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Evaluation of milk sample fractions for characterization of milk microbiota from healthy and clinical mastitis cows
Amplicon sequencing technique has been increasingly applied to the clinical setting as a sensitive diagnostic tool. Therefore, it is of great importance to develop a DNA extraction method that accurate isolates DNA from complex host-associated microbiota. Given the multifactorial etiology of clinica...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5862444/ https://www.ncbi.nlm.nih.gov/pubmed/29561873 http://dx.doi.org/10.1371/journal.pone.0193671 |
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author | Lima, Svetlana Ferreira Bicalho, Marcela Lucas de Souza Bicalho, Rodrigo Carvalho |
author_facet | Lima, Svetlana Ferreira Bicalho, Marcela Lucas de Souza Bicalho, Rodrigo Carvalho |
author_sort | Lima, Svetlana Ferreira |
collection | PubMed |
description | Amplicon sequencing technique has been increasingly applied to the clinical setting as a sensitive diagnostic tool. Therefore, it is of great importance to develop a DNA extraction method that accurate isolates DNA from complex host-associated microbiota. Given the multifactorial etiology of clinical mastitis and the diversified lifestyle of bacterial species harboring in milk, here four distinct milk sample fractions: raw whole milk, milk fat, casein-pellet, and casein-pellet + fat from healthy cows and cows with clinical mastitis, were subjected to bead-beating DNA extraction, followed by high-throughput sequencing. We aimed to identify the best approach for characterization of the milk microbiota and detection of mastitis pathogens (Klebsiella spp., Streptococcus spp. and Escherichia coli). DNA from each milk fraction tested was extracted by two commercial kits, which include physical, mechanical and chemical lysis; in total 280 DNA samples from 35 cows were analyzed. Milk-health-status were categorized into four groups (healthy group; E. coli-mastitis group; Klebsiella spp.-mastitis group; and Streptococcus spp.–mastitis group). Bacterial phyla and families were described for each milk-health-status group across milk sample fractions and DNA extraction kits. For the mastitis groups the relative abundance of f__Enterobacteriaceae and f__Streptococcaceae were compared to determine the efficacy of procedures in detecting the mastitis pathogens. The four milk fractions used allowed efficiently and uniformly detection of the causative agent of mastitis. Only 27% of the families detected in healthy milk were shared among the samples extracted from all fractions of milk samples; followed by 3, 4, and 12% for the samples from E. coli-mastitis, Klebsiella spp.-mastitis and Streptococcus spp-mastitis, respectively. However, the shared families comprised a mean relative abundance greater than 85%, regardless of milk-health-status, milk fraction and DNA isolation method. Taxonomic data at the family level showed that sequences from mastitis milk samples cultured positive for E. coli and Klebsiella spp. were predominantly affiliated with f__Enterobacteriaceae, while for Streptococcus spp. were dominated by f__Streptococcacea, followed by f__Pseudomonadaceae and f__Enterococcaceae. Microbial community analysis revealed that most of the microbial community composition corresponded to milk bacterial species irrespective of the DNA isolation method and milk fraction evaluated. |
format | Online Article Text |
id | pubmed-5862444 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-58624442018-03-28 Evaluation of milk sample fractions for characterization of milk microbiota from healthy and clinical mastitis cows Lima, Svetlana Ferreira Bicalho, Marcela Lucas de Souza Bicalho, Rodrigo Carvalho PLoS One Research Article Amplicon sequencing technique has been increasingly applied to the clinical setting as a sensitive diagnostic tool. Therefore, it is of great importance to develop a DNA extraction method that accurate isolates DNA from complex host-associated microbiota. Given the multifactorial etiology of clinical mastitis and the diversified lifestyle of bacterial species harboring in milk, here four distinct milk sample fractions: raw whole milk, milk fat, casein-pellet, and casein-pellet + fat from healthy cows and cows with clinical mastitis, were subjected to bead-beating DNA extraction, followed by high-throughput sequencing. We aimed to identify the best approach for characterization of the milk microbiota and detection of mastitis pathogens (Klebsiella spp., Streptococcus spp. and Escherichia coli). DNA from each milk fraction tested was extracted by two commercial kits, which include physical, mechanical and chemical lysis; in total 280 DNA samples from 35 cows were analyzed. Milk-health-status were categorized into four groups (healthy group; E. coli-mastitis group; Klebsiella spp.-mastitis group; and Streptococcus spp.–mastitis group). Bacterial phyla and families were described for each milk-health-status group across milk sample fractions and DNA extraction kits. For the mastitis groups the relative abundance of f__Enterobacteriaceae and f__Streptococcaceae were compared to determine the efficacy of procedures in detecting the mastitis pathogens. The four milk fractions used allowed efficiently and uniformly detection of the causative agent of mastitis. Only 27% of the families detected in healthy milk were shared among the samples extracted from all fractions of milk samples; followed by 3, 4, and 12% for the samples from E. coli-mastitis, Klebsiella spp.-mastitis and Streptococcus spp-mastitis, respectively. However, the shared families comprised a mean relative abundance greater than 85%, regardless of milk-health-status, milk fraction and DNA isolation method. Taxonomic data at the family level showed that sequences from mastitis milk samples cultured positive for E. coli and Klebsiella spp. were predominantly affiliated with f__Enterobacteriaceae, while for Streptococcus spp. were dominated by f__Streptococcacea, followed by f__Pseudomonadaceae and f__Enterococcaceae. Microbial community analysis revealed that most of the microbial community composition corresponded to milk bacterial species irrespective of the DNA isolation method and milk fraction evaluated. Public Library of Science 2018-03-21 /pmc/articles/PMC5862444/ /pubmed/29561873 http://dx.doi.org/10.1371/journal.pone.0193671 Text en © 2018 Lima et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Lima, Svetlana Ferreira Bicalho, Marcela Lucas de Souza Bicalho, Rodrigo Carvalho Evaluation of milk sample fractions for characterization of milk microbiota from healthy and clinical mastitis cows |
title | Evaluation of milk sample fractions for characterization of milk microbiota from healthy and clinical mastitis cows |
title_full | Evaluation of milk sample fractions for characterization of milk microbiota from healthy and clinical mastitis cows |
title_fullStr | Evaluation of milk sample fractions for characterization of milk microbiota from healthy and clinical mastitis cows |
title_full_unstemmed | Evaluation of milk sample fractions for characterization of milk microbiota from healthy and clinical mastitis cows |
title_short | Evaluation of milk sample fractions for characterization of milk microbiota from healthy and clinical mastitis cows |
title_sort | evaluation of milk sample fractions for characterization of milk microbiota from healthy and clinical mastitis cows |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5862444/ https://www.ncbi.nlm.nih.gov/pubmed/29561873 http://dx.doi.org/10.1371/journal.pone.0193671 |
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