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An Optimized Method for Extracting Bacterial RNA from Mouse Skin Tissue Colonized by Mycobacterium ulcerans

Overview of attention for article published in Frontiers in Microbiology, March 2017
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Title
An Optimized Method for Extracting Bacterial RNA from Mouse Skin Tissue Colonized by Mycobacterium ulcerans
Published in
Frontiers in Microbiology, March 2017
DOI 10.3389/fmicb.2017.00512
Pubmed ID
Authors

Marie Robbe-Saule, Jérémie Babonneau, Odile Sismeiro, Laurent Marsollier, Estelle Marion

Abstract

Bacterial transcriptome analyses during host colonization are essential to decipher the complexity of the relationship between the bacterium and its host. RNA sequencing (RNA-seq) is a promising approach providing valuable information about bacterial adaptation, the host response and, in some cases, mutual tolerance underlying crosstalk, as recently observed in the context of Mycobacterium ulcerans infection. Buruli ulcer is caused by M. ulcerans. This neglected disease is the third most common mycobacterial disease worldwide. Without treatment, M. ulcerans provokes massive skin ulcers. A healing process may be observed in 5% of Buruli ulcer patients several months after the initiation of disease. This spontaneous healing process suggests that some hosts can counteract the development of the lesions caused by M. ulcerans. Deciphering the mechanisms involved in this process should open up new treatment possibilities. To this end, we recently developed the first mouse model for studies of the spontaneous healing process. We have shown that the healing process is based on mutual tolerance between the bacterium and its host. In this context, RNA-seq seems to be the most appropriate method for deciphering bacterial adaptation. However, due to the low bacterial load in host tissues, the isolation of mycobacterial RNA from skin tissue for RNA-seq analysis remains challenging. We developed a method for extracting and purifying mycobacterial RNA whilst minimizing the amount of host RNA in the sample. This approach was based on the extraction of bacterial RNA by a differential lysis method. The challenge in the development of this method was the choice of a lysis system favoring the removal of host RNA without damage to the bacterial cells. We made use of the thick, resistant cell wall of M. ulcerans to achieve this end.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 61 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 25%
Student > Master 10 16%
Researcher 8 13%
Student > Doctoral Student 6 10%
Student > Bachelor 4 7%
Other 8 13%
Unknown 10 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 31%
Biochemistry, Genetics and Molecular Biology 16 26%
Medicine and Dentistry 5 8%
Immunology and Microbiology 4 7%
Unspecified 3 5%
Other 3 5%
Unknown 11 18%
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 11 April 2017.
All research outputs
#18,541,268
of 22,963,381 outputs
Outputs from Frontiers in Microbiology
#19,444
of 25,008 outputs
Outputs of similar age
#235,348
of 309,202 outputs
Outputs of similar age from Frontiers in Microbiology
#382
of 474 outputs
Altmetric has tracked 22,963,381 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 25,008 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 309,202 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 474 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.