP), red fluorescent protein (RFP) and improved light-oxygen-voltage (iLOV) genes were inserted into the restriction enzyme sites. Transfection of the constructs carrying the reporter genes into BHK-21 â€‹cells proved the rescue of the recombinant reporter viruses. Taken together, the establishment of a reverse genetic system for GETV provides a valuable tool for the study of the virus life cycle, and to aid the development of genetically engineered GETVs as vectors for foreign gene expression.

Pairwise Two-Stream ConvNets for Cross-Domain Action Recognition With Small Data.

In this work, we target cross-domain action recognition (CDAR) in the video domain and propose a novel end-to-end pairwise two-stream ConvNets (PTC) algorithm for real-life conditions, in which only a few labeled samples are available. To cope with the limited training sample problem, we employ pairwise network architecture that can leverage training samples from a source domain and, thus, requires only a few labeled samples per category from the target domain. In particular, a frame self-attention mechanism and an adaptive weight scheme are embedded into the PTC network to adaptively combine the RGB and flow features. This design can effectively learn domain-invariant features for both the source and target domains. In addition, we propose a sphere boundary sample-selecting scheme that selects the training samples at the boundary of a class (in the feature space) to train the PTC model. In this way, a well-enhanced generalization capability can be achieved. To validate the effectiveness of our PTC model, we construct two CDAR data sets (SDAI Action I and SDAI Action II) that include indoor and outdoor environments; all actions and samples in these data sets were carefully collected from public action data sets. To the best of our knowledge, these are the first data sets specifically designed for the CDAR task. Extensive experiments were conducted on these two data sets. The results show that PTC outperforms state-of-the-art video action recognition methods in terms of both accuracy and training efficiency. It is noteworthy that when only two labeled training samples per category are used in the SDAI Action I data set, PTC achieves 21.9% and 6.8% improvement in accuracy over two-stream and temporal segment networks models, respectively. As an added contribution, the SDAI Action I and SDAI Action II data sets will be released to facilitate future research on the CDAR task.

A Pairwise Attentive Adversarial Spatiotemporal Network for Cross-Domain Few-Shot Action Recognition-R2.

- Action recognition is a popular research topic in the computer vision and machine learning domains. Although many action recognition methods have been proposed, only a few researchers have focused on cross-domain few-shot action recognition, which must often be performed in real security surveillance. Since the problems of action recognition, domain adaptation, and few-shot learning need to be simultaneously solved, the cross-domain few-shot action recognition task is a challenging problem. To solve these issues, in this work, we develop a novel end-to-end pairwise attentive adversarial spatiotemporal network (PASTN) to perform the cross-domain few-shot action recognition task, in which spatiotemporal information acquisition, few-shot learning, and video domain adaptation are realised in a unified framework. Specifically, the Resnet-50 network is selected as the backbone of the PASTN, and a 3D convolution block is embedded in the top layer of the 2D CNN (ResNet-50) to capture the spatiotemporal representations. Moreover, a novel attentive adversarial network architecture is designed to align the spatiotemporal dynamics actions with higher domain discrepancies. In addition, the pairwise margin discrimination loss is designed for the pairwise network architecture to improve the discrimination of the learned domain-invariant spatiotemporal feature. The results of extensive experiments performed on three public benchmarks of the cross-domain action recognition datasets, including SDAI Action I, SDAI Action II and UCF50-OlympicSport, demonstrate that the proposed PASTN can significantly outperform the state-of-the-art cross-domain action recognition methods in terms of both the accuracy and computational time. Even when only two labelled training samples per category are considered in the office1 scenario of the SDAI Action I dataset, the accuracy of the PASTN is improved by 6.1%, 10.9%, 16.8%, and 14% compared to that of the TA3N , TemporalPooling, I3D, and P3D methods, respectively.

Emergence and Phylogenetic Analysis of a Getah Virus Isolated in Southern China.

Getah virus (GETV) has caused many outbreaks in animals in recent years. Monitoring of the virus and its related diseases is crucial to control the transmission of the virus. In the summer of 2018, we conducted routine tests on clinical samples from different pig farms in Guangxi province, South China, and isolated and characterized a GETV strain, named GX201808. Cytopathic effects were observed in BHK-21 cells inoculated with GX201808. The expression of E2 protein of GETV could be detected in virus-infected cells by indirect immunofluorescence assays. Electron microscopic analysis showed that the virus particles were spherical and ~70 nm in diameter with featured surface fibers. The multistep growth curves showed the virus propagated well in the BHK-21 cells. Molecular genetic analysis revealed that GX201808 belongs to Group 3, represented by Kochi-01-2005 isolated in Japan in 2005, and it clustered closely with the recently reported Chinese strains isolated from pigs, cattle, and foxes. A comparison of the identities of nucleotides and amino acids in the coding regions demonstrated that the GX201808 showed the highest amino acid identity (99.6%) with the HuN1 strain, a highly pathogenic isolate resulting in an outbreak of GETV infection in swine herds in Hunan province in 2017. In the present study, GETV was identified and isolated for the first time in Guangxi province of southern China, suggesting that future surveillance of this virus should be strengthened.

Generation of a Recombinant Porcine Reproductive and Respiratory Syndrome Virus Stably Expressing Two Marker Genes.

Porcine reproductive and respiratory syndrome virus (PRRSV) has been used as a gene expression vector in the development of vaccines. Most of these recombinant PRRSV vectors express only a single foreign gene through either an internal insertion in the hypervariable region of nsp2 or expression cassette and some of these recombinant vectors are genetically unstable. Here, we combined internal insertion in nsp2 and expression cassette methods to generate a novel recombinant PRRSV stably expressing the red fluorescence protein (RFP) and the green fluorescence protein (GFP) genes. Biological characteristic analysis of the recombinant PRRSV carrying the two marker genes, rGX-RFP-GFP, showed that it displayed similar growth kinetics and yet it yielded less infectious viruses when compared to the parental virus rGXAM. Co-expression of both the RFP and GFP was observed using confocal fluorescence microscopy when the rGX-RFP-GFP viruses infected MARC-145 cells. Furthermore, the PRRSV-based two-marker gene expression vector is genetically stable during 20 serial passages in MARC-145 cells. These data demonstrate that it is possible to express two interested immunogens from a single PRRSV vector.

Full Genomic Analysis of New Variants of Porcine Reproductive and Respiratory Syndrome Virus Revealed Multiple Recombination Events Between Different Lineages and Sublineages.

Porcine reproductive and respiratory syndrome virus (PRRSV) has had a devastating impact on the pig industry in China, and monitoring its genetic diversity is important for epidemiological surveillance and understanding its evolution. Here, we determine the complete genome sequences of two PRRSV strains, GXYL1403 and GXNN1839. Comparative, phylogenetic, and recombination detection program analyses show that the two isolates are recombinant strains with large-fragment amino acid deletions in nsp2. GXYL1403 possesses a unique deletion region of 124 amino acids in nsp2, and GXNN1839 contains a deletion of 131 amino acids in nsp2 as compared with VR2332. Further analysis of the full-length sequence suggests that GXYL1403 is a natural recombinant between sublineages 8.1 (CH-1a like) and 8.3 (JXA1-like). The recombination site of GXYL1403 is located in nsp9-nsp12 (8961nt-11181nt). GXNN1839 is a natural recombinant between the lineage 5 (VR-2332-like) and lineage 1 (NADC30-like) strains. The recombination events occurred in nsp9 (7872nt-8162nt) and in ORF2 (12587nt-13282nt) in the genome of GXNN1839. These results provide new evidence that PRRSV strains circulating in the environment have undergone recombination among the different lineages or sublineages of field strains, and these add to our understanding of RNA combination events that occur in PRRSV.

Fast Matrix Factorization With Nonuniform Weights on Missing Data.

Matrix factorization (MF) has been widely used to discover the low-rank structure and to predict the missing entries of data matrix. In many real-world learning systems, the data matrix can be very high dimensional but sparse. This poses an imbalanced learning problem since the scale of missing entries is usually much larger than that of the observed entries, but they cannot be ignored due to the valuable negative signal. For efficiency concern, existing work typically applies a uniform weight on missing entries to allow a fast learning algorithm. However, this simplification will decrease modeling fidelity, resulting in suboptimal performance for downstream applications. In this paper, we weight the missing data nonuniformly, and more generically, we allow any weighting strategy on the missing data. To address the efficiency challenge, we propose a fast learning method, for which the time complexity is determined by the number of observed entries in the data matrix rather than the matrix size. The key idea is twofold: 1) we apply truncated singular value decomposition on the weight matrix to get a more compact representation of the weights and 2) we learn MF parameters with elementwise alternating least squares (eALS) and memorize the key intermediate variables to avoid repeating computations that are unnecessary. We conduct extensive experiments on two recommendation benchmarks, demonstrating the correctness, efficiency, and effectiveness of our fast eALS method.

Depth-Aware Salient Object Detection and Segmentation via Multiscale Discriminative Saliency Fusion and Bootstrap Learning.

This paper proposes a novel depth-aware salient object detection and segmentation framework via multiscale discriminative saliency fusion (MDSF) and bootstrap learning for RGBD images (RGB color images with corresponding Depth maps) and stereoscopic images. By exploiting low-level feature contrasts, mid-level feature weighted factors and high-level location priors, various saliency measures on four classes of features are calculated based on multiscale region segmentation. A random forest regressor is learned to perform the discriminative saliency fusion (DSF) and generate the DSF saliency map at each scale, and DSF saliency maps across multiple scales are combined to produce the MDSF saliency map. Furthermore, we propose an effective bootstrap learning-based salient object segmentation method, which is bootstrapped with samples based on the MDSF saliency map and learns multiple kernel support vector machines. Experimental results on two large datasets show how various categories of features contribute to the saliency detection performance and demonstrate that the proposed framework achieves the better performance on both saliency detection and salient object segmentation.