Evidence map›Paper›PMID 27055815›Full record

ArticleBMC medicine2016

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

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 and 3 more

Abstract read
In one paragraph

Article in BMC medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed.

  1. Article
  2. Article
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  4. Transcript-Capture sequencing enriches mRNA ofbioRxiv : the preprint server for biology · 2025
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  7. EfpA is required for regrowth ofAntimicrobial agents and chemotherapy · 2024
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  11. Biomedicines · 2022
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  12. Article
  13. Article
  14. Review
  15. Article
  16. TheFrontiers in immunology · 2021
    Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Isobella HoneyborneCentre for Clinical Microbiology, University College London, London, NW3 2PF, UK.
Timothy D McHughCentre for Clinical Microbiology, University College London, London, NW3 2PF, UK.
Iitu KuittinenDepartment of Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Espoo, Finland.
Anna CichonskaDepartment of Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Espoo, Finland.
Dimitrios EvangelopoulosCentre for Clinical Microbiology, University College London, London, NW3 2PF, UK.
Katharina RonacherDepartment of Science and Technology/National Research Foundation Centre of Excellence for Biomedical Tuberculosis Research and Medical Research Council Centre for TB Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Western Cape, South Africa.
Paul D van HeldenDepartment of Science and Technology/National Research Foundation Centre of Excellence for Biomedical Tuberculosis Research and Medical Research Council Centre for TB Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Western Cape, South Africa.
Stephen H GillespieMedical and Biological Sciences Building, University of St Andrews, North Haugh, St Andrews, Fife, KY16 9TF, UK.
Delmiro Fernandez-ReyesDepartment of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK.
Gerhard WalzlDepartment of Science and Technology/National Research Foundation Centre of Excellence for Biomedical Tuberculosis Research and Medical Research Council Centre for TB Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Western Cape, South Africa.
Juho RousuDepartment of Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Espoo, Finland.
Philip D ButcherInstitute for Infection and Immunity, St George's University of London, London, SW17 0RE, UK.
Simon J WaddellBrighton and Sussex Medical School, University of Sussex, Brighton, BN1 9PX, UK. s.waddell@bsms.ac.uk.

Funding

Medical Research Council G0601466
6 · The paper itself

Abstract

backgroundNew 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. METHODS AND

resultsGenome-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).

conclusionsThis 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.

Indexed as

Mycobacterium tuberculosisTuberculosis, PulmonaryAntitubercular AgentsBacillusChromosome MappingDrug MonitoringFemaleHumansMaleMiddle AgedPredictive Value of TestsRNA, MessengerSputumAntitubercular AgentsRNA, MessengerMycobacterium tuberculosisPersistent infectionPredictive biomarkerSputumTranscriptional profiling

Identifiers

PMID27055815
PMCPMC4825072

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.