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Insights Into the Bovine Milk Microbiota in Dairy Farms With Different Incidence Rates of Subclinical Mastitis
Bovine mastitis continues to be a complex disease associated with significant economic loss in dairy industries worldwide. The incidence rate of subclinical mastitis (IRSCM) can show substantial variation among different farms; however, the milk microbiota, which have a direct influence on bovine ma...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6232673/ https://www.ncbi.nlm.nih.gov/pubmed/30459717 http://dx.doi.org/10.3389/fmicb.2018.02379 |
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author | Pang, Maoda Xie, Xing Bao, Hongduo Sun, Lichang He, Tao Zhao, Hang Zhou, Yan Zhang, Lili Zhang, Hui Wei, Ruicheng Xie, Kaizhou Wang, Ran |
author_facet | Pang, Maoda Xie, Xing Bao, Hongduo Sun, Lichang He, Tao Zhao, Hang Zhou, Yan Zhang, Lili Zhang, Hui Wei, Ruicheng Xie, Kaizhou Wang, Ran |
author_sort | Pang, Maoda |
collection | PubMed |
description | Bovine mastitis continues to be a complex disease associated with significant economic loss in dairy industries worldwide. The incidence rate of subclinical mastitis (IRSCM) can show substantial variation among different farms; however, the milk microbiota, which have a direct influence on bovine mammary gland health, have never been associated with the IRSCM. Here, we aimed to use high-throughput DNA sequencing to describe the milk microbiota from two dairy farms with different IRSCMs and to identify the predominant mastitis pathogens along with commensal or potential beneficial bacteria. Our study showed that Klebsiella, Escherichia–Shigella, and Streptococcus were the mastitis-causing pathogens in farm A (with a lower IRSCM), while Streptococcus and Corynebacterium were the mastitis-causing pathogens in farm B (with a higher IRSCM). The relative abundance of all pathogens in farm B (22.12%) was higher than that in farm A (9.82%). However, the genus Bacillus was more prevalent in farm A. These results may be helpful for explaining the lower IRSCM in farm A. Additionally, the gut-associated genera Prevotella, Ruminococcus, Bacteroides, Rikenella, and Alistipes were prevalent in all milk samples, suggesting gut bacteria can be one of the predominant microbial contamination in milk. Moreover, Listeria monocytogenes (a foodborne pathogen) was found to be prevalent in farm A, even though it had a lower IRSCM. Overall, our study showed complex diversity between the milk microbiota in dairy farms with different IRSCMs. This suggests that variation in IRSCMs may not only be determined by the heterogeneity and prevalence of mastitis-causing pathogens but also be associated with potential beneficial bacteria. In the future, milk microbiota should be considered in bovine mammary gland health management. This would be helpful for both the establishment of a targeted mastitis control system and the control of the safety and quality of dairy products. |
format | Online Article Text |
id | pubmed-6232673 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-62326732018-11-20 Insights Into the Bovine Milk Microbiota in Dairy Farms With Different Incidence Rates of Subclinical Mastitis Pang, Maoda Xie, Xing Bao, Hongduo Sun, Lichang He, Tao Zhao, Hang Zhou, Yan Zhang, Lili Zhang, Hui Wei, Ruicheng Xie, Kaizhou Wang, Ran Front Microbiol Microbiology Bovine mastitis continues to be a complex disease associated with significant economic loss in dairy industries worldwide. The incidence rate of subclinical mastitis (IRSCM) can show substantial variation among different farms; however, the milk microbiota, which have a direct influence on bovine mammary gland health, have never been associated with the IRSCM. Here, we aimed to use high-throughput DNA sequencing to describe the milk microbiota from two dairy farms with different IRSCMs and to identify the predominant mastitis pathogens along with commensal or potential beneficial bacteria. Our study showed that Klebsiella, Escherichia–Shigella, and Streptococcus were the mastitis-causing pathogens in farm A (with a lower IRSCM), while Streptococcus and Corynebacterium were the mastitis-causing pathogens in farm B (with a higher IRSCM). The relative abundance of all pathogens in farm B (22.12%) was higher than that in farm A (9.82%). However, the genus Bacillus was more prevalent in farm A. These results may be helpful for explaining the lower IRSCM in farm A. Additionally, the gut-associated genera Prevotella, Ruminococcus, Bacteroides, Rikenella, and Alistipes were prevalent in all milk samples, suggesting gut bacteria can be one of the predominant microbial contamination in milk. Moreover, Listeria monocytogenes (a foodborne pathogen) was found to be prevalent in farm A, even though it had a lower IRSCM. Overall, our study showed complex diversity between the milk microbiota in dairy farms with different IRSCMs. This suggests that variation in IRSCMs may not only be determined by the heterogeneity and prevalence of mastitis-causing pathogens but also be associated with potential beneficial bacteria. In the future, milk microbiota should be considered in bovine mammary gland health management. This would be helpful for both the establishment of a targeted mastitis control system and the control of the safety and quality of dairy products. Frontiers Media S.A. 2018-10-16 /pmc/articles/PMC6232673/ /pubmed/30459717 http://dx.doi.org/10.3389/fmicb.2018.02379 Text en Copyright © 2018 Pang, Xie, Bao, Sun, He, Zhao, Zhou, Zhang, Zhang, Wei, Xie and Wang. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Microbiology Pang, Maoda Xie, Xing Bao, Hongduo Sun, Lichang He, Tao Zhao, Hang Zhou, Yan Zhang, Lili Zhang, Hui Wei, Ruicheng Xie, Kaizhou Wang, Ran Insights Into the Bovine Milk Microbiota in Dairy Farms With Different Incidence Rates of Subclinical Mastitis |
title | Insights Into the Bovine Milk Microbiota in Dairy Farms With Different Incidence Rates of Subclinical Mastitis |
title_full | Insights Into the Bovine Milk Microbiota in Dairy Farms With Different Incidence Rates of Subclinical Mastitis |
title_fullStr | Insights Into the Bovine Milk Microbiota in Dairy Farms With Different Incidence Rates of Subclinical Mastitis |
title_full_unstemmed | Insights Into the Bovine Milk Microbiota in Dairy Farms With Different Incidence Rates of Subclinical Mastitis |
title_short | Insights Into the Bovine Milk Microbiota in Dairy Farms With Different Incidence Rates of Subclinical Mastitis |
title_sort | insights into the bovine milk microbiota in dairy farms with different incidence rates of subclinical mastitis |
topic | Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6232673/ https://www.ncbi.nlm.nih.gov/pubmed/30459717 http://dx.doi.org/10.3389/fmicb.2018.02379 |
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