Effects of Eimeria tenella infection on chicken caecal microbiome diversity, exploring variation associated with severity of pathology

Abstract

Eimeria species cause the intestinal disease coccidiosis, most notably in poultry. While the direct impact of coccidiosis on animal health and welfare is clear, its influence on the enteric microbiota and by-stander effects on chicken health and production remains largely unknown, with the possible exception of Clostridium perfringens (necrotic enteritis). This study evaluated the composition and structure of the caecal microbiome in the presence or absence of a defined Eimeria tenella challenge infection in Cobb500 broiler chickens using 16S rRNA amplicon sequencing. The severity of clinical coccidiosis in individual chickens was quantified by caecal lesion scoring and microbial changes associated with different lesion scores identified. Following E. tenella infection the diversity of taxa within the caecal microbiome remained largely stable. However, infection induced significant changes in the abundance of some microbial taxa. The greatest changes were detected in birds displaying severe caecal pathology; taxa belonging to the order Enterobacteriaceae were increased, while taxa from Bacillales and Lactobacillales were decreased with the changes correlated with lesion severity. Significantly different profiles were also detected in infected birds which remained asymptomatic (lesion score 0), with taxa belonging to the genera Bacteroides decreased and Lactobacillus increased. Many differential taxa from the order Clostridiales were identified, with some increasing and others decreasing in abundance in Eimeria-infected animals. The results support the view that caecal microbiome dysbiosis associated with Eimeria infection contributes to disease pathology, and could be a target for intervention to mitigate the impact of coccidiosis on poultry productivity and welfare. This work highlights that E. tenella infection has a significant impact on the abundance of some caecal bacteria with notable differences detected between lesion score categories emphasising the importance of accounting for differences in caecal lesions when investigating the relationship between E. tenella and the poultry intestinal microbiome.

Fig 1. Bar chart showing relative abundance of bacterial phyla in each broiler, sorted by severity of pathology.

Data were compiled using 8–10 individual caecal samples per infection status: LS 0 (n = 8, no lesions), LS 1 (n = 9, mild lesions), LS 2 (n = 10, moderate lesions), LS 3 (n = 10, severe lesions), LS 4 (n = 8, very severe lesions) and uninfected controls (n = 10). In each group there were three or four dominant phyla, as indicated in bold in the accompanying legend. In both infected (LS 0 –LS 4) and uninfected samples the phylum Firmicutes represented over 50% of all taxa in most birds.

Fig 2. Alpha-diversity plots for each treatment group.

Plot of bacterial species richness (Observed) and alpha diversity measures for each treatment group using; Chao1, ACE (Abundance-based Coverage Estimator), Shannon and Simpson tests. Circles represent individual samples, grouped by colour according to lesion score and uninfected (UN) samples. No significant differences were observed between any of the treatment groups using Kruskal-Wallis tests (P > 0.05).

Fig 3

Weighted UniFrac PCoA. (A) All samples, LS 0 to LS 4 and uninfected (B) Uninfected versus lesion score (LS) 4 (C) Lesion score 0 versus lesion score 3 (D) Lesion score 0 versus lesion score 4. Each point represents a single chicken caecal microbiome. Individual groups are represented by a unique symbol and colour combination. The comparisons shown were significant according to Adonis in Qiime (P < 0.05). Lesion scores 0 to 4 indicate increasing lesion severity.

Fig 4. Plots of OTUs that were significantly differentially abundant (padj < 0.05) according to DESeq2 analysis.

Significant OTUs are represented by single data points (with some data points overlapping), grouped by genus on the x-axis and by colour according to which taxonomic order the OTU originates. (A) Uninfected controls versus all infected samples (LS0 –LS 4), (B) uninfected controls versus lesion score 4, (C) lesion score 0 versus lesion score 3, (D) lesion score 0 versus lesion score 4.