Dataset Information

Microbiome and Metabolome Analyses of Milk From Dairy Cows With Subclinical Streptococcus agalactiae Mastitis-Potential Biomarkers.

ABSTRACT: The microbial ecosystem in the udders of dairy cows directly influences the flavor and quality of milk. However, to our knowledge, no published research has analyzed the complex relationship between the udder microbiome and its associated metabolism in animals with subclinical mastitis. We identified the bacterial species and measured relative population numbers in the milk of cows with subclinical Streptococcus agalactiae mastitis (GBS) and compared this information to that from the milk of healthy cows. Metabolite profiles were determined to investigate correlations between the milk microbiota and metabolic factors in healthy vs. GBS dairy cows. Six milk samples from GBS cows and six from healthy cows were subjected to 16S rRNA gene sequencing to identify the microbial species using a MiSeq high-throughput sequencing apparatus. The metabolites present in the milk were identified by gas chromatography time-of-flight mass spectrometry. Both principal component analysis and orthogonal partial least squares discriminant analysis indicated that the metabolites were well-separated from each other in the milk samples from the two groups. GBS dramatically altered microbial diversity, and the GBS group had significantly fewer Proteobacteria, Actinobacteria, and Acidobacteria than the CON group, with greater relative abundance of Firmicutes (p < 0.01). Several bacterial genera, such as Streptococcus, were significantly more abundant in milk from the GBS group than in milk from the CON group, and there was a tendency for greater abundance of Turicibacter (p = 0.07) and Enterococcus spp. (p = 0.07) in the GBS group. The levels of five milk metabolites were significantly higher in the GBS group than in the CON group: phenylpyruvic acid, the homogentisic acid: 4-hydroxyphenylpyruvic acid ratio, the xanthine: guanine ratio, uridine and glycerol. Metabolic pathway analysis of the different metabolites revealed that the following were enriched in both groups: galactose metabolism; pentose and glucuronate interconversion; starch and sucrose metabolism; alanine, aspartate and glutamate metabolism; arginine biosynthesis; citrate cycle (TCA cycle); D-glutamine and D-glutamate metabolism; and the neomycin, kanamycin, and gentamicin biosynthesis pathways. Several typical metabolites were highly correlated with specific ruminal bacteria, such as Streptococcaceae, Lachnospiraceae, Lactobacillaceae and Corynebacteriaceae, demonstrating the functional correlations between the milk microbiome and associated metabolites. These findings revealed that the milk microbiota and metabolite profiles were significantly different between the two groups of cows, raising the question of whether the microbiota associated with the bovine mammary gland could be related to mammary gland health. There was also a relationship between milk quality and the presence of spoilage bacteria. Other bacterial taxa should be investigated, as related information may provide insights into how perturbations in milk metabolomics profiles relate to differences in milk synthesis between healthy cows and those with subclinical mastitis.

SUBMITTER: Tong J

PROVIDER: S-EPMC6851174 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Microbiome and Metabolome Analyses of Milk From Dairy Cows With Subclinical <i>Streptococcus agalactiae</i> Mastitis-Potential Biomarkers.

Tong Jinjin J Zhang Hua H Zhang Yonghong Y Xiong Benhai B Jiang Linshu L

Frontiers in microbiology 20191106

The microbial ecosystem in the udders of dairy cows directly influences the flavor and quality of milk. However, to our knowledge, no published research has analyzed the complex relationship between the udder microbiome and its associated metabolism in animals with subclinical mastitis. We identified the bacterial species and measured relative population numbers in the milk of cows with subclinical <i>Streptococcus agalactiae</i> mastitis (GBS) and compared this information to that from the milk ...[more]

PMID: 31781063

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Project description:BackgroundDue to the high prevalence and complex etiology, bovine mastitis (BM) is one of the most important diseases to compromise dairy cow health and milk quality. The shift in milk compositions has been widely investigated during mastitis, but recent studies suggested that gastrointestinal microorganism also has a crucial effect on the inflammation of other peripheral tissues and organs, including the mammary gland. However, research focused on the variation of rumen inner-environment during mastitis is still limited. Therefore, the ruminal microbial profiles, metabolites, and milk compositions in cows with different udder health conditions were compared in the present study. Furthermore, the correlations between udder health status and ruminal conditions were investigated. Based on the somatic cell counts (SCC), California mastitis test (CMT) parameters and clinical symptoms of mastitis, 60 lactating Holstein dairy cows with similar body conditions (excepted for the udder health condition) were randomly divided into 3 groups (n = 20 per group) including the healthy (H) group, the subclinical mastitis (SM) group and the clinical mastitis (CM) group. Lactation performance and rumen fermentation parameters were recorded. And rumen microbiota and metabolites were also analyzed via 16S rRNA amplicon sequencing and untargeted metabolomics, respectively.ResultsAs the degree of mastitis increased, rumen lactic acid (LA) (P < 0.01), acetate, propionate, butyrate, valerate (P < 0.001), and total volatile fatty acids (TVFAs) (P < 0.01) concentrations were significantly decreased. In the rumen of CM cows, the significantly increased bacteria related to intestinal and oral inflammation, such as Lachnospiraceae (FDR-adjusted P = 0.039), Moraxella (FDR-adjusted P = 0.011) and Neisseriaceae (FDR-adjusted P = 0.036), etc., were accompanied by a significant increase in 12-oxo-20-dihydroxy-leukotriene B4 (FDR-adjusted P = 5.97 × 10- 9) and 10beta-hydroxy-6beta-isobutyrylfuranoeremophilane (FDR-adjusted P = 3.88 × 10- 10). Meanwhile, in the rumen of SM cows, the Ruminiclostridium_9 (FDR-adjusted P = 0.042) and Enterorhabdus (FDR-adjusted P = 0.043) were increased along with increasing methenamine (FDR-adjusted P = 6.95 × 10- 6), 5-hydroxymethyl-2-furancarboxaldehyde (5-HMF) (FDR-adjusted P = 2.02 × 10- 6) and 6-methoxymellein (FDR-adjusted P = 2.57 × 10- 5). The short-chain fatty acids (SCFAs)-producing bacteria and probiotics in rumen, including Prevoterotoella_1 (FDR-adjusted P = 0.045) and Bifidobacterium (FDR-adjusted P = 0.035), etc., were significantly reduced, with decreasing 2-phenylbutyric acid (2-PBA) (FDR-adjusted P = 4.37 × 10- 6).ConclusionThe results indicated that there was a significant shift in the ruminal microflora and metabolites associated with inflammation and immune responses during CM. Moreover, in the rumen of cows affected by SM, the relative abundance of several opportunistic pathogens and the level of metabolites which could produce antibacterial compounds or had a competitive inhibitory effect were all increased.

Project description:Simple Summary The microRNA (miRNA) cargos of exosomes isolated from milk were investigated in relation to the healthy conditions of the mammary gland. Samples were collected from a group of cows without mastitis (H), a group at risk of mastitis (ARM), and a group with subclinical mastitis (SCM). The differential expression analysis identified 38, 18, and 12 miRNAs (p < 0.05) in the comparisons of H vs. ARM, ARM vs. SCM, and H vs. SCM, respectively. Only bta-mir-221 was shared between the three groups. The miRNA cargos of milk exosomes can be considered to study the complex molecular machinery set in motion in response to mastitis in dairy cows and the quality of milk. Abstract The aim of this study was to compare the cargos of miRNA in exosomes isolated from the milk of healthy (H) cows, cows at risk of mastitis (ARM), and cows with subclinical mastitis (SCM). Based on the number of somatic cells and the percentage of polymorphonuclear cells, 10 cows were assigned to group H, 11 to group ARM, and 11 to group SCM. After isolating exosomes in milk by isoelectric precipitation and ultracentrifugation, the extracted RNA was sequenced to 50 bp long single reads, and these were mapped against Btau_5.0.1. The resulting 225 miRNAs were uploaded to the miRNet suite, and target genes for Bos taurus were identified based on the miRTarBase and miRanda databases. The list of differentially expressed target genes resulting from the comparisons of the three groups was enriched using the Function Explorer of the Kyoto Encyclopedia of Genes and Genomes. A total of 38, 18, and 12 miRNAs were differentially expressed (DE, p < 0.05) in the comparisons of H vs. ARM, ARM vs. SCM, and H vs. SCM, respectively. Only 1 DE miRNA was shared among the three groups (bta-mir-221), 1 DE miRNA in the H vs. SCM comparison, 9 DE miRNAs in the ARM vs. SCM comparison, and 21 DE miRNAs in the H vs. ARM comparison. A comparison of the enriched pathways of target genes from the H, SCM, and ARM samples showed that 19 pathways were differentially expressed in the three groups, while 56 were expressed in the H vs. SCM comparison and 57 in the H vs. ARM comparison. Analyzing milk exosome miRNA cargos can be considered as a promising approach to study the complex molecular machinery set in motion in response to mastitis in dairy cows.

Project description:BackgroundSubclinical intramammary infection (IMI) represents a significant problem in maintaining dairy cows' health. Disease severity and extent depend on the interaction between the causative agent, environment, and host. To investigate the molecular mechanisms behind the host immune response, we used RNA-Seq for the milk somatic cells (SC) transcriptome profiling in healthy cows (n = 9), and cows naturally affected by subclinical IMI from Prototheca spp. (n = 11) and Streptococcus agalactiae (S. agalactiae; n = 11). Data Integration Analysis for Biomarker discovery using Latent Components (DIABLO) was used to integrate transcriptomic data and host phenotypic traits related to milk composition, SC composition, and udder health to identify hub variables for subclinical IMI detection.ResultsA total of 1,682 and 2,427 differentially expressed genes (DEGs) were identified when comparing Prototheca spp. and S. agalactiae to healthy animals, respectively. Pathogen-specific pathway analyses evidenced that Prototheca's infection upregulated antigen processing and lymphocyte proliferation pathways while S. agalactiae induced a reduction of energy-related pathways like the tricarboxylic acid cycle, and carbohydrate and lipid metabolism. The integrative analysis of commonly shared DEGs between the two pathogens (n = 681) referred to the core-mastitis response genes, and phenotypic data evidenced a strong covariation between those genes and the flow cytometry immune cells (r2 = 0.72), followed by the udder health (r2 = 0.64) and milk quality parameters (r2 = 0.64). Variables with r ≥ 0.90 were used to build a network in which the top 20 hub variables were identified with the Cytoscape cytohubba plug-in. The genes in common between DIABLO and cytohubba (n = 10) were submitted to a ROC analysis which showed they had excellent predictive performances in terms of discriminating healthy and mastitis-affected animals (sensitivity > 0.89, specificity > 0.81, accuracy > 0.87, and precision > 0.69). Among these genes, CIITA could play a key role in regulating the animals' response to subclinical IMI.ConclusionsDespite some differences in the enriched pathways, the two mastitis-causing pathogens seemed to induce a shared host immune-transcriptomic response. The hub variables identified with the integrative approach might be included in screening and diagnostic tools for subclinical IMI detection.

Dataset Information

Microbiome and Metabolome Analyses of Milk From Dairy Cows With Subclinical Streptococcus agalactiae Mastitis-Potential Biomarkers.

Publications

Microbiome and Metabolome Analyses of Milk From Dairy Cows With Subclinical <i>Streptococcus agalactiae</i> Mastitis-Potential Biomarkers.

Similar Datasets

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