Evidence map›Paper›PMID 32016399›Full record

ArticleGigaScience2020

Evaluating the genome and resistome of extensively drug-resistant Klebsiella pneumoniae using native DNA and RNA Nanopore sequencing.

Miranda E Pitt, Son H Nguyen, Tânia P S Duarte, Haotian Teng, Mark A T Blaskovich, Matthew A Cooper, Lachlan J M Coin

Abstract read
In one paragraph

Article in GigaScience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Review
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  11. Review
  12. Detection of Streptococcus pyogenes M1Nature communications · 2023
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Rapid Identification of Drug-Resistant Tuberculosis Genes Using Direct PCR Amplification and Oxford Nanopore Technology Sequencing.The Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale · 2022
    Article
  18. Development of ONT-cappable-seq to unravel the transcriptional landscape ofComputational and structural biotechnology journal · 2022
    Article
  19. Review
  20. 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

7 authors.

Miranda E PittInstitute for Molecular Bioscience, The University of Queensland, 306 Carmody Road, Brisbane, Queensland, 4072, Australia.
Son H NguyenInstitute for Molecular Bioscience, The University of Queensland, 306 Carmody Road, Brisbane, Queensland, 4072, Australia.
Tânia P S DuarteInstitute for Molecular Bioscience, The University of Queensland, 306 Carmody Road, Brisbane, Queensland, 4072, Australia.
Haotian TengInstitute for Molecular Bioscience, The University of Queensland, 306 Carmody Road, Brisbane, Queensland, 4072, Australia.
Mark A T BlaskovichInstitute for Molecular Bioscience, The University of Queensland, 306 Carmody Road, Brisbane, Queensland, 4072, Australia.
Matthew A CooperInstitute for Molecular Bioscience, The University of Queensland, 306 Carmody Road, Brisbane, Queensland, 4072, Australia.
Lachlan J M CoinInstitute for Molecular Bioscience, The University of Queensland, 306 Carmody Road, Brisbane, Queensland, 4072, Australia.

Funding

Wellcome TrustWellcome Trust 104797/Z/14/Z
6 · The paper itself

Abstract

backgroundKlebsiella pneumoniae frequently harbours multidrug resistance, and current diagnostics struggle to rapidly identify appropriate antibiotics to treat these bacterial infections. The MinION device can sequence native DNA and RNA in real time, providing an opportunity to compare the utility of DNA and RNA for prediction of antibiotic susceptibility. However, the effectiveness of bacterial direct RNA sequencing and base-calling has not previously been investigated. This study interrogated the genome and transcriptome of 4 extensively drug-resistant (XDR) K. pneumoniae clinical isolates; however, further antimicrobial susceptibility testing identified 3 isolates as pandrug-resistant (PDR).

resultsThe majority of acquired resistance (≥75%) resided on plasmids including several megaplasmids (≥100 kb). DNA sequencing detected most resistance genes (≥70%) within 2 hours of sequencing. Neural network-based base-calling of direct RNA achieved up to 86% identity rate, although ≤23% of reads could be aligned. Direct RNA sequencing (with ∼6 times slower pore translocation) was able to identify (within 10 hours) ≥35% of resistance genes, including those associated with resistance to aminoglycosides, β-lactams, trimethoprim, and sulphonamide and also quinolones, rifampicin, fosfomycin, and phenicol in some isolates. Direct RNA sequencing also identified the presence of operons containing up to 3 resistance genes. Polymyxin-resistant isolates showed a heightened transcription of phoPQ (≥2-fold) and the pmrHFIJKLM operon (≥8-fold). Expression levels estimated from direct RNA sequencing displayed strong correlation (Pearson: 0.86) compared to quantitative real-time PCR across 11 resistance genes.

conclusionOverall, MinION sequencing rapidly detected the XDR/PDR K. pneumoniae resistome, and direct RNA sequencing provided accurate estimation of expression levels of these genes.

Indexed as

Drug Resistance, Multiple, BacterialGenome, BacterialKlebsiella pneumoniaeNanopore SequencingRNA-SeqTranscriptome

Identifiers

PMID32016399
PMCPMC6998412

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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.