Metabarcoding and Metagenomics

Early detection and monitoring of non-indigenous species (NIS) is crucial to prevent their establishment and to reduce ecological and economic impacts in coastal ecosystems. Traditional monitoring approaches, which rely largely on morphological identification of collected organisms, are often time-consuming and may fail to detect species that occur at low abundance, are morphologically cryptic, or are present in the form of inconspicuous life stages. DNA-based approaches, particularly those resorting to environmental DNA, have demonstrated high aptitude for biodiversity monitoring and biosecurity surveillance. By examining the genetic material from bulk community samples or released into the environment, DNA-based approaches enable the detection of species without the need for direct observation, thereby increasing detection sensitivity and expanding the scope of monitoring programs. Despite the rapid growth of its employment in marine monitoring, a global synthesis of the status and trends of DNA-based approaches for detecting NIS in this environment has been lacking. Here, we present such synthesis, based on 146 published studies employing DNA for NIS detections in coastal environments. Two main methodological approaches were used across the reviewed studies, namely DNA metabarcoding which was applied in 49% of studies, closely followed by targeted single-species PCR assays, used in 42% of the studies. A smaller proportion of studies (10%) combined both approaches, integrating broad community screening with targeted detection to improve surveillance efficiency. Globally, 752 NIS were detected across disparate taxonomic groups, with metazoans representing the largest proportion of detections (464 species), followed by Chromista (210 species) and Plantae (77 species). Among these, the most frequently detected taxonomic groups included Dinophyceae (Dinoflagellata), Teleostei (Chordata), Florideophyceae (Rodophyta), Polychaeta (Annelida), Copepoda and Malacostraca (Arthropoda), and Ascidiacea (Chordata). At the species level, several well-known marine invaders were recurrently reported, including Bugula neritina (Linnaeus, 1758), Styela plicata (Lesueur, 1823), Acartia (Acanthacartia) tonsa Dana, 1849-1852, and Botryllus schlosseri (Pallas, 1766), highlighting the ability of DNA approaches to detect widespread and established invaders across different regions. The mitochondrial cytochrome c oxidase subunit I (COI) gene was the most widely used genetic marker, reflecting its broad taxonomic coverage and extensive representation in reference databases, particularly for targeting Metazoa. Ribosomal RNA genes, particularly 18S and 16S rRNA gene markers, were also frequently employed to target a wider range of eukaryotic taxa. Regarding sampled substrates, water was by far the most analyzed substrate, followed by zooplankton and biofouling communities collected from man-made structures. Notably, approximately 31% of all NIS detections reported in the reviewed studies constituted new regional records. These results highlight the potential of eDNA for coastal monitoring but also underline important limitations. Persistent geographical, taxonomic, and methodological biases can affect detection outcomes, and reliance on single sample types or markers may increase false negatives - particularly critical for NIS early detection. Therefore, multi-marker and multi-substrate approaches are essential to improve detection reliability and support effective biosecurity strategies. As reference databases continue to expand and methodological protocols become increasingly standardized, DNA-based monitoring is likely to play a central role in future management and surveillance of biological invasions in coastal ecosystems. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/722998v1_ufig1.gif" ALT="Figure 1"> View larger version (75K): org.highwire.dtl.DTLVardef@17948b1org.highwire.dtl.DTLVardef@193832dorg.highwire.dtl.DTLVardef@189033dorg.highwire.dtl.DTLVardef@33cddf_HPS_FORMAT_FIGEXP M_FIG C_FIG

Metabarcoding is a powerful tool for biodiversity comparisons, where standard-size DNA barcodes (>500 bases) offer better taxonomic resolution than shorter ones. Still, the choice of sequencing platforms and bioinformatics pipelines may strongly affect inferred diversity due to various technical biases. We assessed the relative performance of Illumina MiSeq i100 (2x500 paired-end), PacBio Revio and Oxford Nanopore MinION sequencing and bioinformatics pipelines, using full-length ITS amplicon sequencing datasets from a 103-species mock community and 45 composite soil samples. Despite numerous low-quality reads, PacBio yielded the lowest overall error rate and highest number of taxa. Illumina revealed the highest proportion of chimeric and index-switched reads, along with a strong bias towards shorter amplicons. MinION data analysed using PRONAME and Minovar - a bioinformatics pipeline presented here - had the largest proportion of low-quality data, and rare taxa were lost during data filtering and read polishing steps. Although Minovar enabled amplicon sequence variant (ASV) level precision for common taxa, we recommend clustering ASVs into OTUs. For PacBio, standard filtering approaches outperformed the ASV approach because they retained rare taxa. For Illumina, a stringent ASV approach or removal of rare OTUs would limit artefacts. Across all platforms, excess PCR cycles promoted chimeric and low-quality reads and lost quantitativity in biodiversity assessments. With moderate differences in effect sizes, all analytical approaches supported the conclusion that sampling design determines how we see soil biodiversity responses to land use. For biodiversity surveys based on the full-length ITS metabarcoding, we recommend using PacBio sequencing with standard, non-ASV pipelines.

O_LIEnvironmental DNA (eDNA) metabarcoding is an emerging tool for biodiversity assessment in freshwater systems, offering high-resolution insights into community composition. Here, we apply eDNA metabarcoding to evaluate the ecological impacts of Eurasian beaver (Castor fiber) activity within a seminatural enclosure in the Scottish Highlands. C_LIO_LIWe collected seasonal water samples from nine sites, six influenced by beaver dams and three control sites with no evidence of beaver engineering, across a 40-hectare enclosure. Samples were analysed for vertebrate and macroinvertebrate diversity using established 12S and COI markers. C_LIO_LIVertebrate alpha diversity did not differ significantly between beaver and control sites, likely reflecting the small spatial scale and low species richness of upland Scottish streams. However, community composition differed significantly between treatments, especially for fish (PERMANOVA, R2 = 0.55, P < 0.001), with beaver-influenced sites dominated by three-spined stickleback and control sites by brown trout. Macroinvertebrate communities showed a 78% increase in gamma diversity in beaver-modified habitats relative to controls. Species composition varied strongly with beaver presence (PERMANOVA, R2 = 0.29, P < 0.001), likely due to the creation of lentic-lotic mosaics and associated microhabitat diversity. Seasonal variation was significant in both taxonomic groups, with the lowest species richness and highest community dispersion observed in summer, probably reflecting hydrological and temperature-driven dynamics in eDNA production and transport. C_LIO_LIOur findings reinforce previous evidence that beaver dam-building activity enhances beta diversity in headwater systems. Additionally, we demonstrate that eDNA metabarcoding is a sensitive method for detecting spatial patterns in freshwater biodiversity associated with these activities at scales ranging from tens to hundreds of meters. These approaches could inform future monitoring strategies aligned with landscape-scale beaver management and reintroductions. C_LI

Molecular data have revolutionised taxonomic and ecological research on the hyperdiverse communities of aquatic benthic microinvertebrates known as meiofauna. However, reference sequence databases remain highly incomplete, with variable barcode genes or fragments studied from taxon to taxon. Furthermore, there is a typical tradeoff between universality of primers and phylogenetic resolution, with rRNA markers being robustly recoverable but failing to resolve species-level divergences, and mitochondrial markers showing the reverse trend. Here, we introduce Oxford Nanopore rRNA and COI amplicon sequencing (OrCa-seq), a rapid, low-cost protocol for parallel long-range PCR amplification and multiplexed sequencing of four amplicons, spanning the nearly-complete rRNA cistron ([~]7-8 kb) and the widely studied Folmer region of COI (represented as overlapping 313 and 658 bp amplicons). This protocol, with its associated bioinformatic workflow, was designed for conducting biodiversity inventories of meiofauna and can be easily carried out in field research and educational contexts, with data available from 96-well plates of specimens within a day of lysis. To validate the method, we processed six plates of student-isolated freshwater and limno-terrestrial meiofauna, characterising the recovery of target genes and taxa with both automated and human-curated BLAST database comparisons. These data demonstrate the universal applicability of OrCa-seq across effectively all meiofauna, including the very smallest species. Nonetheless, recovery efficiency for each amplicon shows variation by taxon, with the full-length Folmer COI amplicon standing out as the most challenging. We present exemplar phylogenetic trees integrating reference sequences, demonstrating the utility of these data in confirming morphological determinations and in identifying anonymous specimens in a reverse taxonomy context. While developed in a specific educational context for use on meiofauna, the OrCa-seq approach should be readily scalable to larger research datasets, adaptable to many specimen types, and to any combination of taxon-or target-specific primers. As such, it represents a compelling multi-locus extension to the ever-growing repertoire of nanopore DNA barcoding protocols.

O_LIEnvironmental DNA (eDNA) analyses have become a powerful tool for non-invasive biodiversity monitoring, yet the applicability of population genetic approaches to environmental samples remains largely unexplored. Even when genetic traces originate from a single individual, low target DNA concentrations and amplification or sequencing artefacts can compromise downstream genetic inferences. Here, we present a novel approach for obtaining demographic insights and lineage-level mitogenomic information from aquatic eDNA samples collected near vertebrate individuals. C_LIO_LIPaired eDNA and tissue samples were collected during sperm whale (Physeter macrocephalus) encounters in the Azores. Samples were screened for the presence of vertebrate eDNA and analyzed with a novel molecular sex identification assay. Additionally, long-range PCR was used to amplify up to five mitochondrial DNA fragments ([~]3-4k bp) before subsequent sequencing on an Oxford Nanopore Technologies platform. A stringent three-tier filtering framework capable of identifying true mitogenomic variation across eDNA samples was developed for maximum recovery of genetic diversity at the haplogroup level. By benchmarking eDNA samples via their paired tissues, parameter values were optimized to maximize concordance and minimize spurious variant calls. C_LIO_LISexing was successful for 50% of eDNA samples, with 96% concordance to paired tissues, and marine vertebrate DNA concentration significantly predicted sexing success. Further, Medaka polishing produced high identity mitochondrial consensus sequences (>16 kb) from eDNA samples. Across filtering regimes in the framework, curated SNP panels comprising up to 453 high-confidence mitochondrial SNPs resolved 19 haplogroups, with 93% concordance between eDNA and tissue samples. An intermediate bioinformatics filtering strategy maximized biologically accurate haplogroup recovery while minimizing sequencing artefacts, providing the most reliable lineage-level inferences. C_LIO_LIThis integrative approach demonstrates that targeted nuclear assays combined with long-range mitochondrial sequencing can recover individual-level genetic information from aquatic eDNA. By defining analytical thresholds governing success, the framework advances non-invasive genetic monitoring of populations via eDNA and enables population-level monitoring and conservation of endangered and genetically-vulnerable species. C_LI

The sunflower sea star (Pycnopodia helianthoides) suffered a catastrophic population decline across its range from 2013 to 2017 due to the devastating Vibrio pectenicida FHCF-3 driven sea star wasting disease (SSWD) pandemic with minimal signs of population recovery. The functional extinction of this apex predator across substantial parts of its range has created a need to identify and track the remaining intact populations. Environmental DNA (eDNA) approaches provide a simple, cost-effective, and non-destructive method for monitoring occurrences, and in some cases abundances, of marine species, consistently outperforming visual occurrence monitoring efforts in sensitivity, speed, and cost. Here, we designed, developed, and validated a P. helianthoides-specific eDNA assay to identify refugia, using both quantitative and digital droplet PCR approaches. We first generated the most comprehensive sea star mitochondrial genome reference database to date (n=93 taxa, n= 15 novel). We then used unikseq and Geneious bioinformatics software to identify the unique nad5 gene region and design a highly specific hydrolysis probe-based PCR assay. We validated the performance of this assay through laboratory, mesocosm, and field testing, demonstrating a highly specific and sensitive assay. In a field application of the new assay across regions in British Columbia, Canada, we found a positive correlation between P. helianthoides eDNA concentrations and biomass density, especially when appropriately accounting for spatiotemporal integration scales (R2=0.67). The eDNA assay provides a rapid and scalable tool for monitoring the sunflower sea star which has been proposed for listing as threatened under the U.S. Endangered Species Act of 1973. Molecular tools like the one presented here enhance management and recovery efforts not only by identification and monitoring of remnant wild populations, but also by helping to assess population level response and recovery following reintroduction efforts.

Understanding risks of biological invasions associated with ballast water (BW) requires full understanding of the biodiversity transported in ballast tanks. Here we characterize the remarkable level of diversity that can be carried in the BW of a single vessel. To maximize our ability to capture BW diversity we: 1) utilized DNA-based methods to describe biodiversity, including both native and non-native taxa; 2) exploited multiple primer sets targeting multiple genomic loci with different expectations for taxonomic coverage; 3) assessed multiple tanks on a single vessel to capture different communities present in different tanks; and 4) sampled those tanks with far higher-than-usual replication both to improve representation of the diversity present and to enable statistical estimation of total richness. Using this approach, we found extraordinarily high diversity associated with a single vessel. Across all loci, we estimate a total of 272 taxa that can be assigned species names; looking more broadly at unnamed molecular operational taxonomic units, our estimates are between 425 and 742 individual taxa, depending on the locus. We confirm that only a fraction of this diversity would be captured with typical sampling efforts. We found that different loci capture different snapshots of biodiversity and that our ability to detect taxa of interest (e.g., non-native species) depends on sampling effort and genomic locus. Our results expand upon previous studies describing highly diverse BW communities and add to a growing literature that demonstrates the value of molecular methods for characterizing those communities and assessing the associated risk of non-native species introduction.

BackgroundBenzene, toluene, ethylbenzene, and xylene (BTEX) are volatile aromatic hydrocarbons that are widespread environmental pollutants arising from petroleum processing, fuel combustion, and other industrial activities. Persistent BTEX contamination poses substantial risks to human health and ecosystems, underscoring the need for effective long term remediation strategies. Microbial bioremediation is a promising and sustainable approach for BTEX removal, but development of these approaches requires accurate detection of the genes and pathways responsible for substrate specific degradation. Although profile hidden Markov model (HMM) databases are widely used for functional annotation, existing annotation resources lack the substrate-specific resolution needed to distinguish between closely-related BTEX-degrading enzymes with different catalytic specificities. ResultsWe developed BTEXgenie as a sensitive annotation tool that uses custom HMMs built from alignments of experimentally validated BTEX degradation proteins to identify genes involved in the initial steps of aerobic and anaerobic BTEX degradation. BTEXgenie improved detection of anaerobic BTEX degradation genes that were absent from KOfam annotations. In benchmarking against the KEGG KOfam HMM database, BTEXgenie achieved 17.73%higher overall sensitivity while maintaining comparable specificity at 97.02%across genes involved in BTEX degradation pathways. When applied to environmental metagenomes, BTEXgenie recovered pathway patterns consistent with reported site characteristics and known degradation potential. In addition to gene annotation, BTEXgenie supports downstream interpretation through KEGG pathway-based visualization of detected functions and Circos-based visualization of genomic hit distributions. ConclusionsBTEXgenie is a substrate-specific annotation tool built from custom HMMs for detecting genes involved in BTEX degradation. By integrating gene annotation with pathway and genome-level visualizations, BTEXgenie facilitates characterization of microbial BTEX degradation potential in environmental and comparative genomic studies.

Philippine freshwater ecosystems are considered one of the most diverse ecosystems harboring numerous fish species. However, in the Philippines, these ecosystems are threatened by invasive species that potentially disrupt ecological balance. In this study, we focused on the vermiculated sailfin catfish Pterygoplichthys disjunctivus, an invasive aquarium species reported in several Philippine aquatic ecosystems. Despite its documented spread, its potential range under a rapidly changing climate remains poorly understood for the country. Hence, in this study, we utilized the MaxEnt model to predict its near-current and future habitat suitability in the Philippines. Using 11 reported occurrences, our model showed high predictive accuracy (AUC = 0.882{+/-} .034, TSS = 0.7394 {+/-} 0.154, SEDI = 0.971 {+/-} 0.019). Across the current and future scenarios, slope was the primary contributor (78.7% - 81.3%), followed by BIO 10 or the mean temperature of the warmest quarter(18% - 27.8%), and flow accumulation (0% - 5.2%). However, for the SSP126 scenario, BIO10 is projected to triple by 2050 (18 - 48%). Current projections identify high-risk regions, particularly central Luzon (Laguna de Bay and Lake Taal), the Cagayan River Valley, and portions of eastern Mindanao (Agusan Marsh and Lake Mainit). Sankey transition analysis confirms a high habitat stability rate (>73%) for high-suitability pixels in both SSPs, indicating persistent invasion risk. Overall, our study provides a framework for invasive species management and contributes to the conservation of Philippine aquatic ecosystems.

The prevalence of nitrogen limitation and nitrogen-phosphorus co-limitation (henceforth referred to as nitrogen-related limitation) in Norwegian lakes and their relationships with atmospheric nitrogen deposition, climate, dissolved organic matter (DOM), and catchment characteristics were assessed across space and time. Routine monitoring data from 1,529 lakes in the national Vannmiljo database were analyzed for two multi-year periods (1995-2009 and 2010-2025). Limitation was inferred using the molar NO--N/TP ratio as an indicator of dissolved inorganic nitrogen availability. Nitrogen-related limitation was widespread in both periods and exhibited strong regional structure, with highest prevalence in northern regions and lowest prevalence in southwestern Norway. Overall prevalence increased from 31% to 38% between periods, with significant increases in western regions. Regional-scale models identified climate, forest cover, DOM, agriculture, and atmospheric nitrogen deposition as predictors of limitation probability, whereas study period per se and bog/peatland cover were not significant. At the local scale, atmospheric nitrogen deposition and DOM were the only consistent predictors, with substantially lower explanatory power than at the regional scale. These results indicate that large-scale environmental gradients play a major role in shaping nutrient stoichiometry in Norwegian lakes. Because the monitoring dataset primarily represents lakes affected by human activities, the findings are particularly relevant for water management. The widespread occurrence of nitrogen-related limitation suggests that nitrogen availability may influence phytoplankton growth in many systems and that dual-nutrient management strategies addressing both nitrogen and phosphorus may be required in many regions.

Evidence supporting the use of airborne eDNA for biodiversity studies and ecosystem monitoring is growing. The promise of wide-area population dynamics data for downstream applications in targeted monitoring of pests and pathogens for agriculture and rare species for conservation is appealing; however, several technical challenges persist. Here, we focused on the development of a comprehensive dataset to facilitate assay development and accelerate the use of aerial sampling for species detection. Year-round metabarcoding data was generated using bacterial, fungal, plant, and arthropod primer sets and resulted in relative abundance estimates for 4,960 amplicon sequence variants (ASVs), 1,748 ASVs of which were assigned to a minimum taxonomic level of genus (bacteria, fungi, plants) or class (arthropods). Sequence diversity assessments and seasonal clustering based on presence/absence detection patterns were performed for individual ASVs, while discerning quantitative changes in seasonal abundance required grouping ASVs to at least the genus level. Examination of the technical aspects of metabarcoding suggested that the use of subsampling allows for consistent detection of genera with relative abundance values above 2 %, even when samples have varying sequencing depths. Sequencing depth was the primary determinate for detecting sporadic and/or rare ASVs. Sampler comparisons, common sources of variation, and the benefits of barcoding regional species to supplement the existing taxonomic databases were discussed. Insufficient knowledge of sampler coverage area for the different organism types was identified as a limitation to the deployment of aerial monitoring networks. Considerations for further aerial metabarcoding efforts are suggested based on our experimental findings. ImportanceOur study deals directly with the generation, analysis and limitations of airborne eDNA metabarcoding data for re-use by the broader environmental research community. This includes timing of seasonal detection for possible genera of interest across multiple kingdoms, including bacteria, fungi, plants and animals (specifically arthropods), and support for the generation of local databases to assess the current limitations of universal primers for species/genus taxonomic resolution. With regards to methodology, it continues to build upon established best practices for airborne eDNA collection in areas such as sub-sampling and sampling replicates, sampler type and sequencing depth. To accelerate possible uptake and application of the data, we provide the identified ASVs and their seasonal relative abundances as a resource.

Chelating ion exchange resins are widely used to eliminate metal interferences in the analysis of ammonium (NH4+) in soil extraction solutions. However, their potential to co-adsorb NH4+ remains underexplored. Here, synthetic metal ion solutions containing 6-30 mg L-1 NH4+ and the metal cations Ca2+, Mg2+, Cu2+, Mn2+, and Zn2+ were treated with Amberlite IRC-748 resin. The resin efficiently removed Ca2+ (-42.2%), Mg2+ (-21.1%), Cu2+ (-99.9%), Mn2+ (-56.9%), and Zn2+ (-93.6%). However, NH4+ losses of 2.2-5.6% were observed, indicating concentration-dependent co-adsorption. While these losses may be acceptable for concentration measurements via routine assays such as photometric analysis, they may still affect the accuracy of high-precision N analyses that rely on quantitative NH4+ recovery. This highlights a methodological caveat for resin-treated samples, especially in low-NH4+ environments. We therefore recommend including recovery assessments and correction factors when using chelating resins to improve accuracy in NH4+ quantification.

The use of marine space by human activities is globally increasing, resulting in a competition with spatial management measures for marine conservation. Within the European Union (EU) these measures are currently implemented by the union member states to achieve the UN sustainable development goal (SDG) of protecting at least 10 % of the national marine waters. Further, the EU Marine Strategy Framework Directive (MSFD) and the Nature Restoration Regulation (NRL) are the two main legal means for the implementation of ambitious spatial conservation targets for benthic habitat types, which can range from 10 - 90 %. This study analysis how the targets of the MSFD and NRL are currently met in the German waters of the North Sea and which areas the full implementation of both legislations might require. A spatial optimisation tool ("prioritizr" in R) was used to identify optimised solutions for the conservation of up to 75 % of NRL benthic habitats. The current spatial conservation measures (which ban demersal trawling within certain zones of designated marine protected areas, MPA) are not sufficient to reach the targets of the MSFD and NRL. Extending the exclusion of demersal trawling to the entire area of the MPAs would achieve a sufficient coverage for all habitats except for offshore sand and mud habitats. These could be further protected, when including areas for offshore wind farms, where trawling is also banned. However, to date it is unclear, if and how these (or other human use) areas could be included into spatial conservation regimes, a debate that needs to be resolved to allow for the achievement of the ambitious MSFD and NRL targets.

Telomere length (TL) is increasingly used in ecology as a biomarker of individual quality and environmental stress, yet research on non-model species with complex life histories remains limited. Because TL varies among tissues and across ages in a species-specific manner, identifying non-lethal tissues that reliably reflect whole-organism telomere dynamics is essential for longitudinal telomere studies in the field. This study aimed to evaluate tissue-specific TL in Japanese eel (Anguilla japonica), an endangered catadromous fish. We first mapped the chromosomal distribution of telomeric sequences using fluorescent in situ hybridization (FISH), the first application of this method in this species. We then tested whether muscle and caudal fin, which can be sampled easily and non-lethally, can serve as suitable proxy tissues for TL measurements in wild individuals. Relative telomere length (RTL) was quantified by qPCR in blood, brain, caudal fin, gonads, heart, liver, and muscle. FISH analysis confirmed telomeric repeats at all chromosomal ends, with only weak interstitial signals on three chromosomal pairs unlikely to affect qPCR-based estimates. A generalized additive mixed model and Wilcoxons signed-rank tests revealed significant inter-tissue differences: RTL was shortest in the brain and muscle and longest in liver, blood and caudal fin. Muscle and caudal fin RTL were significantly correlated with RTL in many other tissues, supporting their use as proxy tissues for longitudinal TL monitoring, including responses to environmental variation. Both total length and age were tested as explanatory variables for RTL, and the model including total length showed a better fit than the age-based model. Non-linear relationships between RTL and total length observed in several tissues suggest physiological shifts associated with growth and sexual differentiation. Overall, these findings advance understanding of telomere dynamics in eels and establish muscle and caudal fin as suitable tissues for repeated, non-lethal TL assessment in ecological and conservation contexts.

The 16S rRNA gene is the most widely used genetic marker for microbial community profiling, but its limited sequence divergence often prevents species-level identification. The RNA polymerase {beta}-subunit gene (rpoB) offers higher sequence variability, single-copy occurrence, and stronger phylogenetic consistency, yet its adoption in metataxonomic studies has been constrained by the lack of universal primer sets. Here, we present a novel universal primer pair that amplifies an [~]1,800 bp rpoB region (rpoB_MV) compatible with long-read sequencing platforms. In silico evaluation across 17683 bacterial reference genomes demonstrated high universality, with over 86% of genomes predicted to amplify. Compared with full-length and partial 16S rRNA gene markers, the rpoB_MV amplicon exhibited significantly greater inter-species sequence divergence and improved phylogenetic concordance with core-genome trees. Sequencing of two complementary mock communities confirmed superior species-level identification accuracy, with misclassification rates below 0.01% and no reads assigned to unresolved species clusters. These results establish rpoB_MV as a robust alternative to 16S rRNA gene-based profiling for high-resolution metataxonomic applications. IMPORTANCEMicrobial community studies increasingly require species-level resolution because species within the same genus can differ substantially in pathogenicity, ecological function, and metabolic capacity. Current 16S rRNA gene-based methods frequently fail to distinguish closely related species, collapsing biologically distinct organisms into the same taxonomic assignment and obscuring community differences that matter for clinical diagnostics, food safety, and environmental monitoring. The rpoB_MV primer pair presented here overcomes this limitation by targeting a longer, more variable region of the rpoB gene, enabling accurate species-level identification across diverse bacterial phyla. Combined with advances in long-read sequencing, this approach provides researchers with a practical tool to resolve microbial communities at the species-level.

The prevailing taxonomic profiling methods for an environmental sample rely heavily on PCR amplification of SSU ribosomal RNA (rRNA) genes and genome-based reference databases. Identification and extraction of Illumina metagenomics sequencing data are PCR independent but technically challenging in recognition of the SSU rRNA fragments. Here we present Mitag4taxa, a computational pipeline designed for taxonomic profiling of microbial communities from metagenomic Illumina sequencing reads containing rRNA tags (mitag). A Hidden Markov Model (HMM) of SSU rRNA genes and those for the V4 region of 16S rRNA and the V9 region of 18S rRNA genes were created, respectively, using the representative sequences of different families and corresponding hypervariable regions in the SILVA database. The pipeline identifies and extracts 16S and 18S rRNA gene fragments along with the quality score from metagenomic or metatranscriptomic datasets using HMM search integrated with the models. The hypervariable regions, including the V4 region of 16S rRNA and the V9 region of 18S rRNA genes, can be further scanned and recruited for taxonomic classification and biodiversity estimate. To demonstrate its high reliability, the performance of Mitag4taxa was evaluated using both real and simulated datasets. In human gut metagenomic assessments, taxonomic profiles derived from Mitag4taxa showed high consistency with those based on conventional 16S rRNA gene amplicons, identifying dominant families such as Bacteroidaceae and Prevotellaceae with similar relative abundances. Statistical analyses confirmed highly significant positive correlations between Mitag4taxa and amplicon-based community structures. The 18S V9 module was further validated using shotgun metagenomic data from deep-sea sediment cores, successfully recovering key eukaryotic taxa such as Collodaria and Leotiomycetes. Furthermore, benchmarking against the RiboTagger software using CAMI marine simulated datasets revealed that Mitag4taxa achieved a higher average F1 score and lower error metrics. Overall, Mitag4taxa provides a complementary rRNA gene amplicon- and genome-independent strategy for microbial community profiling, enabling improved detection of both prokaryotic and eukaryotic taxa from metagenomic and metatranscriptomic sequencing data.

There is an urgent need to gather data on harvest rates of waterbirds in Europe to assess the sustainability of hunting. Estimates of total waterbird harvest in the United Kingdom (UK) and the relative harvest of different huntable species come from two separate surveys, the Value of Shooting (PACEC 2014) and National Gamebag Census (NGC, Aebischer 2019), and these have been recently used to explore the likelihood of unsustainable harvests of wild waterbirds by UK hunters (Ellis and Cameron 2022; Madden et al., 2025). The reliability of these sustainability estimates depends on how representative the original surveys are of hunter behaviour and success. There are also 1-3 million released game-farm mallard (Anas platyrhynchos) that takes up considerable and unquantified proportions of the UK waterbird harvest. Here we explore uncertainties in the UK winter harvest of wild waterfowl by comparing estimates from the NGC dataset with those from the Crown Estate coastal hunting clubs, and a novel approach using analysis of social-media images (2019/20 to 2023/24). We explore the difference in species-specific harvest with and without the uncertainties in the number of released mallard and the total number of duck harvested in the UK. Waterbird harvest estimates differ markedly depending on the input dataset and whether released mallard are included in the analysis. Confidence intervals of each estimate are inflated by uncertainties in the number of released game-farm mallard contributing to, and the size of that national bag. Estimates extrapolated from social media suggest the national harvest of several species may be considerably larger than the corresponding NGC estimates (e.g. Teal *2.07 and gadwall *11.2), while mallard harvests away from formal shoots represented by NGC are significantly lower (*0.71). Excluding released mallard reduces the statistical estimate of total wild duck harvest by 56-63%, which would have biologically significant effects if realised.

BackgroundOxford Nanopore Technologies (ONT) sequencing is increasingly used for whole-genome sequencing (WGS) across a wide range of applications. However, the platform has evolved rapidly through updates to flow cell chemistry and basecalling algorithms, altering the characteristics of the resulting sequencing data. Read simulators provide synthetic datasets with known ground truth, enabling controlled development and evaluation of methods. However, many existing simulators were developed for earlier versions of ONT sequencing or use generic long-read assumptions, and their realism for contemporary ONT data is unclear. ResultsWe benchmarked six ONT-compatible read simulators (Badread, LongISLND, lrsim, NanoSim, PBSIM3 and SimLoRD) using a microbial genome reference and ONT R10.4.1 reads as the empirical standard. Each tool was configured to maximise realism, including training on empirical reads when supported. We compared simulated and real datasets with respect to read length, read accuracy, FASTQ quality scores and sequence error profiles. No simulator reproduced all metrics of the real data well. PBSIM3 most closely reproduced read length, read accuracy and FASTQ quality scores, making it a strong simulator for broad read-level realism. However, it did not capture important features of the real error profile, including context-dependent substitution rates and homopolymer-length errors. Badread and LongISLND better reproduced some aspects of the error profile, but showed other departures from the real data. ConclusionPBSIM3 is a good general-purpose choice for many ONT WGS simulation tasks because it reproduced several key read-level properties well. However, Badread or LongISLND may be preferable for applications where error structure is more important. No evaluated tool was realistic across all tested metrics, highlighting a gap for improved long-read simulators.

Terrestrial environmental DNA (eDNA) approaches are rapidly expanding, yet robust, field-ready substrates for detecting insect DNA remain limited in forest ecosystems. Tree sap is a localized microhabitat that attracts diverse insects and may provide a useful substrate for surface eDNA sampling, but its potential for insect monitoring has rarely been evaluated. Here, we present a pilot proof-of-concept study testing naturally exuding tree sap and sap-mimicking traps as terrestrial eDNA substrates. We collected swab samples from sap and trap surfaces at two forest sites in Japan (Fujisawa and Minamisanriku) and performed metabarcoding using COI and an arthropod-focused 16S marker (gInsect). Reads were processed into amplicon sequence variants and assigned by BLAST top hits against NCBI nt, with high-confidence detections defined at identity [&ge;]98%. Across sites, sap and trap swabs yielded multiple high-confidence insect detections spanning several orders, including sap-associated stag beetles (Dorcus spp.). Overlap with contemporaneous conventional monitoring was limited, suggesting that sap-surface eDNA and conventional surveys capture partly different components of sap-associated insect assemblages. In a targeted 2024 spot survey, actively fermenting sap yielded multiple insect eDNA detections, whereas inactive, non-fermented sap yielded no high-confidence insect detections. Although limited by small sample size and the absence of dedicated process controls, these findings support the feasibility of tree sap as a localized terrestrial eDNA substrate and provide a basis for future replicated studies of sap-associated insect monitoring.

Reef manta rays (Mobula alfredi) are threatened by fishing and other anthropogenic threats. Which, when coupled with conservative life history traits, have made this species vulnerable to extinction. Spatiotemporal ecological knowledge, such as site fidelity and visitation patterns to key aggregation sites, are imperative for effective conservation management of M. alfredi. A novel method of environmental sensing, remote underwater photo systems (RUPs), was employed to understand drivers of M. alfredi habitat use and resighting patterns. RUPs were deployed at four cleaning sites around Laamu Atoll, Maldives. Between March 2021 and May 2023, 455,458 photos were analysed. Generalised linear models revealed increases in M. alfredi presence in response to high chlorophyll-a concentrations, low illumination moon states, the Southwest Monsoon, and in the morning, while human presence had no effect. Branchial spot patterns allowed for 81 M. alfredi individuals to be identified, from 629 sightings, representing 51.59% of Laamu Atolls previously identified population (n = 157). Cleaning stations are visited more intensively during periods of increased productivity of the Southwest Monsoon, likely in response to greater foraging opportunities near the study areas. Additionally, moon state, used as a proxy for tidal strength, was associated with increased visitation during new moon periods, suggesting that weaker tidal states may facilitate presence. These data support integrating RUPs with observational surveys to improve inferences about habitat use and our understanding of cleaning sites frequented by M. alfredi. This study aims to inform the implementation of Laamu Atolls first marine protected area management plan.