The milk of lactating cows presents a complex ecosystem of interconnected microbial communities which can influence the pathophysiology of mastitis. We hypothesized possible dynamic shifts of microbiome composition and genomic features with different pathological conditions of mastitis (Clinical Mastitis; CM, Recurrent CM; RCM, Subclinical Mastitis; SCM). To evaluate this hypothesis, we employed whole metagenome sequencing (WMS) in 20 milk samples (CM, 5; RCM, 6; SCM, 4; H, 5) to unravel the microbiome dynamics, interrelation, and relevant metabolic functions. The WMS data mapped to 442 bacterial, 58 archaeal and 48 viral genomes with distinct variation in microbiome composition (CM > H > RCM > SCM). Furthermore, we identified a number of microbial genomic features, including 333, 304, 183 and 50 virulence factors-associated genes (VFGs) and 48, 31, 11 and 6 antibiotic resistance genes (ARGs) in CM, RCM, SCM, and H-microbiomes, respectively. We also detected different metabolic pathway and functional genes associated with mastitis pathogenesis. Therefore, profiling microbiome dynamics in different conditions of mastitis and associated microbial genomic features contributes to developing microbiome-based diagnostics and therapeutics for bovine mastitis.
Keywords: Clinical; Microbiome; Recurrent clinical; Shift; Subclinical mastitis; Virulence and antibiotics resistant genes; Whole metagenome sequencing.
Copyright © 2020. Published by Elsevier Inc.