Minimum Core Genome Sequence Typing of Brucella From China

The Gram-negative bacterial genus Brucella includes six classic species based on host specificity,pathogenicity and phenotypic differences.Four more Brucella species were identified in 2007.Although many Brucella genomes have been sequenced,genome sequences and analysis of Brucella strains isolated in China are still scarce.An efficient genome-based Brucella typing method is also needed.In this study,we used the minimum core genome(MCG)typing method to identify and type Brucella strains.Twenty Brucella isolates fromChinawere newly sequenced.The genome sequences of 55 representative Brucella strainswere downloaded.Among the 75 genomes,1089 genes and 52,030 single nucleotide polymorphisms(SNPs)shared by all isolates were considered as the MCG genes and MCG SNPs.Using these 52,030 MCG SNPs,Brucella was divided into six MCG groups.In addition,average nucleotide identity(ANI)values and the distributions of 184 virulence genes were all computed.The proportions of virulence genes were 90.96%,93.56%,95.89%,86.04%,85.78%and 91.87%for MCG groups 1 to 6,respectively.The intragroup ANI values were higher than the intergroup values,further confirming the validity of the MCG taxonomy classification.Brucella melitensis and Brucella abortus,the two main Brucella species pathogenic to humans,were well separated from other species.With the development and cost reduction of next-generation sequencing,theMCG typing method can be used for rapid identification of Brucella,which can contribute to the rapid diagnosis of brucellosis and ensure timely and effective treatment.

Public health implications of Yersinia enterocolitica investigation:an ecological modeling and molecular epidemiology study

Background Yersinia enterocolitica has been sporadically recovered from animals,foods,and human clinical samples in various regions of Ningxia,China.However,the ecological and molecular characteristics of Y.enterocolitica,as well as public health concerns about infection in the Ningxia Hui Autonomous Region,remain unclear.This study aims to analyze the ecological and molecular epidemiological characteristics of Y.enterocolitis in order to inform the public health intervention strategies for the contains of related diseases.Methods A total of 270 samples were collected for isolation[animals(n=208),food(n=49),and patients(n=13)],then suspect colonies were isolated and identified by the API20E biochemical identification system,serological tests,biotyping tests,and 16S rRNA-PCR.Then,we used an ecological epidemiological approach combined with machine learning algorithms(general linear model,random forest model,and eXtreme Gradient Boosting)to explore the associations between ecological factors and the pathogenicity of Y.enterocolitis.Furthermore,average nucleotide identity(ANI)estimation,single nucleotide polymorphism(SNP),and core gene multilocus sequence typing(cgMLST)were applied to characterize the molecular profile of isolates based on whole genome sequencing.The statistical test used single-factor analysis,Chi-square tests,t-tests/ANOVA-tests,Wilcoxon rank-sum tests,and Kruskal–Wallis tests.Results A total of 270 isolates of Yersinia were identified from poultry and livestock(n=191),food(n=49),diarrhoea patients(n=13),rats(n=15),and hamsters(n=2).The detection rates of samples from different hosts were statistically different(χ^(2)=22.636,P<0.001).According to the relatedness clustering results,270 isolates were divided into 12 species,and Y.enterocolitica(n=187)is a predominated species.Pathogenic isolates made up 52.4%(98/187),while non-pathogenic isolates made up 47.6%(89/187).Temperature and precipitation were strongly associated with the pathogenicity of the isolates(P<0.001).The random forest(RF)prediction model showed the best performance.The prediction result shows a high risk of pathogenicity Y.enterocolitica was located in the northern,northwestern,and southern of the Ningxia Hui Autonomous Region.The Y.enterocolitica isolates were classified into 54 sequence types(STs)and 125 cgMLST types(CTs),with 4/O:3 being the dominant bioserotype in Ningxia.The dominant STs and dominant CTs of pathogenic isolates in Ningxia were ST429 and HC100_2571,respectively.Conclusions The data indicated geographical variations in the distribution of STs and CTs of Y.enterocolitica isolates in Ningxia.Our work offered the first evidence that the pathogenicity of isolates was directly related to fluctuations in temperature and precipitation of the environment.CgMLST typing strategies showed that the isolates were transmitted to the population via pigs and food.Therefore,strengthening health surveillance on pig farms in high-risk areas and focusing on testing food of pig origin are optional strategies to prevent disease outbreaks.

A Brief Review of Software Tools for Pangenomics

Since the proposal for pangenomic study, there have been a dozen software tools actively in use for pangenomic analysis. By the end of 2014, Panseq and the pan-genomes analysis pipeline（PGAP） ranked as the top two most popular packages according to cumulative citations of peerreviewed scientific publications. The functions of the software packages and tools, albeit variable among them, include categorizing orthologous genes, calculating pangenomic profiles, integrating gene annotations, and constructing phylogenies. As epigenomic elements are being gradually revealed in prokaryotes, it is expected that pangenomic databases and toolkits have to be extended to handle information of detailed functional annotations for genes and non-protein-coding sequences including non-coding RNAs, insertion elements, and conserved structural elements. To develop better bioinformatic tools, user feedback and integration of novel features are both of essence.