Evidence map›Paper›PMID 33580146›Full record

ArticleScientific reports2021

Critical evaluation of short, long, and hybrid assembly for contextual analysis of antibiotic resistance genes in complex environmental metagenomes.

Connor L Brown, Ishi M Keenum, Dongjuan Dai, Liqing Zhang, Peter J Vikesland, Amy Pruden

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing 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

46 citing papers in PubMed.

  1. Review
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  9. Review
  10. Analysis of metagenomic data.Nature reviews. Methods primers · 2025
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  18. Capturing clinically relevantMicrobial genomics · 2024
    Article
  19. 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

6 authors.

Connor L Brown *Genetics, Bioinformatics, and Computational Biology, Virginia Tech, Blacksburg, VA, 24060, USA.
Ishi M Keenum *Department of Civil & Environmental Engineering, Virginia Tech, Blacksburg, VA, 24060, USA.
Dongjuan DaiDepartment of Civil & Environmental Engineering, Virginia Tech, Blacksburg, VA, 24060, USA.
Liqing ZhangGenetics, Bioinformatics, and Computational Biology, Virginia Tech, Blacksburg, VA, 24060, USA. lqzhang@vt.edu.
Peter J VikeslandDepartment of Civil & Environmental Engineering, Virginia Tech, Blacksburg, VA, 24060, USA.
Amy PrudenDepartment of Civil & Environmental Engineering, Virginia Tech, Blacksburg, VA, 24060, USA. apruden@vt.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the fight to limit the global spread of antibiotic resistance, the assembly of environmental metagenomes has the potential to provide rich contextual information (e.g., taxonomic hosts, carriage on mobile genetic elements) about antibiotic resistance genes (ARG) in the environment. However, computational challenges associated with assembly can impact the accuracy of downstream analyses. This work critically evaluates the impact of assembly leveraging short reads, nanopore MinION long-reads, and a combination of the two (hybrid) on ARG contextualization for ten environmental metagenomes using seven prominent assemblers (IDBA-UD, MEGAHIT, Canu, Flye, Opera-MS, metaSpades and HybridSpades). While short-read and hybrid assemblies produced similar patterns of ARG contextualization, raw or assembled long nanopore reads produced distinct patterns. Based on an in-silico spike-in experiment using real and simulated reads, we show that low to intermediate coverage species are more likely to be incorporated into chimeric contigs across all assemblers and sequencing technologies, while more abundant species produce assemblies with a greater frequency of inversions and insertion/deletions (indels). In sum, our analyses support hybrid assembly as a valuable technique for boosting the reliability and accuracy of assembly-based analyses of ARGs and neighboring genes at environmentally-relevant coverages, provided that sufficient short-read sequencing depth is achieved.

Indexed as

Anti-Bacterial AgentsComputational BiologyDrug Resistance, MicrobialEnvironmental MicrobiologyEnvironmental MonitoringGenome, BacterialHigh-Throughput Nucleotide SequencingMetagenomeMetagenomicsReproducibility of ResultsSequence Analysis, DNAWastewaterAnti-Bacterial AgentsWastewater

Identifiers

PMID33580146
PMCPMC7881036

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LicenceCC BY
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Registered trials

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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.