Integrated bacterial microbiome–metabolome profiling reveals coupled ecological and biochemical disruption in Cryptosporidium-infected neonatal dairy calves

Background: Cryptosporidiosis is a major cause of neonatal calf diarrhoea with significant economic impact. Although previous work documented dysbiosis in infected calves, no study has jointly characterized microbiome and metabolome at field scale in naturally infected animals stratified by clinical severity. We addressed this critical knowledge gap by examining whether dysbiosis-driven taxonomic shifts translate into measurable biochemical disruption that mechanistically links community composition to functional outcomes.

Methods: Faecal samples were collected from 134 pre-weaned calves across 23 farms in France, classified by Cryptosporidium parvum infection status (Healthy, n = 73; Asymptomatic, n = 41; Symptomatic, n = 20) using gp60 PCR. One hundred and two samples underwent dual profiling: 16S rRNA gene sequencing for community composition and quantitative ¹H-NMR spectroscopy for metabolite quantification (85 metabolites). We integrated both data layers via multivariate analysis, differential abundance testing, pathway enrichment and correlation network analysis.

Results: Health status explained 27.3% of microbiome variance (PERMANOVA, P = 0.001). Symptomatic calves showed reduced Shannon diversity, depletion of butyrogenic taxa and expansion of opportunistic genera including Enterococcus and Faecalimonas. Eight taxa displayed dose–response enrichment with parasite burden. Metabolically, symptomatic animals exhibited hallmark SCFA depletion (acetate, butyrate, propionate) coupled with overflow intermediates (lactate, ethanol, formate, succinate). Nine metabolites met combined criteria for discrimination; seven were novel: 5-aminopentanoate, π-methylhistidine, xanthine, trimethylamine, glycolate, isocitrate and N-acetylglucosamine. Pyruvate metabolism emerged as the top dysregulated pathway. Spearman correlation networks revealed two coherent modules: disease-enriched taxa co-occurring with overflow metabolites, while health-associated taxa correlated with SCFA production, directly coupling microbial ecology to biochemical function.

Conclusions: This study establishes a mechanistic paradigm demonstrating that parasite-driven dysbiosis directly disrupts energy harvest and metabolic function. The coupled microbiome–metabolite signature is robust across farms, scales with parasite burden, and detects early functional erosion in asymptomatic carriers. These findings support ecosystem-level interventions as mechanism-guided therapeutic approaches for a disease lacking licensed treatment.