Between 2018 and 2020, 989 clinical specimens from pigs showing clinical signs of a variety of swine diseases in 27 provinces in China were sampled and submitted for further testing. Nested PCR targeting the 16S rRNA gene of Mycoplasma hyopneumoniae and subsequent sequencing were used to analyse these specimens. Mycoplasma hyopneumoniae-positive samples were assayed by multilocus sequence typing (MLST). The aim of the study was to reveal the distribution of M. hyopneumoniae and determine the genotypes of M. hyopneumoniae in pig herds in China based on MLST. Among these 989 samples, 199 samples were M. hyopneumoniae-positive. The M. hyopneumoniae positivity rate was 7.2% (35/494) in 2018, 18.4% (38/207) in 2019, and 43.8% (126/288) in 2020. In total, 47 samples were successfully assayed by MLST. Sixteen new M. hyopneumoniae sequence types from 9 provinces were recorded in the present study. This is the first report on sample positivity rates and molecular typing results for M. hyopneumoniae in swine herds in China. MLST has revealed high genotype diversity among M. hyopneumoniae from different provinces of China.

Senecavirus A (SVA), classified into the genus Senecavirus in the family Picornaviridae, causes an infectious disease in pigs. This virus can efficiently replicate in some non-pig-derived cells, such as the BHK cell line and its derivative (BSR-T7/5 cell line). We had recovered a wild-type SVA from its cDNA clone previously, and then uncovered the proteomic profile of SVA-infected BSR-T7/5 cells at 12 h post inoculation (hpi). In order to explore the cellular metabolomics further, the SVA-inoculated BSR-T7/5 cell monolayer was collected at 12 hpi for assay via liquid chromatography-tandem mass spectrometry (LC-MS/MS). The resultant data set was comprehensively analyzed using bioinformatics tools. A total of 451 metabolites were identified using in-house and public databases. Out of these metabolites, sixty-one showed significantly differential values (p value < 0.05). The Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to analyze metabolic pathways of the significantly differential metabolites. There were eighty-one identified KEGG pathways, out of which twenty-seven showed their p values < 0.05. The pyrimidine metabolism revealed the minimum p value and the maximum number of significantly differential metabolites, implying the pyrimidine played a key role in cellular metabolism after SVA infection. SVA replication must rely on the cellular metabolism. The present study on metabolomics would shed light on impacts of SVA-induced multiple interactions among metabolites on cells or even on natural hosts.

Senecavirus A (SVA), also known as Seneca Valley virus, belongs to the genus Senecavirus in the family Picornaviridae. SVA can cause vesicular disease and epidemic transient neonatal losses in pigs. This virus efficiently propagates in some non-pig-derived cells, like the baby hamster kidney (BHK) cell line and its derivate (BSR-T7/5). Conventionally, a few proteins or only one protein is selected for exploiting a given mechanism concerning cellular regulation after SVA infection in vitro. Proteomics plays a vital role in the analysis of protein profiling, protein-protein interactions, and protein-directed metabolisms, among others. Tandem mass tag-labeled liquid chromatography-tandem mass spectrometry combined with the parallel reaction monitoring technique is increasingly used for proteomic research. In this study, this combined method was used to uncover separately proteomic profiles of SVA- and non-infected BSR-T7/5 cells. Furthermore, both proteomic profiles were compared with each other. The proteomic profiling showed that a total of 361 differentially expressed proteins were identified, out of which, 305 and 56 were upregulated and downregulated in SVA-infected cells at 12 h post-inoculation, respectively. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analyses showed that cellular metabolisms were affected mainly in SVA-inoculated cells at an early stage of infection. Therefore, an integrated metabolic atlas remains to be explored via metabolomic methods.

Senecavirus A (SVA) is an emerging virus that belongs to the genus Senecavirus in the family Picornaviridae. Its genome is a positive-sense and single-stranded RNA, containing two untranslated regions (UTRs). The 68-nt-long 3′ UTR is computationally predicted to possess two higher-order RNA structures: a kissing-loop interaction and an H-type-like pseudoknot, both of which, however, cannot coexist in the 3′ UTR. In this study, we constructed 17 full-length SVA cDNA clones (cD-1 to -17): the cD-1 to -7 contained different point mutations in a kissing-loop-forming motif (KLFM); the cD-8 to -17 harbored one single or multiple point mutations in a pseudoknot-forming motif (PFM). These 17 mutated cDNA clones were independently transfected into BSR-T7/5 cells for rescuing recombinant SVAs (rSVAs), named rSVA-1 to −17, corresponding to cD-1 to −17. The results showed that the rSVA-1, -2, -3, -4, -5, -6, -7, -9, -13, and -15 were successfully rescued from their individual cDNA clones. Moreover, all mutated motifs were genetically stable during 10 viral passages in vitro. This study unveiled viral abilities of tolerating mutations in the computationally predicted KLFM or PFMs. It can be concluded that the putative kissing-loop structure, even if present in the 3′ UTR, is unnecessary for SVA replication. Alternatively, if the pseudoknot formation potentially occurs in the 3′ UTR, its deformation would have a lethal effect on SVA propagation.

Nipah virus (NiV) is a severe zoonotic pathogen that substantially threatens public health. Pigs are the natural hosts of NiV and can potentially transmit this disease to humans. Establishing a rapid, sensitive, and accurate point-of-care detection method is critical in the timely identification of infected pig herds. In this study, we developed an NiV detection method based on reverse transcription–recombinase polymerase amplification (RT-RAA) and the clustered regularly interspaced short palindromic repeats (CRISPR)-associated protein 13a (Cas13a) system for the precise detection of NiV. The highly conserved region of the NiV gene was selected as the detection target. We first designed eleven pairs of RT-RAA primers, and the optimal primer combination and reaction temperature were identified on the basis of RT-RAA efficiency. Additionally, the most efficient crRNA sequence was selected on the basis of the fluorescence signal intensity. The results revealed that the optimal reaction temperature for the developed method was 37 °C. The detection limit was as low as 1.565 copies/μL. Specificity testing revealed no cross-reactivity with nucleic acids from six common swine viruses, including Seneca virus A (SVA), foot-and-mouth disease virus (FMDV), classical swine fever virus (CSFV), porcine epidemic diarrhea virus (PEDV), African swine fever virus (ASFV), and pseudorabies virus (PRV). A validation test using simulated clinical samples revealed a 100% concordance rate. The detection results can be visualized via a fluorescence reader or lateral flow strips (LFSs). Compared with conventional detection methods, this RT-RAA-CRISPR/Cas13a-based method is rapid and simple and does not require scientific instruments. Moreover, the reagents can be freeze-dried for storage, eliminating the need for cold-chain transportation. This detection technology provides a convenient and efficient new tool for the point-of-care diagnosis of NiV and for preventing and controlling outbreaks.