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Whole genome sequencing data of 1110 Mycobacterium tuberculosis isolates identifies insertions and deletions associated with drug resistance

Overview of attention for article published in BMC Genomics, May 2018
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  • Above-average Attention Score compared to outputs of the same age (60th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

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Title
Whole genome sequencing data of 1110 Mycobacterium tuberculosis isolates identifies insertions and deletions associated with drug resistance
Published in
BMC Genomics, May 2018
DOI 10.1186/s12864-018-4734-6
Pubmed ID
Authors

Xi Zeng, Jamie Sui-Lam Kwok, Kevin Yi Yang, Kenneth Siu-Sing Leung, Mai Shi, Zhiyuan Yang, Wing-Cheong Yam, Stephen Kwok-Wing Tsui

Abstract

Drug resistance in Mycobacterium tuberculosis (MTB) is one of the major challenges in tuberculosis (TB) treatment. However, known mutations cannot explain all of the cases of resistance and little research has focused on the relationship between insertions / deletions (indels) and drug resistance. Here, we retrieved whole genome sequencing data of 743 drug-resistant MTB strains and 367 pan-susceptible strains from TB patients from the public domain to identify novel genomic markers of drug resistance. A total of 20 region markers containing genes and intergenic regions (IGRs) with significant statistical correlation with antibiotic resistance were revealed, four of which have been previously reported to be associated with drug resistance. In addition, 83 point markers containing frameshift (FS) mutations and IGR indels were also identified independently based on differences in their incidence rates between drug-sensitive and -resistant strains. Among the 83 point markers, eight indels were detected in known drug-associated genes or IGRs. Furthermore, the overlap between 20 region markers and 83 point markers further indicated their associations with drug resistance. The markers identified were involved in essential bacterial metabolic functions, including cell wall and transmembrane transporter functions. A strong correlation between FS mutations and mutations in DNA repair genes including I21V in alkA, R48G in mutT4 and P2R in nth was also found. This study identified a set of novel genetic markers with FS mutations and IGR indels associated with MTB drug resistance, which greatly broadens the pool of mutations related to MTB drug resistance. This insight may be important in identifying novel mechanisms of drug resistance in MTB.

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X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 92 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 20 22%
Researcher 16 17%
Student > Ph. D. Student 13 14%
Other 4 4%
Professor 4 4%
Other 15 16%
Unknown 20 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 24 26%
Agricultural and Biological Sciences 14 15%
Medicine and Dentistry 10 11%
Immunology and Microbiology 8 9%
Computer Science 5 5%
Other 7 8%
Unknown 24 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 22 May 2018.
All research outputs
#7,895,566
of 24,460,744 outputs
Outputs from BMC Genomics
#3,613
of 10,986 outputs
Outputs of similar age
#128,811
of 332,493 outputs
Outputs of similar age from BMC Genomics
#90
of 255 outputs
Altmetric has tracked 24,460,744 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 10,986 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 65% 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 332,493 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.
We're also able to compare this research output to 255 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 63% of its contemporaries.