Biology subjects

Dabernig-Heinz, J.

Publications and source records attributed to Dabernig-Heinz, J..

3 recordsLinked to original sources

bioRxiv2025

Accurate and Reproducible Whole-Genome Genotyping for Bacterial Genomic Surveillance with Nanopore Sequencing Data

Despite recent advances in error rate reduction, until recently Oxford Nanopore Technology (ONT) sequences lacked the accuracy required for fine scale bacterial genomic analysis. Here, recent software improvements of ONT and the ONT-cgMLST-Polisher within the SeqSphere+ software were evaluated. We used short-(Illumina) and long-read ONT sequences of 80 multidrug-resistant bacteria (MDROs) for benchmarking. Illumina reads were de-novo-assembled using SKESA. For ONT, Dorado super accurate (SUP) model 4.3 or 5.0 basecalled reads were assembled with Flye and then polished with Medaka v1.12 m4.3 or Medaka v2.0 bacterial methylation model. In addition, the ONT-cgMLST-Polisher was run over all assemblies. The ground truth (GT) hybrid assemblies were created using Hybracter v0.10.0. Sixteen isolates from four species out of the original 80 isolates were sent to six laboratories for a ring trial. The 80 MDROs basecalled with SUP m4.3 had an average cgMLST allele distance (AD) to the GT of 4.94 with Medaka v1.12 and 1.78 with Medaka v2.0, respectively. After further polishing the Medaka v2.0 data with the ONT-cgMLST-Polisher, the AD dropped to 0.09. Using data basecalled with SUP m5.0 with Medaka v2.0 further reduced the AD significantly to 0.04. While the ring trial data basecalled with Dorado SUP m4.3 showed more variability and insufficient results for some samples, model 5.0 data resulted in average ADs of 0.36 and 0.17 without and with the ONT-cgMLST-Polisher, respectively. In conclusion, recent ONT Dorado and Medaka models combined with the ONT-cgMLST-Polisher improved ONT sequencing accuracy and made it sufficiently reproducible for genomic surveillance of bacteria. Importance Oxford Nanopore Technologies (ONT) sequencing methodology is especially attractive for small and medium-sized laboratories due to its relatively low capital investment and price per sample consumable costs. However, until recently it lacked accuracy and reproducibility for bacterial genomic genotyping. Here, we present an evaluation of the most recent ONT bioinformatic (basecalling and polishing of consensus) improvements and a new ONT-cgMLST-Polisher tool. We demonstrate that by applying those procedures ONT whole-genome genotyping-based surveillance of bacteria is finally accurate and reproducible enough for routine application even in small laboratories

bioinformatics↗

bioRxiv2025

Decoding bacterial methylomes in four public health-relevant microbial species: Nanopore sequencing enables reproducible analysis of DNA modifications

Investigating bacterial methylation profiles provides essential complementary information to the native DNA sequence, significantly extending our understanding of how DNA modifications influence virulence, antibiotic resistance, and the ability of bacteria to evade the immune system. Recent advancements in real-time Nanopore sequencing and basecalling algorithms have enabled the direct detection of modified bases from raw signal data, eliminating the need for bisulfite treatment of DNA. However, decoding methylation signals remains challenging due to rapid technological and methodological progress. In this study, we focus on public health-relevant bacterial strains to analyze their methylation profiles and identify methylation motifs. Our dataset includes samples from Staphylococcus aureus, Listeria monocytogenes, Enterococcus faecium, and Klebsiella pneumoniae, sequenced on the Nanopore GridION platform using the latest flow cell chemistry (R10.4.1) and modification basecalling models (Dorado basecalling SUP model v5). We investigated distinct methylation patterns within and between species, focusing on heavily modified genes or genomic regions. Our results reveal distinct species-specific methylation profiles, with each strain exhibiting unique modification patterns. We developed a modular pipeline using Nextflow and the Nanopore Modkit tool to streamline the detection of methylated motifs. We compared the results with outputs from MicrobeMod, a recent toolkit for exploring prokaryotic methylation and base modifications in nanopore sequencing. Our pipeline is publicly available for further use (github.com/rki-mf1/ont-methylation). We identified known methylation motifs already described in the literature and novel de novo motifs, providing deeper insights into the diversity of bacterial DNA modifications. Furthermore, we identified genomic regions that are extensively methylated, which could have implications for bacterial behavior and pathogenicity. We also assess improvements in basecalling accuracy, specifically how methylated bases can influence neighboring basecalls. Recent advances in basecalling models, particularly v5 models as part of Dorado, have reduced these issues, improving the reliability of methylation detection in bacterial genomes. In conclusion, our study highlights the potential of current nanopore sequencing tools for detecting DNA modifications in prokaryotes. By making our pipeline and results publicly available, we facilitate further research into bacterial DNA modifications and their role in microbial pathogenesis.

bioinformatics↗

bioRxiv2023

Nanopore sequencing for accurate bacterial outbreak tracing

Our study investigated the effectiveness of Oxford Nanopore Technologies for accurate outbreak tracing by resequencing 33 isolates of a three-year-long Klebsiella pneumoniae outbreak with Illumina short read sequencing data as the point of reference. We detected considerable base errors through cgMLST and phylogenetic analysis of genomes sequenced with Oxford Nanopore Technologies, leading to the false exclusion of some outbreak-related strains from the outbreak cluster. Nearby methylation sites cause these errors and can also be found in other species besides K. pneumoniae. Based on this data, we explored PCR-based sequencing and a masking strategy, which both successfully addressed these inaccuracies and ensured accurate outbreak tracing. We offer our masking strategy as a bioinformatic workflow (MPOA is freely available on GitHub under the GNUv3 license: github.com/replikation/MPOA) to identify and mask problematic genome positions in a reference-free manner. Our research highlights limitations in using Oxford Nanopore Technologies for sequencing prokaryotic organisms, especially for investing outbreaks. For time-critical projects that cannot wait for further technological developments by Oxford Nanopore Technologies, our study recommends either PCR-based sequencing or using our provided bioinformatic workflow. We would advise that read mapping-based quality control of genomes should be provided when publishing results.

molecular biology↗