Unravelling the complexity of bovine milk microbiome: insights into mastitis through enterotyping using full-length 16S-metabarcoding

Abstract

Abstract Background Mastitis, inflammation of the mammary gland, is a major disease of dairy cattle and the main cause for antimicrobial use. Although mainly caused by bacterial infections, the aetiological agent often remains unidentified by conventional microbiological culture methods. The aim of this study was to test whether shifts in the bovine mammary gland microbiota can result in initiation or progression of mastitis. Methods Oxford-Nanopore long-read sequencing was used to generate full-length 16S rRNA gene reads (16S-metabarcoding) to characterise the microbial population of milk from healthy and diseased udder of cows classified into five groups based on their mastitis history and parity. Results Samples were classified into six enterotypes, each characterised by a marker genus and several differentially-abundant genera. Two enterotypes were exclusively composed of clinical mastitis samples and displayed a marked dysbiosis, with a single pathogenic genus predominating and displacing the endogenous bacterial population. Other mastitis samples (all subclinical and half of the clinical) clustered with those from healthy animals into three enterotypes, probably reflecting intermediate states between health and disease. After an episode of clinical mastitis, clinical recovery and microbiome reconstitution do not always occur in parallel, indicating that the clinical definition of the udder health status does not consistently reflect the microbial profile. Conclusions These results show that mastitis is a dynamic process in which the udder microbiota constantly changes, highlighting the complexity of defining a unique microbiota profile indicative of mastitis.

Keywords

• Mastitis
• Dairy cattle
• Milk microbiome
• Full-length 16S-metabarcoding
• Long-read sequencing
• Enterotyping