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. 2022 Sep 12;11(9):1236.
doi: 10.3390/antibiotics11091236.

Epidemiology of Antimicrobial Resistance Genes in Streptococcus agalactiae Sequences from a Public Database in a One Health Perspective

Affiliations

Epidemiology of Antimicrobial Resistance Genes in Streptococcus agalactiae Sequences from a Public Database in a One Health Perspective

Gabriele Meroni et al. Antibiotics (Basel). .

Abstract

Streptococcus agalactiae is a well-known pathogen in humans and food-producing animals. Therefore, this bacterium is a paradigmatic example of a pathogen to be controlled by a One Health approach. Indeed, the zoonotic and reverse-zoonotic potential of the bacteria, the prevalence of Group B Streptococci (GBS) diseases in both human and animal domains, and the threatening global situation on GBS antibiotic resistance make these bacteria an important target for control programs. An epidemiological analysis using a public database containing sequences of S. agalactiae from all over the world was conducted to evaluate the frequency and evolution of antibiotic resistance genes in those isolates. The database we considered (NCBI pathogen detection isolate browser-NPDIB) is maintained on a voluntary basis. Therefore, it does not follow strict epidemiological criteria. However, it may be considered representative of the bacterial population related to human diseases. The results showed that the number of reported sequences increased largely in the last four years, and about 50% are of European origin. The frequency data and the cluster analysis showed that the AMR genes increased in frequency in recent years and suggest the importance of verifying the application of prudent protocols for antimicrobials in areas with an increasing frequency of GBS infections both in human and veterinary medicine.

Keywords: GBS infections; One Health; S. agalactiae; antimicrobial resistance; molecular epidemiology.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Dendrogram obtained from cluster analysis of the 1824 sequences based on antimicrobial genes frequency.

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