Evidence map›Paper›PMID 28284077›Full record

ArticleBiosensors & bioelectronics2017

Multiplex detection of extensively drug resistant tuberculosis using binary deoxyribozyme sensors.

Hillary N Bengtson, Susanne Homolka, Stefan Niemann, Ana Júlia Reis, Pedro Eduardo da Silva, Yulia V Gerasimova, Dmitry M Kolpashchikov, Kyle H Rohde

Abstract read
In one paragraph

Article in Biosensors & bioelectronics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Review
  6. Article
  7. Revisiting the methods for detectingAccess microbiology · 2021
    Review
  8. Article
  9. Article
  10. Article
  11. 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

8 authors.

Hillary N BengtsonDivision of Immunity and Pathogenesis, Burnett School of Biomedical Sciences, College of Medicine, University of Central Florida, Orlando, FL, USA.
Susanne HomolkaMolecular and Experimental Mycobacteriology, Research Center Borstel, Borstel, Germany.
Stefan NiemannMolecular and Experimental Mycobacteriology, Research Center Borstel, Borstel, Germany; German Center for Infection Research, Borstel, Germany.
Ana Júlia ReisUniversidade Federal do Rio Grande, Rio Grande, RS, Brazil.
Pedro Eduardo da SilvaUniversidade Federal do Rio Grande, Rio Grande, RS, Brazil.
Yulia V GerasimovaDepartment of Chemistry, College of Sciences, University of Central Florida, Orlando, FL, USA.
Dmitry M KolpashchikovDivision of Immunity and Pathogenesis, Burnett School of Biomedical Sciences, College of Medicine, University of Central Florida, Orlando, FL, USA; Department of Chemistry, College of Sciences, University of Central Florida, Orlando, FL, USA.
Kyle H RohdeDivision of Immunity and Pathogenesis, Burnett School of Biomedical Sciences, College of Medicine, University of Central Florida, Orlando, FL, USA. Electronic address: kyle.rohde@ucf.edu.

Funding

Deoxyribozyme sensor-based diagnostics for Mycobacterium tuberculosisR15AI103880 · NIAID · UNIVERSITY OF CENTRAL FLORIDA · PI KOLPASHCHIKOV, DMITRY MIKHAYLOVICH · 2013 to 2013
$430k
NIAID NIH HHS R15 AI103880
6 · The paper itself

Abstract

Current diagnostic tools for Mycobacterium tuberculosis (Mtb) have many disadvantages including low sensitivity, slow turnaround times, or high cost. Accurate, easy to use, and inexpensive point of care molecular diagnostic tests are urgently needed for the analysis of multidrug resistant (MDR) and extensively drug resistant (XDR) Mtb strains that emerge globally as a public health threat. In this study, we established proof-of-concept for a novel diagnostic platform (TB-DzT) for Mtb detection and the identification of drug resistant mutants using binary deoxyribozyme sensors (BiDz). TB-DzT combines a multiplex PCR with single nucleotide polymorphism (SNP) detection using highly selective BiDz sensors targeting loci associated with species typing and resistance to rifampin, isoniazid and fluoroquinolone antibiotics. Using the TB-DzT assay, we demonstrated accurate detection of Mtb and 5 mutations associated with resistance to three anti-TB drugs in clinical isolates. The assay also enables detection of a minority population of drug resistant Mtb, a clinically relevant scenario referred to as heteroresistance. Additionally, we show that TB-DzT can detect the presence of unknown mutations at target loci using combinatorial BiDz sensors. This diagnostic platform provides the foundation for the development of cost-effective, accurate and sensitive alternatives for molecular diagnostics of MDR- and XDR-TB.

Indexed as

Biosensing TechniquesDNA, CatalyticExtensively Drug-Resistant TuberculosisHumansIsoniazidMicrobial Sensitivity TestsMultiplex Polymerase Chain ReactionMutationMycobacterium tuberculosisPolymorphism, Single NucleotideRifampinTuberculosis, Multidrug-ResistantDNA, CatalyticIsoniazidRifampinBinary deoxyribozymeDiagnosticsDrug resistanceMultiplex PCRNucleic acid sensorsTuberculosis

Identifiers

PMID28284077
PMCPMC5407088

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

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.