Evidence map›Paper›PMID 28852109›Full record

ArticleScientific reports2017

Label-free optical vibrational spectroscopy to detect the metabolic state of M. tuberculosis cells at the site of disease.

Vincent O Baron, Mingzhou Chen, Simon O Clark, Ann Williams, Robert J H Hammond, Kishan Dholakia, Stephen H Gillespie

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
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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

7 authors.

Vincent O BaronSchool of Medicine, University of St Andrews, St Andrews, KY16 9TF, UK.
Mingzhou ChenSUPA, School of Physics and Astronomy, University of St Andrews, KY16 9SS, St Andrews, UK. mingzhou.chen@st-andrews.ac.uk.ORCID 0000-0002-6190-5167
Simon O ClarkPublic Health England, Porton Down, Salisbury, Wiltshire, SP4 0JG, UK.
Ann WilliamsPublic Health England, Porton Down, Salisbury, Wiltshire, SP4 0JG, UK.
Robert J H HammondSchool of Medicine, University of St Andrews, St Andrews, KY16 9TF, UK.
Kishan DholakiaSUPA, School of Physics and Astronomy, University of St Andrews, KY16 9SS, St Andrews, UK.
Stephen H GillespieSchool of Medicine, University of St Andrews, St Andrews, KY16 9TF, UK. shg3@st-andrews.ac.uk.

Funding

Department of Health
6 · The paper itself

Abstract

Tuberculosis relapse is a barrier to shorter treatment. It is thought that lipid rich cells, phenotypically resistant to antibiotics, may play a major role. Most studies investigating relapse use sputum samples although tissue bacteria may play an important role. We developed a non-destructive, label-free technique combining wavelength modulated Raman (WMR) spectroscopy and fluorescence detection (Nile Red staining) to interrogate Mycobacterium tuberculosis cell state. This approach could differentiate single "dormant" (lipid rich, LR) and "non-dormant" (lipid poor, LP) cells with high sensitivity and specificity. We applied this to experimentally infected guinea pig lung sections and were able to distinguish both cell types showing that the LR phenotype dominates in infected tissue. Both in-vitro and ex-vivo spectra correlated well, showing for the first time that Mycobacterium tuberculosis, likely to be phenotypically resistant to antibiotics, are present in large numbers in tissue. This is an important step in understanding the pathology of relapse supporting the idea that they may be caused by M. tuberculosis cells with lipid inclusions.

Indexed as

Spectrum AnalysisAnimalsBiomarkersEnergy MetabolismGuinea PigsHumansLipid MetabolismMicroscopy, FluorescenceMycobacterium tuberculosisSpectrum Analysis, RamanTuberculosisTuberculosis, PulmonaryBiomarkers

Identifiers

PMID28852109
PMCPMC5575044

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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.