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Profiling persistent tubercule bacilli from patient sputa during therapy predicts early drug efficacy

Overview of attention for article published in BMC Medicine, April 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

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Title
Profiling persistent tubercule bacilli from patient sputa during therapy predicts early drug efficacy
Published in
BMC Medicine, April 2016
DOI 10.1186/s12916-016-0609-3
Pubmed ID
Authors

Isobella Honeyborne, Timothy D. McHugh, Iitu Kuittinen, Anna Cichonska, Dimitrios Evangelopoulos, Katharina Ronacher, Paul D. van Helden, Stephen H. Gillespie, Delmiro Fernandez-Reyes, Gerhard Walzl, Juho Rousu, Philip D. Butcher, Simon J. Waddell

Abstract

New treatment options are needed to maintain and improve therapy for tuberculosis, which caused the death of 1.5 million people in 2013 despite potential for an 86 % treatment success rate. A greater understanding of Mycobacterium tuberculosis (M.tb) bacilli that persist through drug therapy will aid drug development programs. Predictive biomarkers for treatment efficacy are also a research priority. Genome-wide transcriptional profiling was used to map the mRNA signatures of M.tb from the sputa of 15 patients before and 3, 7 and 14 days after the start of standard regimen drug treatment. The mRNA profiles of bacilli through the first 2 weeks of therapy reflected drug activity at 3 days with transcriptional signatures at days 7 and 14 consistent with reduced M.tb metabolic activity similar to the profile of pre-chemotherapy bacilli. These results suggest that a pre-existing drug-tolerant M.tb population dominates sputum before and after early drug treatment, and that the mRNA signature at day 3 marks the killing of a drug-sensitive sub-population of bacilli. Modelling patient indices of disease severity with bacterial gene expression patterns demonstrated that both microbiological and clinical parameters were reflected in the divergent M.tb responses and provided evidence that factors such as bacterial load and disease pathology influence the host-pathogen interplay and the phenotypic state of bacilli. Transcriptional signatures were also defined that predicted measures of early treatment success (rate of decline in bacterial load over 3 days, TB test positivity at 2 months, and bacterial load at 2 months). This study defines the transcriptional signature of M.tb bacilli that have been expectorated in sputum after two weeks of drug therapy, characterizing the phenotypic state of bacilli that persist through treatment. We demonstrate that variability in clinical manifestations of disease are detectable in bacterial sputa signatures, and that the changing M.tb mRNA profiles 0-2 weeks into chemotherapy predict the efficacy of treatment 6 weeks later. These observations advocate assaying dynamic bacterial phenotypes through drug therapy as biomarkers for treatment success.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 112 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 29 26%
Student > Ph. D. Student 22 20%
Student > Master 12 11%
Student > Bachelor 9 8%
Student > Doctoral Student 8 7%
Other 13 12%
Unknown 19 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 21 19%
Agricultural and Biological Sciences 18 16%
Medicine and Dentistry 17 15%
Immunology and Microbiology 13 12%
Nursing and Health Professions 7 6%
Other 12 11%
Unknown 24 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 24. 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 24 March 2017.
All research outputs
#1,531,126
of 24,752,948 outputs
Outputs from BMC Medicine
#1,072
of 3,831 outputs
Outputs of similar age
#25,748
of 306,622 outputs
Outputs of similar age from BMC Medicine
#17
of 47 outputs
Altmetric has tracked 24,752,948 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,831 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 44.7. This one has gotten more attention than average, scoring higher than 72% 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 306,622 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 47 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 65% of its contemporaries.