Observation of the Gut Microbiota Profile in BALB/c Mice Induced by Plasmodium yoelii 17XL Infection

Rodent malaria caused by Plasmodium yoelii 17XL (Py 17XL) is an ideal animal model for human malaria studies. Although the gut microbiota plays an important role in the occurrence and development of infectious diseases, the gut microbiota associated with Py 17XL infection remains unclear. In the current study, the gut microbiota composition of infected BALB/c mice was surveyed. Mouse fecal samples were collected at 0, 2, 5 days post-infection (dpi), and the gut microbiota was characterized by 16S rRNA sequencing. Operational taxonomic units (OTUs) were 634 +/- 26 on average. Firmicutes and Bacteroidetes were typically predominant in the gut microbiota composition at the phylum level. Compared with the Ctrl, Firmicutes was significantly decreased after infection, while Bacteroidetes was notably increased. The most dominant family was Lactobacillaceae in all samples. The alpha diversity index showed that compared with that of the Ctrl, the observed OTU number was decreased at 2 dpi and then slightly increased at 5 dpi. LEfSe analysis revealed several bacterial taxa were notably related to Py-infected mice at the phylogenetic level. Several bacterial genera, such as Lactobacillus, were overrepresented in the Py-infected fecal microbiota at 2 dpi, while Muribaculaceae was overrepresented at 5 dpi. Moreover, Alistipes and Helicobacter were overrepresented at 5 dpi compared with 2 dpi. The results indicated Py infection could alter the gut microbiota composition of mice. Besides, biomarkers could serve as direct targets to elucidate their roles in the progression and pathogenesis of malaria and provide insights into studies of antimalarial drugs and malaria vaccines.

Automated summary

This study investigated the gut microbiota composition of Py-infected BALB/c mice and found that Py infection could alter the gut microbiota composition. Furthermore, several bacterial taxa were found to be overrepresented at different time points after infection, providing insights into the progression and pathogenesis of malaria.