Biology subjects

Urban, L.

Publications and source records attributed to Urban, L..

At least 19 recordsLinked to original sources

bioRxiv2026

Maturation of Sleep EEG Complexity in Preterm Newborns: Insights from Lempel-Ziv and Joint Lempel-Ziv Analyses

The development of the sleep-wake cycle reflects the progressive structural and functional maturation of the brain. However, the organization of neural dynamics during prematurity remains incompletely understood. In this study, we analyzed the EEG from 54 polysomnographic recordings obtained from 39 preterm infants, grouped according to postmenstrual age (PMA) into three categories: 30-31, 32-33 and 34-35 weeks. Lempel-Ziv Complexity (LZC) and Joint Lempel-Ziv Complexity (JLZC) of the electroencephalogram (EEG) were analyzed during active sleep (AS), quiet sleep (QS), and indeterminate sleep (IS). LZC computed from the raw, unfiltered recordings were significantly higher during QS than during AS and increased with PMA during AS. To further refine the analysis, LZC was also evaluated separately in the low-frequency (1-15.5 Hz) and high-frequency (16-30 Hz) EEG bands. In the low-frequency band, LZC was consistently higher during QS than during AS, an effect that was most pronounced in more immature groups. Furthermore, LZC increased with maturation particularly during AS. Sleep-state comparisons of LZC in the high-frequency EEG band also revealed higher values during QS than during AS across all PMA groups. Moreover, in contrast to the low-frequency band, LZC progressively decreased with advancing PMA both in AS and QS, suggesting that the neural mechanisms underlying low- and high-frequency EEG activity follow distinct maturational trajectories. Interestingly, larger LZC in the temporal cortex and interhemispheric differences were detected in the 32-33 PMA group. On the other hand, JLZC analysis revealed greater joint spatiotemporal dynamics across EEG channels during QS than during AS, with consistently higher JLZC values in temporal regions and lower in occipital regions. Together, these findings show that these complexity metrics distinguishes sleep states and captures maturational changes in EEG activity in preterm infants. These results provide novel insights into early brain development and suggest potential quantitative biomarkers of neonatal brain maturation.

neuroscience↗

bioRxiv2026

Verification of nanopore sequencing technology for clinical carbapenem-resistant Enterobacterales surveillance

Carbapenem-resistant Enterobacterales (CRE) pose a critical threat to global public health and often contribute to the rapid plasmid-mediated dissemination of carbapenemase genes. While established routine diagnostics can confirm the presence of the most common carbapenemases, these approaches do not resolve the genomic context of resistance and thus cannot confirm transmission events, cross-species dissemination, or atypical resistance mechanisms. Nanopore sequencing-based whole-genome sequencing (WGS) can capture this genomic context through complete de novo genome and plasmid assemblies. However, for routine clinical use of nanopore WGS for CRE surveillance, direct comparisons with established diagnostics and clear guidelines on required sequencing depths are needed. We used 100 carbapenemase-producing CRE isolates from routine diagnostics at a tertiary-care hospital to compare results from WGS against established diagnostics, and determined the sequencing depth required for species identification, strain typing, carbapenemase detection, and plasmid-level epidemiology. We additionally examined 10 carbapenem-non-susceptible CRE isolates, for which routine diagnostics identified no carbapenemase gene despite phenotypic carbapenem non-susceptibility. Across all isolates, nanopore WGS reproduced routine carbapenemase family and pathogen detections, and additionally resolved the carbapenemase subtypes and their genomic context, the bacterial species and strain, and resistance mechanisms that established diagnostics had missed. Such strain typing and plasmid-level resolution are essential for infection control responses to differentiate between clonal spread of CRE, dissemination of shared plasmid, or unrelated infection events. Our study thus strongly supports the integration of cost-efficient nanopore WGS into CRE diagnostics, surveillance, and outbreak investigation. The required sequencing depth depends on the clinical objective, with species identification being reliable at a depth of 10x, strain typing and carbapenemase detection at a depth of at least 20x, and robust plasmid-level characterisation at a depth of at least 40x. Across our CRE collection, the detected carbapenemases were mostly plasmid-borne, and predominantly encoded by relatively conserved IncN and more heterogenous IncL/M plasmids. ImportanceCarbapenem-resistant bacteria are among the most serious threats in modern medicine, leaving clinicians with few treatment options. Nanopore sequencing can be a powerful tool to rapidly and precisely track resistance and guide infection control, but limited comparisons with clinically established diagnostics and uncertainty about how much sequencing data is needed currently limit routine clinical use. We show that nanopore sequencing detects all relevant carbapenemase genes identified by routine diagnostics, resolves carbapenem resistance mechanisms that standard tests miss, and generally increases the resolution of pathogen characterizations for transmission and outbreak tracing. We provide guidance on the sequencing depth required for diagnostic tasks, from identifying species to tracking plasmid-borne resistance genes across time and pathogens. By benchmarking nanopore sequencing against established diagnostics and matching sequencing effort to the clinical question, we offer a framework that makes genomic surveillance of carbapenem-resistant bacteria accessible and cost-efficient.

genomics↗

bioRxiv2026

A metagenomic framework for rapid Listeria monocytogenes surveillance in food production environments

Listeria monocytogenes remains a major foodborne pathogen with high mortality and costly persistence in food-processing environments. Established diagnostics rely on selective enrichment and single-colony isolation, which could introduce strong biases by favouring fast-growing strains or those more tolerant to enrichment broth inhibitors, while suppressing slow-growing, viable-but-nonculturable, and other co-occurring strains. This can obscure true pathogen diversity and may contribute to discrepancies between strains detected in food production environments and those associated with disease. To quantify the bias introduced by established culture-based diagnostics and to assess the potential advantage of metagenomics-based pathogen detection directly from the original sample matrix, we developed and evaluated a rapid nanopore sequencing-based metagenomic framework. We designed an artificial metagenomic community of several Listeria strains, comprising L. monocytogenes lineages I-III (including hypervirulent, persistent, and low-virulence strains), other Listeria spp., and a realistic background microbiome representative of food-processing environments. We then used this mock community to spike standard surveillance sponges and compared three workflows: (i) direct nanopore metagenomic sequencing of the original sample matrix, (ii) quasi-metagenomic sequencing after 4 h, 12 h, 24 h, or 48 h of selective enrichment, and (iii) ISO-based culture followed by whole-genome sequencing of a single presumptive L. monocytogenes isolate. We found that the culture-based approach recovered only a limited subset of strains, consistently underrepresenting diversity and failing to detect multi-strain contamination. These findings were reflected by the quasi-metagenomic results, where we found relative L. monocytogenes enrichment to be strain-dependent, indicating selective enrichment bias favouring specific strains. Metagenomics captured the full spectrum of spiked Listeria strains, enabling comprehensive strain-level resolution at all inoculation levels. We only observed relative enrichment of the L. monocytogenes strains by quasi-metagenomics compared with metagenomics after 48 h of selective enrichment. While driven primarily by the additional enrichment of L. innocua, these results suggest that quasi-metagenomics improves L. monocytogenes recovery only at the cost of a substantial reduction in speed. We finally showed that the sensitivity and accuracy of metagenomics could be improved by utilising different environmental sampling materials. We did not find any significant performance improvements from nanopore sequencing-based enrichment of L. monocytogenes through adaptive sampling approaches. We conclude that integrating long-read metagenomics into routine surveillance shows great promise to improve detection and source attribution in food safety systems.

microbiology↗

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↗

bioRxiv2026

Monitoring terrestrial vertebrates with airborne DNA in the Luangwa Valley, Zambia

Vertebrates play vital roles in maintaining ecosystem processes and services and serve as valuable indicators of environmental health, making them an important target for monitoring and conservation efforts. Within the environmental DNA (eDNA) toolbox, airborne environmental DNA has recently emerged as a novel approach for vertebrate monitoring. In this study, we evaluated on-site airborne eDNA for terrestrial vertebrate monitoring in the Luangwa Valley savanna in Zambia, which represents a major biodiversity stronghold of largely intact wilderness and with high levels of vertebrate diversity and endemism. Six air samplers were deployed over four days alongside camera traps for validation, and samples were processed using a mobile molecular laboratory. In total, 120 terrestrial vertebrate taxa were detected with airborne eDNA, including 16 of the 17 taxa recorded by camera traps, demonstrating high sensitivity. Notably, 72.5% of taxa were detected on the first day, and a single sampler recovered 61.7% of all taxa; the taxonomic richness incrementally increased with extended sampling efforts, but the magnitude of these increases declined progressively. The detected taxa spanned the four terrestrial vertebrate classes and encompassed a wide range of ecological traits. These results show that airborne eDNA can quickly recover a substantial and representative fraction of local vertebrate diversity within a short sampling window, while extended sampling can improve detection of less common taxa. Despite existing limitations, our findings support the use of airborne eDNA as an efficient and scalable complementary tool for community-level biodiversity assessments in terrestrial ecosystems such as Zambezian savannas.

ecology↗

bioRxiv2026

Nanopore metagenomic sequencing links clinically relevant resistance determinants to pathogens

Culture-independent metagenomics enables the detection of plasmid-encoded antimicrobial resistance (AMR) genes directly from clinical samples; however, the clinical significance of these genes depends on their bacterial host and genomic context, which metagenomics cannot fully infer. Nanopore sequencing technology intrinsically encodes epigenetic modifications such as methylation, which can be leveraged for plasmid-host associations from metagenomic data. Existing methods rely on the recovery of metagenome-assembled genomes (MAGs), which can introduce bias toward abundant taxa and leave clinically relevant, low-abundance pathogens unassociated. To address this limitation, we extended methylation-based plasmid-host association from the MAG level to individual assembly contigs and sequencing reads. The CUPID pipeline implements the calculation of contig and read similarity scores, which compare weighted mean methylation rates across motifs genetically shared between any contig or read pair. We validated this approach on a mock metagenomic community composed of ten carbapenem-resistant Enterobacterales isolates, where we achieved 93.8% accuracy at the contig level and 100% at the read level for carbapenemase plasmid-host associations. When applied to metagenomic and quasimetagenomic data of sixteen patient rectal swabs collected during routine hospital surveillance, our approach assigned every detected plasmid-encoded carbapenemase to its correct bacterial host at the contig level, using matched culture-based diagnostics and whole-genome sequencing as a ground truth. Read-level analysis identified additional associations that were missed at the contig level, including a multi-host plasmid confirmed by established diagnostics. These findings demonstrate a pathway from rapid AMR gene detection using metagenomics to actionable surveillance for infection prevention, transmission tracing, and outbreak investigation. Impact statementCulture-independent metagenomics can detect antimicrobial resistance genes, but their clinical significance depends on the bacterial host and genomic context. Here, we show that nanopore-derived bacterial DNA methylation patterns can link carbapenemase genes to pathogenic hosts and plasmid context directly from patient samples. This provides a route from rapid antimicrobial resistance gene detection to actionable public health surveillance. Data summaryAll sequencing data after human content filtering have been deposited at the European Nucleotide Archive (ENA, BioProject accession PRJEB108076, with all isolate sequencing data for mock community generation available under the sample accession numbers SAMEA121375149-58, all isolate sequencing data from the rectal swabs available at SAMEA121334008-24, all metagenomic data from the rectal swabs available at SAMEA121325220-27, and all quasimetagenomic data available at SAMEA122914816-23, SAMEA122920068-74). All code is available at GitHub: https://github.com/harikaurel/cupid. All other supporting data are provided in the article and supplementary tables.

genomics↗

bioRxiv2025

Real-time genomic pathogen, resistance, and host range characterization from passive water sampling of wetland ecosystems

Wetland ecosystems provide interfaces for the transmission of microbial pathogens and antimicrobial resistances (AMR) between migratory birds, wild and domestic animals, and human populations. The efficient surveillance of wetlands is, however, challenging, since the typically low concentration of pathogens typically requires the sampling of large volumes of water and subsequent targeted detection, which is inherently limited to a few pathogens or AMR genes of interest. Here, we present a holistic, accessible, and cost-efficient framework to characterize the pathogen and resistance load of water sources together with their potential associated hosts by combining passive water sampling through torpedo-shaped devices with nanopore sequencing technology. We used this framework to characterize anthropogenically influenced and natural wetland ecosystems along the East Atlantic Flyway, where we obtained robust assessments of the microbial communities from long-read metagenomic and RNA virome data, and showed that anthropogenically impacted wetland ecosystems consistently exhibited higher relative abundances of pathogens and AMR genes. By focusing on avian influenza viruses (AIV), we finally highlight the additional need for targeted screening and whole-genome sequencing of pathogens of interest; we detected and characterized AIV at a third of the monitored sites, and used environmental DNA (eDNA) to explore potential animal hosts to better understand the role of wetland ecosystems as One Health interfaces. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=191 HEIGHT=200 SRC="FIGDIR/small/674394v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@1a006f2org.highwire.dtl.DTLVardef@12824c2org.highwire.dtl.DTLVardef@8554bdorg.highwire.dtl.DTLVardef@17e800e_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

Resolving plasmid-encoded carbapenem resistance dynamics and reservoirs in a hospital setting through nanopore sequencing

The growing resistance of Enterobacterales to last-resort antibiotics such as carbapenems puts a significant burden on healthcare systems, also due to plasmids driving a rapid spread of carbapenem resistance. We here evaluate the use of long-read nanopore sequencing to investigate carbapenem resistance dynamics and the role of plasmid transfers and environmental reservoirs in the hospital setting. Over 13 months, routine clinical diagnostics identified recurring isolates of carbapenem-resistant Citrobacter species carrying Klebsiella pneumoniae carbapenemases (KPC) and/or OXA-48-like carbapenemases from patient screening and hospital drain samples. While routine diagnostic approaches provided limited insights into the carbapenem resistance dynamics, we show that near-complete de novo assembly of chromosomes and plasmids by long-read nanopore sequencing allowed for high-resolution strain identification, plasmid profiling, and antibiotic resistance gene detection. Notably, genomically nearly indistinguishable Citrobacter freundii of the high-risk sequence type ST91 genomes were recovered from screening samples collected in the same hospital room one year apart. We further provide evidence of a KPC-2 encoding IncN plasmid that is likely to have spread across bacterial species and between patient and drain isolates, which emphasizes the role of contaminated drains in the persistence and dissemination of resistances within the hospital environment. Overall, this study demonstrates the value of long-read nanopore sequencing for uncovering the complex dynamics of carbapenem resistance spread and persistence in the hospital setting, and its potential implications for Infection Prevention and Control. Impact statementThis study demonstrates how long-read nanopore sequencing can resolve the complex dynamics of plasmid-mediated antimicrobial resistance in clinical and environmental samples within the hospital setting. By linking patient- and drain-derived isolates through near-complete de novo assemblies, we reveal hidden reservoirs and dynamics behind the persistence of cabapenem resistance over extended time periods. This work shows how long-read sequencing approaches can uncover resistance dynamics that are missed using standard diagnostic methods, with implications for infection control and surveillance. Data SummaryThe study sequences are available at the National Center for Biotechnology Information (NCBI) under BioProject accession number PRJNA1297122. The raw sequence read data is available at NCBI sequence read archive (SRA (https://www.ncbi.nlm.nih.gov/sra)) under accession numbers SRR34727947-59. The chromosomal assemblies of all ST91 strains are available at NCBI GenBank under the Biosample accession numbers SAMN50449475-80. All other supporting data are provided in the article and supplementary data files.

microbiology↗

bioRxiv2025

Microbial diversity of Atlantic Rainforest ponds assessed by nanopore sequencing

Despite their limited size, ponds are ecologically important habitats that harbor rich microbial communities and play key roles in global biodiversity and biogeochemical cycling. In this study, we conducted a metagenomic survey of microbial diversity in three ponds - Vermelha, Grande, and Furnas - situated within the Atlantic Rainforest biome in Brazil. Vermelha and Grande are natural, remote, and minimally impacted by human activity, whereas Furnas is an artificial pond with greater human accessibility. Using a long-read nanopore shotgun metagenomics approach, we sequenced DNA extracted from pond water, assembled metagenomes, and performed taxonomic classification and functional annotation. Furthermore, 21 metagenome-assembled genomes (MAGs) were recovered. Our results reveal striking biodiversity contained within ponds, with pond-specific microbial community structures and functional profiles. In addition to bacterial communities, some dsDNA bacteriophages and eukaryotic viruses were also detected. Functional annotation identified putative antimicrobial resistance genes (ARGs), most of them in Furnas, potentially reflecting human impact. Cyanotoxin biosynthesis genes were detected as well, predominantly in Vermelha. Our findings underscore the ecological distinctiveness of each pond and demonstrate the utility of nanopore-based metagenomics for investigating microbial biodiversity in understudied freshwater ecosystems, with implications for conservation and biotechnological exploration. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=126 SRC="FIGDIR/small/660208v3_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1941bd9org.highwire.dtl.DTLVardef@b06d66org.highwire.dtl.DTLVardef@de6df3org.highwire.dtl.DTLVardef@1048bbd_HPS_FORMAT_FIGEXP M_FIG Through nanopore metagenomic sequencing, this work uncovered the microbiome of the 3 analysed freshwater ponds of the Brazilian Atlantic Forest. Results include the taxonomic profile present in each sample, countless genes identified and 21 MAGs recovered. C_FIG

bioinformatics↗

bioRxiv2025

Evaluation of nanopore sequencing for increasing accessibility of eDNA studies in biodiverse countries

Biodiversity loss is a global challenge of the 21st century. Environmental DNA (eDNA)-based metabarcoding offers a cost- and time-efficient alternative to conventional biodiversity surveys, enabling detection of rare, cryptic, and elusive species from environmental samples. However, limited access to genomic technologies restricts the application of eDNA metabarcoding in highly biodiverse remote regions and low- and middle-income countries (LMICs). Here, we directly compared the latest portable nanopore sequencing methods with established Illumina sequencing for vertebrate eDNA metabarcoding of Zambian water samples. Our results show that due to recent improvements in sequencing chemistry and optimized basecalling, nanopore sequencing data can recapitulate or even surpass established protocols, demonstrating the feasibility of in situ biodiversity assessments. eDNA- and camera trap-based species detections had minimal overlap in species detections, suggesting a complementary rather than substituting application of these biodiversity monitoring technologies. We finally demonstrate that our entire eDNA workflow can be successfully implemented in a mobile laboratory under remote field conditions by completing all steps--from sample collection to data analysis--within the Luambe National Park in Zambia. This approach has important implications for capacity building in LMICs and for overcoming limitations associated with sample export.

molecular biology↗

bioRxiv2024

Nanopore- and AI-empowered metagenomic viability inference

The ability to differentiate between viable and dead microorganisms in metagenomic data is crucial for various microbial inferences, ranging from assessing ecosystem functions of environmental microbiomes to inferring the virulence of potential pathogens from metagenomic analysis. While established viability-resolved genomic approaches are labor-intensive as well as biased and lacking in sensitivity, we here introduce a new fully computational framework that leverages nanopore sequencing technology to assess microbial viability directly from freely available nanopore signal data. Our approach utilizes deep neural networks to learn features from such raw nanopore signal data that can distinguish DNA from viable and dead microorganisms in a controlled experimental setting of UV-induced Escherichia cell death. The application of explainable AI tools then allows us to pinpoint the signal patterns in the nanopore raw data that allow the model to make viability predictions at high accuracy. Using the model predictions as well as explainable AI, we show that our framework can be leveraged in a real-world application to estimate the viability of obligate intracellular Chlamydia, where traditional culture-based methods suffer from inherently high false negative rates. This application shows that our viability model captures predictive patterns in the nanopore signal that can be utilized to predict viability across taxonomic boundaries. We finally show the limits of our models generalizability through antibiotic exposure of a simple mock microbial community, where a new model specific to the killing method had to be trained to obtain accurate viability predictions. While the potential of our computational frameworks generalizability and applicability to metagenomic studies needs to be assessed in more detail, we here demonstrate for the first time the analysis of freely available nanopore signal data to infer the viability of microorganisms, with many potential applications in environmental, veterinary, and clinical settings. Author summaryMetagenomics investigates the entirety of DNA isolated from an environment or a sample to holistically understand microbial diversity in terms of known and newly discovered microorganisms and their ecosystem functions. Unlike traditional culturing of microorganisms, genomic approaches are not able to differentiate between viable and dead microorganisms since DNA might persist under different environmental circumstances. The viability of microorganisms is, however, of importance when making inferences about a microorganisms metabolic potential, a pathogens virulence, or an entire microbiomes impact on its environment. As existing viability-resolved genomic approaches are labor-intensive, expensive, and lack sensitivity, we here investigate our hypothesis if freely available nanopore sequencing signal dat that captures DNA molecule information beyond the DNA sequence might be leveraged to infer such viability. This hypothesis assumes that DNA from dead microorganisms accumulates certain damage signatures that reflect microbial viability and can be read from nanopore signal data using fully computational frameworks. We here show first evidence that such a computational framework might be feasible by training a deep model on controlled experimental data to predict viability at high accuracy, exploring what the model has learned, and using it in a real-world application by application to a bacterial species of veterinary relevance. We finally show that a specific model has to be trained to accurately predict viability after antibiotic exposure of a mock microbial community. While the generalizability of our computational framework therefore needs to be assessed in much more detail, we here demonstrate that freely available data might be usable for relevant viability inferences in environmental, veterinary, and clinical settings.

bioinformatics↗

bioRxiv2024

Latest RNA and DNA nanopore sequencing allows for rapid avian influenza profiling

Avian influenza virus (AIV) currently causes a panzootic with extensive mortality in wild birds, poultry, and wild mammals, thus posing a major threat to global health and underscoring the need for efficient monitoring of its distribution and evolution. Here, we utilized a well-defined AIV strain to systematically investigate AIV characterization through rapid, portable nanopore sequencing by (i) benchmarking the performance of fully portable RNA extraction and viral detection; (ii) comparing the latest DNA and RNA nanopore sequencing approaches for in-depth AIV profiling; and (iii) evaluating the performance of various computational pipelines for viral consensus sequence creation and phylogenetic analysis. Our results show that the latest RNA-specific nanopores can accurately genomically profile AIV from native RNA while additionally detecting RNA epigenetic modifications. We further identified an optimal laboratory and bioinformatic pipeline for reconstructing viral consensus genomes from nanopore sequencing data at various rarefaction thresholds, which we validated by application to real-world environmental samples for AIV monitoring in livestock. Author SummaryWe tested portable, rapid, and easy-to-use technology to obtain more information about the potentially zoonotic RNA virus avian influenza virus, or AIV. AIV has spread globally via the migratory paths of wild birds, and endangers domestic birds, mammals, and human populations given past evidence of infections of different animal species. We here used novel genomic technology that is based on nanopores to explore the genomes of the virus; we established optimized ways of creating the viral genome by comparing different laboratory and computational approaches and the performance of nanopores that either sequence the viral RNA directly or the converted DNA. We then applied the optimized protocol to dust samples which were collected from a duck farm in France during an AIV outbreak. We showed that we were able to use the resulting data to reconstruct the relationship between the virus responsible for the outbreak and previously detected AIV. Altogether, we showed how novel easy-to-use genomic technology can support the surveillance of potentially zoonotic pathogens by accurately recreating the viral genomes to better understand evolution and transmission of these pathogens.

genomics↗

bioRxiv2023

Air monitoring by nanopore sequencing

While the air microbiome and its diversity are essential for human health and ecosystem resilience, comprehensive air microbial diversity monitoring has remained rare, so that little is known about the air microbiomes composition, distribution, or functionality. Here we show that nanopore sequencing-based metagenomics can robustly assess the air microbiome in combination with active air sampling through liquid impingement and tailored computational analysis. We provide fast and portable laboratory and computational approaches for air microbiome profiling, which we leverage to robustly assess the taxonomic composition of the core air microbiome of a controlled greenhouse environment and of a natural outdoor environment. We show that long-read sequencing can resolve species-level annotations and specific ecosystem functions through de novo metagenomic assemblies despite the low amount of fragmented DNA used as an input for nanopore sequencing. We then apply our pipeline to assess the diversity and variability of an urban air microbiome, using Barcelona, Spain, as an example; this randomized experiment gives first insights into the presence of highly stable location-specific air microbiomes within the citys boundaries, and showcases the robust microbial assessments that can be achieved through automatable, fast, and portable nanopore sequencing technology.

molecular biology↗

bioRxiv2023

The ghost of selection past: evolution and conservation relevance of the kakapo color polymorphism

The information contained in population genomic data can tell us much about the past ecology and evolution of species. We leveraged detailed phenotypic and genomic data of nearly all living k[a]k[a]p[o] to understand the evolution of its remarkable feather color polymorphism. The k[a]k[a]p[o] is an endangered and culturally significant parrot endemic to Aotearoa New Zealand, and the green and olive feather colorations are present at similar frequencies in the population. The presence of such a neatly balanced color polymorphism is remarkable because the entire population currently numbers less than 250 birds, which means it has been exposed to severe genetic drift. We dissected the color phenotype, demonstrating that the two colors differ in their light reflectance patterns due to differential feather structure. We used quantitative genomics methods to identify two genetic variants whose epistatic interaction can fully explain the species color phenotype. Our genomic forward simulations show that balancing selection might have been pivotal to establish the polymorphism in the ancestrally large population, and to maintain it during population declines that involved a severe bottleneck. We hypothesize that an extinct apex predator was the likely agent of balancing selection, making the color polymorphism in the k[a]k[a]p[o] a "ghost of selection past".

genomics↗

bioRxiv2023

A novel preclinical secondary pharmacology resource illuminates target-adverse drug reaction associations of marketed drugs

In vitro secondary pharmacology assays are an important tool for predicting clinical adverse drug reactions (ADRs) of investigational drugs. We created the Secondary Pharmacology Database (SPD) by testing 1958 drugs using 200 assays to validate target-ADR associations. Compared to public and subscription resources, 95% of all and 36% of active (AC50 < 1 {micro}M) results were unique to SPD, with bias towards higher activity in public resources. Annotating drugs with free maximal plasma concentrations, we found 684 physiologically relevant novel off-target activities. Furthermore, 64% of putative ADRs linked to target activity in key literature reviews were not statistically significant in SPD. Systematic analysis of all target-ADR pairs identified several novel associations confirmed by publications. Finally, candidate mechanisms for known ADRs are proposed based on SPD off-target activities. Taken together, we present a unique freely-available resource for benchmarking ADR predictions, explaining novel phenotypic activity and investigating clinical properties of marketed drugs.

pharmacology and toxicology↗

bioRxiv2022

Non-invasive real-time genomic monitoring of the critically endangered kakapo

We used non-invasive real-time genomic approaches to monitor one of the last surviving populations of the critically endangered k[a]k[a]p[o] (Strigops habroptilus). We first established an environmental DNA metabarcoding protocol to identify the distribution of k[a]k[a]p[o] and other vertebrate species in a highly localized manner using soil samples. Harnessing real-time nanopore sequencing and the high-quality k[a]k[a]p[o] reference genome, we then extracted species-specific DNA from soil. We combined long read-based haplotype phasing with known individual genomic variation in the k[a]k[a]p[o] population to identify the presence of individuals, and confirmed these genomically informed predictions through detailed metadata on k[a]k[a]p[o] distributions. This study shows that individual identification is feasible through nanopore sequencing of environmental DNA, with important implications for future efforts in the application of genomics to the conservation of rare species, potentially expanding the application of real-time environmental DNA research from monitoring species distribution to inferring fitness parameters such as genomic diversity and inbreeding.

genomics↗

bioRxiv2022

Capturing species-wide diversity of the gut microbiota and its relationship with genomic variation in the critically endangered kakapo

The gut microbiota plays an essential role in host health that has important implications for the conservation management of threatened wildlife. While factors such as diet, medication, and habitat are known to shape the microbiota, our understanding of the entirety of factors, including the complex role of the host genomic background, remains incomplete. Our research on the gut microbiota of the critically endangered k[a]k[a]p[o] (Strigops habroptilus), a flightless parrot species endemic to Aotearoa New Zealand, represents, to our knowledge, the first study to describe the gastrointestinal bacterial diversity for virtually an entire species and to assess the relationship between gut microbiota and host genomic diversity in a highly threatened population. Here we report a 16S rRNA gene-based analysis of k[a]k[a]p[o] faecal samples representing the gut microbiota for 84% of k[a]k[a]p[o] (n = 133). This survey was then leveraged with exceptional metadata to tease apart the impact of host genomic diversity and factors such as sex, diet, antibiotic treatment, disease status, habitat, and time of sampling on the k[a]k[a]p[o] gut microbiota, with sex being the only covariate significantly associated with gut microbiota diversity. We find evidence of a highly polygenic genomic architecture of the gut microbiota and further identify putative associations between gut bacterial diversity and functional biological pathways related to intestinal homeostasis, inflammation, immune response and metabolism. This improved understanding of the k[a]k[a]p[o] gut microbiota - and its relationship with host genomics - can directly benefit k[a]k[a]p[o] management and conservation by providing new insights into the role of the gut microbiome in k[a]k[a]p[o] health and disease mitigation. Overall, we anticipate that an integration of microbiome studies in conservation research and management will improve our understanding of how the concept of One Health with its implications for human, animal and environmental welfare can be achieved.

microbiology↗

bioRxiv2022

Species-wide genomics of kakapo provides transformational tools to accelerate recovery

The k[a]k[a]p[o] is a critically endangered, intensively managed, long-lived nocturnal parrot endemic to Aotearoa New Zealand. We generated and analyzed whole-genome sequence data for nearly all individuals living in early 2018 (169 individuals) to generate a high-quality species-wide genetic variant callset. We leverage extensive long-term metadata to quantify genome-wide diversity of the species over time and present new approaches using probabilistic programming, combined with a phenotype dataset spanning five decades, to disentangle phenotypic variance into environmental and genetic effects while quantifying uncertainty in small populations. We find associations for growth, disease susceptibility, clutch size, and egg fertility within genic regions previously shown to influence these traits in other species. Finally, we generate breeding values to predict phenotype and illustrate that active management over the past 45 years has maintained both genome-wide diversity and diversity in breeding values, and hence, evolutionary potential. We provide new pathways for informing future conservation management decisions for k[a]k[a]p[o], including prioritizing individuals for translocation and monitoring individuals with poor growth or high disease risk. Overall, by explicitly addressing the challenge of small sample size, we provide a template for the inclusion of genomic data that will be transformational for species recovery efforts around the globe.

genomics↗