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Application of a Dot Blot Hybridization Platform to Assess Streptococcus uberis Population Structure in Dairy Herds

Overview of attention for article published in Frontiers in Microbiology, January 2017
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Title
Application of a Dot Blot Hybridization Platform to Assess Streptococcus uberis Population Structure in Dairy Herds
Published in
Frontiers in Microbiology, January 2017
DOI 10.3389/fmicb.2017.00054
Pubmed ID
Authors

Pedro Albuquerque, Niza Ribeiro, Alexandre Almeida, Irena Panschin, Afonso Porfirio, Marta Vales, Francisca Diniz, Helena Madeira, Fernando Tavares

Abstract

Streptococcus uberis is considered one of the most important pathogens associated with bovine mastitis. While traditionally acknowledged as an environmental pathogen, S. uberis has been shown to adopt a contagious epidemiological pattern in several dairy herds. Since different control strategies are employed depending on the mode of transmission, in-depth studies of S. uberis populations are essential to determine the best practices to control this pathogen. In this work, we optimized and validated a dot blot platform, combined with automatic image analysis, to rapidly assess the population structure of infective S. uberis, and evaluated its efficiency when compared to multilocus sequence analysis (MLSA) genotyping. Two dairy herds with prevalent S. uberis infections were followed in a 6 month period, in order to collect and characterize isolates from cows with persistent infections. These herds, located in Portugal (Barcelos and Maia regions), had similar management practices, with the herd from Barcelos being smaller and having a better milking parlor management, since infected cow segregation was immediate. A total of 54 S. uberis isolates were obtained from 24 different cows from the two herds. To overcome operator-dependent analysis of the dot blots and increase the technique's consistency and reliability, the hybridization signals were converted into probability values, with average probabilities higher than 0.5 being considered positive results. These data allowed to confirm the isolates' identity as S. uberis using taxa-specific markers and to determine the presence of virulence- and antibiotic resistance-related genes. In addition, MLSA allowed to disclose the most prevalent S. uberis clonal lineages in both herds. Seven different clusters were identified, with Barcelos showing a high clonal diversity and Maia a dominant lineage infecting most cows, suggesting distinct epidemiological patterns, with S. uberis displaying an environmental or contagious transmission pattern depending on the herd. Overall, this work showed the utility of dot blot and MLSA to characterize population structure and epidemiological patterns of mastitis-causing S. uberis. This approach allowed to disclose prevalent virulence patterns and clonal lineages of S. uberis in two distinct herds, and gain insights on the impact of herd management practices on pathogen population structure.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 25%
Student > Bachelor 4 13%
Student > Doctoral Student 2 6%
Professor > Associate Professor 2 6%
Researcher 2 6%
Other 5 16%
Unknown 9 28%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 28%
Biochemistry, Genetics and Molecular Biology 3 9%
Medicine and Dentistry 3 9%
Business, Management and Accounting 2 6%
Veterinary Science and Veterinary Medicine 2 6%
Other 2 6%
Unknown 11 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 January 2017.
All research outputs
#18,525,776
of 22,947,506 outputs
Outputs from Frontiers in Microbiology
#19,422
of 24,976 outputs
Outputs of similar age
#309,738
of 419,047 outputs
Outputs of similar age from Frontiers in Microbiology
#339
of 407 outputs
Altmetric has tracked 22,947,506 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 24,976 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one is in the 9th percentile – i.e., 9% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 419,047 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 407 others from the same source and published within six weeks on either side of this one. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.