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 Published: 11 Dec 2017 | Last Updated: 11 Dec 2017 10:46:56

Dr Dong Xia has been awarded a grant by the  to work on Impact of Eimeria Infection on Chicken Organ-Specific Microbiota and Host Cell Responses. He will be working closely with Professors Fiona Tomley and Damer Blake on this project.

Chickens are the most numerous livestock species in the world and account for 43% of meat consumed in the UK. Infectious diseases of chickens have significant impact on food security and animal welfare, as well as prompting food safety concerns for pathogens with zoonotic potential. In addition to study on isolated effects from individual infectious agents, increasing evidence has highlighted the importance of understanding the interplay of concurrent infection events. For example, it has been demonstrated that Eimeria maxima and Clostridium perfringens together create a more severe phenotype of necrotic enteritis in chickens.  

Previous work in the group has demonstrated the influence of the coccidian parasite Eimeria tenella on Campylobacter jejuni count in various chicken organs, where the Eimeria infection event has resulted in a 2-log increase in C. jejuni count in the caeca. Intriguingly, C. jejuni counts in liver and spleen exhibited a concurrent 1-log decrease. The mechanisms of Eimeria infection affecting these bacteria abnormalities in the extra-intestinal sampling sites as well as its effect on the broader host microbiome remains unclear. Moreover, the group have qPCR data indicating variations in liver beta-defensin profiles +/- Eimeria, suggesting the involvement of host factors during these infections.  

The group hypothesize that the bacterial abnormalities observed within different chicken organs influenced by Eimeria infection has a wider implication in chicken health, productivity and risk to human health, and that host factors also play important roles in these concurrent infection events. They propose to test these hypotheses by investigating chicken organ-specific microbiota using Illumina next-generation sequencing and host responses from simultaneously collected samples using a quantitative proteomics approach. An integrative bioinformatics approach will be employed to decipher the host-pathogen interactions during the infection.