Benchmarking bioinformatic tools for fast and accurate eDNA metabarcoding species identification

Streamlining large-scale oceanic biomonitoring using passive eDNA samplers integrated into vessel's continuous pump underway seawater systems

Passive samplers are enabling the scaling of environmental DNA (eDNA) biomonitoring in our oceans, by circumventing the time-consuming process of water filtration. Designing a novel passive sampler that does not require extensive sample handling time and can be connected to ocean-going vessels without impeding normal underway activities has potential to rapidly upscale global biomonitoring efforts onboard the world's oceanic fleet. Here, we demonstrate the utility of an artificial sponge sampler connected to the continuous pump underway seawater system as a means to enable oceanic biomonitoring. We compared the performance of this passive sampling protocol with standard water filtration at six locations during a research voyage from New Zealand to Antarctica in early 2023. Eukaryote metabarcoding of the mitochondrial COI gene revealed no significant difference in phylogenetic α-diversity between sampling methods and both methods delineated a progressive reduction in number of Zero-Radius Operational Taxonomic Units (ZOTUs) with increased latitudes. While both sampling methods revealed comparable trends in geographical community compositions, distinct clusters were identified for passive samplers and water filtration at each location. Additionally, greater variability between replicates was observed for passive samplers, resulting in an increased estimated level of replication needed to recover 90 % of the biodiversity. Furthermore, traditional water filtration failed to detect three phyla observed by passive samplers and extrapolation analysis estimated passive samplers recover a larger number of ZOTUs compared to water filtration for all six locations. Our results demonstrate the potential of this passive eDNA sampler protocol and highlight areas where this emerging technology could be improved, thereby enabling large-scale offshore marine eDNA biomonitoring by leveraging the world's oceanic fleet without interfering with onboard activities.

New insights into biologic interpretation of bioinformatic pipelines for fish eDNA metabarcoding: A case study in Pearl River estuary

Environmental DNA (eDNA) metabarcoding is an emerging tool for monitoring biological communities in aquatic ecosystems. The selection of bioinformatic pipelines significantly impacts the results of biodiversity assessments. However, there is currently no consensus on the appropriate bioinformatic pipelines for fish community analysis in eDNA metabarcoding. In this study, we compared three bioinformatic pipelines (Uparse, DADA2, and UNOISE3) using real and mock (constructed with 15/30 known fish) communities to investigate the differences in biological interpretation during the data analysis process in eDNA metabarcoding. Performance evaluation and diversity analyses revealed that the choice of bioinformatic pipeline could impact the biological results of metabarcoding experiments. Among the three pipelines, the operational taxonomic units (OTU)-based pipeline (Uparse) showed the best performance (sensitivity: 0.6250 ± 0.0166; compositional similarity: 0.4000 ± 0.0571), the highest richness (25-102) and minimal inter-group differences in alpha diversity. It suggested the OTU-based pipeline possessed superior capability in fish diversity monitoring compared to ASV/ZOTU-based pipeline. Additionally, the Bray-Curtis distance matrix achieved the highest discriminative effect in the PCoA (43.3%-53.89%) and inter-group analysis (P < 0.01), indicating it was better at distinguishing compositional differences or specific genera of fish community at different sampling sites than other distance matrices. These findings provide new insights into fish community monitoring through eDNA metabarcoding in estuarine environments.

Transforming gastrointestinal helminth parasite identification in vertebrate hosts with metabarcoding: a systematic review

BACKGROUND

Gastrointestinal helminths are a very widespread group of intestinal parasites that can cause major health issues in their hosts, including severe illness or death. Traditional methods of helminth parasite identification using microscopy are time-consuming and poor in terms of taxonomic resolution, and require skilled observers. DNA metabarcoding has emerged as a powerful alternative for assessing community composition in a variety of sample types over the last few decades. While metabarcoding approaches have been reviewed for use in other research areas, the use of metabarcoding for parasites has only recently become widespread. As such, there is a need to synthesize parasite metabarcoding methodology and highlight the considerations to be taken into account when developing a protocol.

METHODS

We reviewed published literature that utilized DNA metabarcoding to identify gastrointestinal helminth parasites in vertebrate hosts. We extracted information from 62 peer-reviewed papers published between 2014 and 2023 and created a stepwise guide to the metabarcoding process.

RESULTS

We found that studies in our review varied in technique and methodology, such as the sample type utilized, genetic marker regions targeted and bioinformatic databases used. The main limitations of metabarcoding are that parasite abundance data may not be reliably attained from sequence read numbers, metabarcoding data may not be representative of the species present in the host and the cost and bioinformatic expertise required to utilize this method may be prohibitive to some groups.

CONCLUSIONS

Overall, using metabarcoding to assess gastrointestinal parasite communities is preferable to traditional methods, yielding higher taxonomic resolution, higher throughput and increased versatility due to its utility in any geographical location, with a variety of sample types, and with virtually any vertebrate host species. Additionally, metabarcoding has the potential for exciting new discoveries regarding host and parasite evolution.

The "Dry-Lab" Side of Food Authentication: Benchmark of Bioinformatic Pipelines for the Analysis of Metabarcoding Data

Next Generation Sequencing Technologies (NGS), particularly metabarcoding, are valuable tools for authenticating foodstuffs and detecting eventual fraudulent practices such as species substitution. This technique, mostly used for the analysis of prokaryotes in several environments (including food), is in fact increasingly applied to identify eukaryotes (e.g., fish, mammals, avian, etc.) in multispecies food products. Besides the "wet-lab" procedures (e.g., DNA extraction, PCR, amplicon purification, etc.), the metabarcoding workflow includes a final "dry-lab" phase in which sequencing data are analyzed using a bioinformatic pipeline (BP). BPs play a crucial role in the accuracy, reliability, and interpretability of the metabarcoding results. Choosing the most suitable BP for the analysis of metabarcoding data could be challenging because it might require greater informatics skills than those needed in standard molecular analysis. To date, studies comparing BPs for metabarcoding data analysis in foodstuff authentication are scarce. In this study, we compared the data obtained from two previous studies in which fish burgers and insect-based products were authenticated using a customizable, ASV-based, and command-line interface BP (BP1) by analyzing the same data with a customizable but OTU-based and graphical user interface BP (BP2). The final sample compositions were compared statistically. No significant difference in sample compositions was highlighted by applying BP1 and BP2. However, BP1 was considered as more user-friendly than BP2 with respect to data analysis streamlining, cost of analysis, and computational time consumption. This study can provide useful information for researchers approaching the bioinformatic analysis of metabarcoding data for the first time. In the field of food authentication, an effective and efficient use of BPs could be especially useful in the context of official controls performed by the Competent Authorities and companies' self-control in order to detect species substitution and counterfeit frauds.

Novel community data in ecology-properties and prospects

New technologies for monitoring biodiversity such as environmental (e)DNA, passive acoustic monitoring, and optical sensors promise to generate automated spatiotemporal community observations at unprecedented scales and resolutions. Here, we introduce 'novel community data' as an umbrella term for these data. We review the emerging field around novel community data, focusing on new ecological questions that could be addressed; the analytical tools available or needed to make best use of these data; and the potential implications of these developments for policy and conservation. We conclude that novel community data offer many opportunities to advance our understanding of fundamental ecological processes, including community assembly, biotic interactions, micro- and macroevolution, and overall ecosystem functioning.

rCRUX: A Rapid and Versatile Tool for Generating Metabarcoding Reference libraries in R

The sequencing revolution requires accurate taxonomic classification of DNA sequences. Key to making accurate taxonomic assignments are curated, comprehensive reference barcode databases. However, the generation and curation of such databases has remained challenging given the large and continuously growing volumes of both DNA sequence data and novel reference barcode targets. Monitoring and research applications require a greater diversity of specialized gene regions and targeted taxa then are currently curated by professional staff. Thus there is a growing need for an easy to implement computational tool that can generate comprehensive metabarcoding reference libraries for any bespoke locus. We address this need by reimagining CRUX from the Anacapa Toolkit and present the rCRUX package in R which, like it's predecessor, relies on sequence homology and PCR primer compatibility instead of keyword-searches to avoid limitations of user-defined metadata. The typical workflow involves searching for plausible seed amplicons (get_seeds_local() or get_seeds_remote()) by simulating in silico PCR to acquire a set of sequences analogous to PCR products containing a user-defined set of primer sequences. Next, these seeds are used to iteratively blast search seed sequences against a local copy of the National Center for Biotechnology Information (NCBI) formatted nt database using a taxonomic-rank based stratified random sampling approach ( blast_seeds() ). This results in a comprehensive set of sequence matches. This database is dereplicated and cleaned (derep_and_clean_db()) by identifying identical reference sequences and collapsing the taxonomic path to the lowest taxonomic agreement across all matching reads. This results in a curated, comprehensive database of primer-specific reference barcode sequences from NCBI. Databases can then be compared (compare_db()) to determine read and taxonomic overlap. We demonstrate that rCRUX provides more comprehensive reference databases for the MiFish Universal Teleost 12S, Taberlet trnl, fungal ITS, and Leray CO1 loci than CRABS, MetaCurator, RESCRIPt, and ecoPCR reference databases. We then further demonstrate the utility of rCRUX by generating 24 reference databases for 20 metabarcoding loci, many of which lack dedicated reference database curation efforts. The rCRUX package provides a simple to use tool for the generation of curated, comprehensive reference databases for user-defined loci, facilitating accurate and effective taxonomic classification of metabarcoding and DNA sequence efforts broadly.

rCRUX: A Rapid and Versatile Tool for Generating Metabarcoding Reference libraries in R

Key to making accurate taxonomic assignments are curated, comprehensive reference barcode databases. However, the generation and curation of such databases has remained challenging given the large and continuously growing volumes of DNA sequence data and novel reference barcode targets. Monitoring and research applications require a greater diversity of specialized gene regions and targeted taxa to meet taxonomic classification goals then are currently curated by professional staff. Thus, there is a growing need for an easy to implement tool that can generate comprehensive metabarcoding reference libraries for any bespoke locus. We address this need by reimagining CRUX from the Anacapa Toolkit and present the rCRUX package in R. The typical workflow involves searching for plausible seed amplicons (get_seeds_local() or get_seeds_remote()) by simulating in silico PCR to acquire seed sequences containing a user-defined primer set. Next these seeds are used to iteratively blast search seed sequences against a local NCBI formatted database using a taxonomic rank based stratified random sampling approach (blast_seeds()) that results in a comprehensive set of sequence matches. This database is dereplicated and cleaned (derep_and_clean_db()) by identifying identical reference sequences and collapsing the taxonomic path to the lowest taxonomic agreement across all matching reads. This results in a curated, comprehensive database of primer specific reference barcode sequences from NCBI. We demonstrate that rCRUX provides more comprehensive reference databases for the MiFish Universal Teleost 12S, Taberlet trnl, and fungal ITS locus than CRABS, METACURATOR, RESCRIPt, and ECOPCR reference databases. We then further demonstrate the utility of rCRUX by generating 16 reference databases for metabarcoding loci that lack dedicated reference database curation efforts. The rCRUX package provides a simple to use tool for the generation of curated, comprehensive reference databases for user-defined loci, facilitating accurate and effective taxonomic classification of metabarcoding and DNA sequence efforts broadly.

Maximizing the reliability and the number of species assignments in metabarcoding studies using a curated regional library and a public repository

Biodiversity assessments relying on DNA have increased rapidly over the last decade. However, the reliability of taxonomic assignments in metabarcoding studies is variable and affected by the reference databases and the assignment methods used. Species level assignments are usually considered as reliable using regional libraries but unreliable using public repositories. In this study, we aimed to test this assumption for metazoan species detected in the Gulf of St. Lawrence in the Northwest Atlantic. We first created a regional library (GSL-rl) by data mining COI barcode sequences from BOLD, and included a reliability ranking system for species assignments. We then estimated 1) the accuracy and precision of the public repository NCBI-nt for species assignments using sequences from the regional library and 2) compared the detection and reliability of species assignments of a metabarcoding dataset using either NCBI-nt or the regional library and popular assignment methods. With NCBI-nt and sequences from the regional library, the BLAST-LCA (least common ancestor) method was the most precise method for species assignments, but the accuracy was higher with the BLAST-TopHit method (&gt;80% over all taxa, between 70% and 90% amongst taxonomic groups). With the metabarcoding dataset, the reliability of species assignments was greater using GSL-rl compared to NCBI-nt. However, we also observed that the total number of reliable species assignments could be maximized using both GSL-rl and NCBI-nt with different optimized assignment methods. The use of a two-step approach for species assignments, i.e., using a regional library and a public repository, could improve the reliability and the number of detected species in metabarcoding studies.

Benchmarking Bioinformatic Tools for Amplicon-Based Sequencing of Norovirus

In order to survey noroviruses in our environment, it is essential that both wet-lab and computational methods are fit for purpose. Using a simulated sequencing data set, denoising-based (DADA2, Deblur and USEARCH-UNOISE3) and clustering-based pipelines (VSEARCH and FROGS) were compared with respect to their ability to represent composition and sequence information. Open source classifiers (Ribosomal Database Project [RDP], BLASTn, IDTAXA, QIIME2 naive Bayes, and SINTAX) were trained using three different databases: a custom database, the NoroNet database, and the Human calicivirus database. Each classifier and database combination was compared from the perspective of their classification accuracy. VSEARCH provides a robust option for analyzing viral amplicons based on composition analysis; however, all pipelines could return OTUs with high similarity to the expected sequences. Importantly, pipeline choice could lead to more false positives (DADA2) or underclassification (FROGS), a key aspect when considering pipeline application for source attribution. Classification was more strongly impacted by the classifier than the database, although disagreement increased with norovirus GII.4 capsid variant designation. We recommend the use of the RDP classifier in conjunction with VSEARCH; however, maintenance of the underlying database is essential for optimal use. IMPORTANCE In benchmarking bioinformatic pipelines for analyzing high-throughput sequencing (HTS) data sets, we provide method standardization for bioinformatics broadly and specifically for norovirus in situations for which no officially endorsed methods exist at present. This study provides recommendations for the appropriate analysis and classification of norovirus amplicon HTS data and will be widely applicable during outbreak investigations.

Applications of environmental DNA (eDNA) in agricultural systems: Current uses, limitations and future prospects

Global food production, food supply chains and food security are increasingly stressed by human population growth and loss of arable land, becoming more vulnerable to anthropogenic and environmental perturbations. Numerous mutualistic and antagonistic species are interconnected with the cultivation of crops and livestock and these can be challenging to identify on the large scales of food production systems. Accurate identifications to capture this diversity and rapid scalable monitoring are necessary to identify emerging threats (i.e. pests and pathogens), inform on ecosystem health (i.e. soil and pollinator diversity), and provide evidence for new management practices (i.e. fertiliser and pesticide applications). Increasingly, environmental DNA (eDNA) is providing rapid and accurate classifications for specific organisms and entire species assemblages in substrates ranging from soil to air. Here, we aim to discuss how eDNA is being used for monitoring of agricultural ecosystems, what current limitations exist, and how these could be managed to expand applications into the future. In a systematic review we identify that eDNA-based monitoring in food production systems accounts for only 4 % of all eDNA studies. We found that the majority of these eDNA studies target soil and plant substrates (60 %), predominantly to identify microbes and insects (60 %) and are biased towards Europe (42 %). While eDNA-based monitoring studies are uncommon in many of the world's food production systems, the trend is most pronounced in emerging economies often where food security is most at risk. We suggest that the biggest limitations to eDNA for agriculture are false negatives resulting from DNA degradation and assay biases, as well as incomplete databases and the interpretation of abundance data. These require in silico, in vitro, and in vivo approaches to carefully design, test and apply eDNA monitoring for reliable and accurate taxonomic identifications. We explore future opportunities for eDNA research which could further develop this useful tool for food production system monitoring in both emerging and developed economies, hopefully improving monitoring, and ultimately food security.

Fishing for fish environmental DNA: Ecological applications, methodological considerations, surveying designs, and ways forward

Vast global declines of freshwater and marine fish diversity and population abundance pose serious threats to both ecosystem sustainability and human livelihoods. Environmental DNA (eDNA)-based biomonitoring provides robust, efficient, and cost-effective assessment of species occurrences and population trends in diverse aquatic environments. Thus, it holds great potential for improving conventional surveillance frameworks to facilitate fish conservation and fisheries management. However, the many technical considerations and rapid developments underway in the eDNA arena can overwhelm researchers and practitioners new to the field. Here, we systematically analysed 416 fish eDNA studies to summarize research trends in terms of investigated targets, research aims, and study systems, and reviewed the applications, rationales, methodological considerations, and limitations of eDNA methods with an emphasis on fish and fisheries research. We highlighted how eDNA technology may advance our knowledge of fish behaviour, species distributions, population genetics, community structures, and ecological interactions. We also synthesized the current knowledge of several important methodological concerns, including the qualitative and quantitative power eDNA has to recover fish biodiversity and abundance, and the spatial and temporal representations of eDNA with respect to its sources. To facilitate ecological applications implementing fish eDNA techniques, recent literature was summarized to generate guidelines for effective sampling in lentic, lotic, and marine habitats. Finally, we identified current gaps and limitations, and pointed out newly emerging research avenues for fish eDNA. As methodological optimization and standardization improve, eDNA technology should revolutionize fish monitoring and promote biodiversity conservation and fisheries management that transcends geographic and temporal boundaries.

Environmental DNA analysis as an emerging non-destructive method for plant biodiversity monitoring: a review

Environmental DNA (eDNA) analysis has recently transformed and modernized biodiversity monitoring. The accurate detection, and to some extent quantification, of organisms (individuals/populations/communities) in environmental samples is galvanizing eDNA as a successful cost and time-efficient biomonitoring technique. Currently, eDNA's application to plants remains more limited in implementation and scope compared to animals and microorganisms. This review evaluates the development of eDNA-based methods for (vascular) plants, comparing its performance and power of detection with that of traditional methods, to critically evaluate and advise best-practices needed to innovate plant biomonitoring. Recent advancements, standardization and field applications of eDNA-based methods have provided enough scope to utilize it in conservation biology for numerous organisms. Despite our review demonstrating only 13% of all eDNA studies focus on plant taxa to date, eDNA has considerable environmental DNA has considerable potential for plants, where successful detection of invasive, endangered and rare species, and community-level interpretations have provided proof-of-concept. Monitoring methods using eDNA were found to be equal or more effective than traditional methods; however, species detection increased when both methods were coupled. Additionally, eDNA methods were found to be effective in studying species interactions, community dynamics and even effects of anthropogenic pressure. Currently, elimination of potential obstacles (e.g. lack of relevant DNA reference libraries for plants) and the development of user-friendly protocols would greatly contribute to comprehensive eDNA-based plant monitoring programs. This is particularly needed in the data-depauperate tropics and for some plant groups (e.g., Bryophytes and Pteridophytes). We further advocate to coupling traditional methods with eDNA approaches, as the former is often cheaper and methodologically more straightforward, while the latter offers non-destructive approaches with increased discrimination ability. Furthermore, to make a global platform for eDNA, governmental and academic-industrial collaborations are essential to make eDNA surveys a broadly adopted and implemented, rapid, cost-effective and non-invasive plant monitoring approach.

Developing Indicators of Nutrient Pollution in Streams Using 16S rRNA Gene Metabarcoding of Periphyton-Associated Bacteria

Indicators based on nutrient-biota relationships in streams can inform water quality restoration and protection programs. Bacterial assemblages could be particularly useful indicators of nutrient effects because they are species-rich, important contributors to ecosystem processes in streams, and responsive to rapidly changing conditions. Here, we sampled 25 streams weekly (12-14 times each) and used 16S rRNA gene metabarcoding of periphyton-associated bacteria to quantify the effects of total phosphorus (TP) and total nitrogen (TN). Threshold indicator taxa analysis identified assemblage-level changes and amplicon sequence variants (ASVs) that increased or decreased with increasing TP and TN concentrations (i.e., low P, high P, low N, and high N ASVs). Boosted regression trees confirmed that relative abundances of gene sequence reads for these four indicator groups were associated with nutrient concentrations. Gradient forest analysis complemented these results by using multiple predictors and random forest models for each ASV to identify portions of TP and TN gradients at which the greatest changes in assemblage structure occurred. Synthesized statistical results showed bacterial assemblage structure began changing at 24 μg TP/L with the greatest changes occurring from 110 to 195 μg/L. Changes in the bacterial assemblages associated with TN gradually occurred from 275 to 855 μg/L. Taxonomic and phylogenetic analyses showed that low nutrient ASVs were commonly Firmicutes, Verrucomicrobiota, Flavobacteriales, and Caulobacterales, Pseudomonadales, and Rhodobacterales of Proteobacteria, whereas other groups, such as Chitinophagales of Bacteroidota, and Burkholderiales, Rhizobiales, Sphingomonadales, and Steroidobacterales of Proteobacteria comprised the high nutrient ASVs. Overall, the responses of bacterial ASV indicators in this study highlight the utility of metabarcoding periphyton-associated bacteria for quantifying biotic responses to nutrient inputs in streams.

Applying convolutional neural networks to speed up environmental DNA annotation in a highly diverse ecosystem

High-throughput DNA sequencing is becoming an increasingly important tool to monitor and better understand biodiversity responses to environmental changes in a standardized and reproducible way. Environmental DNA (eDNA) from organisms can be captured in ecosystem samples and sequenced using metabarcoding, but processing large volumes of eDNA data and annotating sequences to recognized taxa remains computationally expensive. Speed and accuracy are two major bottlenecks in this critical step. Here, we evaluated the ability of convolutional neural networks (CNNs) to process short eDNA sequences and associate them with taxonomic labels. Using a unique eDNA data set collected in highly diverse Tropical South America, we compared the speed and accuracy of CNNs with that of a well-known bioinformatic pipeline (OBITools) in processing a small region (60 bp) of the 12S ribosomal DNA targeting freshwater fishes. We found that the taxonomic labels from the CNNs were comparable to those from OBITools, with high correlation levels for the composition of the regional fish fauna. The CNNs enabled the processing of raw fastq files at a rate of approximately 1 million sequences per minute, which was about 150 times faster than with OBITools. Given the good performance of CNNs in the highly diverse ecosystem considered here, the development of more elaborate CNNs promises fast deployment for future biodiversity inventories using eDNA.

Influence of DNA extraction kits on freshwater fungal DNA metabarcoding

Background

Environmental DNA (eDNA) metabarcoding is a common technique for efficient biodiversity monitoring, especially of microbes. Recently, the usefulness of aquatic eDNA in monitoring the diversity of both terrestrial and aquatic fungi has been suggested. In eDNA studies, different experimental factors, such as DNA extraction kits or methods, can affect the subsequent analyses and the results of DNA metabarcoding. However, few methodological studies have been carried out on eDNA of fungi, and little is known about how experimental procedures can affect the results of biodiversity analysis. In this study, we focused on the effect of DNA extraction method on fungal DNA metabarcoding using freshwater samples obtained from rivers and lakes.

Methods

DNA was extracted from freshwater samples using the DNeasy PowerSoil kit, which is mainly used to extractmicrobial DNA from soil, and the DNeasy Blood & Tissue kit, which is commonly used for eDNA studies on animals. We then compared PCR inhibition and fungal DNA metabarcoding results; i.e., operational taxonomic unit (OTU) number and composition of the extracted samples.

Results

No PCR inhibition was detected in any of the samples, and no significant differences in the number of OTUs and OTU compositions were detected between the samples processed using different kits. These results indicate that both DNA extraction kits may provide similar diversity results for the river and lake samples evaluated in this study. Therefore, it may be possible to evaluate the diversity of fungi using a unified experimental method, even with samples obtained for diversity studies on other taxa such as those of animals.