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Role of MIRU-VNTR and spoligotyping in assessing the genetic diversity of Mycobacterium tuberculosis in Henan Province, China

Overview of attention for article published in BMC Infectious Diseases, September 2018
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6 tweeters

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Title
Role of MIRU-VNTR and spoligotyping in assessing the genetic diversity of Mycobacterium tuberculosis in Henan Province, China
Published in
BMC Infectious Diseases, September 2018
DOI 10.1186/s12879-018-3351-y
Pubmed ID
Authors

Jie Shi, Danwei Zheng, Yankun Zhu, Xiaoguang Ma, Shaohua Wang, Hui Li, Jin Xing

Abstract

Tuberculosis remains a serious threat to human health as an infectious disease in China. Henan, a most populated province in China, has a high incidence of tuberculosis (TB). Though the genetic diversity of Mycobacterium tuberculosis (MTB) has been investigated in many regions, there have been only a few studies on the molecular characteristics and drug resistance phenotypes in Henan. This is the first study on the genetic profile of MTB from Henan. A total of 668 MTB isolates from various areas were genotyped with spoligotyping and 26-locus MIRU-VNTR (classical 24-locus MIRU-VNTR and 2 other loci). The association between TB spoligotype signatures and drug-resistant profiles was analysed. Our data revealed that MTB isolates circulating in Henan had a high degree of genetic variation. The Beijing family was the most predominant genotype (83.53%,n = 558), and the typical Beijing type(ST1) was the major sublineage (81.73%,n = 546). In total,668 isolates were divided into 567 different types, forming 38 clusters (2-15 isolates per cluster), and 529 unique types by 26-locus MIRU-VNTR analysis. There was no correlation between the Beijing family and gender, age at diagnosis or treatment history, whereas the Beijing family was significantly associated with all four first-line drug resistance and multidrug-resistant phenotypes. For these samples, 15 of 26 MIRU-VNTR loci had high or moderate discriminatory power according to the Hunter-Gaston discriminatory index. A combination of the 10 most polymorphic loci had similar discriminatory power as the 26-locus set. The Beijing genotype is the most prevalent family. Ten-locus MIRU-VNTR in combination with spoligotyping can efficiently classify the molecular type of MTB in Henan Province.

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 57 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 18%
Student > Bachelor 9 16%
Student > Master 4 7%
Unspecified 3 5%
Student > Postgraduate 2 4%
Other 5 9%
Unknown 24 42%
Readers by discipline Count As %
Medicine and Dentistry 11 19%
Immunology and Microbiology 8 14%
Biochemistry, Genetics and Molecular Biology 3 5%
Unspecified 3 5%
Agricultural and Biological Sciences 3 5%
Other 5 9%
Unknown 24 42%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 12 October 2018.
All research outputs
#9,134,867
of 15,915,110 outputs
Outputs from BMC Infectious Diseases
#2,490
of 5,796 outputs
Outputs of similar age
#138,404
of 276,637 outputs
Outputs of similar age from BMC Infectious Diseases
#1
of 1 outputs
Altmetric has tracked 15,915,110 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,796 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one has gotten more attention than average, scoring higher than 54% 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 276,637 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them