Analysis of the vp2 gene sequence of a new mutated mink enteritis parvovirus strain in PR China

<p>Abstract</p> <p>Background</p> <p>Mink enteritis virus (MEV) causes a highly contagious viral disease of mink with a worldwide distribution. MEV has a linear, single-stranded, negative-sense DNA with a genome length of approximately 5,000 bp. The VP2 protein is the major structural protein of the parvovirus encoded by the <it>vp</it>2 gene. VP2 is highly antigenic and plays important roles in determining viral host ranges and tissue tropisms. This study describes the bionomics and <it>vp</it>2 gene analysis of a mutated strain, MEV-DL, which was isolated recently in China and outlines its homologous relationships with other selected strains registered in Genbank.</p> <p>Results</p> <p>The MEV-DL strain can infect F81 cells with cytopathic effects. Pig erythrocytes were agglutinated by the MEV-DL strain. The generation of MEV-DL in F81 cells could infect mink within three months and cause a disease that was similar to that caused by wild-type MEV. A comparative analysis of the <it>vp</it>2 gene nucleotide (nt) sequence of MEV-DL showed that this was more than 99% homologous with other mink enteritis parvoviruses in Genbank. However, the nucleotide residues at positions 1,065 and 1,238 in the MEV-DL strain of the <it>vp</it>2 gene differed from those of all the other MEV strains described previously. It is noteworthy that the mutation at the nucleotide residues position 1,238 led to Asp/Gly replacement. This may lead to structural changes. A phylogenetic tree and sequence distance table were obtained, which showed that the MEV-DL and ZYL-1 strains had the closest inheritance distance.</p> <p>Conclusions</p> <p>A new variation of the <it>vp</it>2 gene exists in the MEV-DL strain, which may lead to structural changes of the VP2 protein. Phylogenetic analysis showed that MEV-DL may originate from the ZYL-1 strain in DaLian.</p

Secondary infection with Streptococcus suis serotype 7 increases the virulence of highly pathogenic porcine reproductive and respiratory syndrome virus in pigs

<p>Abstract</p> <p>Background</p> <p>Porcine reproductive and respiratory syndrome virus (PRRSV) and <it>Streptococcus suis </it>are common pathogens in pigs. In samples collected during the porcine high fever syndrome (PHFS) outbreak in many parts of China, PRRSV and <it>S. suis </it>serotype 7 (SS7) have always been isolated together. To determine whether PRRSV-SS7 coinfection was the cause of the PHFS outbreak, we evaluated the pathogenicity of PRRSV and/or SS7 in a pig model of single and mixed infection.</p> <p>Results</p> <p>Respiratory disease, diarrhea, and anorexia were observed in all infected pigs. Signs of central nervous system (CNS) disease were observed in the highly pathogenic PRRSV (HP-PRRSV)-infected pigs (4/12) and the coinfected pigs (8/10); however, the symptoms of the coinfected pigs were clearly more severe than those of the HP-PRRSV-infected pigs. The mortality rate was significantly higher in the coinfected pigs (8/10) than in the HP-PRRSV- (2/12) and SS7-infected pigs (0/10). The deceased pigs of the coinfected group had symptoms typical of PHFS, such as high fever, anorexia, and red coloration of the ears and the body. The isolation rates of HP-PRRSV and SS7 were higher and the lesion severity was greater in the coinfected pigs than in monoinfected pigs.</p> <p>Conclusion</p> <p>HP-PRRSV infection increased susceptibility to SS7 infection, and coinfection of HP-PRRSV with SS7 significantly increased the pathogenicity of SS7 to pigs.</p

Rapid detection of grass carp reovirus type 1 using RPA-based test strips combined with CRISPR Cas13a system

IntroductionDue to the existence of grass carp reovirus (GCRV), grass carp hemorrhagic disease occurs frequently, and its high pathogenicity and infectivity are great challenges to the aquaculture industry. As a highly pathogenic pathogen, the outbreak of hemorrhagic disease often causes tremendous economic losses. Therefore, it is important to rapidly and accurately detect GCRV on site to control timely.MethodsIn this study, recombinant enzyme amplification (RPA) combined with clustered regularly interspaced short palindromic repeats (CRISPR)/Cas13a system was employed to establish a method to detect the vp7 gene of grass carp reovirus type 1. This method can be adopted for judging the results by collecting fluorescence signal, ultraviolet excitation visual fluorescence and test strip.ResultsCombined with the RPA amplification experiment, the detection limit of the RPA-CRISPR method can reach 7.2 × 101 copies/μL of vp7 gene per reaction, and the detection process can be completed within 1 h. In addition, this method had no cross-reaction with the other 11 common aquatic pathogens. Then, the performance of the RPA-CRISPR/Cas13a detection method was evaluated by comparing it with the real-time fluorescence quantitative PCR detection method of clinical samples. The results of RPA-CRISPR/Cas13a detection were shown to be in consistence with the results obtained from the real-time fluorescence quantitative PCR detection. The coincidence rate of this method with 26 GCRV clinical samples was 92.31%.DiscussionIn summary, this method has high sensitivity, specificity and on-site practicability for detecting GCRV type 1, and has great application potential in on-site GCRV monitoring

A Method for Generation Phage Cocktail with Great Therapeutic Potential

Background: Bacteriophage could be an alternative to conventional antibiotic therapy against multidrug-resistant bacteria. However, the emergence of resistant variants after phage treatment limited its therapeutic application. Methodology/Principal Findings: In this study, an approach, named ‘‘Step-by-Step’ ’ (SBS), has been established. This method takes advantage of the occurrence of phage-resistant bacteria variants and ensures that phages lytic for wild-type strain and its phage-resistant variants are selected. A phage cocktail lytic for Klebsiella pneumoniae was established by the SBS method. This phage cocktail consisted of three phages (GH-K1, GH-K2 and GH-K3) which have different but overlapping host strains. Several phage-resistant variants of Klebsiella pneumoniae were isolated after different phages treatments. The virulence of these variants was much weaker [minimal lethal doses (MLD).1.3610 9 cfu/mouse] than that of wild-type K7 countpart (MLD = 2.5610 3 cfu/mouse). Compared with any single phage, the phage cocktail significantly reduced the mutation frequency of Klebsiella pneumoniae and effectively rescued Klebsiella pneumoniae bacteremia in a murine K7 strain challenge model. The minimal protective dose (MPD) of the phage cocktail which was sufficient to protect bacteremic mice from lethal K7 infection was only 3.0610 4 pfu, significantly smaller (p,0.01) than that of single monophage. Moreover, a delayed administration of this phage cocktail was still effective in protection against K7 challenge. Conclusions/Significance: Our data showed that the phage cocktail was more effective in reducing bacterial mutatio

Three Capsular Polysaccharide Synthesis-Related Glucosyltransferases, GT-1, GT-2 and WcaJ, Are Associated With Virulence and Phage Sensitivity of Klebsiella pneumoniae

Klebsiella pneumoniae (K. pneumoniae) spp. are important nosocomial and community-acquired opportunistic pathogens, which cause various infections. We observed that K. pneumoniae strain K7 abruptly mutates to rough-type phage-resistant phenotype upon treatment with phage GH-K3. In the present study, the rough-type phage-resistant mutant named K7RR showed much lower virulence than K7. Liquid chromatography-tandem mass spectrometry (LC-MS-MS) analysis indicated that WcaJ and two undefined glycosyltransferases (GTs)- named GT-1, GT-2- were found to be down-regulated drastically in K7RR as compared to K7 strain. GT-1, GT-2, and wcaJ are all located in the gene cluster of capsular polysaccharide (CPS). Upon deletion, even of single component, of GT-1, GT-2, and wcaJ resulted clearly in significant decline of CPS synthesis with concomitant development of GH-K3 resistance and decline of virulence of K. pneumoniae, indicating that all these three GTs are more likely involved in maintenance of phage sensitivity and bacterial virulence. Additionally, K7RR and GT-deficient strains were found sensitive to endocytosis of macrophages. Mitogen-activated protein kinase (MAPK) signaling pathway of macrophages was significantly activated by K7RR and GT-deficient strains comparing with that of K7. Interestingly, in the presence of macromolecular CPS residues (&gt;250 KD), K7(ΔGT-1) and K7(ΔwcaJ) could still be bounded by GH-K3, though with a modest adsorption efficiency, and showed minor virulence, suggesting that the CPS residues accumulated upon deletion of GT-1 or wcaJ did retain phage binding sites as well maintain mild virulence. In brief, our study defines, for the first time, the potential roles of GT-1, GT-2, and WcaJ in K. pneumoniae in bacterial virulence and generation of rough-type mutation under the pressure of bacteriophage

New findings on the function and potential applications of the trimeric autotransporter adhesin

Trimeric autotransporter adhesins (TAAs) are located on the surface of many pathogenic Gram-negative bacteria. TAAs belong to the autotransporter protein family and consist of three identical monomers. These obligate homotrimeric proteins are secreted through the bacterial type Vc secretion system and share a common molecular organization that each monomer consists of a N-terminal "passenger" domain and a C-terminal translocation domain. TAAs are important virulence factors that are involved in bacterial life cycle and participate in mediating infection, invasion, dissemination and evasion of host immune responses. TAAs have also proved to be useful for many applications, such as vaccines and disease biomarkers. We here mainly focused on new findings on bio-function and application of TAAs in addition to their common structure and secretion mechanism

A Model to Predict Crosscut Stress Based on an Improved Extreme Learning Machine Algorithm

The analysis of crosscut stability is an indispensable task in underground mining activities. Crosscut instabilities usually cause geological disasters and delay of the project. On site, mining engineers analyze and predict the crosscut condition by monitoring its convergence and stress; however, stress monitoring is time-consuming and expensive. In this study, we propose an improved extreme learning machine (ELM) algorithm to predict crosscut&rsquo;s stress based on convergence data, for the first time in literature. The performance of the proposed technique is validated using a crosscut response by means of the FLAC3D finite difference program. It is found that the improved ELM algorithm performs higher generalization performance compared to traditional ELM, as it eliminates the random selection for input weights. Furthermore, a crosscut construction project in an underground mine, Yanqianshan iron mine, located in Liaoning Province (China), is selected as the case study. The accuracy and efficiency of the improved ELM algorithm has been demonstrated by comparing predicted stress data to measured data on site. Additionally, a comparison is conducted between the improved ELM algorithm and other commonly used artificial neural network algorithms

A Parameter-Free Outlier Detection Algorithm Based on Dataset Optimization Method

Recently, outlier detection has widespread applications in different areas. The task is to identify outliers in the dataset and extract potential information. The existing outlier detection algorithms mainly do not solve the problems of parameter selection and high computational cost, which leaves enough room for further improvements. To solve the above problems, our paper proposes a parameter-free outlier detection algorithm based on dataset optimization method. Firstly, we propose a dataset optimization method (DOM), which initializes the original dataset in which density is greater than a specific threshold. In this method, we propose the concepts of partition function (P) and threshold function (T). Secondly, we establish a parameter-free outlier detection method. Similarly, we propose the concept of the number of residual neighbors, as the number of residual neighbors and the size of data clusters are used as the basis of outlier detection to obtain a more accurate outlier set. Finally, extensive experiments are carried out on a variety of datasets and experimental results show that our method performs well in terms of the efficiency of outlier detection and time complexity