Evaluation of Protective Immune Response Induced by a DNA Vaccine Encoding GRA8 against Acute Toxoplasmosis in a Murine Model.

Toxoplasma gondii is an apicomplexan zoonotic protozoan parasite that infects most species of warm-blooded animals, including humans. The heavy incidence and severe or lethal damage caused by T. gondii infection clearly indicate a need for the development of an effective vaccine. T. gondii GRA8 is a member of the dense granules protein family and is used as a marker of acute infection. In the present study, we evaluated the protective immunity induced by DNA vaccination based on a recombinant eukaryotic plasmid, pDsRed2-GRA8, against acute toxoplasmosis in mice. BALB/c mice were intramuscularly immunized with the pDsRed2-GRA8 plasmid and then challenged by infection with the highly virulent GFP-RH strain of T. gondii. The specific immune responses and protective efficacy against T. gondii of this vaccine were analyzed by measuring cytokine and serum antibody titers, splenocyte proliferation assays, and the survival times of mice after challenge. Our results showed that mice immunized with pDsRed2-GRA8 demonstrated specific humoral and cellular responses, induced higher IgG antibody titers with predominant IgG2a production; increased levels of IL-10, IL-12 (p70), IFN-γ, TNF-α, and splenocyte proliferation; and prolonged survival times compared to those of control mice. The present study showed that DNA immunization with pDsRed2-GRA8 induced humoral and cellular immune responses, and all immunized mice showed greater Th1-type immune responses and longer survival times than those of control mice. These results indicated that T. gondii GRA8 DNA immunization induces a partial protective effect against acute toxoplasmosis.

Bacterial communities in semen from men of infertile couples: metagenomic sequencing reveals relationships of seminal microbiota to semen quality.

Some previous studies have identified bacteria in semen as being a potential factor in male infertility. However, only few types of bacteria were taken into consideration while using PCR-based or culturing methods. Here we present an analysis approach using next-generation sequencing technology and bioinformatics analysis to investigate the associations between bacterial communities and semen quality. Ninety-six semen samples collected were examined for bacterial communities, measuring seven clinical criteria for semen quality (semen volume, sperm concentration, motility, Kruger's strict morphology, antisperm antibody (IgA), Atypical, and leukocytes). Computer-assisted semen analysis (CASA) was also performed. Results showed that the most abundant genera among all samples were Lactobacillus (19.9%), Pseudomonas (9.85%), Prevotella (8.51%) and Gardnerella (4.21%). The proportion of Lactobacillus and Gardnerella was significantly higher in the normal samples, while that of Prevotella was significantly higher in the low quality samples. Unsupervised clustering analysis demonstrated that the seminal bacterial communities were clustered into three main groups: Lactobacillus, Pseudomonas, and Prevotella predominant group. Remarkably, most normal samples (80.6%) were clustered in Lactobacillus predominant group. The analysis results showed seminal bacteria community types were highly associated with semen health. Lactobacillus might not only be a potential probiotic for semen quality maintenance, but also might be helpful in countering the negative influence of Prevotella and Pseudomonas. In this study, we investigated whole seminal bacterial communities and provided the most comprehensive analysis of the association between bacterial community and semen quality. The study significantly contributes to the current understanding of the etiology of male fertility.

Clinical detection of human probiotics and human pathogenic bacteria by using a novel high-throughput platform based on next generation sequencing.

BACKGROUND: The human body plays host to a vast array of bacteria, found in oral cavities, skin, gastrointestinal tract and the vagina. Some bacteria are harmful while others are beneficial to the host. Despite the availability of many methods to identify bacteria, most of them are only applicable to specific and cultivable bacteria and are also tedious. Based on high throughput sequencing technology, this work derives 16S rRNA sequences of bacteria and analyzes probiotics and pathogens species. RESULTS: We constructed a database that recorded the species of probiotics and pathogens from literature, along with a modified Smith-Waterman algorithm for assigning the taxonomy of the sequenced 16S rRNA sequences. We also constructed a bacteria disease risk model for seven diseases based on 98 samples. Applicability of the proposed platform is demonstrated by collecting the microbiome in human gut of 13 samples. CONCLUSIONS: The proposed platform provides a relatively easy means of identifying a certain amount of bacteria and their species (including uncultivable pathogens) for clinical microbiology applications. That is, detecting how probiotics and pathogens inhabit humans and how affect their health can significantly contribute to develop a diagnosis and treatment method.

A new method for post Genome-Wide Association Study (GWAS) analysis of colorectal cancer in Taiwan.

Recently, single nucleotide polymorphisms (SNPs) located in specific loci or genes have been identified associated with susceptibility to colorectal cancer (CRC) in Genome-Wide Association Studies (GWAS). However, in different ethnicities and regions, the genetic variations and the environmental factors can widely vary. Therefore, here we propose a post-GWAS analysis method to investigate the CRC susceptibility SNPs in Taiwan by conducting a replication analysis and bioinformatics analysis. One hundred and forty-four significant SNPs from published GWAS results were collected by a literature survey, and two hundred and eighteen CRC samples and 385 normal samples were collected for post-GWAS analysis. Finally, twenty-six significant SNPs were identified and reported as associated with susceptibility to colorectal cancer, other cancers, obesity, and celiac disease in a previous GWAS study. Functional analysis results of 26 SNPs indicate that most biological processes identified are involved in regulating immune responses and apoptosis. In addition, an efficient prediction model was constructed by applying Jackknife feature selection and ANOVA testing. As compared to another risk prediction model of CRC for European Caucasians population, which performs 0.616 of AUC by using 54 SNPs, the proposed model shows good performance in predicting CRC risk within the Taiwanese population, i.e., 0.724 AUC by using 16 SNPs. We believe that the proposed risk prediction model is highly promising for predicting CRC risk within the Taiwanese population. In addition, the functional analysis results could be helpful to explore the potential associated regulatory mechanisms that may be involved in CRC development.

miRTarBase: a database curates experimentally validated microRNA-target interactions.

MicroRNAs (miRNAs), i.e. small non-coding RNA molecules (∼22 nt), can bind to one or more target sites on a gene transcript to negatively regulate protein expression, subsequently controlling many cellular mechanisms. A current and curated collection of miRNA-target interactions (MTIs) with experimental support is essential to thoroughly elucidating miRNA functions under different conditions and in different species. As a database, miRTarBase has accumulated more than 3500 MTIs by manually surveying pertinent literature after data mining of the text systematically to filter research articles related to functional studies of miRNAs. Generally, the collected MTIs are validated experimentally by reporter assays, western blot, or microarray experiments with overexpression or knockdown of miRNAs. miRTarBase curates 3576 experimentally verified MTIs between 657 miRNAs and 2297 target genes among 17 species. miRTarBase contains the largest amount of validated MTIs by comparing with other similar, previously developed databases. The MTIs collected in the miRTarBase can also provide a large amount of positive samples to develop computational methods capable of identifying miRNA-target interactions. miRTarBase is now available on http://miRTarBase.mbc.nctu.edu.tw/, and is updated frequently by continuously surveying research articles.