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A Functional Metagenomic Analysis of Tetracycline Resistance in Cheese Bacteria

Overview of attention for article published in Frontiers in Microbiology, May 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

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Title
A Functional Metagenomic Analysis of Tetracycline Resistance in Cheese Bacteria
Published in
Frontiers in Microbiology, May 2017
DOI 10.3389/fmicb.2017.00907
Pubmed ID
Authors

Ana B Flórez, Lucía Vázquez, Baltasar Mayo

Abstract

Metagenomic techniques have been successfully used to monitor antibiotic resistance genes in environmental, animal and human ecosystems. However, despite the claim that the food chain plays a key role in the spread of antibiotic resistance, metagenomic analysis has scarcely been used to investigate food systems. The present work reports a functional metagenomic analysis of the prevalence and evolution of tetracycline resistance determinants in a raw-milk, blue-veined cheese during manufacturing and ripening. For this, the same cheese batch was sampled and analyzed on days 3 and 60 of manufacture. Samples were diluted and grown in the presence of tetracycline on plate count milk agar (PCMA) (non-selective) and de Man Rogosa and Sharpe (MRS) agar (selective for lactic acid bacteria, LAB). DNA from the cultured bacteria was then isolated and used to construct four fosmid libraries, named after the medium and sampling time: PCMA-3D, PCMA-60D, MRS-3D, and MRS-60D. Clones in the libraries were subjected to restriction enzyme analysis, PCR amplification, and sequencing. Among the 300 fosmid clones analyzed, 268 different EcoRI restriction profiles were encountered. Sequence homology of their extremes clustered the clones into 47 groups. Representative clones of all groups were then screened for the presence of tetracycline resistance genes by PCR, targeting well-recognized genes coding for ribosomal protection proteins and efflux pumps. A single tetracycline resistance gene was detected in each of the clones, with four such resistance genes identified in total: tet(A), tet(L), tet(M), and tet(S). tet(A) was the only gene identified in the PCMA-3D library, and tet(L) the only one identified in the PCMA-60D and MRS-60D libraries. tet(M) and tet(S) were both detected in the MRS-3D library and in similar numbers. Six representative clones of the libraries were sequenced and analyzed. Long segments of all clones but one showed extensive homology to plasmids from Gram-positive and Gram-negative bacteria. tet(A) was found within a sequence showing strong similarity to plasmids pMAK2 and pO26-Vir from Salmonella enterica and Escherichia coli, respectively. All other genes were embedded in, or near to, sequences homologous to those of LAB species. These findings strongly suggest an evolution of tetracycline resistance gene types during cheese ripening, which might reflect the succession of the microbial populations. The location of the tetracycline resistance genes in plasmids, surrounded or directly flanked by open reading frames encoding transposases, invertases or mobilization proteins, suggests they might have a strong capacity for transference. Raw-milk cheeses should therefore be considered reservoirs of tetracycline resistance genes that might be horizontally transferred.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 66 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 14%
Researcher 9 14%
Student > Master 9 14%
Other 5 8%
Student > Bachelor 4 6%
Other 13 20%
Unknown 17 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 27%
Biochemistry, Genetics and Molecular Biology 8 12%
Immunology and Microbiology 7 11%
Veterinary Science and Veterinary Medicine 3 5%
Medicine and Dentistry 2 3%
Other 3 5%
Unknown 25 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 27 June 2017.
All research outputs
#4,309,326
of 24,093,053 outputs
Outputs from Frontiers in Microbiology
#4,161
of 27,122 outputs
Outputs of similar age
#72,159
of 317,189 outputs
Outputs of similar age from Frontiers in Microbiology
#148
of 508 outputs
Altmetric has tracked 24,093,053 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 27,122 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.5. This one has done well, scoring higher than 84% of its peers.
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 317,189 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 508 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.