Background and aims: Cryptosporidiosis is a major global human health concern. Our understanding of the infection mechanism remains limited, compounding the difficulty of clinical diagnosis. This study investigated the underlying biochemistry of host-microbiome-parasite relationships during infection.
Methods: C57BL/6J mice were infected with 1 x 105Cryptosporidium parvum oocysts via oral gavage. Faecal samples were collected daily, while blood, liver tissues and luminal contents of the small and large intestines were collected 10 days post infection. High-resolution liquid chromatography and low-resolution gas chromatography coupled with mass spectrometry were used to analyse the proteomes and metabolomes of faeces, serum, liver, and luminal contents. Faecal samples were additionally subjected to 16S rRNA gene sequencing. Univariate and multivariate statistical analysis were applied to all datasets.
Results: Host and microbial energy pathways altered during infection. Glycolysis/citrate cycle metabolites, such as malate and lactate, were elevated in the large intestine. Short-chain fatty acids, formate and acetate, increased in the small intestine, while butanoate increased in the caecum-colon. This correlated with an increased abundance of bacteria associated with a stressed host environment, including Lactobacillus (small intestine) and Coriobacteriaceae (throughout the intestine, but more prominently in colon). The expression of host electron transfer flavoprotein, phosphoglycerate kinase and acetyl CoA binding proteins, yeast glyceraldehyde-3-phosphate dehydrogenase, and Lactobacillus glyceraldehyde-3-phosphate dehydrogenase significantly increased in the infected gut. Liver oxalate increase was also seen during infection.
Conclusions: The microbiome-parasite relationship is more influential than the previously thought host-parasite relationship, in mediating major biochemical changes in the mouse gut during cryptosporidiosis. Defining this parasite-microbiome interaction is the first step towards building a comprehensive cryptosporidiosis model.