对日本狗食和生肉狗食中分离出的肠炎沙门氏菌进行多焦点序列分型。

IF 1.6 Q2 MULTIDISCIPLINARY SCIENCES

BMC Research Notes Pub Date : 2024-12-19 DOI:10.1186/s13104-024-07014-0

Shoichiro Yukawa, Miho Morita

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引用次数: 0

摘要

目的：沙门氏菌是一种重要的人畜共患食源性致病菌，是世界范围内公认的重大公共卫生问题。沙门氏菌污染在狗粮和生肉狗粮（rmbd）中非常普遍。狗粮和生肉狗粮通常被认为是人类感染的主要来源。许多国家的流行病学研究都集中在沙门氏菌的特征上。但在日本没有这样的报道。采用多位点序列分型（MLST）技术对沙门氏菌的遗传特性进行了研究。结果：分离到14株沙门氏菌，分为ST19、ST26、ST32、ST34、ST241、ST469、ST864和ST1861 8个序列型。最常见的类型是ST32和ST34 （21%, n = 3）。第二常见的类型是ST26和ST469 （14%, n = 2）。

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Multi-locus sequence typing of Salmonella enterica isolates from dog treats and raw meat-based dog food in Japan.

Objective: Salmonella is an important zoonotic foodborne pathogen which is recognized as a major public health concern worldwide. Salmonella contamination are highly prevalent in dog treats and raw meat-based dog food (RMBDs). And dog treats and raw meat-based dog food are often implicated as main sources of human infection. Many epidemiological studies have focused on the characteristics of Salmonella in many countries. But there are no such reports in Japan. This study was conducted to investigate the genetic characteristics of Salmonella using multi-locus sequence typing (MLST).

Results: Fourteen Salmonella isolates were assigned to 8 sequence types: ST19, ST26, ST32, ST34, ST241, ST469, ST864 and ST1861. The most common types were ST32 and ST34 (21%, n = 3). The second most common types were ST26 and ST469 (14%, n = 2).

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来源期刊

BMC Research Notes Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (all)

CiteScore

3.60

自引率

0.00%

发文量

363

审稿时长

15 weeks

期刊介绍： BMC Research Notes publishes scientifically valid research outputs that cannot be considered as full research or methodology articles. We support the research community across all scientific and clinical disciplines by providing an open access forum for sharing data and useful information; this includes, but is not limited to, updates to previous work, additions to established methods, short publications, null results, research proposals and data management plans.