APDDD: Animal parasitic diseases and drugs database.

Animal parasitic diseases not only have an economic impact, but also have serious social and public health impacts. Although antiparasitic drugs can treat these diseases, it seems difficult for users to comprehensively utilize the information, due to incomplete and difficult data collection. Thus, there is an urgent need to establish a comprehensive database, that includes parasitic diseases and related drugs. In this paper, we develop a knowledge database dedicated to collecting and analyzing animal parasitic diseases and related drugs, named Animal Parasitic Diseases and Drugs Database (APDDD). The current version of APDDD includes animal parasitic disease data of 8 major parasite classifications that cause common parasitic diseases and 96 subclass samples mined from many literature and authoritative books, as well as 182 antiparasitic drugs. Furthermore, we utilized APDDD data to add a knowledge graph representing the relationships between parasitic diseases, drugs, and the targeted gene of drugs acting on parasites. We hope that APDDD will become a good database for animal parasitic diseases and antiparasitic drugs research and that users can gain a more intuitive understanding of the relationships between parasitic diseases, drugs, and targeted genes through the knowledge graph.

Epidemiological survey of tick-borne pathogens in dogs in Anhui Province, China.

Tick-borne diseases have continued to increase worldwide in both developing and many developed countries due to the widespread of different tick species and tick's adaptability to different climatic weather. In order to investigate the prevalence of the tick-borne pathogens, EDTA-anticoagulated whole blood samples were aseptically collected from 765 pet dogs in twenty veterinary clinics located in sixteen prefecture-level cities in Anhui Province, China, and the samples were examined and analyzed for tick-borne pathogens using both microscopy and PCR. Our result analysis revealed 17(2.22%) positive samples to Babesia spp and 4(0.52%) positive samples to Hepatozoon spp, of which case of co-infection was recorded in Lu'An and Chuzhou. The BLAST analysis results of the 18S rRNA gene revealed that the dogs were infected with Babesia gibsoni and Hepatozoon canis. All samples were negative for Anaplasma spp., Ehrlichia spp., and Rickettsia spp. This is the first molecular report of B. gibsoni and H. canis in dogs in Anhui, China.

Development and validation of a machine learning algorithm prediction for dense granule proteins in Apicomplexa.

BACKGROUND: Apicomplexa consist of numerous pathogenic parasitic protistan genera that invade host cells and reside and replicate within the parasitophorous vacuole (PV). Through this interface, the parasite exchanges nutrients and affects transport and immune modulation. During the intracellular life-cycle, the specialized secretory organelles of the parasite secrete an array of proteins, among which dense granule proteins (GRAs) play a major role in the modification of the PV. Despite this important role of GRAs, a large number of potential GRAs remain unidentified in Apicomplexa. METHODS: A multi-view attention graph convolutional network (MVA-GCN) prediction model with multiple features was constructed using a combination of machine learning and genomic datasets, and the prediction was performed on selected Neospora caninum protein data. The candidate GRAs were verified by a CRISPR/Cas9 gene editing system, and the complete NcGRA64(a,b) gene knockout strain was constructed and the phenotypes of the mutant were analyzed. RESULTS: The MVA-GCN prediction model was used to screen N. caninum candidate GRAs, and two novel GRAs (NcGRA64a and NcGRA64b) were verified by gene endogenous tagging. Knockout of complete genes of NcGRA64(a,b) in N. caninum did not affect the parasite's growth and replication in vitro and virulence in vivo. CONCLUSIONS: Our study showcases the utility of the MVA-GCN deep learning model for mining Apicomplexa GRAs in genomic datasets, and the prediction model also has certain potential in mining other functional proteins of apicomplexan parasites.

Development and application of an indirect ELISA to detect antibodies to Neospora caninum in cattle based on a chimeric protein rSRS2-SAG1-GRA7.

Neospora caninum is an important apicomplexan parasite causing neosporosis in cattle. The disease is recognized as one of the most important cause of reproductive problems and abortion in cattle worldwide. In this context, we developed an indirect enzyme-linked immunosorbent assays (ELISA) with chimeric protein rSRS2-SAG1-GRA7 to diagnose antibodies to Neospora-infection. This indirect ELISA was compared to indirect fluorescent antibody test (IFAT) and western blotting (WB), and the sensitivity and specificity results of ELISA were calculated to be 86.7 and 96.1%, respectively. The overall coincidence rate was 92.6% using IFAT and WB. Additionally, 329 aborting dairy cattle serum samples were tested using this ELISA to evaluate the prevalence of N. caninum in Ningxia, China. The positive rate of N. caninum in these farms was from 19.05 to 57.89%, and the mean rate was 41.64% (±11.01%), indicating that infection with N. caninum may be one of the important causes of cattle abortion in this region. This established rSRS2-SAG1-GRA7 indirect ELISA is capable for detecting the antibodies against N. caninum, and it could be a useful screening tool for monitoring the epidemiology of neosporosis in cattle.