Microbiota characterization of sheep milk and its association with somatic cell count using 16s rRNA gene sequencing.
J Anim Breed Genet
; 137(1): 73-83, 2020 Jan.
Article
in En
| MEDLINE
| ID: mdl-31602717
ABSTRACT
This work aimed to use 16S ribosomal RNA sequencing with the Illumina MiSeq platform to describe the milk microbiota from 50 healthy Assaf ewes. The global observed microbial community for clinically healthy milk samples analysed was complex and showed a vast diversity. The core microbiota of the sheep milk includes five genera Staphylococcus, Lactobacillus, Corynebacterium, Streptococcus and Escherichia/Shigella. Although there are some differences, some of these genera are common with the microbiota core pattern of milk from other species, especially with dairy cows. The microbial composition of the studied samples, based on the definition of amplicon sequence variants, was analysed through a correlation network. A preliminary analysis by grouping the milk samples based on their somatic cell count (SCC), which is considered an indicator of subclinical mastitis (SM), showed certain differences for the core of the samples identified as SM. The differences in the microbiota diversity pattern among samples might also suggest that subclinical mastitis would be associated with the significant increase in some genera that are inhabitants of the mammary gland and a remarkable concomitant reduction in the microbial diversity. Additionally, we have also presented here a preliminary analysis to assess the impact of the sheep milk microbiome on SCC, as an indicator of subclinical mastitis. The results here reported provide a first characterization of the sheep milk microbiota and settle the basis for future studies in this field.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Sheep
/
RNA, Ribosomal, 16S
/
Sequence Analysis, RNA
/
Milk
/
Microbiota
Type of study:
Risk_factors_studies
Limits:
Animals
Language:
En
Journal:
J Anim Breed Genet
Journal subject:
GENETICA
/
MEDICINA VETERINARIA
Year:
2020
Document type:
Article
Affiliation country: