Genomic Analysis And Metabolomics Analysis Of Riemerella Anatipestifer

Riemerella anatipestifer(RA)is a gram-negative bacterium that has a high potential to infect waterfowl.With the rapid development of high throughput technology,multi-omics data provide a basis for the prevention and treatment of the pathogenic bacteria.Genomics and transcriptomics studies have been done on RA over the years,but no data about multi-omics study in RA have been reported.In this study,we combined microbial genomics and metabolomics to investigate the genetic evolution relation and metabolism of RA.The main results were as follows:1 Codon usage bias in Riemerella anatipestiferThe synonymous codon usage patterns of bacteria reflect a series of evolutionary changes that enable bacteria to improve tolerance of the various environments.We detailed the codon usage patterns of RA isolates from the available 12 sequenced genomes by multiple codon analysis and statistical methods.Nucleotide compositions and relative synonymous codon usage(RSCU)analysis revealed that A or U ending codons are predominant in RA.Neutrality analysis found no significant correlation between GC12 and GC3(P>0.05).Correspondence analysis and ENc-plot results showed that natural selection dominated over mutation in the codon usage bias.The tree of cluster analysis based on RSCU was concordant with dendrogram based on genomic BLAST by Neighbor-Joining method.By comparative analysis,about 50 highly expressed genes that were orthologs across all 12 strains,were found in the top 5%of high value CAI.Based on these CAI values,we infer that RA contains a number of predicted highly expressed coding sequences,involved in transcriptional regulation and metabolism,reflecting their requirement for dealing with diverse environmental conditions.These results provide some useful information on the mechanisms that contribute to codon usage bias and evolution of RA.2 Multilocus Sequence Typing of Riemerella anatipestifer from Ducks in ChinaTo predict the evolutionary trajectories of accurate information on the population structure of RA is crucial.In the present study,117 RA species isolated from 1998 to 2017 were studied by multilocus sequence typing(MLST)scheme based on seven housekeeping genes(dnaB,gluD,gpi,groEL,gyrA,mdh and rpoB).The fragment sizes of the seven amplified housekeeping genes ranged in length from 460 bp to 650 bp.In total,290 polymorphic nucleotide sites were detected among seven housekeeping genes.Sequence analysis indicated 52 different sequence types(STs)and the phylogenetic analysis based on the STs of the seven loci indicated that the 117 strains belonged to four major clusters.Split decomposition analysis showed that intraspecies recombination played a role in generating diversity among strains.The minimum spanning tree showed that the evolution of the STs was correlated with geographical origin.Importantly,the results suggest that RA originated in Guangdong.This study signifies that the multilocus sequence typing is a valuable tool to access the genetic diversity among RA and can be used further to monitoring of the epidemic.3 Comparative genome-scale modeling of the pathogenic Flavobacteriaceae species Riemerella anatipestifer in ChinaAlthough more and more genomes of RA have been generated comparative genomic analysis of RA still remains at the level of individual species.In this study,we analyzed the pan-genome of 27 RA virulent isolates to reveal the intraspecies genomic diversity from various aspects.Results of pan-genome analysis revealed an open pan-genome for all 27 species with the sizes of 2,967 genes.We identified 387 genes among 555 unique genes originated by horizontal gene transfer.Further studies showed 204 strain-specific HGT genes were predicted as virulent proteins.Screening the 1,113 core genes in RA through subtractive genomic approach,70 putative vaccine targets out of 125 non-cytoplasmic proteins have been predicted.Further analysis of these non A.platyrhynchos homologous proteins predicted that 56 essential proteins as drug targets with more interaction partners were involved in unique metabolic pathways of RA.In conclusion,the present study indicated the essence and the diversity of RA,and also provides useful information for identification of vaccine and drug candidates in the future.4 Comparative genomics and metabolomics analysis of Riemerella anatipestifer strain CH-1 and CH-2Serotypes 1 and 2 were most pathogenic,prevalent,and liable over the world.In this study,the intracellular metabolites in R.anatipestifer strains RA-CH-1(serotype 1)and RA-CH-2(serotype 2)were identified by gas chromatography-mass spectrometer(GC-MS).The metabolic profiles were performed using hierarchical clustering and partial least squares discriminant analysis(PLS-DA).The results of hierarchical cluster analysis showed that the amounts of the detected metabolites were more abundant in RA-CH-2.RA-CH-1 and RA-CH-2 were separated by the PLS-DA model.24 potential biomarkers participated in nine metabolisms were contributed predominantly to the separation.Based on the complete genome sequence database and metabolite data,the first large-scale metabolic models of iJL463(RA-CH-1)and iDZ470(RA-CH-2)were reconstructed.In addition,we explained the change of purine metabolism combined with the transcriptome and metabolomics data.The study showed that it is possible to detect and differentiate between these two organisms based on their intracellular metabolites using GC-MS.The present research fills a gap in the metabolomics characteristics of R.anatipestifer.