MIDORI server: a webserver for taxonomic assignment of unknown metazoan mitochondrial-encoded sequences using a curated database

Assessing the effects of urban effluent pollution on freshwater biodiversity and community networks using eDNA metabarcoding

Aquatic ecosystems provide essential services, yet they face increasing pressures from anthropogenic activities, including land-use change, eutrophication, browning, and contaminant pollution. While the ecological effects of these stressors are documented, the impacts of complex contaminant mixtures, particularly those from wastewater treatment plant (WWTP) effluents, remain poorly understood. Mixtures effects are typically assessed using traditional species-by-species toxicological approaches, which, though the gold standard, are time-intensive, require test animals, and have limited extrapolability. New Approach Methodologies (NAMs), such as environmental DNA (eDNA), offer a non-invasive alternative, enabling broader assessments of taxa responses across trophic levels. Here, we apply an eDNA approach to assess community-wide responses to effluent discharge in the St. Lawrence River, one of North America's most diverse freshwater ecosystems. We sampled water and aquatic communities along the effluent plume of the Montréal WWTP, analyzing taxa-specific responses across trophic levels using high-throughput sequencing. We evaluated the influence of water physico-chemistry and per- and polyfluoroalkyl substances (PFAS) on aquatic beta diversity and network structure. To validate our eDNA results, we compared fish-specific detections with traditional fishing surveys. Our findings highlight how wastewater-derived contaminants influence biodiversity patterns and species interactions, with taxonomic responses varying across trophic levels. Network analyses revealed shifts in ecological stability, with changes in species connectivity and modularity influenced by effluent exposure. This study demonstrates the value of eDNA for characterizing biodiversity responses to anthropogenic stressors and provides insights into the broader implications of point-source pollution for freshwater ecosystem resilience.

Advancing molecular macrobenthos biodiversity monitoring: a comparison between Oxford Nanopore and Illumina based metabarcoding and metagenomics

DNA-based methods and developments of sequencing technologies are integral to macrobenthos biodiversity studies, and their implementation as standardized monitoring methods is approaching. Evaluating the efficacy and reliability of these technological developments is crucial for macrobenthos biodiversity assessments. In this study, we compared three DNA-based techniques for assessing the diversity of bulk macrobenthos samples from the Belgian North Sea. Specifically, we compared amplicon sequencing using Illumina MiSeq and portable real-time sequencing of Oxford Nanopore versus shotgun sequencing using Illumina NovaSeq sequencing. The 313 bp mitochondrial cytochrome c oxidase subunit I (COI) metabarcoding fragment served as the target region for the metabarcoding analysis. Our results indicate that Oxford Nanopore and MiSeq metabarcoding had similar performances in terms of alpha and beta diversity, revealing highly similar location-specific community compositions. The NovaSeq metagenomics method also resulted in similar alpha diversity, but slightly different community compositions compared to the metabarcoding approach. Despite these differences, location-specific community compositions were maintained across all platforms. Notably, read counts from the NovaSeq metagenomic analysis showed the weakest correlation to size corrected morphological abundance and there were mismatches between morphological identification and all DNA based findings which are likely caused by a combination of factors such as primer efficiency and an incomplete reference database. Our findings underscore the critical importance of database completeness prior to implementing DNA-based techniques as standardized monitoring method, especially for metagenomics. Nevertheless, our findings emphasize that Oxford Nanopore metabarcoding proves to be a viable alternative to the conventional Illumina MiSeq metabarcoding platform for macrobenthos biodiversity monitoring.

Using iDNA to determine impacts of Amazonian deforestation on Leishmania hosts, vectors, and their interactions

BACKGROUND

There is debate concerning whether there exists a generalizable effect of land-use change on zoonotic disease risk. Strong data informing this debate are sparse because it is challenging to establish direct links between hosts, vectors, and pathogens. However, molecular methods using invertebrate-derived DNA (iDNA) can now measure species composition and interactions from vector samples at landscape scales, which has the potential to improve mechanistic understanding of the effects of land-use change on zoonotic disease risk.

METHODOLOGY/PRINCIPAL FINDINGS

We used iDNA metabarcoding of sandflies to disentangle the relationships between Leishmania parasites, sandfly vectors, and vertebrate hosts. We paired these samples with iDNA metabarcoding of carrion flies to survey vertebrates independent of sandfly feeding preferences. We collected sandflies and carrion flies at forest sites across a deforestation gradient in the southern Amazon 'Arc of Deforestation', which exemplifies global patterns of deforestation due to agricultural expansion. We used a series of models to test whether sandflies and the vertebrate they feed upon were influenced by deforestation, which we measured using percent forest cover, percent pasture cover, and distance to the major urban center. We found that vectors were encountered less frequently in forests surrounded by pasture. We also found that the probability of a Leishmania host/reservoir being detected in sandfly bloodmeals was quadratically related to local forest cover, with the highest probability found at sites with intermediate levels of deforestation. Hosts were also detected most often with carrion flies at sites with intermediate forest cover, suggesting that increased host availability rather than feeding preferences was responsible for this result. Domestic dogs and the nine-banded armadillo, Dasypus novemcinctus, were the most prevalent hosts found in the sandfly iDNA data.

CONCLUSIONS/SIGNIFICANCE

Our results did not support the generality of the 'dilution effect' hypothesis. However, important vectors and hosts showed consistent responses to deforestation and our findings suggest that interactions between domestic dogs and sylvatic hosts are a pathway for zoonotic disease transmission in human impacted tropical forests.

Bridging the gaps through environmental DNA: A review of critical considerations for interpreting the biodiversity data in coral reef ecosystems

Coral reefs, the rainforests of the sea, are vital hotspots for marine biodiversity. However, the persistent challenge of climate change directly threatens the delicate balance of coral reef ecosystems, impacting myriad species and critical ecosystem services. Therefore, this comprehensive review critically discusses the associated challenges in assessing and preserving coral reef diversity, emphasizing the need for novel biomonitoring techniques due to the elusive and cryptic nature of many reef organisms. The review focuses on environmental DNA (eDNA) analysis as a non-invasive tool for coral species monitoring at various ecological levels. The review highlights that using eDNA in coral reef monitoring requires careful consideration of multiple factors, such as strategic assay development, optimization, and marker selection, substrate selection, and sample volume, which are critical for maximizing the probability of species detection. Moreover, integrating environmental RNA (eRNA) provides additional insights into temporal aspects advancing the coral reef biodiversity research and conservation efforts.

Most soil and litter arthropods are unidentifiable based on current DNA barcode reference libraries

We are far from knowing all species living on the planet. Understanding biodiversity is demanding and requires time and expertise. Most groups are understudied given problems of identifying and delimiting species. DNA barcoding emerged to overcome some of the difficulties in identifying species. Its limitations derive from incomplete taxonomic knowledge and the lack of comprehensive DNA barcode libraries for so many taxonomic groups. Here, we evaluate how useful barcoding is for identifying arthropods from highly diverse leaf litter communities in the southern Appalachian Mountains (USA). We used 3 reference databases and several automated classification methods on a data set including several arthropod groups. Acari, Araneae, Collembola, Coleoptera, Diptera, and Hymenoptera were well represented, showing different performances across methods and databases. Spiders performed the best, with correct identification rates to species and genus levels of ~50% across databases. Springtails performed poorly, no barcodes were identified to species or genus. Other groups showed poor to mediocre performance, from around 3% (mites) to 20% (beetles) correctly identified barcodes to species, but also with some false identifications. In general, BOLD-based identification offered the best identification results but, in all cases except spiders, performance is poor, with less than a fifth of specimens correctly identified to genus or species. Our results indicate that the soil arthropod fauna is still insufficiently documented, with many species unrepresented in DNA barcode libraries. More effort toward integrative taxonomic characterization is needed to complete our reference libraries before we can rely on DNA barcoding as a universally applicable identification method.

Implementing high-throughput insect barcoding in microbiome studies: impact of non-destructive DNA extraction on microbiome reconstruction

Background

Symbiotic relationships with diverse microorganisms are crucial for many aspects of insect biology. However, while our understanding of insect taxonomic diversity and the distribution of insect species in natural communities is limited, we know much less about their microbiota. In the era of rapid biodiversity declines, as researchers increasingly turn towards DNA-based monitoring, developing and broadly implementing approaches for high-throughput and cost-effective characterization of both insect and insect-associated microbial diversity is essential. We need to verify whether approaches such as high-throughput barcoding, a powerful tool for identifying wild insects, would permit subsequent microbiota reconstruction in these specimens.

Methods

High-throughput barcoding ("megabarcoding") methods often rely on non-destructive approaches for obtaining template DNA for PCR amplification by leaching DNA out of insect specimens using alkaline buffers such as HotSHOT. This study investigated the impact of HotSHOT on microbial abundance estimates and the reconstructed bacterial community profiles. We addressed this question by comparing quantitative 16S rRNA amplicon sequencing data for HotSHOT-treated or untreated specimens of 16 insect species representing six orders and selected based on the expectation of limited variation among individuals.

Results

We find that in 13 species, the treatment significantly reduced microbial abundance estimates, corresponding to an estimated 15-fold decrease in amplifiable 16S rRNA template on average. On the other hand, HotSHOT pre-treatment had a limited effect on microbial community composition. The reconstructed presence of abundant bacteria with known significant effects was not affected. On the other hand, we observed changes in the presence of low-abundance microbes, those close to the reliable detection threshold. Alpha and beta diversity analyses showed compositional differences in only a few species.

Conclusion

Our results indicate that HotSHOT pre-treated specimens remain suitable for microbial community composition reconstruction, even if abundance may be hard to estimate. These results indicate that we can cost-effectively combine barcoding with the study of microbiota across wild insect communities. Thus, the voucher specimens obtained using megabarcoding studies targeted at characterizing insect communities can be used for microbiome characterizations. This can substantially aid in speeding up the accumulation of knowledge on the microbiomes of abundant and hyperdiverse insect species.

Limited variation in microbial communities across populations of Macrosteles leafhoppers (Hemiptera: Cicadellidae)

Microbial symbionts play crucial roles in insect biology, yet their diversity, distribution, and temporal dynamics across host populations remain poorly understood. In this study, we investigated the spatio-temporal distribution of bacterial symbionts within the widely distributed and economically significant leafhopper genus Macrosteles, with a focus on Macrosteles laevis. Using host and symbiont marker gene amplicon sequencing, we explored the intricate relationships between these insects and their microbial partners. Our analysis of the cytochrome oxidase subunit I (COI) gene data revealed several intriguing findings. First, there was no strong genetic differentiation across M. laevis populations, suggesting gene flow among them. Second, we observed significant levels of heteroplasmy, indicating the presence of multiple mitochondrial haplotypes within individuals. Third, parasitoid infections were prevalent, highlighting the complex ecological interactions involving leafhoppers. The 16S rRNA data confirmed the universal presence of ancient nutritional endosymbionts-Sulcia and Nasuia-in M. laevis. Additionally, we found a high prevalence of Arsenophonus, another common symbiont. Interestingly, unlike most previously studied species, M. laevis exhibited only occasional cases of infection with known facultative endosymbionts and other bacteria. Notably, there was no significant variation in symbiont prevalence across different populations or among sampling years within the same population. Comparatively, facultative endosymbionts such as Rickettsia, Wolbachia, Cardinium and Lariskella were more common in other Macrosteles species. These findings underscore the importance of considering both host and symbiont dynamics when studying microbial associations. By simultaneously characterizing host and symbiont marker gene amplicons in large insect collections, we gain valuable insights into the intricate interplay between insects and their microbial partners. Understanding these dynamics contributes to our broader comprehension of host-microbe interactions in natural ecosystems.

Taxonomic position of holothurian Eupentactafraudatrix (Echinodermata, Holothuroidea)

Samples of the holothurian Eupentactafraudatrix (Djakonov & Baranova in Djakonov, Baranova & Saveljeva, 1958) from the Sea of Japan were studied and the relationships of the genera Eupentacta and Sclerodactyla, as well as related taxa, were evaluated on the basis of phylogenetic analysis of the mitochondrial DNA COI and 16S rRNA genes. Using three methods, phylogenetic trees were constructed, and the degree of reliability of topological reconstructions was estimated by means of a nonparametric bootstrap test for the neighbor joining (NJ) and maximum likelihood (ML) techniques, as well as by a posteriori probability for Bayesian inference (BI) analysis. Genetic data confirm the validity of the assignment of Cucumariafraudatrix to the genus Eupentacta Deichmann, 1938. The study of sequences obtained from the holothurian specimens collected in Russian waters, near the city of Vladivostok, and determined by morphological characters clearly indicate that these specimens belong to the genus Eupentacta and are assigned as E.fraudatrix . The specimens from China in GenBank named as Sclerodactylamultipes and used in the present study, were likely misidentified, and after re-examination they may be assigned to the genus Eupentacta, either as E.fraudatrix or another taxon. Analyses of morphological characters of S.multipes unequivocally affirm that this species must be excluded from Sclerodactyla Ayres, 1851 and is provisionally assigned to the genus Sclerothyone Thandar, 1989 based on the external morphological characters and the body wall ossicles.

taxalogue: a toolkit to create comprehensive CO1 reference databases

Background

Taxonomic identification through DNA barcodes gained considerable traction through the invention of next-generation sequencing and DNA metabarcoding. Metabarcoding allows for the simultaneous identification of thousands of organisms from bulk samples with high taxonomic resolution. However, reliable identifications can only be achieved with comprehensive and curated reference databases. Therefore, custom reference databases are often created to meet the needs of specific research questions. Due to taxonomic inconsistencies, formatting issues, and technical difficulties, building a custom reference database requires tremendous effort. Here, we present taxalogue, an easy-to-use software for creating comprehensive and customized reference databases that provide clean and taxonomically harmonized records. In combination with extensive geographical filtering options, taxalogue opens up new possibilities for generating and testing evolutionary hypotheses.

Methods

taxalogue collects DNA sequences from several online sources and combines them into a reference database. Taxonomic incongruencies between the different data sources can be harmonized according to available taxonomies. Dereplication and various filtering options are available regarding sequence quality or metadata information. taxalogue is implemented in the open-source Ruby programming language, and the source code is available at https://github.com/nwnoll/taxalogue. We benchmark four reference databases by sequence identity against eight queries from different localities and trapping devices. Subsamples from each reference database were used to compare how well another one is covered.

Results

taxalogue produces reference databases with the best coverage at high identities for most tested queries, enabling more accurate, reliable predictions with higher certainty than the other benchmarked reference databases. Additionally, the performance of taxalogue is more consistent while providing good coverage for a variety of habitats, regions, and sampling methods. taxalogue simplifies the creation of reference databases and makes the process reproducible and transparent. Multiple available output formats for commonly used downstream applications facilitate the easy adoption of taxalogue in many different software pipelines. The resulting reference databases improve the taxonomic classification accuracy through high coverage of the query sequences at high identities.

Seq' and ARMS shall find: DNA (meta)barcoding of Autonomous Reef Monitoring Structures across the tree of life uncovers hidden cryptobiome of tropical urban coral reefs

Coral reefs are among the richest marine ecosystems on Earth, but there remains much diversity hidden within cavities of complex reef structures awaiting discovery. While the abundance of corals and other macroinvertebrates are known to influence the diversity of other reef-associated organisms, much remains unknown on the drivers of cryptobenthic diversity. A combination of standardized sampling with 12 units of the Autonomous Reef Monitoring Structure (ARMS) and high-throughput sequencing was utilized to uncover reef cryptobiome diversity across the equatorial reefs in Singapore. DNA barcoding and metabarcoding of mitochondrial cytochrome c oxidase subunit I, nuclear 18S and bacterial 16S rRNA genes revealed the taxonomic composition of the reef cryptobiome, comprising 15,356 microbial ASVs from over 50 bacterial phyla, and 971 MOTUs across 15 metazoan and 19 non-metazoan eukaryote phyla. Environmental factors across different sites were tested for relationships with ARMS diversity. Differences among reefs in diversity patterns of metazoans and other eukaryotes, but not microbial communities, were associated with biotic (coral cover) and abiotic (distance, temperature and sediment) environmental variables. In particular, ARMS deployed at reefs with higher coral cover had greater metazoan diversity and encrusting plate cover, with larger-sized non-coral invertebrates influencing spatial patterns among sites. Our study showed that DNA barcoding and metabarcoding of ARMS constitute a valuable tool for quantifying cryptobenthic diversity patterns and can provide critical information for the effective management of coral reef ecosystems.

Till evolution do us part: The diversity of symbiotic associations across populations of Philaenus spittlebugs

Symbiotic bacteria have played crucial roles in the evolution of sap-feeding insects and can strongly affect host function. However, their diversity and distribution within species are not well understood; we do not know to what extent environmental factors or associations with other species may affect microbial community profiles. We addressed this question in Philaenus spittlebugs by surveying both insect and bacterial marker gene amplicons across multiple host populations. Host mitochondrial sequence data confirmed morphology-based identification of six species and revealed two divergent clades of Philaenus spumarius. All of them hosted the primary symbiont Sulcia that was almost always accompanied by Sodalis. Interestingly, populations and individuals often differed in the presence of Sodalis sequence variants, suggestive of intra-genome 16S rRNA variant polymorphism combined with rapid genome evolution and/or recent additional infections or replacements of the co-primary symbiont. The prevalence of facultative endosymbionts, including Wolbachia, Rickettsia, and Spiroplasma, varied among populations. Notably, cytochrome I oxidase (COI) amplicon data also showed that nearly a quarter of P. spumarius were infected by parasitoid flies (Verralia aucta). One of the Wolbachia operational taxonomic units (OTUs) was exclusively present in Verralia-parasitized specimens, suggestive of parasitoids as their source and highlighting the utility of host gene amplicon sequencing in microbiome studies.

Plumbing the depths with environmental DNA (eDNA): Metabarcoding reveals biodiversity zonation at 45-60 m on mesophotic coral reefs

Mesophotic coral ecosystems (MCEs) are tropical reefs found at depths of ~30-150 m, below the region most heavily impacted by heat stress and other disturbances. Hence, MCEs may serve as potential refugia for threatened shallow reefs, but they also harbour depth-endemic fauna distinct from shallow reefs. Previous studies have characterized biodiversity patterns along depth gradients, but focussed primarily on conspicuous taxa (fishes, corals, etc.). Environmental DNA (eDNA) metabarcoding offers a more holistic approach to assess biodiversity patterns across the tree of life. Here, we use three metabarcoding assays targeting fishes (16S rRNA), eukaryotes (18S rDNA) and metazoans (COI) to assess biodiversity change from the surface to ~90 m depth across 15-m intervals at three sites within the Hawaiian Archipelago. We observed significant community differences between most depth zones, with distinct zonation centred at 45-60 m for eukaryotes and metazoans, but not for fishes. This finding may be attributable to the higher mobility of reef fishes, although methodological limitations are likely a contributing factor. The possibility for MCEs to serve as refugia is not excluded for fishes, but invertebrate communities >45 m are distinct, indicating limited connectivity for the majority of reef fauna. This study provides a new approach for surveying biodiversity on MCEs, revealing patterns in a much broader context than the limited-taxon studies that comprise the bulk of our present knowledge.

crabs-A software program to generate curated reference databases for metabarcoding sequencing data

The measurement of biodiversity is an integral aspect of life science research. With the establishment of second- and third-generation sequencing technologies, an increasing amount of metabarcoding data is being generated as we seek to describe the extent and patterns of biodiversity in multiple contexts. The reliability and accuracy of taxonomically assigning metabarcoding sequencing data have been shown to be critically influenced by the quality and completeness of reference databases. Custom, curated, eukaryotic reference databases, however, are scarce, as are the software programs for generating them. Here, we present crabs (Creating Reference databases for Amplicon-Based Sequencing), a software package to create custom reference databases for metabarcoding studies. crabs includes tools to download sequences from multiple online repositories (i.e., NCBI, BOLD, EMBL, MitoFish), retrieve amplicon regions through in silico PCR analysis and pairwise global alignments, curate the database through multiple filtering parameters (e.g., dereplication, sequence length, sequence quality, unresolved taxonomy, inclusion/exclusion filter), export the reference database in multiple formats for immediate use in taxonomy assignment software, and investigate the reference database through implemented visualizations for diversity, primer efficiency, reference sequence length, database completeness and taxonomic resolution. crabs is a versatile tool for generating curated reference databases of user-specified genetic markers to aid taxonomy assignment from metabarcoding sequencing data. crabs can be installed via docker and is available for download as a conda package and via GitHub (https://github.com/gjeunen/reference_database_creator).

Exploring microbial functional biodiversity at the protein family level-From metagenomic sequence reads to annotated protein clusters

Metagenomics has enabled accessing the genetic repertoire of natural microbial communities. Metagenome shotgun sequencing has become the method of choice for studying and classifying microorganisms from various environments. To this end, several methods have been developed to process and analyze the sequence data from raw reads to end-products such as predicted protein sequences or families. In this article, we provide a thorough review to simplify such processes and discuss the alternative methodologies that can be followed in order to explore biodiversity at the protein family level. We provide details for analysis tools and we comment on their scalability as well as their advantages and disadvantages. Finally, we report the available data repositories and recommend various approaches for protein family annotation related to phylogenetic distribution, structure prediction and metadata enrichment.

Rubble fields shape planktonic protist communities in Indonesia at a local scale

The Coral Triangle encompasses nearly 30% of the world's coral reefs and is widely considered the epicenter of marine biodiversity. Destructive fishing practices and natural disturbances common to this region damage reefs leaving behind fields of coral rubble. While the impacts of disturbances in these ecosystems are well documented on metazoans, we have a poor understanding of their impact on microbial communities at the base of the food web. We use metabarcoding to characterize protist community composition in sites of varying fisheries management schemes and benthic profiles across the island of Lombok, Indonesia. Our study shows that rubble coverage and net primary productivity are the strongest explainers of variation in protist communities across Lombok. More specifically, rubble fields are characterized by increases in small heterotrophic protists, including ciliates and cercozoans. In addition to shifts in heterotrophic protist communities, we also observed increases in diatom relative abundance in rubble fields, which corresponded to sites with higher net primary productivity. These results are the first to characterize protist communities in tropical marine rubble fields and provide insight on environmental factors potentially driving these shifts on a local scale.

Development of transcriptomics-based growth rate indices in two model eukaryotes and relevance to metatranscriptomic datasets

Growth rate estimation is important to understand the flow of energy and nutrient elements in an ecosystem, but it has remained challenging, especially on microscopic organisms. In this study, we propose four growth rate indices that use mRNA abundance ratios between nuclear and mitochondrial genes: (1) total nuclear and mitochondrial mRNA ratio (Nuc:Mito‐TmRNA); (2) nuclear and mitochondrial ribosomal protein mRNA ratio (Nuc:Mito‐RPmRNA); (3) gene ontology (GO) terms and total mitochondrial mRNA ratios; and (4) nuclear and mitochondrial specific gene mRNA ratio. We examine these proposed ratios using RNA‐Seq datasets of Daphnia magna, and Saccharomyces cerevisiae retrieved from the NCBI Short Read Archive. The results showed that both Nuc:Mito‐TmRNA and Nuc:Mito‐RPmRNA ratio indices showed significant correlations with the growth rate for both species. A large number of GO terms mRNA ratios showed significant correlations with the growth rate of S. cerevisiae. Lastly, we identified mRNA ratios of several specific nuclear and mitochondrial gene pairs that showed significant correlations. We foresee future implications for the proposed mRNA ratios used in metatranscriptome analyses to estimate the growth rate of communities and species.

PREGO: A Literature and Data-Mining Resource to Associate Microorganisms, Biological Processes, and Environment Types

To elucidate ecosystem functioning, it is fundamental to recognize what processes occur in which environments (where) and which microorganisms carry them out (who). Here, we present PREGO, a one-stop-shop knowledge base providing such associations. PREGO combines text mining and data integration techniques to mine such what-where-who associations from data and metadata scattered in the scientific literature and in public omics repositories. Microorganisms, biological processes, and environment types are identified and mapped to ontology terms from established community resources. Analyses of comentions in text and co-occurrences in metagenomics data/metadata are performed to extract associations and a level of confidence is assigned to each of them thanks to a scoring scheme. The PREGO knowledge base contains associations for 364,508 microbial taxa, 1090 environmental types, 15,091 biological processes, and 7971 molecular functions with a total of almost 58 million associations. These associations are available through a web portal, an Application Programming Interface (API), and bulk download. By exploring environments and/or processes associated with each other or with microbes, PREGO aims to assist researchers in design and interpretation of experiments and their results. To demonstrate PREGO’s capabilities, a thorough presentation of its web interface is given along with a meta-analysis of experimental results from a lagoon-sediment study of sulfur-cycle related microbes.

RESCRIPt: Reproducible sequence taxonomy reference database management

Nucleotide sequence and taxonomy reference databases are critical resources for widespread applications including marker-gene and metagenome sequencing for microbiome analysis, diet metabarcoding, and environmental DNA (eDNA) surveys. Reproducibly generating, managing, using, and evaluating nucleotide sequence and taxonomy reference databases creates a significant bottleneck for researchers aiming to generate custom sequence databases. Furthermore, database composition drastically influences results, and lack of standardization limits cross-study comparisons. To address these challenges, we developed RESCRIPt, a Python 3 software package and QIIME 2 plugin for reproducible generation and management of reference sequence taxonomy databases, including dedicated functions that streamline creating databases from popular sources, and functions for evaluating, comparing, and interactively exploring qualitative and quantitative characteristics across reference databases. To highlight the breadth and capabilities of RESCRIPt, we provide several examples for working with popular databases for microbiome profiling (SILVA, Greengenes, NCBI-RefSeq, GTDB), eDNA and diet metabarcoding surveys (BOLD, GenBank), as well as for genome comparison. We show that bigger is not always better, and reference databases with standardized taxonomies and those that focus on type strains have quantitative advantages, though may not be appropriate for all use cases. Most databases appear to benefit from some curation (quality filtering), though sequence clustering appears detrimental to database quality. Finally, we demonstrate the breadth and extensibility of RESCRIPt for reproducible workflows with a comparison of global hepatitis genomes. RESCRIPt provides tools to democratize the process of reference database acquisition and management, enabling researchers to reproducibly and transparently create reference materials for diverse research applications. RESCRIPt is released under a permissive BSD-3 license at https://github.com/bokulich-lab/RESCRIPt.

Generating and managing sequence and taxonomy reference data presents a bottleneck to many researchers, whether they are generating custom databases or attempting to format existing, curated reference databases for use with standard sequence analysis tools. Evaluating database quality and choosing the “best” database can be an equally formidable challenge. We developed RESCRIPt to alleviate this bottleneck, supporting reproducible, streamlined generation, curation, and evaluation of reference sequence databases. RESCRIPt uses QIIME 2 artifact file formats, which store all processing steps as data provenance within each file, allowing researchers to retrace the computational steps used to generate any given file. We used RESCRIPt to benchmark several commonly used marker-gene sequence databases for 16S rRNA genes, ITS, and COI sequences, demonstrating both the utility of RESCRIPt to streamline use of these databases, but also to evaluate several qualitative and quantitative characteristics of each database. We show that larger databases are not always best, and curation steps to reduce redundancy and filter out noisy sequences may be beneficial for some applications. We anticipate that RESCRIPt will streamline the use, management, and evaluation/selection of reference database materials for microbiomics, diet metabarcoding, eDNA, and other diverse applications.

Profiling of RNA Viruses in Biting Midges (Ceratopogonidae) and Related Diptera from Kenya Using Metagenomics and Metabarcoding Analysis

Vector-borne diseases (VBDs) cause enormous health burden worldwide, as they account for more than 17% of all infectious diseases and over 700,000 deaths each year. A significant number of these VBDs are caused by RNA virus pathogens. Here, we used metagenomics and metabarcoding analysis to characterize RNA viruses and their insect hosts among biting midges from Kenya. We identified a total of 15 phylogenetically distinct insect-specific viruses. These viruses fall into six families, with one virus falling in the recently proposed negevirus taxon. The six virus families include Partitiviridae, Iflaviridae, Tombusviridae, Solemoviridae, Totiviridae, and Chuviridae. In addition, we identified many insect species that were possibly associated with the identified viruses. Ceratopogonidae was the most common family of midges identified. Others included Chironomidae and Cecidomyiidae. Our findings reveal a diverse RNA virome among Kenyan midges that includes previously unknown viruses. Further, metabarcoding analysis based on COI (cytochrome c oxidase subunit 1 mitochondrial gene) barcodes reveal a diverse array of midge species among the insects used in the study. Successful application of metagenomics and metabarcoding methods to characterize RNA viruses and their insect hosts in this study highlights a possible simultaneous application of these two methods as cost-effective approaches to virus surveillance and host characterization. IMPORTANCE The majority of the viruses that currently cause diseases in humans and animals are RNA viruses, and more specifically arthropod-transmitted viruses. They cause diseases such as dengue, West Nile infection, bluetongue disease, Schmallenberg disease, and yellow fever, among others. Several sequencing investigations have shown us that a diverse array of RNA viruses among insect vectors remain unknown. Some of these could be ancient lineages that could aid in comprehensive studies on RNA virus evolution. Such studies may provide us with insights into the evolution of the currently pathogenic viruses. Here, we applied metagenomics to field-collected midges and we managed to characterize several RNA viruses, where we recovered complete and nearly complete genomes of these viruses. We also characterized the insect host species that are associated with these viruses. These results add to the currently known diversity of RNA viruses among biting midges as well as their associated insect hosts.

Using metatranscriptomics to estimate the diversity and composition of zooplankton communities

DNA metabarcoding is a rapid, high‐resolution tool used for biomonitoring complex zooplankton communities. However, diversity estimates derived with this approach can be biased by the co‐detection of sequences from environmental DNA (eDNA), nuclear‐encoded mitochondrial (NUMT) pseudogene contamination, and taxon‐specific PCR primer affinity differences. To avoid these methodological uncertainties, we tested the use of metatranscriptomics as an alternative approach for characterizing zooplankton communities. Specifically, we compared metatranscriptomics with PCR‐based methods using genomic (gDNA) and complementary DNA (cDNA) amplicons, and morphology‐based data for estimating species diversity and composition for both mock communities and field‐collected samples. Mock community analyses showed that the use of gDNA mitochondrial cytochrome c oxidase I (mtCO1) amplicons inflates species richness due to the co‐detection of extra‐organismal eDNA. Significantly more amplicon sequence variants, nucleotide diversity, and indels were observed with gDNA amplicons than with cDNA, indicating the presence of putative NUMT pseudogenes. Moreover, PCR‐based methods failed to detect the most abundant species in mock communities due to priming site mismatch. Overall, metatranscriptomics provided estimates of species richness and composition that closely resembled those derived from morphological data. The use of metatranscriptomics was further tested using field‐collected samples, with the results showing consistent species diversity estimates among biological and technical replicates. Additionally, temporal zooplankton species composition changes could be monitored using different mitochondrial markers. These findings demonstrate the advantages of metatranscriptomics as an effective tool for monitoring diversity in zooplankton research.

Evaluating the Efficiency of DNA Metabarcoding to Analyze the Diet of Hippocampus guttulatus (Teleostea: Syngnathidae)

Seahorses are considered a flagship species for conservation efforts and due to their conservation status, improving knowledge on their dietary composition while applying a non-invasive approach, could be useful. Using Hippocampus guttulatus as a case study, the present study represents pioneering research into investigating the diet of seahorses by NGS-based DNA metabarcoding of fecal samples. The study developed and tested the protocol for fecal DNA metabarcoding during the feeding trials where captive seahorses were fed on a diet of known composition; the process was subsequently applied on fecal samples collected from wild individuals. The analysis of samples collected during the feeding trials indicated the reliability of the applied molecular approach by allowing the characterization of the effectively ingested prey. In the field study, among detected prey species, results revealed that the majority of the seahorse samples contained taxa such as Amphipoda, Decapoda, Isopoda, and Calanoida, while less common prey taxa were Gastropoda and Polyplacophora. As only a small amount of starting fecal material is needed and the sampling procedure is neither invasive nor lethal. The present study indicates DNA metabarcoding as useful for investigating seahorse diet and could help define management and conservation actions.

Just keep it simple? Benchmarking the accuracy of taxonomy assignment software in metabarcoding studies

How do you put a name on an unknown piece of DNA? From microbes to mammals, high-throughput metabarcoding studies provide a more objective view of natural communities, overcoming many of the inherent limitations of traditional field surveys and microscopy-based observations (Deiner et al., 2017). Taxonomy assignment is one of the most critical aspects of any metabarcoding study, yet this important bioinformatics task is routinely overlooked. Biodiversity surveys and conservation efforts often depend on formal species inventories: the presence (or absence) of species, and the number of individuals reported across space and time. However, computational workflows applied in eukaryotic metabarcoding studies were originally developed for use with bacterial/archaeal data sets, where microbial researchers rely on one conserved locus (nuclear 16S rRNA) and have access to vast databases with good coverage across most prokaryotic lineages - a situation not mirrored in most multicellular taxa. In this issue of Molecular Ecology Resources, Hleap et al. (2021) carry out an extensive benchmarking exercise focused on taxonomy assignment strategies for eukaryotic metabarcoding studies utilizing the mitochondrial Cytochrome C oxidase I marker gene (COI). They assess the performance and accuracy of software tools representing diverse methodological approaches: from "simple" strategies based on sequence similarity and composition, to model-based phylogenetic and probabilistic classification tools. Contrary to popular assumptions, less complex approaches (BLAST and the QIIME2 feature classifier) consistently outperformed more sophisticated mathematical algorithms and were highly accurate for assigning taxonomy at higher levels (e.g. family). Lower-level assignments at the genus and species level still pose significant challenge for most existing algorithms, and sparse eukaryotic reference databases further limit software performance. This study illuminates current best practices for metabarcoding taxonomy assignments, and underscores the need for community-driven efforts to expand taxonomic and geographic representation in reference DNA barcode databases.

The largest moss carpet transplant in Antarctica and its bryosphere cryptic biodiversity

As part of the reconstruction of the Brazilian Antarctic Station on King George Island, three areas of moss carpet were transplanted to minimize the impact of the new facilities on the local biodiversity. A total of 650 m² of moss carpet was transplanted to neighboring but previously uncolonized locations and has subsequently survived for the last 3 years. Antarctic moss carpets typically comprise low moss species diversity and are often monospecific. We investigated the cryptic biodiversity that was transplanted along with the carpets using a metabarcoding approach through high throughput sequencing. We targeted 16S rRNA for Bacteria and Archaea, ITS for Fungi and Viridiplantae and Cox1 for Metazoa. We detected DNA representing 263 taxa from five Kingdoms (Chromista, Fungi, Metazoa, Protista and Viridiplantae), two Domains (Archaea and Bacteria) and 33 Phyla associated with the carpet. This diversity included one Archaea, 189 Bacteria, 24 Chromista, 19 Fungi, eight Metazoa, seven Protista and 16 Viridiplantae. Bacteria was the most abundant, rich and diverse group, with Chromista second in diversity and richness. Metazoa was less diverse but second highest in dominance. This is the first study to attempt transplanting a significant area of moss carpet to minimize anthropogenic environmental damage in Antarctica and to use metabarcoding as a proxy to assess diversity associated with Antarctic moss carpets, further highlighting the importance of such habitats for other organisms and their importance for conservation.

Some Examples of the Use of Molecular Markers for Needs of Basic Biology and Modern Society

Application of molecular genetic markers appeared to be very fruitful in achieving many goals, including (i) proving the theoretic basements of general biology and (ii) assessment of worldwide biodiversity. Both are provided in the present meta-analysis and a review as the main signal. One of the basic current challenges in modern biology in the face of new demands in the 21st century is the validation of its paradigms such as the synthetic theory of evolution (STE) and biological species concept (BSC). Another of most valuable goals is the biodiversity assessment for a variety of social needs including free web-based information resources about any living being, renovation of museum collections, nature conservation that recognized as a global project, iBOL, as well as resolving global trading problems such as false labeling of species specimens used as food, drug components, entertainment, etc. The main issues of the review are focused on animals and combine four items. (1) A combination of nDNA and mtDNA markers best suits the identification of hybrids and estimation of genetic introgression. (2) The available facts on nDNA and mtDNA diversity seemingly make introgression among many taxa obvious, although it is evident, that introgression may be quite restricted or asymmetric, thus, leaving at least the "source" taxon (taxa) intact. (3) If we consider sexually reproducing species in marine and terrestrial realms introgressed, as it is still evident in many cases, then we should recognize that the BSC, in view of the complete lack of gene flow among species, is inadequate because many zoological species are not biological ones yet. However, vast modern molecular data have proven that sooner or later they definitely become biological species. (4) An investigation into the fish taxa divergence using the BOLD database shows that most gene trees are basically monophyletic and interspecies reticulations are quite rare.

Assessment of current taxonomic assignment strategies for metabarcoding eukaryotes

The effective use of metabarcoding in biodiversity science has brought important analytical challenges due to the need to generate accurate taxonomic assignments. The assignment of sequences to genus or species level is critical for biodiversity surveys and biomonitoring, but it is particularly challenging as researchers must select the approach that best recovers information on species composition. This study evaluates the performance and accuracy of seven methods in recovering the species composition of mock communities by using COI barcode fragments. The mock communities varied in species number and specimen abundance, while upstream molecular and bioinformatic variables were held constant, and using a set of COI fragments. We evaluated the impact of parameter optimization on the quality of the predictions. Our results indicate that BLAST top hit competes well with more complex approaches if optimized for the mock community under study. For example, the two machine learning methods that were benchmarked proved more sensitive to reference database heterogeneity and completeness than methods based on sequence similarity. The accuracy of assignments was impacted by both species and specimen counts (query compositional heterogeneity) which ultimately influence the selection of appropriate software. We urge researchers to: (i) use realistic mock communities to allow optimization of parameters, regardless of the taxonomic assignment method employed; (ii) carefully choose and curate the reference databases including completeness; and (iii) use QIIME, BLAST or LCA methods, in conjunction with parameter tuning to better assign taxonomy to diverse communities, especially when information on species diversity is lacking for the area under study.

Deep-sea predator niche segregation revealed by combined cetacean biologging and eDNA analysis of cephalopod prey

Fundamental insight on predator-prey dynamics in the deep sea is hampered by a lack of combined data on hunting behavior and prey spectra. Deep-sea niche segregation may evolve when predators target specific prey communities, but this hypothesis remains untested. We combined environmental DNA (eDNA) metabarcoding with biologging to assess cephalopod community composition in the deep-sea foraging habitat of two top predator cetaceans. Risso's dolphin and Cuvier's beaked whale selectively targeted distinct epi/meso- and bathypelagic foraging zones, holding eDNA of 39 cephalopod taxa, including 22 known prey. Contrary to expectation, extensive taxonomic overlap in prey spectra between foraging zones indicated that predator niche segregation was not driven by prey community composition alone. Instead, intraspecific prey spectrum differences may drive differentiation for hunting fewer, more calorific, mature cephalopods in deeper waters. The novel combination of methods presented here holds great promise to disclose elusive deep-sea predator-prey systems, aiding in their protection.

Beyond the visual: using metabarcoding to characterize the hidden reef cryptobiome

In an era of coral reef degradation, our knowledge of ecological patterns in reefs is biased towards large conspicuous organisms. The majority of biodiversity, however, inhabits small cryptic spaces within the framework of the reef. To assess this biodiverse community, which we term the ‘reef cryptobiome’, we deployed 87 autonomous reef monitoring structures (ARMS), on 22 reefs across 16 degrees latitude of the Red Sea. Combining ARMS with metabarcoding of the mitochondrial cytochrome oxidase I gene, we reveal a rich community, including the identification of 14 metazoan phyla within 10 416 operational taxonomic units (OTUs). While mobile and sessile subsets were similarly structured along the basin, the main environmental driver was different (particulate organic matter and sea surface temperature, respectively). Distribution patterns of OTUs showed that only 1.5% were present in all reefs, while over half were present in a single reef. On both local and regional scales, the majority of OTUs were rare. The high heterogeneity in community patterns of the reef cryptobiome has implications for reef conservation. Understanding the biodiversity patterns of this critical component of reef functioning will enable a sound knowledge of how coral reefs will respond to future anthropogenic impacts.

A DNA barcode reference library of French Polynesian shore fishes

The emergence of DNA barcoding and metabarcoding opened new ways to study biological diversity, however, the completion of DNA barcode libraries is fundamental for such approaches to succeed. This dataset is a DNA barcode reference library (fragment of Cytochrome Oxydase I gene) for 2,190 specimens representing at least 540 species of shore fishes collected over 10 years at 154 sites across the four volcanic archipelagos of French Polynesia; the Austral, Gambier, Marquesas and Society Islands, a 5,000,000 km2 area. At present, 65% of the known shore fish species of these archipelagoes possess a DNA barcode associated with preserved, photographed, tissue sampled and cataloged specimens, and extensive collection locality data. This dataset represents one of the most comprehensive DNA barcoding efforts for a vertebrate fauna to date. Considering the challenges associated with the conservation of coral reef fishes and the difficulties of accurately identifying species using morphological characters, this publicly available library is expected to be helpful for both authorities and academics in various fields.

Over 2.5 million COI sequences in GenBank and growing

The increasing popularity of cytochrome c oxidase subunit 1 (COI) DNA metabarcoding warrants a careful look at the underlying reference databases used to make high-throughput taxonomic assignments. The objectives of this study are to document trends and assess the future usability of COI records for metabarcode identification. The number of COI records deposited to the NCBI nucleotide database has increased by a geometric average of 51% per year, from 8,137 records deposited in 2003 to a cumulative total of ~ 2.5 million by the end of 2017. About half of these records are fully identified to the species rank, 92% are at least 500 bp in length, 74% have a country annotation, and 51% have latitude-longitude annotations. To ensure the future usability of COI records in GenBank we suggest: 1) Improving the geographic representation of COI records, 2) Improving the cross-referencing of COI records in the Barcode of Life Data System and GenBank to facilitate consolidation and incorporation into existing bioinformatic pipelines, 3) Adherence to the minimum information about a marker gene sequence guidelines, and 4) Integrating metabarcodes from eDNA and mixed community studies with existing reference sequences. The growth of COI reference records over the past 15 years has been substantial and is likely to be a resource across many fields for years to come.