Graphical Overall BacAnt’s service workflow. The figure is adapted with permissions from IntegronFinder (Cury et al., 2016).

Background: Safety issues of probiotic products have been reported frequently in recent years. Ten bacterial strains isolated from seven commercial probiotic products on market were evaluated for their safety, by whole-genome analysis. Results: We found that the bacterial species of three probiotic products were incorrectly labeled. Furthermore, six probiotic product isolates (PPS) contained genes for the production of toxic metabolites, while another three strains contained virulence genes, which might pose a potential health risk. In addition, three of them have drug-resistance genes, among which two strains potentially displayed multidrug resistance. One isolate has in silico predicted transferable genes responsible for toxic metabolite production, and they could potentially transfer to human gut microflora or environmental bacteria. Isolates of Lactobacillus rhamnosus and Bifidobacterium animalis subsp. lactis are associated with low risk for human consumption. Based on a comparative genome analysis, we found that the isolated Enterococcus faecium TK-P5D clustered with a well-defined probiotic strain, while E. faecalis TK-P4B clustered with a pathogenic strain. Conclusions: Our work clearly illustrates that whole-genome analysis is a useful method to evaluate the quality and safety of probiotic products. Regulatory quality control and stringent regulations on probiotic products are needed to ensure safe consumption and protect human health.

The plant genome can produce long non-coding RNAs (lncRNAs), some of which have been identified as important regulators of gene expression. To better understand the response mechanism of rice plants to Rice black-streaked dwarf virus (RBSDV) infection, we performed a comparative transcriptome analysis between the RBSDV-infected and non-infected rice plants. A total of 1342 mRNAs and 22 lncRNAs were identified to be differentially expressed after RBSDV infection. Most differentially expressed transcripts involved in the plant–pathogen interaction pathway were upregulated after RBSDV infection, indicating the activation of rice defense response by RBSDV. A network of differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) was then constructed. In this network, there are 56 plant–pathogen interaction-related DEmRNAs co-expressing with 20 DElncRNAs, suggesting these DElncRNAs and DEmRNAs may play essential roles in rice innate immunity against RBSDV. Moreover, some of the lncRNA–mRNA regulatory relationships were experimentally verified in rice calli by a quick and effective method established in this study. Three DElncRNAs were selected to be tested, and the results indicated that five mRNAs were found to be regulated by them. Together, we give a whole landscape of rice mRNAs and lncRNAs in response to RBSDV infection, and a feasible method to rapidly verify the lncRNA–mRNA regulatory relationship in rice.

To study the contamination of microorganisms in the food industry, pharmaceutical industry, clinical diagnosis, or bacterial taxonomy, accurate identification of species is a key starting point of further investigation. The conventional method of identification by the 16S rDNA gene or other marker gene comparison is not accurate, because it uses a tiny part of the genomic information. The average nucleotide identity calculated between two whole bacterial genomes was proven to be consistent with DNA–DNA hybridization and adopted as the gold standard of bacterial species delineation. Furthermore, there are more bacterial genomes available in public databases recently. All of those contribute to a genome era of bacterial species identification. However, wrongly labeled and low-quality bacterial genome assemblies, especially from type strains, greatly affect accurate identification. In this study, we employed a multi-step strategy to create a type-strain genome database, by removing the wrongly labeled and low-quality genome assemblies. Based on the curated database, a fast bacterial genome identification platform (fIDBAC) was developed (http://fbac.dmicrobe.cn/). The fIDBAC is aimed to provide a single, coherent, and automated workflow for species identification, strain typing, and downstream analysis, such as CDS prediction, drug resistance genes, virulence gene annotation, and phylogenetic analysis.

Acinetobacter baumannii has three clusters of genes for polysaccharide synthesis. Capsular polysaccharides and lipopolysaccharides are major virulence determinants in many Gram-negative bacteria, and play key roles in the overall fitness and virulence in A. baumannii, meanwhile poly-beta-1-6-N-acetylglucosamine was critical for biofilm formation. A variety of studies have been conducted which focused on the surveillance of antimicrobial resistance genes and clones in A. baumannii. However, a tool to perform serotype prediction in A. baumannii is still lacking. Here we present Bautype, a tool for whole genome sequencing-based K and O locus typing in A. baumannii. Using Bautype, users can upload and analyze the genome assembled in a web browser, with the results being displayed in a tabular or graphical format. We demonstrated the high accuracy of predicting K and O locus diversity using Bautype when analyzing more than 3000 A. baumannii genomes. Using our software, we were able to analyze K and O locus diversity among 593 genomes belonging to ST208 (3 K and 8 O). These diverse loci can serve as epidemiological markers for Multi-drug Resistance (MDR) strain subtyping. We also identified 45 novel O locus types. Our findings highlight the importance in monitoring the capsule type and LOS of A. baumannii strains for which Bautype is a tailored clinical software. Bautype is available at http://BauType.net.