Biology subjects

Zomer, A. L.

Publications and source records attributed to Zomer, A. L..

14 recordsLinked to original sources

bioRxiv2026

Population analysis and host-disease associations of Shiga toxin-producing Escherichia coli from various sources across eleven European countries using whole genome sequencing

Shiga toxin-producing Escherichia coli (STEC) are important foodborne pathogens, able to cause severe disease in humans. In the DiSCoVeR project (https://onehealthejp.eu/jrp-discover/) a STEC inventory from human and non-human sources from 11 European countries was set up and [≥] 3500 strains were sequenced to perform comparative genomics analysis. We used this dataset to assess STEC population structure and to investigate potential associations between genomic features, host reservoirs and symptoms. Most STEC isolates analysed by Whole Genome Sequencing (WGS) in this study were collected between years 2010-2020. An ad hoc pipeline was deployed for a harmonised characterization of the STEC in the database, allowing the determination of serotyping, stx gene subtyping, 7-loci MLST, virulotyping and cgMLST. The results were analysed with Principal Component Analysis (PCoA) in relation with isolation source to assess clustering of STEC subpopulations. When human STEC data were analysed, the PCoA revealed three distinct human STEC subpopulations (STEC_1, STEC_2 and STEC_3), which were further analysed for associations between genomic features, symptoms and variance. The non-human STEC showed a more dispersed distribution, except for one subpopulation with genes linked to specific host species, and some virulence profiles overlapping with the STEC_1 population. In conclusion, our analysis identified distinct STEC subpopulations from human cases, each characterized by specific genetic features and associated with varying proportions of severe disease outcomes. These findings provide novel insights supporting the risk assessment of STEC. Impact statement[This lay summary of your article should be no more than 200 words, and should a) provide a perspective of how this article adds to the literature in the field; b) identify breadth of interest/utility; and c) state the significance of output (incremental or step), in terms of relevance.] This study is based on the establishment of a One Health STEC genomes database, including sequences from isolates of different sources. Most of the isolates had been isolated in the ten-years time span 2010-2020, in 11 different countries, for surveillance and monitoring activities or specific surveys and research purposes. The final dataset included the whole genome sequencing of 3,418 STEC isolates, mainly from human cases of infections. The metadata included the host symptoms, where available, for human STEC strains and the animal source the strains had been isolated from. We set up a pipeline for the harmonized analysis of STEC WGS, called Discover, made available though ARIES webserver or GitHub. The analysis allowed a deep characterization of STEC strains circulating in Europe. We used this resource to assess STEC population structure and to investigate potential associations between genomic features, host reservoirs, and various symptoms associated with STEC infection by PCoA. This analysis highlighted the presence of subpopulation of human STEC associated with specific features. We provide new information useful for risk characterization, as well as a large dataset genome database and associated metadata compiled from STEC strains, representing a valuable resource for the scientific community, enabling further investigations into STEC diversity, evolution, source attribution and public health relevance. Data summaryThe authors confirm all supporting data, including sequence data accession numbers, code and protocols have been provided within the article or through supplementary data files. One supplementary method and five supplementary tables are available with the online version of this article

genomics↗

bioRxiv2026

Exploring differences across pangenome-graph representations using Escherichia coli O157:H7 as a model

Pangenome graphs are increasingly used to represent population-scale bacterial diversity, yet construction methods span fundamentally different representation paradigms whose outputs and sensitivities to assembly quality remain poorly quantified. We systematically reviewed microbial pangenome graph tools and benchmarked six representative methods spanning gene-cluster, compacted coloured de Bruijn graph (ccDBG), multiple sequence alignment, and hybrid approaches. Using a repeat-rich Escherichia coli O157:H7 dataset with complete genomes and matched short-read data, we constructed graphs from identical inputs and observed orders-of-magnitude differences in graph size and fragmentation, indicating that global topology is driven by representation strategy. Varying completeness composition revealed that assembly fragmentation is a first-order determinant of graph structure: gene-cluster graphs contracted as draft assemblies replaced complete genomes, whereas unitig graphs expanded, with distinct degree-prevalence fingerprints across tools. Computational cost mirrored these shifts and depended strongly on completeness composition, including a pronounced runtime penalty for one ccDBG implementation on all-draft inputs. Finally, analysis of Shiga toxin loci showed that pangenome-level reconciliation does not reliably correct assembly artefacts at challenging multi-copy genes and that performance varies by locus. Together, these findings show that pangenome graphs are representation-dependent models of bacterial diversity, and that assembly completeness is a primary determinant of their topology, scalability, and locus-level accuracy. Authors SummaryBacterial populations are often described using "pangenome graphs," which aim to capture all genetic variation across many genomes in a single structure. However, different tools build these graphs in fundamentally different ways, and little is known about how those differences affect the results. In this study, we systematically compared several widely used approaches using a clinically important strain of Escherichia coli that is rich in repeated and mobile DNA. We found that the size, connectivity, and overall structure of the resulting graphs varied dramatically depending on the method used. Importantly, we also show that incomplete genome assemblies (common in large sequencing studies) strongly alter graph structure, and that different tools respond to incomplete data in different ways. In some cases, this affects the detection of medically relevant genes, including Shiga toxin genes linked to severe disease. Our results demonstrate that pangenome graphs are not interchangeable representations of bacterial diversity. Instead, their structure depends on both the method and the quality of the input data. We argue that researchers should choose graph-building tools carefully and report structural properties explicitly to ensure reproducible and interpretable results.

bioinformatics↗

bioRxiv2025

MetaPointFinder: Detection of Antimicrobial Resistance-Conferring Point Mutations (ARMs) from Metagenomic Reads

BackgroundMany clinically important antimicrobial resistance (AMR) phenotypes such as fluoroquinolones and rifamycins are driven by antimicrobial resistance-conferring mutations (ARMs) in conserved chromosomal loci (e.g., gyrA, parC, rpoB). Resistome profiling by metagenomics sequencing is often proposed as an ideal AMR surveillance tool as it is organism-agnostic, but currently, existing metagenomic AMR surveillance pipelines are only able to identify acquired AMR genes but not point mutations associated with AMR. This is a serious gap in metagenomics-based AMR surveillance, as the true extent of AMR may be underestimated. MethodsWe developed MetaPointFinder (v1), a read-based method that can process both long and short metagenomic reads. The tool identifies resistance-determining regions in reads using DIAMOND (translated protein) and KMA (nucleotide), and classifies known resistant versus wild-type variants by aligning the sequences using pwalign and assessing the observed mutations based on known resistance mutations in the AMRFinderPlus database. The tool outputs ARMs per read, per gene and per antibiotic class. ResultsIn proof-of-concept analyses, MetaPointFinder identified known AMR-associated mutations and quantified resistant/susceptible read counts and ratios from metagenomic samples with corroborating phenotypic resistance data when available. We benchmark our tool using simulated reads from DNA and from reverse-translated protein references with read lengths of 100-5000 bp and error rates between 0 and 30%, simulating both Illumina and Nanopore error rates. We show that MetaPointFinder outperforms any available method for detection of ARMs in metagenomics data. ConclusionMetaPointFinder complements gene-centric resistome profiling by capturing chromosomal mutation-based AMR directly from metagenomes. Impact StatementMany clinically important antimicrobial resistance (AMR) phenotypes such as fluoroquinolones and rifamycins are driven by antimicrobial resistance-conferring mutations (ARMs) in conserved chromosomal loci (e.g., gyrA, parC, rpoB). Resistome profiling by metagenomic sequencing is ideal for AMR surveillance, but existing pipelines detect only acquired genes and ignore point mutations. MetaPointFinder bridges this gap. The tool accurately identifies reads carrying resistance-determining regions using DIAMOND (protein) and KMA (DNA), aligns them, and classifies resistant versus wild-type variants using known mutations from the AMRFinderPlus database.

bioinformatics↗

bioRxiv2025

Barbell Resolves Demultiplexing and Trimming Issues in Nanopore Data

BackgroundOxford Nanopore sequencing enables long-read sequencing across diverse applications, yet the experimental artifacts introduced by Nanopore barcoding are not well characterized. These artifacts can affect demultiplexing accuracy and downstream analyses. ResultsWe performed a rapid barcoding experiment on 66 diagnostic samples and found that 83% of reads carried the expected single-barcode pattern, while 17% contained multiple barcodes or other artifacts. Current demultiplexers, including the widely used Dorado, fail to correctly handle these complex cases, leaving approximately 7% of reads partially trimmed and contaminated with adapter fragments. Additional issues include the presence of two barcodes at the same read end--either identical, originating from the same sample, or different, introduced after pooling. The latter can lead to barcode bleeding when the outer barcode is incorrectly selected. To address these challenges, we developed Barbell, a pattern-aware demultiplexer that detects all barcode configurations. Barbell reduces trimming errors by three orders of magnitude, minimizes barcode bleeding, and supports custom experimental setups such as shorter barcodes, dual-end barcodes, and custom flank sequences. ConclusionsOur results highlight the impact of complex barcode attachments in Nanopore sequencing and demonstrate that Barbell drastically reduces their effects on downstream analyses. Barbell is open source and available at https://github.com/rickbeeloo/barbell.

bioinformatics↗

bioRxiv2024

Bacterial cell-free DNA profiling reveals co-elevation of multiple bacteria in newborn foals with suspected sepsis

BackgroundSepsis is the leading cause of death in newborn foals. This study investigates whether cell-free DNA (cfDNA) sequencing can enhance bacterial pathogen detection in foals with suspected sepsis and addresses existing knowledge gaps and diagnostic challenges. MethodsWe developed a foal cfDNA sequencing for bacteria identification (cfFBI) workflow, integrating wetlab and computational protocols to detect increased bacterial cfDNA abundance in blood. Specifically, cfFBI focusses on enriching bacterial cfDNA molecules and preventing false positive bacterial identifications. cfFBI was applied to blood samples of 25 hospitalized foals categorized according to the neonatal Systemic Inflammatory Response Syndrome (nSIRS) criteria and 7 healthy foals. ResultscfDNA levels of potential sepsis-causing bacterial genera were elevated in all 11 nSIRS-positive foals compared to healthy foals (n=7), and in 8/11 (72.7%) when compared to both nSIRS-negative (n=4; nSIRS=0) and healthy foals, with multiple genera elevated in 5/11 (45.5%). The total cfDNA concentration, bacterial cfDNA fraction and bacterial diversity were not different between the foal groups. However, nSIRS-positive foals showed significantly different end-motifs in host chromosomal cfDNA, and a decrease in host mitochondrial cfDNA fraction. ConclusionsThis study is the first to demonstrate that cfDNA sequencing in blood samples from newborn foals enables detection of pathogenic bacteria and can help identify novel host-related sepsis biomarkers. The elevated presence of multiple sepsis-causing genera in nSIRS-positive foals and the difference in end-motif, suggests that multibacterial elevation may be more common than previously thought. These findings indicate that cfDNA sequencing holds promise as a future diagnostic tool for identifying sepsis in newborn foals.

pathology↗

bioRxiv2024

Targeted isolation of bacteria with potential to competitively exclude Staphylococcus aureus in the upper respiratory tract of pigs

Considering global antimicrobial resistance (AMR) prevalence, alternative or complementary strategies to antimicrobial use, are of interest. Livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) is of particular interest as despite significant AMU reduction, LA-MRSA prevalence in pig husbandry has not decreased. We performed targeted isolation of bacterial species with potential antagonism against LA-MRSA in pig farms. Duplicate piglet nasal swabs from three European countries (Germany, Ireland and The Netherlands) were taken longitudinally from birth up to 10 weeks, one for amplicon sequencing and qPCR, and the other was cryopreserved for culturing. We identified potential probiotic species by anticorrelation analysis of bacterial abundance from amplicon sequencing data with quantitative S. aureus estimates from qPCR data from the samples. A literature-screen was performed on the species identified, to determine their probiotic potential. Following this, 1302 isolates were grown from selected cryopreserved swabs and identified using MALDI-TOF and additional 16S rRNA gene sequencing to isolate the anticorrelating species. Ninety-five isolates of interest were screened for absence of tetracycline resistance and hemolytic activity and whole genome sequencing was conducted to verify their taxonomy and to assess their AMR and virulence gene profile. Additional phenotypic antimicrobial resistance testing selected three different Lactococcus lactis strains. During an in vitro challenge using spent medium, all three strains demonstrated inhibition against two S. aureus strains. These L. lactis strains may have the ability to be used safely to reduce LA-MRSA carriage in the nasal passages of pigs but further in vivo testing is necessary to confirm this potential. ImportanceAn approach to tackle antimicrobial resistance in livestock is to use competitive exclusion agents. We employed a sequencing guided isolation approach to identify bacterial species with in silico antagonism to livestock-associated Staphylococcus aureus (LA-MRSA) in the nasal microbiome of piglets. Based on this, three Lactococcus lactis isolates were found to be suitable for further probiotic testing. This strategy can be used to effectively identify, isolate, and screen bacteria that live in antagonism with opportunistic pathogens such as LA-MRSA in a complex microbiome.

microbiology↗

bioRxiv2024

Flumequine, a fluoroquinolone in disguise

Fluoroquinolone resistance in E. coli isolates from livestock in Europe remains high even though the EMA restricted fluoroquinolone use in animals. However, flumequine, a quinolone similar to fluoroquinolones, is still used in livestock in the Netherland, Belgium, Greece or France. Therefore, we investigated whether flumequine selects for the same resistance mechanisms in E. coli. To accomplish this, we investigated and enumerated resistant and non-resistant E. coli isolates obtained from caecal fermentation assays and from broilers exposed to different concentrations of flumequine and enrofloxacin. Flumequine usage leads to approximately 3-fold increase of resistant E. coli in the caecal fermentation, comparable with enrofloxacin. After in vitro exposure to flumequine and enrofloxacin we detected the same SNPs (S83L, D87G) in gyrA. Furthermore, the same resistance-causing SNPs were found in phenotypic resistant E. coli isolates from broilers treated with enrofloxacin and flumequine. Flumequine induces similar resistance mechanisms as enrofloxacin and restriction for use should be the same.

microbiology↗

bioRxiv2024

Extended period of selection for antimicrobial resistance due to persistency of antimicrobials in broilers

Antimicrobials can select for antimicrobial resistant bacteria. After treatment the active compound is excreted through urine and faeces. As some antimicrobials are chemically stable and very persistent, recirculation of sub-inhibitory concentrations of antimicrobials may occur due to coprophagic behaviour of animals such as chickens. The persistence of three antimicrobials over time and their potential effects on antimicrobial resistance were determined in four groups of broilers. Groups were left untreated (control) or were treated with amoxicillin (non-persistent), doxycycline or enrofloxacin (persistent). Antimicrobials were extracted from the faecal samples and concentrations were measured by LC-MS/MS. We determined the resistome genotypically using shotgun metagenomics and phenotypically by using Escherichia coli as indicator microorganism. Up to 37 days after treatment, persistent antimicrobials (doxycycline and enrofloxacin) had concentrations in faeces equal to or higher than the minimal selective concentration (MSC), in contrast to the non-persistent (amoxicillin) treatment. The amoxicillin treatment showed a significant difference (p [≤] 0.01 and p [≤] 0.0001) in the genotypic resistance only directly after treatment. On the other hand, the doxycycline treatment showed approximately 52% increase in phenotypic and a significant difference (p [≤] 0.05 and p [≤] 0.0001) in genotypic resistance throughout the trial. Furthermore, the enrofloxacin treatment resulted in a complete enrofloxacin-resistant E. coli population but the quantity of resistance genes was similar to the control group, likely because resistance is mediated by point mutations. Based on our findings, we suggest that persistency of antimicrobials should be taken into consideration in the assessment of priority classification of antimicrobials in livestock.

microbiology↗

bioRxiv2024

Lapidary: Identifying and reporting amino acid sequences in metagenomes using sequence reads and Diamond

Genome and metagenome comparisons rely on identifying genetic elements that differ or are in common between samples. These genetic elements can be identified by assembling sequenced reads and identifying the genetic element in the assembly, or by aligning nucleotide sequences in the reads to the nucleotide sequences of a reference genetic element. The first relies on the complete assembly of the genetic element of interest, and the second relies on a reference sequence represented in nucleotides. This is particularly challenging with metagenome data, where the genetic elements, including genes, are often fragmented because sequences are shared between different species in the metagenomic data, resulting in contig breaks in or around genetic elements. This presents a difficulty when identifying genetic elements through the first approach. A common approach with metagenomes is to map reads against reference nucleotide sequences and extract the depth and coverage from those reference sequences. However, currently no software exists to identity and report genetic elements using DNA-protein alignments in metagenomes. We have developed the software Lapidary to identify the identity, coverage, depth, and most likely sequence of amino acid sequences from both genome and metagenome read files. We tested the effectiveness of the method against simulated, genomic and metagenomic read datasets. Lapidary is more sensitive than assembly methods for metagenomic data that often have fragmented assemblies but is less sensitive when assemblies are more complete, as is the case with genomic data.

bioinformatics↗

bioRxiv2023

The developing pig respiratory microbiome harbours strains antagonistic to common respiratory pathogens

In the global efforts to combat antimicrobial resistance and reduce antimicrobial use in pig production, there is a continuous search for methods to prevent and/or treat infections. Within this scope, we explored the relationship between the developing piglet nasal microbiome and (zoonotic) bacterial pathogens from birth until ten weeks of life. The nasal microbiome of 54 pigs was longitudinally studied over 16 time-points on nine farms in three European countries (Germany, Ireland, and the Netherlands) using amplicon sequencing targeting the V3-V4 16S rRNA region as well as the tuf gene for its Staphylococcal discrimination power. The piglets age, the farm, and the litter affected the nasal microbiome, with piglets age explaining 19% of the variation in microbial composition between samples. Stabilization of the microbiome occurred around two weeks post-weaning. Notably, while opportunistic pathogens were ubiquitously present, they did not cause disease. The piglet nasal microbiome often carried species associated with gut, skin, or vagina, which suggests that contact with the vaginal and faecal microbiomes shape the piglet nasal microbiome. We identified bacterial Co-Abundance Groups (CAGs) of species that were present in the nasal microbiomes in all three countries over time. Anticorrelation between these species and known bacterial pathogens identified strains that might be exploited for pathogen reduction. Further experimental evidence is required to confirm these findings. Overall, this study advances our understanding of the longitudinal development and factors influencing the piglet nasal microbiome, providing insights into its role in health and disease. ImportanceOur study on longitudinal analysis of the developing nasal microbiota of piglets in farms in three European countries showed consistent microbiome compositions and that colonization of porcine pathogens occurred in relation with anticorrelating species. These findings enhance our knowledge of co-colonizing species in the nasal cavity, and the identified microbial interactions can be explored for the development of interventions to control pathogens in porcine husbandry.

microbiology↗

bioRxiv2023

Defining minimal selective concentrations of amoxicillin, doxycycline and enrofloxacin in broiler-derived cecal fermentations by phenotype, microbiome and resistome

Antimicrobial resistance (AMR) is an emerging worldwide problem. Exposure to antimicrobials selects for resistant bacteria which are a health threat for humans and animals. The concentration at which selection for resistant bacteria occurs is often lower than the minimum inhibitory concentration (MIC) and also differs between environments. Defining this minimal selective concentration (MSC) under natural conditions is essential to understand the selective window for resistant bacteria which are exposed to residual antimicrobials in humans, animals and the environment. In this study we estimated the MSCs of three antimicrobial compounds, amoxicillin, doxycycline and enrofloxacin in a complex microbial community by conducting fermentation assays with cecal material derived from broilers. We examined the phenotypic resistance of Escherichia coli, resistome and microbiome after 6 and 30 hours of fermenting in the presence of antimicrobials of interest. The concentrations are 10 to 100 times lower than the epidemiological cut-off values in E. coli for the respective antimicrobials as determined by EUCAST (https://mic.eucast.org/). In contrast to the amoxicillin and doxycycline exposure we could not determine any molecular resistance mechanism in the resistome analysis for the enrofloxacin exposure, likely because they are the result of point mutations. Our findings show at which concentrations there still is selection for AMR bacteria. This knowledge can be used to manage the risk of the emergence of AMR bacteria. ImportanceAntimicrobial resistance is an emerging threat to the health of humans and animals; it might affect economic prosperity in the future. The rise of antimicrobial resistant bacteria is a consequence of the use of antimicrobial compounds in humans and animals which selects for resistant bacteria. It is critical to understand the relation between the concentrations of antimicrobial compounds and their selection for antimicrobial resistant bacteria. In our study we are providing the minimal selective concentrations for amoxicillin, doxycycline and enrofloxacin by using cecal fermentations assays.

microbiology↗

bioRxiv2021

Development of Kaptive databases for Vibrio parahaemolyticus O- and K-antigen serotyping

Vibrio parahaemolyticus is an important food-borne human pathogen and is divided in 16 O- serotypes and 71 K-serotypes. Agglutination tests are still the gold standard for serotyping, but many V. parahaemolyticus isolates are not typable by agglutination. An alternative for agglutination tests is serotyping using whole genome sequencing data. In this study, V. parahaemolyticus isolates are serotyped and sequenced, and all known and several novel O- and K-loci are identified. We developed Kaptive databases for all O- and K-loci after manual curation of the loci. These Kaptive databases with the identified V. parahaemolyticus O- and K -loci can be used to identify the O- and K-serotypes of V. parahaemolyticus isolates from genome sequences.

microbiology↗

bioRxiv2020

RFPlasmid: Predicting plasmid sequences from short read assembly data using machine learning

Antimicrobial resistance (AMR) genes in bacteria are often carried on plasmids and these plasmids can transfer AMR genes between bacteria. For molecular epidemiology purposes and risk assessment, it is important to know if the genes are located on highly transferable plasmids or in the more stable chromosomes. However, draft whole genome sequences are fragmented, making it difficult to discriminate plasmid and chromosomal contigs. Current methods that predict plasmid sequences from draft genome sequences rely on single features, like k-mer composition, circularity of the DNA molecule, copy number or sequence identity to plasmid replication genes, all of which have their drawbacks, especially when faced with large single copy plasmids, which often carry resistance genes. With our newly developed prediction tool RFPlasmid, we use a combination of multiple features, including k-mer composition and databases with plasmid and chromosomal marker proteins, to predict if the likely source of a contig is plasmid or chromosomal. The tool RFPlasmid supports models for 17 different bacterial species, including Campylobacter, E. coli, and Salmonella, and has a species agnostic model for metagenomic assemblies or unsupported organisms. RFPlasmid is available both as standalone tool and via web interface.

bioinformatics↗

bioRxiv2017

The contribution of genetic variation of Streptococcus pneumoniae to the clinical manifestation of invasive pneumococcal disease

BackgroundDifferent clinical manifestations of invasive pneumococcal disease (IPD) have thus far mainly been explained by patient characteristics. Here we studied the contribution of pneumococcal genetic variation to IPD phenotype.\n\nMethodsThe index cohort consisted of 349 patients admitted to two Dutch hospitals between 2000-2011 with pneumococcal bacteraemia. We performed genome-wide association studies to identify pneumococcal lineages, genes and allelic variants associated with 23 clinical IPD phenotypes. The identified associations were validated in a nationwide (n=482) and a post-pneumococcal vaccination cohort (n=121). The contribution of confirmed pneumococcal genotypes to the clinical IPD phenotype, relative to known clinical predictors, was tested by regression analysis.\n\nFindingsThe presence of pneumococcal gene slaA was a nationwide confirmed independent predictor of meningitis (OR=10.5, p=0.001), as was sequence cluster 9 (OR=3.68, p=0.057). A set of 4 pneumococcal genes co-located on a prophage was a confirmed independent predictor of 30-day mortality (OR=3.4, p=0.003). We could detect the pneumococcal variants of concern in these patients blood samples by molecular amplification. In the post-vaccination cohort where the distribution of both patient characteristics and pneumococcal serotypes had changed, the relative importance of the prophage was no longer supported.\n\nInterpretationKnowledge of pneumococcal genotypic variants improved our clinical risk assessment for detrimental manifestations of IPD. This provides us with novel opportunities to target, anticipate or avert the pathogenic effects that are related to particular pneumococcal variants. Therefore, future diagnostics should facilitate prompt appreciation of pathogen diversity in clinical sepsis management. Ongoing surveillance is warranted to monitor the clinical value of information on pathogen variants in dynamic microbial and susceptible host populations.\n\nFundingNone.

microbiology↗