Evidence map›Paper›PMID 41540427›Full record

ArticleBMC medical genomics2026

Benchmarking Illumina and Oxford Nanopore Technologies (ONT) sequencing platforms for whole genome sequencing of bacterial genomes and use in clinical microbiology.

Srinithi Purushothaman, Tim Roloff, Adrian Egli, Helena Mb Seth-Smith

Abstract read
In one paragraph

Article in BMC medical genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Draft genome ofMicrobiology resource announcements · 2026
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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

4 authors.

Srinithi PurushothamanInstitute of Medical Microbiology, University of Zurich, Gloriastrasse 28, Zurich, 8006, Switzerland.
Tim RoloffInstitute of Medical Microbiology, University of Zurich, Gloriastrasse 28, Zurich, 8006, Switzerland.
Adrian Egli *Institute of Medical Microbiology, University of Zurich, Gloriastrasse 28, Zurich, 8006, Switzerland.
Helena Mb Seth-Smith *Institute of Medical Microbiology, University of Zurich, Gloriastrasse 28, Zurich, 8006, Switzerland. hsethsmith@imm.uzh.ch.

Funding

Swiss National Science Foundation 310030_192515
6 · The paper itself

Abstract

backgroundIn microbial diagnostics, whole-genome sequencing (WGS) is used to address key questions such as species identification, presence of antimicrobial resistance genes (ARGs), virulence genes, and outbreak detection. The choice of sequencing technology is crucial to ensure high-quality data, cost-effectiveness, and efficient reporting times. We aimed to compare Illumina (short-read) and ONT (long-read) sequencing methods for WGS on different bacterial species for base accuracy and reliable taxonomic and ARG identification. MATERIALS AND

methodsWe used clinical isolates of ESKAPE pathogens (n = 12) and ATCC strains (n = 8) of varying %G + C. Illumina sequencing was performed on MiSeq (PE150) and ONT sequencing using GridION with R9.4.1 and R10.4.1 flowcells. Base-calling was performed using Guppy, Dorado, and Rerio software. We performed de novo assembly with Unicycler for Illumina and Flye for ONT, and two types of hybrid assemblies, Unicycler and Polypolish. We annotated genomes with Bakta and assessed the quality (QUAST, GTDB-Tk). We identified ARGs (AMRFinderPlus) and plasmids (MOB-suite). We mapped reads and called SNPs using Minimap2, Pilon, vcftools, and Snippy (Illumina). Core genome MLST analysis was conducted with Ridom Seqsphere+.

resultsWe observed that Illumina sequencing provided consistently high-quality reads (median Q-score 35), whereas for ONT R10.4.1, SUP model showed higher median quality (median Q-score 15.3) compared to R9.4.1 (median Q-score 13.9, SUP model). We observed that Illumina-based assemblies generated fewer genes annotated as disrupted; for ONT assemblies, the base-caller affects assembly annotation accuracy, with High accuracy (HAC) and Super accuracy (SUP) base-calling models perform better than FAST model. ONT assemblies resolved rRNA operons better than Illumina assemblies. Sequencing errors were determined by SNP calling, and varied widely by species, with ONT often generating more sequencing errors compared to Illumina. Hybrid assemblies combine accuracy and completeness effectively. Taxonomic identification and ARG detection were reliable across all methods.

conclusionCombining Illumina and ONT technologies yielded optimal bacterial genome sequencing results, leveraging the high accuracy of short reads and improved contiguity of ONT long reads. The HAC and SUP ONT models with Dorado notably enhance genome assembly annotation and resolution of complex regions, although species-specific issues, likely due to repeat regions and base modifications, remain challenging even in SUP model with Dorado. Hybrid approaches currently offer the most comprehensive and accurate genome assemblies for clinical microbiology. For reliable cgMLST even using the most recent ONT methods, resolution must be assessed on a species-by-species basis.

Indexed as

BacteriaGenome, BacterialHigh-Throughput Nucleotide SequencingNanopore SequencingWhole Genome SequencingBenchmarkingHumansIlluminaOxford Nanopore TechnologiesWhole genome sequencing

Identifiers

PMID41540427
PMCPMC12903679

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LicenceCC BY-NC-ND
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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.