Environmental DNA Metabarcoding Research Articles

Evaluating zooplankton species diversity using environmental DNA and bulk-DNA metabarcoding in the Ulleung Basin of the Southeastern Korean Peninsula in the summer

Accurately investigating the composition of zooplankton species is crucial for monitoring changes in marine ecosystems and assessing biodiversity. In this study, we utilized bulk DNA and environmental DNA metabarcoding in the Ulleung Basin, known for its high zooplankton species diversity among the seas surrounding the Korean Peninsula. Genomic DNA extracted from samples collected during three summer seasons in the survey area was analyzed using high-throughput sequencing of the cytochrome c oxidase I barcode region. We identified 350 species, which were three to six times more than those identified by traditional morphological methods. Furthermore, we observed significant differences in species composition and diversity between bulk DNA and eDNA samples. Notably, eDNA metabarcoding effectively detected species with high swimming ability and those that were difficult to capture using traditional sampling methods. This study underscores the significant impact of sampling methods on research outcomes in zooplankton species diversity studies and highlights the importance of integrating different sampling techniques. Specifically, it suggests the need for the active adoption of non-invasive methods, such as eDNA metabarcoding, for the comprehensive monitoring of diverse biological groups in marine ecosystems.

Environmental DNA metabarcoding as an efficient tool to monitor freshwater systems in northwestern Italy

Environmental DNA metabarcoding as an efficient tool to monitor freshwater systems in northwestern Italy

Environmental DNA Metabarcoding of Cephalopod Diversity in the Tyrrhenian Deep Sea

The deep sea, the largest biome on Earth, is the least explored and understood. This lack of knowledge hampers our ability to understand and protect this important environment. In this study, water and sediment samples were collected at different depths in the central Mediterranean (224–780 m), specifically, within the Dohrn Canyon and the Palinuro Seamount, to investigate the diversity of cephalopods and establish a baseline knowledge of their distribution in these sites to preserve their habitats and estimate the impacts of human-driven environmental changes. Key taxa identified included Heteroteuthis sp., Loligo sp., and Histioteuthis sp., which were the most abundant across all sampling stations. A low overlap in species detection was observed between water and sediment samples, confirming previous findings that the typology of environmental matrices used in eDNA metabarcoding has a significant impact on the organisms detected and, therefore, the integrated use of different matrices to better represent local biodiversity is recommended. Furthermore, this study highlights the limitations posed by gaps in reference databases, particularly for deep-sea organisms, and addresses these by emphasising the need for improved multi-marker approaches and expanded reference databases to enhance the accuracy of eDNA-based biodiversity assessment.

A spatial matrix factorization method to characterize ecological assemblages as a mixture of unobserved sources: An application to fish eDNA surveys

Abstract Understanding how ecological assemblages vary in space and time is essential for advancing our knowledge of biodiversity dynamics and ecosystem functioning. Metabarcoding of environmental DNA (eDNA) is an efficient method for documenting biodiversity changes in both marine and terrestrial ecosystems. However, current methods fail to detect and display the biodiversity structure within and between eDNA samples limiting ecological and biogeographical interpretations. We present a spatial matrix factorization method that identifies optimal eDNA sample assemblages—called pools—assuming that taxonomic unit composition is based on a fixed number of unknown sources. These sources, in turn, represent taxonomic units sharing similar habitat properties or characteristics. The method aims to reduce the multi‐taxa composition structure into a low number of dimensions defined by these sources. This method is inspired by admixture analysis in population genetics. Using a marine fish eDNA survey on 263 sampling stations detecting 2888 molecular operational taxonomic units (MOTUs), we apply this method to analyse the biogeography and mixing patterns of fish assemblages at regional and large scales. At large scale, our analysis reveals six primary pools of fish samples characterized by distinct biogeographic patterns, with some mixtures between these pools. We identify pools composed of unique sources, corresponding to distinct and more isolated regions such as the Mediterranean and Scotia Seas. We also identify pools composed of a greater mix of sources, corresponding to geographically connected areas, such as tropical regions. Additionally, we identify the taxa underpinning the formation of each pool. In the regional analysis of Mediterranean eDNA samples, our method successfully identifies different pools, allowing the detection of not only geographic gradients but also human‐induced gradients corresponding to protection levels. Spatial matrix factorization adds a new method in community ecology, where each sample is considered as a mixture of K unobserved sources, to assess the dissimilarity of ecological assemblages revealing environmental and human‐induced gradients. Beyond the study of fish eDNA samples, this method has the potential to shed new light on any biodiversity survey and provide new bioindicators of global change.

Evaluation of Fish Biodiversity in Estuaries Through Environmental DNA Metabarcoding: A Comprehensive Review

Traditional methods face difficulties in capturing elusive species and navigating the complexities of estuarine environments. The adoption of eDNA metabarcoding has revolutionized biodiversity assessment, offering non-invasive and comprehensive sampling. Challenges specific to estuaries, such as sediment loads and salinity fluctuations, were initially addressed through improved DNA extraction, optimized primers, and specialized bioinformatics tools. The integration of multiple genetic markers and quantitative eDNA approaches has enhanced resolution, enabling the detection of rare and cryptic species. Standardized sampling protocols and validation through traditional methods contribute to the reliability of eDNA metabarcoding. This technology holds promise for informing conservation and management strategies in estuarine ecosystems by providing timely and cost-effective biodiversity data.

Zoom into a twilight zone: a biodiversity survey of the Dohrn Canyon (Mediterranean sea) through environmental DNA metabarcoding

Zoom into a twilight zone: a biodiversity survey of the Dohrn Canyon (Mediterranean sea) through environmental DNA metabarcoding

Complementary roles of eDNA metabarcoding and microscopy in plankton monitoring across seven habitats

Abstract Plankton biodiversity in aquatic ecosystems is currently investigated by labor-intensive and time-consuming microscope identification. Environmental DNA (eDNA) metabarcoding is emerging as a highly effective and objective tool for assessing biodiversity. In this study, we compared the effectiveness of eDNA metabarcoding with conventional microscope identification for monitoring plankton biodiversity in seven habitats. The eDNA metabarcoding identified a rich diversity of 190 families, 410 genera and 871 species within the planktonic community across seven habitats. In contrast, traditional microscope identification only identified 51 families, 75 genera and 96 species. In addition, primer choice influenced the detected plankton community diversity, with the V4 primers performing poorly for detecting Cladocera and Euglenophyta taxa and the V9 primers revealing more eukaryotic plankton species. Despite primer-specific differences in species detection, there was substantial overlap between the species detected by eDNA metabarcoding strategies and microscope identification. These results suggest that eDNA metabarcoding can be used as a complementary method alongside microscope identification rather than replacing them entirely.

Artificial Intelligence-Assisted Environmental DNA Metabarcoding and High-Resolution Underwater Optical Imaging for Noninvasive and Innovative Marine Environmental Monitoring

To effectively protect the marine environment, it is crucial to establish effective environ mental monitoring platforms. Traditional marine environmental monitoring methods heavily rely on morphological identification and field expertise, with the sampling process being disruptive and potentially destructive to vulnerable marine environments. In light of emerging biomonitoring needs and biodiversity declines, we reviewed the urgently needed, ongoing advances in developing effective, noninvasive, and innovative monitoring methods and systems to examine the complex marine environment for better strategic conservation and protection, using the coral ecosystem as one of the representative forefront examples in marine protection. This review summarizes current trends and efforts in transitioning into more standardizable and automatable utilizations of environmental DNA metabarcoding-based monitoring strategies and high-resolution underwater optical imaging monitoring systems as two of the promising pillars for the next generation of noninvasive biomonitoring and associated applications. The assistance of artificial intelligence for environmental DNA metabarcoding and high-resolution underwater optical imaging into an empowered, all-rounded monitoring platform for enhanced monitoring capacity is discussed as a highly potent direction for future research exploration. This review will be a cornerstone reference for the future development of artificial intelligence-assisted, noninvasive, and innovative marine environmental monitoring systems.

Composition, divergence and variability: A comprehensive analysis of fish trait responses to connectivity

Connectivity, a fundamental concept in ecology, refers to the extent to which different habitats or ecosystems are interconnected through the movement of organisms, nutrients, and energy. Lateral hydrological connectivity (LHC) plays an especially critical role in shaping aquatic community organization in river-floodplain systems. However, a comprehensive understanding of various trait responses to LHC remains elusive. We characterized how attributes of fish community traits, specifically composition, divergence, and temporal variability respond to LHC in the Austrian-Hungarian floodplains of the Danube River using environmental DNA (eDNA) metabarcoding. Trait composition was quantified by community-level weighted means (CWM) as the degree of changes in trait responses along the LHC gradient from isolated oxbows to the main river. Divergence was measured using Rao’s quadratic functional diversity index and a null model approach to calculate standardized effect sizes (SES), with larger SES values indicating greater divergence and smaller values indicating convergence. Temporal variability, representing the degree of instability in community traits over time, was calculated using a functional beta diversity measure for multiple communities. Our findings revealed apparent compositional changes for many trait variables, highlighting the significance of LHC in shaping community functional diversity. Divergence patterns indicated that isolated habitats foster trait convergence presumably due to habitat filtering, whereas more connected areas promote trait divergence due to higher species richness and habitat availability. Temporal variability of traits associated with flow preference exhibited a hump-shaped relationship with LHC, suggesting intermediate connectivity zones are hotspots of ecological dynamism. The study suggests that examining composition, divergence, and temporal variability together provides a more complete understanding of trait responses to connectivity, stressing the importance of maintaining diverse connectivity levels in river-floodplain systems for effective conservation and ecosystem management.

Impacts of phosphite treatment on Phytophthora community assemblages and inoculum abundances in Phytophthora-infected forest soil

Phytophthora are causing declines in forest tree species worldwide and the chemical control treatment, phosphite, is the only treatment consistently shown to provide some protection to natural ecosystems from Phytophthora diseases. Phosphite inhibits Phytophthora growth and sporulation whilst boosting defence responses in the plant host. It is unclear, however, the extent of the impact of phosphite on Phytophthora species assemblages and inoculum abundances in soil around trees following treatment within natural ecosystems. In New Zealand, kauri (Agathis australis), an endemic and threatened foundation species, suffers from a dieback disease primarily caused by Phytophthora agathidicida. Phosphite is applied by trunk injection to kauri and has been shown to improve resin ‘bleed’ symptoms from basal trunk lesions and to promote recovery of thinned canopies. Phytophthora community and inoculum abundance were investigated in response to phosphite treatments at two field sites (Huia and Waitoki) in infected kauri stands in Auckland, New Zealand. At Huia, soil sampling and tree health surveying were conducted in November 2023 on trees treated with phosphite in 2012 as part of an earlier study. At Waitoki, the response to phosphite treatment was monitored 6 and 18 months following treatment. Phytophthora species were detected using soil baiting and metabarcoding of environmental DNA (eDNA) from soil and quantified with qPCR of root and soil DNA. Three species were detected with soil baiting (P. agathidicida, P. cinnamomi, and P. multivora) and two additional species with metabarcoding (P. pseudocryptogea, and an unknown clade 7 species similar to P. europaea). Phytophthora cinnamomi was the most abundant species, followed by P. agathidicida. Both species were more likely to occur together than by chance alone and were associated with declining tree health. The P. europaea-like species was in approximately 50% of the samples and was less likely to occur in roots with poorer health, or in association with P. agathidicida. The abundance of P. agathidicida inoculum was lower in the soil around the phosphite-treated trees than around the untreated control trees 1.5 years after treatment at Waitoki. Phosphite halted the lateral expansion of basal resin bleeds, and resin viscosity was reduced. Not only did phosphite treatments improve kauri dieback symptoms, but the phosphite treatments potentially had a direct impact on the epidemiology of the disease by reducing inoculum load around treated trees, with direct implications for disease management as an effective way to protect uninfected areas and minimise the spread of inoculum from infested zones.

Environmental DNA reveals spatial and temporal variation in fish communities before the 10-year fishing ban in the Poyang Lake Basin

Poyang Lake is the largest freshwater lake in China, and its unique ecosystem is an important biodiversity reservoir. Fish play an important role in the aquatic ecosystem of Poyang Lake. Accurate assessment of fish species diversity and community composition is essential for studies of fish ecology and conservation management. In this study, environmental DNA metabarcoding was used to analyze fish diversity and community structure in different habitats and seasons in the Poyang Lake Basin. A total of 52 fish species were identified, and limnicolous fish were the most abundant; most fish were omnivorous and small. The fish diversity index was highest in the spring and in the main lake area of Poyang Lake. Cluster analysis and non-metric multidimensional scaling analysis revealed significant differences in fish community structure among habitats. Water temperature and pH were the main environmental factors affecting fish community structure in the Poyang Lake Basin. Non-invasive environmental DNA monitoring methods could provide an important auxiliary method for monitoring fishery resources during the 10-year fishing ban period. This study provides basic information on the fish resources in the Poyang Lake Basin and has implications for fishery management and the development of ecological protection policies.

Dammed coastal waterways are less diverse, more homogenous, and dominated by non-native species: Comprehensive insights from quantitative analysis of environmental DNA

Small dams are commonplace worldwide and impact local and regional aquatic diversity by altering habitats and disrupting dispersal networks. Quantifying the local and regional impacts of dams requires nearly comprehensive species occurrence data. We used environmental DNA (eDNA) metabarcoding to test theoretical predictions about the impacts of dams on local and regional bony fish diversity within the Chesapeake Bay Watershed, USA. We analyzed eDNA from 465 sampling points within 34 waterbodies documenting the distributions of 61 species. On average, dammed waterbodies had approximately half (48 %) as many species per site as undammed (lower alpha diversity) and more homogenous species composition (lower beta diversity). Native migratory species were less than one tenth (0.08) as likely to be detected at dammed sites than undammed sites, native resident (non-migratory) species were one third (0.34) as likely, whereas introduced species were 2.6 times more likely to be detected. Our sampling and bioinformatics methods were validated by a diverse mock community control. Our results suggest that dams in coastal waterways homogenize fish metacommunities, reduce local biodiversity through dispersal limitation and habitat alteration, and favor the dominance of lentic-adapted introduced species while potentially restricting the spread of introduced catfish. Decisions to construct or decommission dams should consider local and regional impacts on biodiversity.

Using environmental DNA metabarcoding to assess the spatiotemporal occurrence of the imperiled River Redhorse (Moxostoma carinatum) in the Escambia-Conecuh River system of Florida and Alabama, USA

Using environmental DNA metabarcoding to assess the spatiotemporal occurrence of the imperiled River Redhorse (Moxostoma carinatum) in the Escambia-Conecuh River system of Florida and Alabama, USA

Evaluating the quantitative performance of environmental DNA metabarcoding for freshwater zooplankton community: a case study in Lake Biwa, Japan.

Zooplankton monitoring is important for understanding their population dynamics and life history, ecosystem health, and environmental changes. Compared with traditional morphological identification, environmental DNA (eDNA) analysis allows for more sensitive and efficient monitoring of zooplankton diversity. Previous eDNA studies have primarily used metabarcoding approaches to reveal their richness and composition, whereas its performance in predicting zooplankton abundance remains understudied. We conducted water and bulk sampling in Lake Biwa, Japan, showing that the number of sequence reads by metabarcoding moderately correlated with eDNA concentrations estimated by quantitative real-time PCR (qPCR). In addition, the eDNA read number was significantly related to cladoceran and copepod abundance estimated by microscopy sorting, although there remained too much uncertainty in the read-abundance relationship. Moreover, there was a significant difference in species composition between eDNA metabarcoding and sorting. Although our results indicated the potential applicability of eDNA metabarcoding for quantifying multiple zooplankton abundance, several methodological validations in eDNA metabarcoding would also be required to optimize its performance in the future.

Environmental DNA metabarcoding in the Cape Fold aquatic ecoregion: Opportunities and challenges for eDNA uptake in an endemism hotspot

Abstract Environmental DNA (eDNA) metabarcoding has the potential to significantly improve surveys of biodiversity in freshwater systems. However, this methodology is still infrequently used in global hotspots of endemic species, in part because of two major barriers to the success of eDNA metabarcoding: (1) insufficient regional taxonomic representation in public reference sequence databases; and (2) inconsistent species incidence and abundance estimates when compared to conventional surveys. We sampled eDNA and conducted visual surveys in the headwaters of two rivers in the Cape Fold aquatic ecoregion, South Africa. A reference sequence database was generated for the regional diversity of fishes to improve taxonomic classification of endemic species. We also compared the consistency of incidence data and relative abundance estimates of fishes from eDNA metabarcoding sequencing results and visual surveys (snorkel and underwater cameras) at each site sampled. Only 1% of eDNA metabarcoding reads could be classified to fish species without the supplementation of reference sequence databases for local endemic species. Once regional reference sequences were added, a total of nine species were detected and >99% reads classified. A strong positive relationship (Φ = 0.75) was observed between the patterns of detections using eDNA and visual approaches. However, eDNA metabarcoding detected more species than visual methods. In addition, the relative read frequency and abundance observed in visual surveys was significantly correlated (R2 = 0.85–0.88, p < 0.001) in the majority of the small pools surveyed. Incomplete public reference sequence databases hinder the use of eDNA metabarcoding in regions of high endemicity. Local reference sequence libraries can overcome these challenges. When appropriately implemented, eDNA metabarcoding shows promise, producing results consistent or better than the more frequently used and labour‐intensive visual surveys. Efficient survey methods like eDNA metabarcoding are urgently needed to improve aquatic monitoring efforts globally. Understanding how eDNA metabarcoding sequencing results relate to conventional survey methods is a key step in its implementation in ecoregions with high endemicity.

A systematic survey of environmental DNA in Palau's lakes and waterfalls reveals an increase in Leptospira levels after flooding

ObjectiveLeptospirosis is an important bacterial zoonosis which is widespread in tropical and subtropical islands and influences human and animal health which has secondary economic effects. Although leptospirosis is endemic in Palau, an Oceanian Pacific Island country, few systematic surveys of potential risk factors for Leptospira infection, such as weather and host animals, have been conducted in the natural environment. We used environmental DNA metabarcoding to assess the distribution, species diversity, and abundance of pathogenic Leptospira in this endemic region to investigate the potential environmental risks. MethodsForty-two paired water samples, representing fine and rainy weather conditions, were collected from four representative waterfalls and lakes on Babeldaob Island, the largest island in Palau. High-throughput sequencing analysis was conducted for polymerase chain reaction products of leptospiral 16S rRNA and vertebrate animal mitochondrial 12S rRNA genes. ResultsWe revealed greater Leptospira diversity and abundance in samples collected after continuous rain, particularly in the presence of flooding, compared with samples collected under typhoon, monsoon, or fine weather conditions. From same samples, six mammalian species including cats (Felis catus), mice (Mus musculus), Yap flying fox (Pteropus yapensis), rats (Rattus spp.), and pigs (Sus scrofa) were repeatedly detected. These may be candidates of host animals of Leptospira in Palau; however, their detection was not clearly correlated with that of Leptospira. ConclusionWe repeatedly detected several species of pathogenic Leptospira from water samples of a wide region of Babeldaob Island. We confirmed that Leptospira contamination in freshwater environments increased under rainy conditions, particularly in the presence of flooding. This information could be used to improve public health control measures in this region.

Using grass inflorescence as source material for biomonitoring through environmental DNA metabarcoding

BackgroundOver the last decade, increasing attention has been directed to using different substrates as sources of environmental DNA (eDNA) in ecological research. Reports on the use of environmental DNA located on the surface of plant leaves and flowers have highlighted the utility of this DNA source in studies including, but not limited to, biodiversity, invasive species, and pollination ecology. The current study assesses grass inflorescence as a source of eDNA for detecting invertebrate taxa.Methods and resultsInflorescences from four common grass species in a central South African grassland were collected for high-throughput sequencing analysis. Universal COI primers were utilised to detect Metazoan diversity. The sequencing results allowed for the detection of three Arthropoda orders, with most OTUs assigned to fungal taxa (Ascomycota and Basidiomycota). Some biases were detected while observing the relative read abundance (RRA) results.DiscussionThe observed biases could be explained by the accidental inclusion of invertebrate specimens during sample collection and DNA extraction. Primer biases towards the amplified taxa could be another reason for the observed RRA results. This study provided insight into the invertebrate community associated with the four sampled grass species. It should be noted that with the lack of negative field controls, it is impossible to rule out the influence of airborne eDNA on the observed diversity associated with each grass species. The lack of the inclusion of PCR and extraction blanks in the sequencing step, as well as the inclusion of negative field controls, including other areas for refinement were highlighted, and suggestions were provided to improve the outcomes of future studies.

A comparative analysis of eDNA metabarcoding and field surveys: Exploring freshwater plant communities in rivers

While environmental DNA (eDNA) metabarcoding holds promise as a holistic approach to assess vegetation changes and community composition across diverse spatial and temporal scales, systematic investigations of its efficacy compared to conventional field surveys remain scarce in the literature. The present study explores the differences in plant diversity recovered from field surveys and captured with a multi-marker eDNA metabarcoding approach (two nrDNA ITS1 and ITS2, and two cpDNA rbcL and trnL) from river water samples. The eDNA metabarcoding approach retrieved 46 aquatic plants (hydrophytes and helophytes) and 245 terrestrial plants, compared to 24 and 127 species identified from field surveys. On average, eDNA samples collected immediately downstream of the survey sites recovered 43 % and 39 % of the aquatic and terrestrial species observed, respectively. Discrepancies were explained by differences in taxonomic resolution, the stochasticity of the retrieval of rare and elusive species, and the presence of reference sequences. We found a significant positive correlation between spatial and community distances at scales ranging from 2 to 9 km and identified turnover as the driving force of these differences. Metabarcoding demonstrated sensitivity to community changes and both approaches converge on a similar community structure. Interestingly, eDNA samples collected immediately upstream of the survey sites exhibited significant species overlap with the downstream samples (c. 100 m apart). Overall, our results demonstrate that within-site species mismatches between the methods are nonnegligible, and they question the use of eDNA for generating complete species lists at scales comparable to our field surveys (< 100-m transects). However, with adequate sampling and a multi-marker metabarcoding approach, eDNA has the potential to approximate catchment gamma diversity with less sampling effort than conventional surveys.

Supervised machine learning for understanding and predicting the status of bistable eukaryotic plankton community in urbanized rivers

Understanding and predicting the ecological status of urbanized rivers is crucial for their restoration and management. However, the complex and nonlinear nature of ecological responses poses a challenge to the development of predictive models. Here, the study investigated and predicted the status of eukaryotic plankton communities in urbanized rivers by coupling environmental DNA metabarcoding, the alternative stable states theory, and supervised machine learning (SML) models. The results revealed two distinct states of eukaryotic plankton communities under similar environmental conditions: one state was characterized by the enrichment of a diverse phytoplankton population and the high relative abundance of protozoa, whereas the alternative state was characterized by abundant phytoplankton and fungi with an associated risk of algal blooms. Turbidity was identified as a key driver based on the SML model and Mantel test. Potential analysis demonstrated that the response pattern of eukaryotic plankton communities to turbidity was thresholds with hysteresis (Threshold1 = 17 NTU, Threshold2 = 24 NTU). A reduction in turbidity induced a regime shift in the eukaryotic plankton community toward an alternative state associated with a risk of algal blooms. In the prediction of ecological status, both SML models showed excellent performance (R2 > 0.80, RMSE < 0.1, Kappa > 0.70). Additionally, SHapley Additive exPlanations analysis identified turbidity, chlorophyll-a, chemical oxygen demand (COD), ammonia nitrogen and green algae's amplicon sequence variants as crucial features for prediction, with turbidity and COD showing a synergistic effect on ecological status. A framework was further proposed to enhance the understanding and prediction of ecological status in urbanized rivers. The obtained results of this study demonstrated the feasibility of using SML models to predict and explain the ecological status of urbanized rivers with alternative stable states. This provides valuable insights for the application of SML models in the restoration and management of urbanized rivers.

Structural variability of protist assemblages in surface sediments across Italian Mediterranean marine subregions

Marine sediments host heterogeneous protist communities consisting of both living benthic microorganisms and planktonic resting stages. Despite their key functions in marine ecosystem processes and biogeochemical cycles, their structure and dynamics are largely unknown. In the present study, with a spatially intensive sampling design we investigated benthic protist diversity and function of surface sediment samples from three subregions of the Mediterranean Sea, through an environmental DNA metabarcoding approach targeting the 18S V4 region of rRNA gene. Protists were characterized at the taxonomic level and trophic function, both in terms of alpha diversity and community composition, testing for potential differences among marine subregions and bathymetric groups. Overall, Alveolata and Stramenopiles were the two divisions that dominated the communities. These dominant groups exhibited significant differences among the three Mediterranean subregions in the alpha diversity estimates based on the detected ASVs, for all computed indices (ASV richness, Shannon and Simpson indices). Protist communities were also found to be significantly different in terms of composition at the order rank in the three subregions p-value &amp;lt; 0.01). These differences were mainly driven by Anoecales, Peridiniales, Borokales, Paraliales and Gonyaulacales, which together contributed almost 80% of the average dissimilarity. Anoecales was the dominant order in the Ionian – Central Mediterranean and Adriatic Sea, but with considerably different relative abundances (52% and 36%, respectively), while Borokales was the dominant order in the Western Mediterranean Sea (33%). Similarly, significant differences among the three marine subregions were also highlighted when protist assemblages were examined in terms of trophic function, both in terms of alpha diversity (calculated on the ASVs for each trophic group) and community composition p-value &amp;lt; 0.01. In particular, the Adriatic Sea stood out for having the highest relative abundance of autotrophic/mixotrophic components in the surface sediments analyzed. Conversely, no significant differences in protist assemblages were found among depth groups. This study provided new insights into the taxonomic and trophic composition of benthic protist communities found in Mediterranean surface sediments, revealing geographical differences among regional seas. The results were discussed in relation to the Mediterranean environmental features that could generate the differences among benthic protist communities.