Metabarcoding of bacteria and parasites in the gut of Apodemus agrarius.

backgroundThe 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.

methodsWe 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.

resultsAmong 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.

conclusionsThis 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.