期刊
VETERINARY SCIENCES
卷 9, 期 10, 页码 -出版社
MDPI
DOI: 10.3390/vetsci9100521
关键词
honey bee; Paenibacillus larvae; variability; MALDI-TOF; biotyping
资金
- VEGA [2/0100/19, 1/0779/21]
- National Reference Laboratory for Pesticides at the University of Veterinary Medicine and Pharmacy in Kosice, Slovakia
Understanding the diversity of Paenibacillus larvae, the cause of American foulbrood disease, is crucial for disease investigations. Protein fingerprinting-based MALDI-TOF method provides more insight into P. larvae diversity compared to current DNA fingerprinting methods.
Simple Summary An understanding of Paenibacillus larvae, the etiological agent of American foulbrood disease, species diversity is crucial for disease epidemiology investigations. Our data indicate that the protein fingerprinting-based MALDI-TOF method provides a much more thorough insight into P. larvae diversity compared to the DNA fingerprinting methods used at present. In recent decades, the significant deterioration of the health status of honey bees has been observed throughout the world. One of the most severe factors affecting the health of bee colonies worldwide is American foulbrood disease. This devastating disease, with no known cure, is caused by the Gram-positive spore-forming bacteria of Paenibacillus larvae species. At present, DNA-based methods are being used for P. larvae identification and typing. In our study, we compare two of the most advanced DNA-based technologies (rep-PCR and 16S rRNA analyses) with MALDI-TOF MS fingerprinting to evaluate P. larvae variability in Central Europe. While 16S rRNA analysis presents a very limited variation among the strains, MALDI-TOF MS is observed to be more efficient at differentiating P. larvae. Remarkably, no clear correlation is observed between whole-genome rep-PCR fingerprinting and MALDI-TOF MS-based typing. Our data indicate that MALDI-TOF protein profiling provides accurate and cost-effective methods for the rapid identification of P. larvae strains and provides novel perspectives on strain diversity compared to conventional DNA-based genotyping approaches. The current study provides a good foundation for future studies.
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