Evidence map›Paper›PMID 29549470›Full record

ArticleEuropean journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology2018

Development and evaluation of a culture-free microbiota profiling platform (MYcrobiota) for clinical diagnostics.

Stefan A Boers, Saskia D Hiltemann, Andrew P Stubbs, Ruud Jansen, John P Hays

Abstract readEvaluation Study
In one paragraph

Article in European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Trial
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  11. Understanding and overcoming the pitfalls and biases of next-generation sequencing (NGS) methods for use in the routine clinical microbiological diagnostic laboratory.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2019
    Review
  12. Article
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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

5 authors.

Stefan A BoersDepartment of Medical Microbiology and Infectious Diseases, Erasmus University Medical Centre Rotterdam (Erasmus MC), Wytemaweg 80, 3015 CN, Rotterdam, the Netherlands.
Saskia D HiltemannDepartment of Bioinformatics, Erasmus University Medical Centre Rotterdam (Erasmus MC), Rotterdam, the Netherlands.
Andrew P StubbsDepartment of Bioinformatics, Erasmus University Medical Centre Rotterdam (Erasmus MC), Rotterdam, the Netherlands.
Ruud JansenDepartment of Molecular Biology, Regional Laboratory of Public Health Kennemerland, Haarlem, the Netherlands.
John P HaysDepartment of Medical Microbiology and Infectious Diseases, Erasmus University Medical Centre Rotterdam (Erasmus MC), Wytemaweg 80, 3015 CN, Rotterdam, the Netherlands. j.hays@erasmusmc.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbiota profiling has the potential to greatly impact on routine clinical diagnostics by detecting DNA derived from live, fastidious, and dead bacterial cells present within clinical samples. Such results could potentially be used to benefit patients by influencing antibiotic prescribing practices or to generate new classical-based diagnostic methods, e.g., culture or PCR. However, technical flaws in 16S rRNA gene next-generation sequencing (NGS) protocols, together with the requirement for access to bioinformatics, currently hinder the introduction of microbiota analysis into clinical diagnostics. Here, we report on the development and evaluation of an "end-to-end" microbiota profiling platform (MYcrobiota), which combines our previously validated micelle PCR/NGS (micPCR/NGS) methodology with an easy-to-use, dedicated bioinformatics pipeline. The newly designed bioinformatics pipeline processes micPCR/NGS data automatically and summarizes the results in interactive, but simple web reports. In order to explore the utility of MYcrobiota in clinical diagnostics, 47 clinical samples (40 "damaged skin" samples and 7 synovial fluids) were investigated using routine bacterial culture as comparator. MYcrobiota confirmed the presence of bacterial DNA in 37/37 culture-positive samples and detected bacterial taxa in 2/10 culture-negative samples. Moreover, 36/38 potentially relevant aerobic bacterial taxa and 3/3 mixtures of anaerobic bacteria were identified using culture and MYcrobiota, with the sensitivity and specificity being 95%. Interestingly, the majority of the 448 bacterial taxa identified using MYcrobiota were not identified using culture, which could potentially have an impact on clinical decision-making. Taken together, the development of MYcrobiota is a promising step towards the introduction of microbiota analysis into clinical diagnostic laboratories.

Indexed as

BacteriaClinical Laboratory TechniquesComputational BiologyDNA, BacterialHigh-Throughput Nucleotide SequencingHumansMicrobiotaMolecular Diagnostic TechniquesPhylogenyPolymerase Chain ReactionRetrospective StudiesRNA, Ribosomal, 16SSequence Analysis, DNAUlcerWounds and InjuriesDNA, BacterialRNA, Ribosomal, 16S16S rRNA gene sequencingBioinformatics pipelineClinical diagnosticsMicelle PCRMicrobiotaMYcrobiota

Identifiers

PMID29549470
PMCPMC5948305

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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.