Variation in gut bacterial composition is associated with Haemonchus contortus parasite infection of sheep

Abstract

Background: One of the greatest impediments to global small ruminant production is infection with the gastrointestinal parasite, Haemonchus contortus. In recent years there has been considerable interest in the gut microbiota and its impact on health. Relatively little is known about interactions between the gut microbiota and gastrointestinal tract pathogens in sheep. Thus, this study was undertaken to investigate the link between the faecal microbiota of sheep, as a sample representing the gastrointestinal microbiota, and infection with H. contortus. Results: Sheep (n = 28) were experimentally inoculated with 14,000 H. contortus infective larvae. Faecal samples were collected 4 weeks prior to and 4 weeks after infection. Microbial analyses were conducted using automated ribosomal intergenic spacer analysis (ARISA) and 16S rRNA gene sequencing. A comparison of pre-infection microbiota to post-infection microbiota was conducted. A high parasite burden associated with a relatively large change in community composition, including significant (p ≤ 0.001) differences in the relative abundances of Firmicutes and Bacteroidetes following infection. In comparison, low parasite burden associated with a smaller change in community composition, with the relative abundances of the most abundant phyla remaining stable. Interestingly, differences were observed in pre-infection faecal microbiota in sheep that went on to develop a high burden of H. contortus infection (n = 5) to sheep that developed a low burden of infection (n = 5). Differences observed at the community level and also at the taxa level, where significant (p ≤ 0.001) in relative abundance of Bacteroidetes (higher in high parasite burden sheep) and Firmicutes (lower in high parasite burden sheep). Conclusions: This study reveals associations between faecal microbiota and high or low H. contortus infection in sheep. Further investigation is warranted to investigate causality and the impact of microbiome manipulation.