Biology subjects

Stephan, R.

Publications and source records attributed to Stephan, R..

10 recordsLinked to original sources

bioRxiv2026

Continued genomic surveillance of Vibrio cholerae O1 isolates from cholera cases in Europe, 2023-2024

Background: Following the global resurgence of cholera in 2022, 51 cholera cases were reported by European countries. We previously characterised 49 Vibrio cholerae O1 isolates from these cases using whole genome sequencing. In 2023 and 2024, 59 additional cholera cases were reported by 11 European countries. Aim: We aimed to confirm that V. cholerae O1 isolates associated with cholera cases reported in Europe in 2023-2024 belonged to the epidemic seventh pandemic El Tor (7PET) lineage rather than to non-epidemic V. cholerae O1 lineages, and to characterise their virulence, antimicrobial resistance (AMR) determinants and phylogenetic relationships. Methods: Fifty V. cholerae O1 isolates were available for whole genome sequencing, of which 49 yielded genomes of sufficient quality for analysis. Genomes were analysed together with more than 1,500 publicly available 7PET genomes to place the European isolates into a global phylogenetic context. Results: All 49 genomes belonged to the 7PET lineage and Wave 3. Four sub-lineages were identified: BD1.2 (2/49), AFR12 (6/49), AFR13 (8/49) and Pre-AFR15 (33/49). The predominance of Pre-AFR15 confirms its continued contribution to the ongoing global cholera resurgence. In contrast to our 2022 survey, eight highly drug-resistant AFR13 isolates were detected, documenting the international spread of this highly drug-resistant clone resistant to multiple first-line antimicrobial agents. Conclusion: Whole genome sequencing should be routinely used by reference laboratories to distinguish epidemic 7PET from non-epidemic V. cholerae O1 lineages and to monitor the emergence and international spread of AMR clones. Continued collaborative genomic surveillance of travel-associated cholera cases can provide early insights into the emergence, international spread and antimicrobial resistance of 7PET sub-lineages.

genomics↗

bioRxiv2026

Loss of NudE-mediated dynein activation at synaptic terminals causes progressive axon length-dependent neurodegeneration

Progressive, axon length-dependent degeneration of nerve terminals is a defining feature of dying-back neuropathies; yet, whether defects in axonal transport initiate or are a consequence of this process remains unresolved. Here, we show that NudE, a scaffold for dynein motor activation, is required for the initiation of retrograde axonal transport at Drosophila motoneuron synapses in vivo. Loss of NudE impairs dynein activation at the synaptic terminal, severely reducing the proportion of cargo entering retrograde transport and decreasing retrograde motor velocity. Live imaging and temporal analysis establish that this transport initiation defect is the earliest event in a degenerative cascade, followed by progressive microtubule destabilization, impaired synaptic transmission, and structural degeneration in a distal-to-proximal gradient that recapitulates dying-back neuropathies. Structure-function analysis validates the biochemically defined NudE-dynein binding domains in vivo, with graded disruption producing correspondingly graded phenotypes. Genetic two-hit experiments uncover a reciprocal dependence between transport initiation and microtubule maintenance: perturbations in either process that are individually tolerated synergistically trigger degeneration when combined, while increasing microtubule levels alone cannot compensate for failed dynein activation. These findings reveal retrograde transport initiation as a critical vulnerability point in motoneurons and provide a mechanistic basis for how defects in dynein activation produce progressive neurodegeneration.

neuroscience↗

bioRxiv2026

Standalone nanopore sequencing for foodborne pathogen surveillance: a large-scale evaluation and quality control framework

Whole-genome sequencing (WGS) is central to foodborne pathogen surveillance and cross-border outbreak detection. Long-read sequencing using Oxford Nanopore Technologies (ONT) promises rapid, complete, and cost-effective genome assemblies in a single workflow. However, the adoption of standalone ONT sequencing of native DNA has been slowed by concerns that DNA modifications can compromise per-base sequencing accuracy and downstream genotyping. In this study, we evaluated ONT-only sequencing performance across 294 genetically diverse isolates representing ten major foodborne pathogens. Using the SUP@v5.2 basecalling model at 50x coverage, 97.3% (286/294) of the ONT assemblies produced identical or near-identical cgMLST profiles ([≤]3 allelic differences) as Illumina-polished hybrid assemblies. Elevated error rates were observed in four Salmonella enterica serovar Kentucky and four Listeria monocytogenes isolates and were associated with the presence of specific DNA phosphorothioation or methylation systems. Re-basecalling the same dataset with the newly released HAC@v6.0 model revealed a different error profile: although 93.5% (275/294) of assemblies remained highly accurate, all 13 isolates carrying dnd (DNA phosphorothioation) or dpd (7-deazaguanine modification) systems, including isolates of S. enterica, Cronobacter sakazakii, and Vibrio parahaemolyticus, exhibited high error rates, suggesting that such atypical modifications were not adequately represented in the models training dataset. To enable rapid identification of unreliable assemblies, we developed alpaqa, a lightweight computational tool that detects systematic nanopore assembly errors without requiring supplemental short-read data or reference genomes. By identifying affected assemblies, alpaqa provides a quality safeguard for ONT-only workflows. Masking low-quality bases in assemblies flagged by alpaqa improved cgMLST accuracy, although this reduced the number of callable loci and therefore genotyping resolution. Our findings demonstrate that standalone ONT sequencing of native DNA is sufficiently accurate for routine foodborne pathogen surveillance when combined with appropriate quality control, supporting its use in harmonised genomic surveillance frameworks. Data summaryAll sequencing data generated in this study have been submitted to the NCBI Sequence Read Archive. Accession numbers for Illumina and ONT (SUP@v5.2) reads are listed in Supplementary Table S1. Raw pod5 files from error-prone isolates have been deposited in SquiDBase (SQB000021). Alpaqa is available at github.com/MBiggel/alpaqa/. An automated ONT assembly and quality control pipeline integrating alpaqa is available at github.com/MBiggel/boap/. Impact statementThis study demonstrates that standalone Oxford Nanopore sequencing of native DNA can achieve highly accurate genotyping for routine foodborne pathogen surveillance across diverse species. We show that the remaining inaccuracies are linked to specific DNA modification systems, including phosphorothioation and 7-deazaguanine modifications, which are identified here as previously unrecognised sources of systematic sequencing errors. To address this limitation, we introduce alpaqa, a reference-free method for detecting such error-prone assemblies, providing a practical quality-control framework for ONT-only workflows. Together, these results support the reliable use of nanopore sequencing in routine genomic surveillance.

genomics↗

bioRxiv2025

Application of Large Language Models for Annotating Genes into Reactome Pathways

Reactome is the most comprehensive, open source, open access biological pathway knowledgebase, widely used in the research community. To ensure the highest quality of its content, human pathway data in Reactome is manually curated. However, manual curation is labor-intensive, time-consuming, and increasingly difficult to keep up with the ever-growing biomedical literature. Large language model (LLM)-driven artificial intelligence (AI) technologies are transforming many fields, including bioinformatics resource development. Applying LLM/AI technologies in Reactome may offer a powerful way to scale curation and consolidate pathway-related data into a single resource. This manuscript describes the first stage of our attempt to adopt LLM/AI technologies for Reactome manual curation. We developed an LLM workflow that can assist curators in adding new genes to existing pathways and refining the functional annotations of existing ones. The workflow predicts pathways in which genes are likely to function, identifies PubMed-indexed literature that may support these predictions, generates text summaries describing potential molecular mechanisms, and extracts functional relationships among biological entities from full-text PDF papers. To validate the workflow output, we used a computational approach based on semantic similarity between LLM workflow-generated summaries and Reactome manual annotations. The results show significant enrichment of high-similarity matches. Manual evaluation of 19 genes indicated that more than half of the outputs are useful for supporting curation. Based on these results, we developed an enhanced workflow that incorporates protein-protein interaction data, facilitating Reactomes reaction-based annotation. In summary, our initial adoption of LLM/AI technologies produced encouraging results and provides a practical framework for integrating AI-assisted methods into Reactomes curation pipeline. The strategies described here may be broadly applicable to community knowledgebases in general.

bioinformatics↗

bioRxiv2024

Oxford Nanopore's 2024 sequencing technology for Listeria monocytogenes outbreak detection and source attribution: progress and clone-specific challenges

Whole genome sequencing is an essential cornerstone of pathogen surveillance and outbreak detection. Established sequencing technologies are currently challenged by Oxford Nanopore Technologies (ONT), which offers an accessible and cost-effective alternative enabling gap-free assemblies of chromosomes and plasmids. Limited accuracy has hindered its use for investigating pathogen transmission, but recent technology updates have brought significant improvements. To evaluate its readiness for outbreak detection, we selected 78 Listeria monocytogenes isolates from diverse lineages or known epidemiological clusters for sequencing with ONTs V14 Rapid Barcoding Kit and R10.4.1 flow cells. The most accurate of several tested workflows generated assemblies with a median of one error (SNP or indel) per assembly. For 66 isolates, cgMLST profiles from ONT-only assemblies were identical to those generated from Illumina data. Eight assemblies were of lower quality with more than 20 erroneous sites each, primarily caused by methylations at the GAAGAC motif (5'-GAAG6mAC-3 / 3'-GT4mCTTC-5'). This led to inaccurate clustering, failing to group isolates from a persistence-associated clone that carried the responsible restriction-modification system. Out of 50 methylation motifs detected among the 78 isolates, only the GAAGAC motif was linked to substantially increased error rates. Our study shows that most L. monocytogenes genomes assembled from ONT-only data are suitable for high-resolution genotyping, but further improvements of chemistries or basecallers are required for reliable routine use in outbreak and food safety investigations.

genomics↗

bioRxiv2023

ChatGPT usage in the Reactome curation process

Appreciating the rapid advancement and ubiquity of generative AI, particularly ChatGPT, a chatbot using large language models like GPT, we endeavour to explore the potential application of ChatGPT in the data collection and annotation stages within the Reactome curation process. This exploration aimed to create an automated or semi-automated framework to mitigate the extensive manual effort traditionally required for gathering and annotating information pertaining to biological pathways, adopting a Reactome "reaction-centric" approach. In this pilot study, we used ChatGPT/GPT4 to address gaps in the pathway annotation and enrichment in parallel with the conventional manual curation process. This approach facilitated a comparative analysis, where we assessed the outputs generated by ChatGPT against manually extracted information. The primary objective of this comparison was to ascertain the efficiency of integrating ChatGPT or other large language models into the Reactome curation workflow and helping plan our annotation pipeline, ultimately improving our protein-to-pathway association in a reliable and automated or semi-automated way. In the process, we identified some promising capabilities and inherent challenges associated with the utilisation of ChatGPT/GPT4 in general and also specifically in the context of Reactome curation processes. We describe approaches and tools for refining the output given by ChatGPT/GPT4 that aid in generating more accurate and detailed output.

molecular biology↗

bioRxiv2023

Pathway-based, reaction-specific annotation of disease variants for elucidation of molecular phenotypes

Disease variant annotation in the context of biological reactions and pathways can provide a standardized overview of molecular phenotypes of pathogenic mutations that is amenable to computational mining and mathematical modeling. Reactome, an open source, manually curated, peer-reviewed database of human biological pathways, provides annotations for over 4000 disease variants of close to 400 genes in the context of [~]800 disease reactions constituting [~]400 disease pathways. Functional annotation of disease variants proceeds from normal gene functions, through disease variants whose divergence from normal molecular behaviors has been experimentally verified, to extrapolation from molecular phenotypes of characterized variants to variants of unknown significance using criteria of the American College of Medical Genetics and Genomics (ACMG). Reactomes pathway-based, reaction-specific disease variant dataset and data model provide a platform to infer pathway output impacts of numerous human disease variants and model organism orthologs, complementing computational predictions of variant pathogenicity.

systems biology↗

bioRxiv2021

Open Natural Products Research: Curation and Dissemination of Biological Occurrences of Chemical Structures through Wikidata

Contemporary bioinformatic and chemoinformatic capabilities hold promise to reshape knowledge management, analysis and interpretation of data in natural products research. Currently, reliance on a disparate set of non-standardized, insular, and specialized databases presents a series of challenges for data access, both within the discipline and for integration and interoperability between related fields. The fundamental elements of exchange are referenced structure-organism pairs that establish relationships between distinct molecular structures and the living organisms from which they were identified. Consolidating and sharing such information via an open platform has strong transformative potential for natural products research and beyond. This is the ultimate goal of the newly established LOTUS initiative, which has now completed the first steps toward the harmonization, curation, validation and open dissemination of 750,000+ referenced structure-organism pairs. LOTUS data is hosted on Wikidata and regularly mirrored on https://lotus.naturalproducts.net. Data sharing within the Wikidata framework broadens data access and interoperability, opening new possibilities for community curation and evolving publication models. Furthermore, embedding LOTUS data into the vast Wikidata knowledge graph will facilitate new biological and chemical insights. The LOTUS initiative represents an important advancement in the design and deployment of a comprehensive and collaborative natural products knowledge base. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=61 SRC="FIGDIR/small/433265v3_ufig1.gif" ALT="Figure 1"> View larger version (14K): org.highwire.dtl.DTLVardef@184136borg.highwire.dtl.DTLVardef@16e0d6org.highwire.dtl.DTLVardef@30ae1org.highwire.dtl.DTLVardef@1bf4825_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2019

Isolation and comparative genomic analysis of reuterin-producing Lactobacillus reuteri from poultry gastrointestinal tract

Lactobacillus reuteri is a natural inhabitant of selected animal and human gastrointestinal tract (GIT). Certain strains have the capacity to transform glycerol to 3-hydroxypropionaldehyde (3-HPA), further excreted to form reuterin, a potent antimicrobial system. Reuterin-producing strains may be applied as a natural antimicrobial in feed to prevent pathogen colonization of animals, such as in poultry, and replace added antimicrobials. To date, only seven L. reuteri strains isolated from poultry have been characterized which limits phylogenetic studies and host-microbes interactions characterization. This study aimed to isolate L. reuteri strains from poultry GIT and to characterize their reuterin production and antimicrobial resistance (AMR) profiles using phenotypic and genetic methods. Seventy reuterin-producing strains were isolated from poultry crop, faeces and caeca and twenty-five selected for further characterization. Draft genomes were generated for the new 25 isolates and integrated in a phylogenetic tree of 40 strains from different hosts. Phylogenetic analysis based on gene content as well as on core genomes showed grouping of the selected 25 L. reuteri poultry isolates within the poultry/human lineage VI. Strains harbouring pdu-cob-cbi-hem genes (23/25) produced between 156 mM {+/-} 11 and 330 mM {+/-} 14 3-HPA, from 600 mM of glycerol, in the conditions of the test. All 25 poultry strains were sensitive to cefotaxime (MIC between 0.016 and 1 g/mL) and penicillin (MIC between 0.02 and 4 g/mL). Akin to the reference strains DSM20016 and SD2112, the novel isolates were resistant to penicillin, possibly associated with identified point mutations in ponA, pbpX, pbpF and pbpB. All strains resistant to erythromycin (4/27) carried the ermB gene, and it was only present in poultry strains. All strains resistant to tetracycline (5/27) harbored tetW gene. This study confirms the evolutionary history of poultry/human lineage VI and identifies pdu-cob-cbi-hem as a frequent trait but not always present in this lineage. L. reuteri poultry strains producing high 3-HPA yield may have potential to prevent enteropathogen colonization of poultry.

genomics↗

bioRxiv2018

Growth potential of Listeria monocytogenes in twelve different types of RTE salads: impact of food matrix, storage temperature and shelf life

Listeriosis is a food borne disease associated with high hospitalization and fatality rates; in 2014, EU member states reported 2194 cases with 98.9% hospitalization rates and 210 fatalities. Proper risk analysis and the development of effective food safety strategies critically depend on the knowledge of the growth characteristics of L. monocytogenes on the product in question. Ready-to-eat (RTE) salads present a challenge in this context due to the absence of a heat treatment step before consumption and the interaction of pathogens with the plant microbial microbiota. This study provides challenge-test based data of the growth characteristics of L. monocytogenes on twelve RTE salads. The food matrix, storage time and storage temperature were factors with a significant impact on the growth of L. monocytogenes. While most tested salads permitted a significant increase of L. monocytogenes in at least one of the tested conditions, no growth was observed on celeriac, carrot and corn salad products. There was a considerable increase in growth at 8 {degrees}C compared to 5 {degrees}C. Our data indicate that the reduction of the storage temperature at retail level to 5 {degrees}C and product shelf life could help mitigate the risk of L. monocytogenes in RTE salads.

microbiology↗