Dataset Information

First multi-locus sequence typing scheme for Arcobacter spp.

ABSTRACT:

Background

Arcobacter spp. are a common contaminant of food and water, and some species, primarily A. butzleri and A. cryaerophilus, have been isolated increasingly from human diarrheal stool samples. Here, we describe the first Arcobacter multilocus sequence typing (MLST) method for A. butzleri, A. cryaerophilus, A. skirrowii, A. cibarius and A. thereius.

Results

A sample set of 374 arcobacters, including 275 A. butzleri, 72 A. cryaerophilus, 15 A. skirrowii and 8 A. cibarius isolates from a wide variety of geographic locations and sources, was typed in this study. Additionally, this sample set contained four strains representing a new Arcobacter species, A. thereius. The seven loci used in the four-species Arcobacter MLST method are the same as those employed previously in C. jejuni, C. coli, C. helveticus and C. fetus (i.e. aspA, atpA(uncA), glnA, gltA, glyA, pgm and tkt). A large number of alleles were identified at each locus with the majority of isolates containing a unique sequence type. All Arcobacter isolates typed in this study contain two glyA genes, one linked to lysS (glyA1) and the other linked to ada (glyA2). glyA1 was incorporated into the Arcobacter MLST method while glyA2 was not because it did not increase substantially the level of discrimination.

Conclusion

No association of MLST alleles or sequence types with host or geographical source was observed with this sample set. Nevertheless, the large number of identified alleles and sequence types indicate that this MLST method will prove useful in both Arcobacter strain discrimination and in epidemiological studies of sporadic Arcobacter-related gastroenteritis. A new Arcobacter MLST database was created http://pubmlst.org/arcobacter/; allele and ST data generated in this study were deposited in this database and are available online.

SUBMITTER: Miller WG

PROVIDER: S-EPMC2755481 | biostudies-literature | 2009 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

First multi-locus sequence typing scheme for Arcobacter spp.

Miller William G WG Wesley Irene V IV On Stephen L W SL Houf Kurt K Mégraud Francis F Wang Guilin G Yee Emma E Srijan Apichai A Mason Carl J CJ

BMC microbiology 20090914

<h4>Background</h4>Arcobacter spp. are a common contaminant of food and water, and some species, primarily A. butzleri and A. cryaerophilus, have been isolated increasingly from human diarrheal stool samples. Here, we describe the first Arcobacter multilocus sequence typing (MLST) method for A. butzleri, A. cryaerophilus, A. skirrowii, A. cibarius and A. thereius.<h4>Results</h4>A sample set of 374 arcobacters, including 275 A. butzleri, 72 A. cryaerophilus, 15 A. skirrowii and 8 A. cibarius iso ...[more]

PMID: 19751525

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Project description:BackgroundMulti-locus sequence typing (MLST) has become the gold standard for population analyses of bacterial pathogens. This method focuses on the sequences of a small number of loci (usually seven) to divide the population and is simple, robust and facilitates comparison of results between laboratories and over time. Over the last decade, researchers and population health specialists have invested substantial effort in building up public MLST databases for nearly 100 different bacterial species, and these databases contain a wealth of important information linked to MLST sequence types such as time and place of isolation, host or niche, serotype and even clinical or drug resistance profiles. Recent advances in sequencing technology mean it is increasingly feasible to perform bacterial population analysis at the whole genome level. This offers massive gains in resolving power and genetic profiling compared to MLST, and will eventually replace MLST for bacterial typing and population analysis. However given the wealth of data currently available in MLST databases, it is crucial to maintain backwards compatibility with MLST schemes so that new genome analyses can be understood in their proper historical context.ResultsWe present a software tool, SRST, for quick and accurate retrieval of sequence types from short read sets, using inputs easily downloaded from public databases. SRST uses read mapping and an allele assignment score incorporating sequence coverage and variability, to determine the most likely allele at each MLST locus. Analysis of over 3,500 loci in more than 500 publicly accessible Illumina read sets showed SRST to be highly accurate at allele assignment. SRST output is compatible with common analysis tools such as eBURST, Clonal Frame or PhyloViz, allowing easy comparison between novel genome data and MLST data. Alignment, fastq and pileup files can also be generated for novel alleles.ConclusionsSRST is a novel software tool for accurate assignment of sequence types using short read data. Several uses for the tool are demonstrated, including quality control for high-throughput sequencing projects, plasmid MLST and analysis of genomic data during outbreak investigation. SRST is open-source, requires Python, BWA and SamTools, and is available from http://srst.sourceforge.net.

Project description:BackgroundMycoplasma anserisalpingitidis is a waterfowl pathogen that mainly infects geese, can cause significant economic losses and is present worldwide. With the advance of whole genome sequencing technologies, new methods are available for the researchers; one emerging methodology is the core genome Multi-Locus Sequence Typing (cgMLST). The core genome contains a high percentage of the coding DNA sequence (CDS) set of the studied strains. The cgMLST schemas are powerful genotyping tools allowing for the investigation of potential epidemics, and precise and reliable classification of the strains. Although whole genome sequences of M. anserisalpingitidis strains are available, to date, no cgMLST schema has been published for this species.ResultsIn this study, Illumina short reads of 81 M. anserisalpingitidis strains were used, including samples from Hungary, Poland, Sweden, and China. Draft genomes were assembled with the SPAdes software and analysed with the online available chewBBACA program. User made modifications in the program enabled analysis of mycoplasmas and provided similar results as the conventional SeqSphere+ software. The threshold of the presence of CDS in the strains was set to 93% due to the quality of the draft genomes, resulting in the most accurate and robust schema. Three hundred thirty-one CDSs constituted our cgMLST schema (representing 42,77% of the whole CDS set of M. anserisalpingitidis ATCC BAA-2147), and a Neighbor joining tree was created using the allelic profiles. The correlation was observed between the strains' cgMLST profile and geographical origin; however, strains from the same integration but different locations also showed close relationship. Strains isolated from different tissue samples of the same animal revealed highly similar cgMLST profiles.ConclusionsThe Neighbor joining tree from the cgMLST schema closely resembled the real-life spatial and temporal relationships of the strains. The incongruences between background data and the cgMLST profile in the strains from the same integration can be because of the higher probability of contacts between the flocks. This schema can help with the epidemiological investigation and can be used as a basis for further studies.

Dataset Information

First multi-locus sequence typing scheme for Arcobacter spp.

Background

Results

Conclusion

Publications

First multi-locus sequence typing scheme for Arcobacter spp.

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