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Background: A significant portion of South Korea's population, approximately a quarter, owns pets, with dogs being the most popular choice among them. However, studies analyzing the fecal organism communities of dogs in South Korea are lacking, and limited efforts have been exerted to identify pathogens with potential zoonotic implications. Therefore, this study aimed to investigate potential pathogens using metabarcoding analysis and evaluate the risk of zoonotic diseases in dog feces in Seoul, South Korea., Methodology: Fecal samples were collected from both pet and stray dogs in the Mapo district of Seoul. Next-generation sequencing (NGS) was utilized, employing 16S rRNA amplicon sequencing to identify prokaryotic pathogens, and 18S rRNA amplicon sequencing for eukaryotic pathogens. The data obtained from the QIIME2 pipeline were subjected to various statistical analyses to identify different putative pathogens and their compositions., Principal Findings: Significant variations in microbiota composition were found between stray and pet dogs, and putative prokaryotic and eukaryotic pathogens were identified. The most prevalent putative bacterial pathogens were Fusobacterium, Helicobacter, and Campylobacter. The most prevalent putative eukaryotic pathogens were Giardia, Pentatrichomonas, and Cystoisospora. Interestingly, Campylobacter, Giardia, and Pentatrichomonas were found to be significantly more prevalent in stray dogs than in pet dogs. The variation in the prevalence of potential pathogens in dog feces could be attributed to environmental factors, including dietary variances and interactions with wildlife, particularly in stray dogs. These factors likely contributed to the observed differences in pathogen occurrence between stray and pet dogs., Conclusions/significance: This study offers valuable insights into the zoonotic risks associated with dog populations residing in diverse environments. By identifying and characterizing putative pathogens in dog feces, this research provides essential information on the impact of habitat on dog-associated pathogens, highlighting the importance of public health planning and zoonotic risk management., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Liyanagama et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

T. gondii is a highly prevalent parasite worldwide, with cats serving as its final host. However, few studies have investigated the impact of T. gondii infection on cat gut microbiota. Therefore, this study examined the influence of T. gondii infection on the gut microbiota of stray cats and identified potential pathogens in their feces. This study examined T. gondii infection through blood of stray cats and the influence of microbiota in their feces using 16S rRNA gene amplicon sequencing. The results revealed significant differences in gut microbiota composition and diversity between the T. gondii seropositive and seronegative groups. Seropositive samples displayed a lower number of operational taxonomic units and reduced Shannon index than the seronegative samples. The seropositive and seronegative groups exhibited enrichment of taxa, including Escherichia and Enterobacteriaceae and Collinsella, Bifidobacterium, and Roseburia, respectively. Furthermore, potential pathogen species, including Campylobacter, Escherichia, and Streptococcus, were identified in the fecal samples. These findings suggest that T. gondii infection significantly impacts gut microbiota composition and diversity in stray cats. Additionally, an increased potential pathogen load, represented by Escherichia spp., was observed. These results underscore the importance of monitoring the prevalence of zoonotic pathogens in stray cats, as they can serve as reservoirs for zoonotic diseases. [ABSTRACT FROM AUTHOR]

Background: The striped field mouse Apodemus agrarius is a wild rodent commonly found in fields in Korea. It is a known carrier of various pathogens. Amplicon-based next-generation sequencing (NGS) targeting the 16S ribosomal RNA (rRNA) gene is the most common technique used to analyze the bacterial microbiome. Although many bacterial microbiome analyses have been attempted using feces of wild animals, only a few studies have used NGS to screen for parasites. This study aimed to rapidly detect bacterial, fungal and parasitic pathogens in the guts of A. agrarius using NGS-based metabarcoding analysis. Methods: We conducted 18S/16S rDNA-targeted high-throughput sequencing on cecal samples collected from A. agrarius (n = 48) trapped in May and October 2017. Taxa of protozoa, fungi, helminths and bacteria in the cecal content were then identified. Results: Among the protozoa identified, the most prevalent was Tritrichomonas sp., found in all of the cecal samples, followed by Monocercomonas sp. (95.8% prevalence; in 46/48 samples) and Giardia sp. (75% prevalence; in 36/48 samples). For helminths, Heligmosomoides sp. was the most common, found in 85.4% (41/48) of samples, followed by Hymenolepis sp. (10.4%; 5/48) and Syphacia sp. (25%; 12/48). The 16S rRNA gene analysis showed that the microbial composition of the cecal samples changed by season (P = 0.005), with the linear discriminant analysis effect size showing that in the spring Escherichia coli and Lactobacillus murinus were more abundant and Helicobacter rodentium was less abundant. Helicobacter japonicus was more abundant and Prevotella_uc was less abundant in males. The microbial composition changed based on the Heligmosomoides sp. infection status (P = 0.019); specifically, Lactobacillus gasseri and Lactobacillus intestinalis were more abundant in the Heligmosomoides sp.-positive group than in the Heligmosomoides sp.-negative group. Conclusions: This study demonstrated that bacterial abundance changed based on the season and specific parasitic infection status of the trapped mice. These results highlight the advantages of NGS technology in monitoring zoonotic disease reservoirs. [ABSTRACT FROM AUTHOR]