Environmental DNA最新文献

A large number of marker typologies have been developed for the metabarcoding of environmental DNA (eDNA). Generalist markers have been advocated for their ability to amplify many taxa simultaneously and produce exhaustive biodiversity assessments, while more specific markers have been proposed for their higher ability to detect and discriminate taxa within a more restricted group. Quantitative comparisons between generalist and specific markers are needed to assess their relative efficiency depending on study targets. Here we compared the performance of one generalist (Euka02, amplifying all eukaryotic groups), one intermediate (Arth02, amplifying arthropods), and two specific markers (Coll01 and Inse01, amplifying springtails and insects, respectively) for the assessment of springtails and insects diversity using eDNA metabarcoding. The four markers were used to analyze eDNA extracted from > 1200 soil samples collected in recently deglaciated terrains. We then assessed whether the different markers were able to detect community responses to key environmental drivers (soil temperature, time since glacier retreat, plant productivity, and topographic wetness). The two specific markers detected more taxa of both springtails and insects than the generalist markers; still the taxonomic richness and community dissimilarity were well correlated between generalist and specific markers. There was good overlap between the taxa identified by the specific markers and those identified by the generalist ones, but the specific markers often detected the taxa identified by the generalist markers, plus several additional ones. Both generalist and specific markers detected the impact of key environmental drivers on arthropods; still the specific markers showed the strongest power to detect relationships, and the most generalist marker was unable to identify the weaker relationships. Generalist markers efficiently provide an overall view of soil biodiversity; nevertheless complementing them with specific markers allows more detailed biodiversity measures, and provides a clearer picture of its response to environmental stressors.

Environmental DNA (eDNA) metabarcoding is widely used in biodiversity monitoring, and its popularity is also growing because of its potential to simultaneously detect multiple taxonomic groups, allowing holistic community assessments. When working with water samples, the choice of the filter type is one of the key methodological factors influencing community characterization, with 0.22 μm pore size filters typically used for microbial communities and larger filters for eDNA of larger organisms. However, as holistic community assessments are increasingly adopted, the use of a single filter pore size would help to optimize sampling and experimental efforts. Yet, it remains unclear whether filters with large pore sizes can effectively capture both microbial and macro-organism eDNA. This study evaluates the use of 0.45 μm filters, commonly used for metazoan eDNA metabarcoding, in assessing microbial diversity across different coastal environments. Replicates of water samples from the Venice Lagoon and nearby waters were filtered independently using both 0.45 μm and the standard 0.22 μm pore size filters and analyzed through 16S rRNA gene metabarcoding. Both filters capture a shared core microbial community, but they also retain distinct taxa. Alpha diversity was significantly higher in samples collected with the 0.45 μm filters, which also showed a more effective recovery of particle-associated microbes. Our work contributes to optimizing eDNA-based methodologies for large-scale multi-taxa biodiversity monitoring, demonstrating that 0.45 μm filters can effectively capture microbial diversity and supporting their use in holistic studies in aquatic environments.

Environmental DNA (eDNA)-based detection is a valuable biomonitoring tool that is well-developed for water, soil, and scat substrates. Emergent research is focusing on air as a new substrate, including opportunistically collected natural spiderwebs which may have negative impacts on local spider diversity. Here, we design novel artificial spiderwebs and compare their effectiveness with natural spiderwebs and aquatic eDNA approaches for biomonitoring of terrestrial taxa. A total of 33 eDNA samples (18 water, 6 natural spiderwebs, 9 artificial spiderwebs) were collected from a rural property in Palmerston North (Aotearoa New Zealand). Three amplicons (COI, 16S, and ITS) were sequenced for each sample to evaluate the performance of each collection method for detecting invertebrates, vertebrates, and plant/algal taxa. The 16S amplicon performed best in terms of sequencing output and consistency, as well as species accumulation curves, with the COI dataset performing worst for all eDNA collection methods. Alpha diversity varied by amplicon and collection method in both value and consistency among samples, with 16S and ITS retrieving higher diversity for water samples and both artificial and natural webs outperforming water in fungal COI diversity recovery. Ordination plots showed clear differences in sample similarity across biomes, with all three amplicons showing differentiation between water and either web type. However, specialist species were recovered by each of the two web types, with artificial webs consistently recovering more unique diversity than natural webs. Our results suggest that artificial spiderwebs could be a promising new method in the eDNA biomonitoring toolbox, providing biodiversity data that complements water-based collections and, depending on the research question, may serve as a sufficient proxy for natural spiderweb studies.

Metabarcoding has been proven to be a highly effective tool for surveying biodiversity in aquatic ecosystems. Despite the recent explosion of metabarcoding studies, relatively few efforts have focused on freshwater zooplankton communities, even though they form an essential component of freshwater ecosystems. Here, we evaluate some essential aspects of metabarcoding surveys to provide a solid basis for the development of qualitative and quantitative metabarcoding surveys for freshwater zooplankton communities. We developed and validated taxon-specific and universally applicable metabarcoding primers for Cladocera, Copepoda and Rotifera. These primers were subsequently used to assess optimal sample collection, preservation and DNA extraction protocols and gain insights into the key biases that may influence the interpretation of freshwater zooplankton metabarcoding results. The presented primers performed well when applied to both bulk community samples and eDNA samples, although the latter seemed to slightly decrease the performance of metabarcoding analyses. We found significant effects of subsample size, sample preservation, DNA extraction and lysis methods for bulk community samples with inadequate protocols likely to underestimate Cladocera diversity. Primer amplification efficiency was found to be the primary driver of biases in the quantitative interpretation of metabarcoding data, regardless of the taxonomic target or sequencing depth. General correction factors based on primer amplification efficiency may thus be sufficient to enhance the quantitative nature of metabarcoding surveys.

The Nile is the longest river in the world and has a long history of taxonomic research on its plankton species, but there is little information about the composition of present-day communities. Zooplankton are ecologically important members of river ecosystems and environmental DNA (eDNA) metabarcoding of bulk plankton samples is increasingly used to study their composition and diversity. We sampled zooplankton communities in the White Nile and Blue Nile rivers near Khartoum, Sudan from December 2017 to April 2018 and from October 2019 to March 2020. Using a fragment of the V4 region (~240–408 bp) of the 18S rRNA gene and the PR² reference database, eDNA recovered 40 taxa assigned to genus or species in Cladocera, Copepoda, and Rotifera (53%–72% of amplicon sequence variants—ASVs), 15 of which were known from the Nile. The remaining 25 were presumed to be misassignments due to a lack of reference sequences for species known from the Nile, but 17 of these could be provisionally assigned based on historical data, distribution records, and morphological identifications. Rotifers were the most taxonomically diverse group in our study. The low count of Cladocera reads in our eDNA data likely resulted from primer mismatch, although a similar number of taxa were identified morphologically. The Blue Nile had a significantly more diverse and temporally variable community which we hypothesize is related to greater variation in flow and nutrient supply. We conclude that biodiversity monitoring in the Nile using eDNA metabarcoding provides a meaningful overview of the zooplankton community despite the lack of reference sequences at present, and that ongoing and future pressures on the Nile River ecosystem require improved efforts to monitor its biodiversity.

Mangrove ecosystems support a diverse array of animal species and also provide pivotal ecosystem services, such as coastal protection, food provisioning, and carbon capture. However, these vital habitats are in decline, leading to coastal degradation in many parts of the globe. To address this, a mangrove restoration project in Demak, Java, Indonesia, introduced the use of semi-permeable coastal protective barriers made of bamboo pilings to safeguard the shore zone and hinterlands. The introduction of such hard substrate in the marine environment can attract a range of species, and it is important to be able to monitor changes in biodiversity from a restoration point of view. Here, we assessed whether environmental DNA metabarcoding can be applied to monitor fish biodiversity in an understudied area. Our results show slight but significant differences in species richness and fish community composition within a short timeframe of only 4 months, although we cannot disentangle the effects of seasonal variation from those of the introduction of hard substrate. More importantly, this study demonstrates a useful level of temporal resolution of eDNA metabarcoding and establishes a baseline for fish species richness in an understudied mangrove coastal zone in Demak, Java, Indonesia. Our results are of value for informing future restoration efforts and other (metabarcoding) biodiversity studies in the region.

Environmental DNA (eDNA) sampling has become a common tool for monitoring rare and declining aquatic species. However, results can be biased by the spatiotemporal variation in eDNA signals, yet the biological and environmental factors that cause this variation are not well understood. Here, we examined the seasonal and fine-scale (< 100 m) longitudinal variation in eDNA concentration and detection in situ for a rare aquatic salamander, the Eastern Hellbender (Cryptobranchus alleganiensis alleganiensis). We also applied multivariate generalized linear mixed-effects models to investigate how physical and hydrological stream characteristics influence eDNA concentration estimates and detection rates. Both metrics spiked during the hellbender breeding season but remained low at other times of the year. This was primarily driven by one site in which hellbenders are dense and actively reproducing; once this site was removed from analyses, temporal variation in eDNA signals was no longer observed. No fine-scale spatial eDNA pattern emerged, but concentrations and detections were highly variable across temporal and spatial replicates within sites, emphasizing the importance of collecting replicate eDNA samples at multiple scales. Only PCR inhibitors present in our samples significantly reduced concentrations and detections; however, general negative relationships were still apparent with flow velocity. Increased surface water temperature and pH were also tenuously associated with eDNA concentrations but did not influence detections. Our study contributes important knowledge regarding biological and environmental factors driving eDNA spatiotemporal variability, facilitating a refinement in eDNA sampling strategies for hellbenders and other rare aquatic organisms so that accurate scientific inferences about their populations can be made.

The use of Next-Generation Sequencing (NGS) in environmental DNA (eDNA) research offers increased sensitivity in detecting rare species within vast marine ecosystems. However, conventional NGS methods often fail to accurately capture low-frequency variants, posing risks of imprecise detections. Inspired by clinical research, innovations like SiMSen-Seq (simple multiplexed PCR-based barcoding of DNA for ultrasensitive mutation detection using sequencing) have emerged. SiMSen-Seq utilizes molecular barcoding to track individual DNA templates, correcting polymerase-induced errors and quantification biases. In this study, we adapted the SiMSen-Seq protocol for eDNA analysis, targeting 18S rRNA metabarcoding in seawater samples to enhance marine biodiversity assessment, particularly for identifying rare non-indigenous species (NIS). Comparative analysis against an Illumina MiSeq protocol (Illumina—DADA2) and the SiMSen-Seq protocol with DADA2 bioinformatics (SiMSen-Seq—DADA2) revealed that SiMSen-Seq detected a higher number (1495) of molecular Operational Taxonomic Units (mOTUs) compared to the other two pipelines (Illumina—DADA2: 585 and SiMSen-Seq—DADA2: 578). In terms of genera, SiMSen-Seq detected the lowest number of genera, Illumina—DADA2 the highest number, and 45% of genera were detected across protocols. While all three protocols identified the predominant NIS, they differed in detecting rare taxa: SiMSen-Seq uniquely detected Arenigobius bifrenatus and Pseudopolydora paucibranchiata but did not detect some others (e.g., Asterias amurensis/A. forbesi). These findings suggest that for some species (especially Stylea plicata and Ciona savignyi), SiMSen-Seq could potentially be useful to detect intraspecific variability for population genetic studies, with uses in more precise ecological monitoring and effective marine conservation.

Microbial communities play a fundamental role in biogeochemical cycling within salt and brackish marsh ecosystems, yet fungal-prokaryotic interactions in these environments remain poorly understood. This study employed metabarcoding of the 16S and 28S rRNA genes to investigate prokaryotic and fungal communities across four locations in sediments and surface waters of the North Inlet salt marsh and Winyah Bay brackish marsh (South Carolina, USA) over four time points from 2020 to 2021. Co-occurrence network analyses were used to identify potential microbial interactions and their ecological implications. Distinct fungal and prokaryotic communities were observed between the two marsh types. From the 16S prokaryotic primer set, Proteobacteria, Bacteroidota, and Cyanobacteriota dominated both marshes. Early diverging fungi and Actinomycetota (bacteria) were prevalent in the brackish marsh, whereas salt marsh communities were primarily composed of Dikarya fungi (Ascomycota and Basidiomycota) and Desulfobacteria. Network analyses revealed contrasting interactions between surface water and sediment. In brackish marsh sediments, fungi and prokaryotes exhibited nearly exclusively negative connections, suggesting strong resource competition. In contrast, Dikarya fungi in brackish marsh surface water displayed numerous positive connections with bacteria, suggesting potential cross-feeding interactions. In the salt marsh, fungi and prokaryotes exhibited potential cooperative and competitive/antagonistic interactions. Ascomycota were positively connected with Desulfobacteria, suggesting a role in complex organic matter degradation. Conversely, negative connections between Chytridiomycota (early diverging fungi) and Cyanobacteriota (bacteria) implied parasitic interactions. These findings highlight the dynamic nature of fungal-prokaryotic interactions in coastal ecosystems. By analyzing potential microbial relationships in salt and brackish marshes, this study provides new insights into the ecological roles of fungi in estuarine environments, particularly their contributions to nutrient cycling and organic matter decomposition. Understanding these interactions is crucial for generating hypotheses and predicting microbial responses to environmental changes—such as shifts in salinity and nutrient availability—and their potential impacts on marsh ecosystem functioning.