Bovine Teat Cistern Microbiota Composition and Richness Are Associated With the Immune and Microbial Responses During Transition to Once-Daily Milking

Rault, Lucie; Leveque, Pierre-Alexandre; Barbey, Sarah; Launay, Frédéric; Larroque, Hélène; Loir, Yves Le; Germon, Pierre; Guinard-Flament, Jocelyne; Even, Sergine

doi:10.3389/fmicb.2020.602404

Cited by 12 publications

(8 citation statements)

References 47 publications

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“…The 16S rRNA approach uses sequence variability in certain regions of the 16S rRNA gene to taxonomically classify DNA fragments extracted from a raw sample such as bovine milk [10]. Using this approach, previous studies have reported associations between the bovine milk microbiome and immune responses [11], development of mastitis [4], quality and safety of dairy products [12], and the gut microbiota of both calves and consumers [5,13]. Taken together, this body of literature suggests that the milk microbiome is a crucial component of cow health and production as well as milk safety and quality.…”

Section: Introductionmentioning

confidence: 99%

The impact of kit, environment and sampling contamination on the observed microbiome of bovine milk

Dean,

Deng,

Wehri

et al. 2023

Preprint

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Contaminants can easily outnumber bacteria that originate within the milk itself, milk microbiome research currently suffers from a critical knowledge gap; namely, does non-mastitis bovine milk contain a native microbiome? In this study, we sampled external and internal mammary epithelium, stripped and cisternal milk, used numerous negative controls to identify potential sources of microbial contamination. Two algorithms were used to mathematically remove this contamination and to track potential movement of microbes among our samples. Our results suggest that majority (i.e., >75%) of the sequence data generated from bovine milk and mammary epithelium samples represents contaminating DNA. The contaminants in milk samples were primarily sourced from the DNA extraction kits and the internal and external skin of the teat, while the teat canal and apex samples were mainly contaminated during the sampling process. After decontamination, the milk microbiome displayed a more dispersed, less diverse and compositionally distinct bacterial profile compared with the teat skin samples. Similar microbial compositions were observed between cisternal and stripped milk samples, as well as between teat apex and canal samples.StaphylococcusandAcinetobacterwere the predominant genera detected in the sequences of milk samples, and bacterial culture showed growth ofStaphylococcusandCorynebacteriumspp. in 50% (7/14) of stripped milk samples and growth ofStaphylococcusspp. in 7% (1/14) of cisternal milk samples. Our study suggests that microbiome data generated from milk samples obtained from clinically healthy bovine udders may be heavily biased by contaminants that enter the sample during the sample collection and processing workflows.ImportanceObtaining a non-contaminated sample of bovine milk is challenging due to the nature of the sampling environment and the route by which milk is typically extracted from the mammary gland. Furthermore, the very low bacterial biomass of bovine milk exacerbates the impacts of contaminant sequences in downstream analyses, which can lead to severe biases. Our finding showed that bovine milk contains very low bacterial biomass, and each contamination event (including sampling procedure and DNA extraction process) introduces bacteria and/or DNA fragments that easily outnumber the native bacterial cells. This finding has important implications for our ability to draw robust conclusions from milk microbiome data, especially if the data have not been subjected to rigorous decontamination procedures. Based on these findings, we strongly urge researchers to include numerous negative controls into their sampling and sample processing workflows; and to utilize several complementary methods for identifying potential contaminants within the resulting sequence data. These measures will improve the accuracy, reliability, reproducibility, and interpretability of milk microbiome data and research.

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Section: Introductionmentioning

confidence: 99%

The impact of kit, environment and sampling contamination on the observed microbiome of bovine milk

Dean,

Deng,

Wehri

et al. 2023

Preprint

View full text Add to dashboard Cite

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“…Lima et al found that primiparous cows, as opposed to multiparous cows, harbors microbial diversity and taxonomic markers that likely contributes to a healthier udder [ 21 ]. Studies have also discovered that a greater richness of the udder microbiota makes the udder more resistant to infection [ 22 – 24 ]. These studies all put emphasis on the microbial composition of the udder.…”

Section: Introductionmentioning

confidence: 99%

Metataxonomic analysis and host proteome response in dairy cows with high and low somatic cell count: a quarter level investigation

Winther

Duarte

Porcellato

2023

Vet Res

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Host response to invasive microbes in the bovine udder has an important role on the animal health and is essential to the dairy industry to ensure production of high-quality milk and reduce the mastitis incidence. To better understand the biology behind these host-microbiome interactions, we investigated the somatic cell proteomes at quarter level for four cows (collected before and after milking) using a shotgun proteomics approach. Simultaneously, we identified the quarter microbiota by amplicon sequencing to detect presence of mastitis pathogens or other commensal taxa. In total, 32 quarter milk samples were analyzed divided in two groups depending on the somatic cell count (SCC). The high SCC group (>100,000 cell/mL) included 10 samples and significant different proteome profiles were detected. Differential abundance analysis uncovers a specific expression pattern in high SCC samples revealing pathways involved in immune responses such as inflammation, activation of the complement system, migration of immune cells, and tight junctions. Interestingly, different proteome profiles were also identified in quarter samples containing one of the two mastitis pathogens, Staphylococcus aureus and Streptococcus uberis, indicating a different response of the host depending on the pathogen. Weighted correlation network analysis identified three modules of co-expressed proteins which were correlated with the SCC in the quarters. These modules contained proteins assigned to different aspects of the immune response, but also amino sugar and nucleotide sugar metabolism, and biosynthesis of amino acids. The results of this study provide deeper insights on how the proteome expression changes at quarter level in naturally infected cows and pinpoint potential interactions and important biological functions during host-microbe interaction.

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“…Bovine mastitis, caused by a variety of organisms, including Staphylococci, Streptococci, and Enterobacteria, is a mammary gland infection posing a great threat to the dairy industry, and is the costliest disease affecting cattle, due to its impact on the quality and quantity of milk production 1 , 2 . The immune response to pathogens in the mammary gland is highly complex, having to first identify the pathogen, recruit the appropriate immune cells, remove the pathogen, and then terminate the inflammatory response 3 .…”

Section: Introductionmentioning

confidence: 99%

Regulatory network of miRNA, lncRNA, transcription factor and target immune response genes in bovine mastitis

Tucker

Salazar

Ayoola

et al. 2021

Sci Rep

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Pre- and post-transcriptional modifications of gene expression are emerging as foci of disease studies, with some studies revealing the importance of non-coding transcripts, like long non-coding RNAs (lncRNAs) and microRNAs (miRNAs). We hypothesize that transcription factors (TFs), lncRNAs and miRNAs modulate immune response in bovine mastitis and could potentially serve as disease biomarkers and/or drug targets. With computational analyses, we identified candidate genes potentially regulated by miRNAs and lncRNAs base pair complementation and thermodynamic stability of binding regions. Remarkably, we found six miRNAs, two being bta-miR-223 and bta-miR-24-3p, to bind to several targets. LncRNAs NONBTAT027932.1 and XR_003029725.1, were identified to target several genes. Functional and pathway analyses revealed lipopolysaccharide-mediated signaling pathway, regulation of chemokine (C-X-C motif) ligand 2 production and regulation of IL-23 production among others. The overarching interactome deserves further in vitro/in vivo explication for specific molecular regulatory mechanisms during bovine mastitis immune response and could lay the foundation for development of disease markers and therapeutic intervention.

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Bovine Teat Cistern Microbiota Composition and Richness Are Associated With the Immune and Microbial Responses During Transition to Once-Daily Milking

Cited by 12 publications

References 47 publications

The impact of kit, environment and sampling contamination on the observed microbiome of bovine milk

The impact of kit, environment and sampling contamination on the observed microbiome of bovine milk

Metataxonomic analysis and host proteome response in dairy cows with high and low somatic cell count: a quarter level investigation

Regulatory network of miRNA, lncRNA, transcription factor and target immune response genes in bovine mastitis

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