Evidence map›Paper›PMID 36759384›Full record

ArticleCurrent microbiology2023

Fast Identification Method for Screening Bacteria from Faecal Samples Using Oxford Nanopore Technologies MinION Sequencing.

Ana Sofia G Borges, Meghna Basu, Erik Brinks, Corinna Bang, Gyu-Sung Cho, John F Baines, Andre Franke, Charles M A P Franz

Open access · hybridAbstract read
In one paragraph

Article in Current microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.2field-weighted citation impact, top 21% of its field
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

4 citing papers in PubMed, 8 citations in OpenAlex.

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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

8 authors at 3 institutions in 1 country.

Ana Sofia G BorgesDepartment of Microbiology and Biotechnology, Max Rubner-Institut, Federal Research Institute for Nutrition and Food, Hermann-Weigmann-Straße 1, 24103, Kiel, Germany.
Meghna BasuSection of Evolutionary Medicine, Institute for Experimental Medicine, Christian-Albrechts-University Kiel, UKSH, Campus Kiel, Michaelisstraße 5, 24105, Kiel, Germany.
Erik BrinksDepartment of Microbiology and Biotechnology, Max Rubner-Institut, Federal Research Institute for Nutrition and Food, Hermann-Weigmann-Straße 1, 24103, Kiel, Germany.
Corinna BangInstitute of Clinical Molecular Biology, Christian Albrechts University of Kiel, Rosalind-Franklin-Straße 12, 24105, Kiel, Germany.
Gyu-Sung ChoDepartment of Microbiology and Biotechnology, Max Rubner-Institut, Federal Research Institute for Nutrition and Food, Hermann-Weigmann-Straße 1, 24103, Kiel, Germany. Gyusung.Cho@mri.bund.de.
John F BainesSection of Evolutionary Medicine, Institute for Experimental Medicine, Christian-Albrechts-University Kiel, UKSH, Campus Kiel, Michaelisstraße 5, 24105, Kiel, Germany.
Andre FrankeInstitute of Clinical Molecular Biology, Christian Albrechts University of Kiel, Rosalind-Franklin-Straße 12, 24105, Kiel, Germany.
Charles M A P FranzDepartment of Microbiology and Biotechnology, Max Rubner-Institut, Federal Research Institute for Nutrition and Food, Hermann-Weigmann-Straße 1, 24103, Kiel, Germany.
Max Rubner Institut · DEKiel University · DEMax Planck Institute for Evolutionary Biology · DE

Funding

Deutsche Forschungsgemeinschaft Cluster of Excellence 2167Deutsche Forschungsgemeinschaft CRC 1182Deutsche Forschungsgemeinschaft Research Unit 5042 "miTarget"Deutsche Forschungsgemeinschaft RTG 2501 TransEvo
6 · The paper itself

Abstract

Most bacterial identification methods require extensive culturing, strain purification and DNA extraction protocols. This leads to additional expenses and time lags when isolating specific bacteria from complex microbiological ecosystems. This study aimed to develop a fast and robust method for identification of lactobacilli, bifidobacteria and Bacteroides in human faecal samples. Bacteria from faecal samples were cultured anaerobically on selective media. Sonication-based DNA extraction was performed, followed by almost complete 16S rRNA gene polymerase chain reaction amplification and MinION sequencing with the Flongle adapter. Sequence analysis was performed using NanoCLUST, while RStudio was used for graphics. For 110 of the 125 colonies investigated, 100% of reads were attributed to a single species, while the remaining 15 colonies consisted of mixtures of up to three different species. The proposed bacterial identification method is advantageous for isolating particular bacteria for which there are no exclusively selective media, as it avoids lengthy colony purification and DNA purification methods, and yields a quick colony identification with high accuracy. Therefore, this method can be used for directly screening for pure cultures of target microorganisms and is suitable for the identification of bacteria in culturomics studies.

Indexed as

NanoporesBacteriaDNA, BacterialEcosystemHigh-Throughput Nucleotide SequencingHumansRNA, Ribosomal, 16SSequence Analysis, DNADNA, BacterialRNA, Ribosomal, 16S

Identifiers

PMID36759384
PMCPMC9911510
OpenAlexW4319812719

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.