Evidence map›Paper›PMID 39331342›Full record

ArticleVeterinary research communications2024

Rapid detection of causative bacteria including multiple infections of bovine respiratory disease using 16S rRNA amplicon-based nanopore sequencing.

Shingo Okamura, Akira Fukuda, Masaru Usui

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Article in Veterinary research communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 citing papers in PubMed.

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4 · The record

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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

3 authors.

Shingo OkamuraLaboratory of Food Microbiology and Food Safety, School of Veterinary Medicine, Rakuno Gakuen University, 582 Midorimachi, Bunkyodai, Ebetsu, 069- 8501, Hokkaido, Japan.
Akira FukudaLaboratory of Food Microbiology and Food Safety, School of Veterinary Medicine, Rakuno Gakuen University, 582 Midorimachi, Bunkyodai, Ebetsu, 069- 8501, Hokkaido, Japan.
Masaru UsuiLaboratory of Food Microbiology and Food Safety, School of Veterinary Medicine, Rakuno Gakuen University, 582 Midorimachi, Bunkyodai, Ebetsu, 069- 8501, Hokkaido, Japan. usuima@rakuno.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bovine respiratory disease (BRD) is a multifaceted condition that poses a primary challenge in calf rearing. Viruses and bacteria are etiological agents of BRD. Viral BRD is typically managed symptomatically, whereas bacterial BRD is predominantly managed through the empirical administration of antimicrobials. However, this empirical administration has raised concerns regarding the emergence of antimicrobial-resistant bacteria. Thus, rapid identification of pathogenic bacteria and judicious selection of antimicrobials are required. This study evaluated the usefulness of 16S rRNA analysis through nanopore sequencing for the rapid identification of BRD-causing bacteria. A comparative evaluation of nanopore sequencing and traditional culture method was performed on 100 calf samples detected with BRD. Nanopore sequencing facilitated the identification of bacteria at the species level in bovine nasal swabs, ear swabs, and lung tissue samples within approximately 6 h. Of the 92 samples in which BRD-causing bacteria were identified via nanopore sequencing, 82 (89%) were concordant with the results of culture isolation. In addition, the occurrence of multiple infections exceeded that of singular infections. These results suggest that 16S rRNA sequencing via nanopore technology is effective in reducing analysis time and accurately identifying BRD-causing bacteria. This method is particularly advantageous for the initial detectable screening of BRD.

Indexed as

Nanopore SequencingRNA, Ribosomal, 16SAnimalsBacteriaBovine Respiratory Disease ComplexCattleCattle DiseasesCoinfectionRNA, BacterialRNA, BacterialRNA, Ribosomal, 16S16S rRNA sequencingBovine respiratory diseaseBRD-causing bacteriaNanopore sequence

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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.