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Analysis of the Global Population Structure of Paenibacillus larvae and Outbreak Investigation of American Foulbrood Using a Stable wgMLST Scheme
Analysis of the Global Population Structure of Paenibacillus larvae and Outbreak Investigation of American Foulbrood Using a Stable wgMLST Scheme
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Analysis of the Global Population Structure of Paenibacillus larvae and Outbreak Investigation of American Foulbrood Using a Stable wgMLST Scheme
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Analysis of the Global Population Structure of Paenibacillus larvae and Outbreak Investigation of American Foulbrood Using a Stable wgMLST Scheme
Analysis of the Global Population Structure of Paenibacillus larvae and Outbreak Investigation of American Foulbrood Using a Stable wgMLST Scheme

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Analysis of the Global Population Structure of Paenibacillus larvae and Outbreak Investigation of American Foulbrood Using a Stable wgMLST Scheme
Analysis of the Global Population Structure of Paenibacillus larvae and Outbreak Investigation of American Foulbrood Using a Stable wgMLST Scheme
Journal Article

Analysis of the Global Population Structure of Paenibacillus larvae and Outbreak Investigation of American Foulbrood Using a Stable wgMLST Scheme

2021
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Overview
Paenibacillus larvae causes the American foulbrood (AFB), a highly contagious and devastating disease of honeybees. Whole-genome sequencing (WGS) has been increasingly used in bacterial pathogen typing, but rarely applied to study the epidemiology of P. larvae . To this end, we used 125 P. larvae genomes representative of a species-wide diversity to construct a stable whole-genome multilocus sequence typing (wgMLST) scheme consisting of 5745 loci. A total of 51 P. larvae isolates originating from AFB outbreaks in Slovenia were used to assess the epidemiological applicability of the developed wgMLST scheme. In addition, wgMLST was compared with the core-genome MLST (cgMLST) and whole-genome single nucleotide polymorphism (wgSNP) analyses. All three approaches successfully identified clusters of outbreak-associated strains, which were clearly separated from the epidemiologically unlinked isolates. High levels of backward comparability of WGS-based analyses with conventional typing methods (ERIC-PCR and MLST) were revealed; however, both conventional methods lacked sufficient discriminatory power to separate the outbreak clusters. The developed wgMLST scheme provides an improved understanding of the intra- and inter-outbreak genetic diversity of P. larvae and represents an important progress in unraveling the genomic epidemiology of this important honeybee pathogen.