A spatio-temporal analysis of marine diatom communities associated with pristine and aged plastics.

Complex microbial communities colonize plastic substrates over time, strongly influencing their fate and potential impacts on marine ecosystems. Among the first colonizers, diatoms play an important role in the development of this 'plastiphere'. We investigated 936 biofouling samples and the factors influencing diatom communities associated with plastic colonization. These factors included geographic location (up to 800 km apart), duration of substrate submersion (1 to 52 weeks), plastics (5 polymer types) and impact of artificial ageing with UV light. Diatom communities colonizing plastic debris were primarily determined by their geographic location and submersion time, with the strongest changes occurring within two weeks of submersion. Several taxa were identified as early colonizers (e.g. Cylindrotheca, Navicula and Nitzschia spp.) with known strong adhesion capabilities. To a lesser extent, plastic-type and UV-ageing significantly affected community composition, with 14 taxa showing substrate-specificity. This study highlights the role of plastics types-state for colonization in the ocean.

Ecosystems monitoring powered by environmental genomics: A review of current strategies with an implementation roadmap.

A decade after environmental scientists integrated high-throughput sequencing technologies in their toolbox, the genomics-based monitoring of anthropogenic impacts on the biodiversity and functioning of ecosystems is yet to be implemented by regulatory frameworks. Despite the broadly acknowledged potential of environmental genomics to this end, technical limitations and conceptual issues still stand in the way of its broad application by end-users. In addition, the multiplicity of potential implementation strategies may contribute to a perception that the routine application of this methodology is premature or "in development", hence restraining regulators from binding these tools into legal frameworks. Here, we review recent implementations of environmental genomics-based methods, applied to the biomonitoring of ecosystems. By taking a general overview, without narrowing our perspective to particular habitats or groups of organisms, this paper aims to compare, review and discuss the strengths and limitations of four general implementation strategies of environmental genomics for monitoring: (a) Taxonomy-based analyses focused on identification of known bioindicators or described taxa; (b) De novo bioindicator analyses; (c) Structural community metrics including inferred ecological networks; and (d) Functional community metrics (metagenomics or metatranscriptomics). We emphasise the utility of the three latter strategies to integrate meiofauna and microorganisms that are not traditionally utilised in biomonitoring because of difficult taxonomic identification. Finally, we propose a roadmap for the implementation of environmental genomics into routine monitoring programmes that leverage recent analytical advancements, while pointing out current limitations and future research needs.

Environmental DNA surveys detect distinct metazoan communities across abyssal plains and seamounts in the western Clarion Clipperton Zone.

The deep seafloor serves as a reservoir of biodiversity in the global ocean, with >80% of invertebrates at abyssal depths still undescribed. These diverse and remote deep-sea communities are critically under-sampled and increasingly threatened by anthropogenic impacts, including future polymetallic nodule mining. Using a multigene environmental DNA (eDNA) metabarcoding approach, we characterized metazoan communities sampled from sediments, polymetallic nodules and seawater in the western Clarion Clipperton Zone (CCZ) to test the hypotheses that deep seamounts (a) are species richness hotspots in the abyss, (b) have structurally distinct communities in comparison to other deep-sea habitats, and (c) that seafloor particulate organic carbon (POC) flux and polymetallic nodule density are positively correlated with metazoan diversity. eDNA metabarcoding was effective at characterizing distinct biotas known to occur in association with different abyssal substrate types (e.g., nodule- and sediment-specific fauna), with distinct community composition and few taxa shared across substrates. Seamount faunas had higher overall taxonomic richness, and different community composition and biogeography than adjacent abyssal plains, with seamount communities displaying less connectivity between regions than comparable assemblages on the abyssal plains. Across an estimated gradient of low to moderate POC flux, we find lowest taxon richness at the lowest POC flux, as well as an effect of nodule size on community composition. Our results suggest that while abyssal seamounts are important reservoirs of metazoan diversity in the CCZ, given limited taxonomic overlap between seamount and plains fauna, conservation of seamount assemblages will be insufficient to protect biodiversity and ecosystem function in regions targeted for mining.

Elucidating Biodiversity Shifts in Ballast Water Tanks during a Cross-Latitudinal Transfer: Complementary Insights from Molecular Analyses.

In this study, the evolution of ballast water (BW) assemblages across different trophic levels was characterized over a 21 day cross-latitudinal vessel transit using a combination of molecular methods. Triplicate BW samples were collected every second day and size-fractionated (<2.7, 10, >50 µm). Measurements of adenosine triphosphate (ATP) and metabarcoding of environmental nucleic acid (DNA and RNA) analyses, complemented by microscopy and flow cytometry, were performed on each sample. Measured ATP concentrations exhibited high variance between replicates and a strong negative trend in the large (≥50 µm) fraction over the voyage. In concert with microscopy, the metabarcoding data indicated a die-off of larger metazoans during the first week of study and gradual reductions in dinoflagellates and ochrophytes. The ATP and metabarcoding data signaled persistent or increased cellular activity of heterotrophic bacteria and protists in the BW, which was supported by flow cytometry. The metabarcoding showed the presence of active bacteria in all size fractions, suggesting that the sequential filtration approach does not ensure taxonomical differentiation, which has implications for BW quality assessment. Although our data show that ATP and metabarcoding have potential for indicative BW screening for BW compliance monitoring, further research and technological development is needed to improve representativeness of sampling and deliver the unequivocal response criteria required by the international Ballast Water Management Convention.

Characterization of the transcriptional effects of the plastic additive dibutyl phthalate alone and in combination with microplastic on the green-lipped mussel Perna canaliculus.

The presence and persistence of microplastics (MPs) in diverse aquatic environments are of global concern. Microplastics can impact marine organisms via direct physical interaction and the release of potentially harmful chemical additives incorporated into the plastic. These chemicals are physically bound to the plastic matrix and can leach out. The hazards associated with chemical additives to exposed organisms is not well characterized. We investigated the hazards of plastic additives leaching from plastic. We used the common plasticizer dibutyl phthalate (DBP) as a chemical additive proxy and the New Zealand green-lipped mussel (Perna canaliculus) as a model. We used early-adult P. canaliculus exposed to combinations of virgin and DBP-spiked polyvinyl chloride (PVC), MPs, and DBP alone for 7 days. Whole transcriptome sequencing (RNA-seq) was conducted to assess whether leaching of DBP from MPs poses a hazard. The differences between groups were evaluated using pairwise permutational multivariate analysis of variance (PERMANOVA), and all treatments were significantly different from controls. In addition, a significant difference was seen between DBP and PVC MP treatment. Transcriptome analysis revealed that mussels exposed to DBP alone had the most differentially expressed genes (914), followed by PVC MP + DBP (448), and PVC MP (250). Gene ontology functional analysis revealed that the most enriched pathway types were in cellular metabolism, immune response, and endocrine disruption. Microplastic treatments enriched numerous pathways related to cellular metabolism and immune response. The combined exposure of PVC MP + DBP appears to cause combined effects, suggesting that DBP is bioavailable to the exposed mussels in the PVC MP + DBP treatment. Our results support the hypothesis that chemical additives are potentially an important driver of MP toxicity. Environ Toxicol Chem 2024;43:1604-1614. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Differential responses of selectively bred mussels (Perna canaliculus) to heat stress-survival, immunology, gene expression and microbiome diversity.

New Zealand's green-lipped mussel (Perna canaliculus) is an ecologically and economically important species. Marine heatwaves are increasing in frequency around NZ's coastline, and these events are correlated with increased stress and mortality of some aquaculture species. This study aimed to identify general biomarkers of heat stress in P. canaliculus and to assess whether responses differed between genetically distinct selectively bred mussels. We exposed three families of selectively bred mussels (families A, B and C) to three seawater temperature regimes in the laboratory: 1) a "control" treatment (ambient 12°C), 2) a 26°C heat challenge with a subsequent recovery period, and 3) a sustained 26°C heat challenge with no recovery. We investigated whether the survival, immune response (hemocyte concentration and viability, oxidative stress and total antioxidant capacity), hemocyte gene expression and gill microbiome differed between the families during the temperature challenges. In the sustained heat-stress treatment, family A had the highest survival rate (42% compared with 25% and 5% for families C and B, respectively). Gene expression levels significantly shifted during thermal stress and differed between families, with family A more dissimilar than families B and C. Family C had substantially more genes impacted by temperature treatment and timepoint than the other families, while family B had very little genes/pathways that responded to thermal stress. Genes related to heat shock proteins and immune responses (e.g., AIF1, CTSC, TOLL8, CASP9, FNTA, AHCY, CRYAB, PPIF) were upregulated in all families during heat stress. Microbiome species-richness differed between families before and during heat-stress, with family A having a distinctly different microbiome flora than the other families. Microbial diversity changed similarly in all families exposed to prolonged heat-stress, with species of Vibrio and Campylobacter increasing in these mussels. Our study highlights the use of non-lethal sampling of hemocytes as a diagnostic tool to explore the immune response and gene expression of selectively bred mussels, to predict their response to ocean warming. This approach can identify potential thermotolerant candidates for further selective breeding, which may increase the resilience of the mussel aquaculture industry in a warming ocean.

Prediction of Feed Efficiency and Performance-Based Traits in Fish via Integration of Multiple Omics and Clinical Covariates.

Fish aquaculture is a rapidly expanding global industry, set to support growing demands for sources of marine protein. Enhancing feed efficiency (FE) in farmed fish is required to reduce production costs and improve sector sustainability. Recognising that organisms are complex systems whose emerging phenotypes are the product of multiple interacting molecular processes, systems-based approaches are expected to deliver new biological insights into FE and growth performance. Here, we establish 14 diverse layers of multi-omics and clinical covariates to assess their capacities to predict FE and associated performance traits in a fish model (Oncorhynchus tshawytscha) and uncover the influential variables. Inter-omic relatedness between the different layers revealed several significant concordances, particularly between datasets originating from similar material/tissue and between blood indicators and some of the proteomic (liver), metabolomic (liver), and microbiomic layers. Single- and multi-layer random forest (RF) regression models showed that integration of all data layers provide greater FE prediction power than any single-layer model alone. Although FE was among the most challenging of the traits we attempted to predict, the mean accuracy of 40 different FE models in terms of root-mean square errors normalized to percentage was 30.4%, supporting RF as a feature selection tool and approach for complex trait prediction. Major contributions to the integrated FE models were derived from layers of proteomic and metabolomic data, with substantial influence also provided by the lipid composition layer. A correlation matrix of the top 27 variables in the models highlighted FE trait-associations with faecal bacteria (Serratia spp.), palmitic and nervonic acid moieties in whole body lipids, levels of free glycerol in muscle, and N-acetylglutamic acid content in liver. In summary, we identified subsets of molecular characteristics for the assessment of commercially relevant performance-based metrics in farmed Chinook salmon.

First transcriptome of the copepod Gladioferens pectinatus subjected to chronic contaminant exposures.

Contaminants are often at low concentrations in ecosystems and their effects on exposed organisms can occur over long periods of time and across multiple generations. Alterations to subcellular mechanistic pathways in response to exposure to contaminants can provide insights into mechanisms of toxicity that methods measuring higher levels of biological may miss. Analysis of the whole transcriptome can identify novel mechanisms of action leading to impacts in exposed biota. The aim of this study was to characterise how exposures to copper, benzophenone and diclofenac across multiple generations altered molecular expression pathways in the marine copepod Gladioferens pectinatus. Results of the study demonstrated differential gene expression was observed in cultures exposure to diclofenac (569), copper (449) and benzophenone (59). Pathways linked to stress, growth, cellular and metabolic processes were altered by exposure to all three contaminants with genes associated with oxidative stress and xenobiotic regulation also impacted. Protein kinase functioning, cytochrome P450, transcription, skeletal muscle contraction/relaxation, mitochondrial phosphate translocator, protein synthesis and mitochondrial methylation were all differentially expressed with all three chemicals. The results of the study also suggested that using dimethyl sulfoxide as a dispersant influenced the transcriptome and future research may want to investigate it's use in molecular studies. Data generated in this study provides a first look at transcriptomic response of G. pectinatus exposed to contaminants across multiple generations, future research is needed to validate the identified biomarkers and link these results to apical responses such as population growth to demonstrate the predictive capacity of molecular tools.

Understanding the Dynamic of POMS Infection and the Role of Microbiota Composition in the Survival of Pacific Oysters, Crassostrea gigas.

For over a decade, Pacific oyster mortality syndrome (POMS), a polymicrobial disease, induced recurring episodes of massive mortality affecting Crassostrea gigas oysters worldwide. Recent studies evidenced a combined infection of the ostreid herpesvirus (OsHV-1 µVar) and opportunistic bacteria in affected oysters. However, the role of the oyster microbiota in POMS is not fully understood. While some bacteria can protect hosts from infection, even minor changes to the microbial communities may also facilitate infection and worsen disease severity. Using a laboratory-based experimental infection model, we challenged juveniles from 10 biparental oyster families with previously established contrasted genetically based ability to survive POMS in the field. Combining molecular analyses and 16S rRNA gene sequencing with histopathological observations, we described the temporal kinetics of POMS and characterized the changes in microbiota during infection. By associating the microbiota composition with oyster mortality rate, viral load, and viral gene expression, we were able to identify both potentially harmful and beneficial bacterial amplicon sequence variants (ASVs). We also observed a delay in viral infection resulting in a later onset of mortality in oysters compared to previous observations and a lack of evidence of fatal dysbiosis in infected oysters. Overall, these results provide new insights into how the oyster microbiome may influence POMS disease outcomes and open new perspectives on the use of microbiome composition as a complementary screening tool to determine shellfish health and potentially predict oyster vulnerability to POMS. IMPORTANCE For more than a decade, Pacific oyster mortality syndrome (POMS) has severely impacted the Crassostrea gigas aquaculture industry, at times killing up to 100% of young farmed Pacific oysters, a key commercial species that is cultivated globally. These disease outbreaks have caused major financial losses for the oyster aquaculture industry. Selective breeding has improved disease resistance in oysters, but some levels of mortality persist, and additional knowledge of the disease progression and pathogenicity is needed to develop complementary mitigation strategies. In this holistic study, we identified some potentially harmful and beneficial bacteria that can influence the outcome of the disease. These results will contribute to advance disease management and aquaculture practices by improving our understanding of the mechanisms behind genetic resistance to POMS and assisting in predicting oyster vulnerability to POMS.

Beyond taxonomy: Validating functional inference approaches in the context of fish-farm impact assessments.

Characterization of microbial assemblages via environmental DNA metabarcoding is increasingly being used in routine monitoring programs due to its sensitivity and cost-effectiveness. Several programs have recently been developed which infer functional profiles from 16S rRNA gene data using hidden-state prediction (HSP) algorithms. These might offer an economic and scalable alternative to shotgun metagenomics. To date, HSP-based methods have seen limited use for benthic marine surveys and their performance in these environments remains unevaluated. In this study, 16S rRNA metabarcoding was applied to sediment samples collected at 0 and ≥1,200 m from Norwegian salmon farms, and three metabolic inference approaches (Paprica, Picrust2 and Tax4Fun2) evaluated against metagenomics and environmental data. While metabarcoding and metagenomics recovered a comparable functional diversity, the taxonomic composition differed between approaches, with genera richness up to 20× higher for metabarcoding. Comparisons between the sensitivity (highest true positive rates) and specificity (lowest true negative rates) of HSP-based programs in detecting functions found in metagenomic data ranged from 0.52 and 0.60 to 0.76 and 0.79, respectively. However, little correlation was observed between the relative abundance of their specific functions. Functional beta-diversity of HSP-based data was strongly associated with that of metagenomics (r ≥ 0.86 for Paprica and Tax4Fun2) and responded similarly to the impact of fish farm activities. Our results demonstrate that although HSP-based metabarcoding approaches provide a slightly different functional profile than metagenomics, partly due to recovering a distinct community, they represent a cost-effective and valuable tool for characterizing and assessing the effects of fish farming on benthic ecosystems.

Global Trends of Benthic Bacterial Diversity and Community Composition Along Organic Enrichment Gradients of Salmon Farms.

The analysis of benthic bacterial community structure has emerged as a powerful alternative to traditional microscopy-based taxonomic approaches to monitor aquaculture disturbance in coastal environments. However, local bacterial diversity and community composition vary with season, biogeographic region, hydrology, sediment texture, and aquafarm-specific parameters. Therefore, without an understanding of the inherent variation contained within community complexes, bacterial diversity surveys conducted at individual farms, countries, or specific seasons may not be able to infer global universal pictures of bacterial community diversity and composition at different degrees of aquaculture disturbance. We have analyzed environmental DNA (eDNA) metabarcodes (V3-V4 region of the hypervariable SSU rRNA gene) of 138 samples of different farms located in different major salmon-producing countries. For these samples, we identified universal bacterial core taxa that indicate high, moderate, and low aquaculture impact, regardless of sampling season, sampled country, seafloor substrate type, or local farming and environmental conditions. We also discuss bacterial taxon groups that are specific for individual local conditions. We then link the metabolic properties of the identified bacterial taxon groups to benthic processes, which provides a better understanding of universal benthic ecosystem function(ing) of coastal aquaculture sites. Our results may further guide the continuing development of a practical and generic bacterial eDNA-based environmental monitoring approach.

Dietary Exposure of Pacific Oyster (Crassostrea gigas) Larvae to Compromised Microalgae Results in Impaired Fitness and Microbiome Shift.

The Pacific oyster Crassostrea gigas is the world's most cultivated oyster and seed supply is heavily reliant on hatchery production where recurring mass mortality events are a major constraint. Outbreaks of bacterial infection via microalgal feed are frequently implicated in these mortalities. This study assessed the effects of feeding compromised microalgae to developing oyster larvae. Intentionally 'stressed' (high pH) or non-stressed microalgae were fed to 11 day-old oyster larvae at two feeding rations for 96 h, followed by a recovery period. Biological endpoints of larval performance were measured following the 96 h exposure and subsequent recovery. Bacterial communities associated with the microalgae feed, rearing seawater, and the oyster larvae, were characterized and correlated with effects on oyster fitness parameters. Feeding stressed algae to oyster larvae for 96 h increased the occurrence of deformities (>70% vs. 20% in control), reduced feeding and swimming ability, and slowed development. Following the recovery period, fewer larvae reached pediveliger stage (2.7% vs. 36% in control) and became spat (1.5% vs. 6.6% in control). The quantity of stressed algae supplied to oyster larvae also influenced overall larval performance, with high feeding rations generally causing greater impairment than low rations. Bacterial profiling using 16S rRNA showed that most bacterial families characterized in larval tissue were also present in larval rearing seawater and in the microalgae feed (98%). The rearing seawater showed the highest bacterial richness compared to the larval and the microalgal compartments, regardless of feeding regime. In larval tissue, bacterial richness was highest in stressed and high-feed treatments, and negatively correlated with larval fitness parameters. These results suggest significant dysbiosis induced by compromised feed and/or increased feed ration. Several bacterial genera (e.g., Halomonas, Marinomonas) were strongly associated with impaired larval performance while the presence of genera in larvae including Vibrio was closely associated with overfeeding. Our research demonstrated that metabarcoding can be effectively used to identify microbiota features associated with larval fitness.

Trace Metal Residues in Marine Mussels: A Global Survey.

Pressures from anthropogenic activities are causing degradation of estuarine and coastal ecosystems around the world. Trace metals are key pollutants that are released and can partition in a range of environmental compartments, to be ultimately accumulated in exposed biota. The level of pressure varies with locations and the range and intensity of anthropogenic activities. The present study measured residues of trace metals in Mytilus mussel species collected from a range of locations around the world in areas experiencing a gradient of anthropogenic pressures that we classified as low, moderate, or high impact. The data showed no grouping/impact level when sampling sites in all countries were incorporated in the analysis, but there was significant clustering/impact level for most countries. Overall, high-impact areas were characterized by elevated concentrations of zinc, lead, nickel, and arsenic, whereas copper and silver were detected at higher concentrations in medium-impact areas. Finally, whereas most metals were found at lower concentrations in areas classified as low impact, cadmium was typically elevated in these areas. The present study provides a unique snapshot of worldwide levels of coastal metal contamination through the use of Mytilus species, a well-established marine biomonitoring tool. Environ Toxicol Chem 2021;40:3434-3440. © 2021 SETAC.

Is a Central Sediment Sample Sufficient? Exploring Spatial and Temporal Microbial Diversity in a Small Lake.

(1) Background: Paleolimnological studies use sediment cores to explore long-term changes in lake ecology, including occurrences of harmful cyanobacterial blooms. Most studies are based on single cores, assuming this is representative of the whole lake, but data on small-scale spatial variability of microbial communities in lake sediment are scarce. (2) Methods: Surface sediments (top 0.5 cm) from 12 sites (n = 36) and two sediment cores were collected in Lake Rotorua (New Zealand). Bacterial community (16S rRNA metabarcoding), Microcystis specific 16S rRNA, microcystin synthetase gene E (mcyE) and microcystins (MCs) were assessed. Radionuclide measurements (210Pb, 137Cs) were used to date sediments. (3) Results: Bacterial community, based on relative abundances, differed significantly between surface sediment sites (p < 0.001) but the majority of bacterial amplicon sequence variants (88.8%) were shared. Despite intense MC producing Microcystis blooms in the past, no Microcystis specific 16S rRNA, mcyE and MCs were found in surface sediments but occurred deeper in sediment cores (approximately 1950's). 210Pb measurements showed a disturbed profile, similar to patterns previously observed, as a result of earthquakes. (4) Conclusions: A single sediment core can capture dominant microbial communities. Toxin producing Microcystis blooms are a recent phenomenon in Lake Rotorua. We posit that the absence of Microcystis from the surface sediments is a consequence of the Kaikoura earthquake two years prior to our sampling.

Broad and Fine Scale Variability in Bacterial Diversity and Cyanotoxin Quotas in Benthic Cyanobacterial Mats.

Benthic proliferations of Microcoleus autumnalis (basionym Phormidium autumnale) and closely related taxa are being reported with increasing frequency in streams and rivers worldwide. This species commonly produces the potent neurotoxin anatoxin, and exposure to this has resulted in animal fatalities and human health concerns. Bacterial communities within cyanobacterial assemblages can facilitate processes such as nutrient cycling and are posited to influence cyanobacterial growth and function. However, there is limited knowledge on spatial variability of bacterial communities associated with benthic cyanobacteria and anatoxin content and quotas. In this study, M. autumnalis-dominated mat samples were collected from six sites in two New Zealand streams. Associated bacterial communities were characterized using 16S rRNA metabarcoding, anatoxin content by liquid chromatography-mass spectrometry and anaC copies using droplet digital PCR. Bacterial assemblages differed significantly when amplicon sequence variants were compared between streams and most sites within streams. These differences were associated with conductivity, DRP, DIN, temperature, anatoxin concentration, and quota. Despite the differences in bacterial community composition; at phyla, class and order levels there was high similarity across spatial scales, with Bacteroidetes (ca. 67%) and Proteobacteria (ca. 25%) dominant. There was significant variability in total anatoxin concentrations between sites in both streams (p < 0.001). When the data were converted to anatoxin quotas variability was reduced, suggesting that the relative abundance of toxic genotypes is a key driver of total anatoxin concentrations in mats. This study demonstrates the complexity of microbial communities within M. autumnalis-dominated mats and highlights their likely important role in within-mat nutrient cycling processes.

Comparing sediment DNA extraction methods for assessing organic enrichment associated with marine aquaculture.

Marine sediments contain a high diversity of micro- and macro-organisms which are important in the functioning of biogeochemical cycles. Traditionally, anthropogenic perturbation has been investigated by identifying macro-organism responses along gradients. Environmental DNA (eDNA) analyses have recently been advocated as a rapid and cost-effective approach to measuring ecological impacts and efforts are underway to incorporate eDNA tools into monitoring. Before these methods can replace or complement existing methods, robustness and repeatability of each analytical step has to be demonstrated. One area that requires further investigation is the selection of sediment DNA extraction method. Environmental DNA sediment samples were obtained along a disturbance gradient adjacent to a Chinook (Oncorhynchus tshawytscha) salmon farm in Otanerau Bay, New Zealand. DNA was extracted using four extraction kits (Qiagen DNeasy PowerSoil, Qiagen DNeasy PowerSoil Pro, Qiagen RNeasy PowerSoil Total RNA/DNA extraction/elution and Favorgen FavorPrep Soil DNA Isolation Midi Kit) and three sediment volumes (0.25, 2, and 5 g). Prokaryotic and eukaryotic communities were amplified using primers targeting the 16S and 18S ribosomal RNA genes, respectively, and were sequenced on an Illumina MiSeq. Diversity and community composition estimates were obtained from each extraction kit, as well as their relative performance in established metabarcoding biotic indices. Differences were observed in the quality and quantity of the extracted DNA amongst kits with the two Qiagen DNeasy PowerSoil kits performing best. Significant differences were observed in both prokaryotes and eukaryotes (p < 0.001) richness among kits. A small proportion of amplicon sequence variants (ASVs) were shared amongst the kits (~3%) although these shared ASVs accounted for the majority of sequence reads (prokaryotes: 59.9%, eukaryotes: 67.2%). Differences were observed in the richness and relative abundance of taxonomic classes revealed with each kit. Multivariate analysis showed that there was a significant interaction between "distance" from the farm and "kit" in explaining the composition of the communities, with the distance from the farm being a stronger determinant of community composition. Comparison of the kits against the bacterial and eukaryotic metabarcoding biotic index suggested that all kits showed similar patterns along the environmental gradient. Overall, we advocate for the use of Qiagen DNeasy PowerSoil kits for use when characterizing prokaryotic and eukaryotic eDNA from marine farm sediments. We base this conclusion on the higher DNA quality values and richness achieved with these kits compared to the other kits/amounts investigated in this study. The additional advantage of the PowerSoil Kits is that DNA extractions can be performed using an extractor robot, offering additional standardization and reproducibility of results.

A comparison of droplet digital polymerase chain reaction (PCR), quantitative PCR and metabarcoding for species-specific detection in environmental DNA.

Targeted species-specific and community-wide molecular diagnostics tools are being used with increasing frequency to detect invasive or rare species. Few studies have compared the sensitivity and specificity of these approaches. In the present study environmental DNA from 90 filtered seawater and 120 biofouling samples was analyzed with quantitative PCR (qPCR), droplet digital PCR (ddPCR) and metabarcoding targeting the cytochrome c oxidase I (COI) and 18S rRNA genes for the Mediterranean fanworm Sabella spallanzanii. The qPCR analyses detected S. spallanzanii in 53% of water and 85% of biofouling samples. Using ddPCR S. spallanzanii was detected in 61% of water of water and 95% of biofouling samples. There were strong relationships between COI copy numbers determined via qPCR and ddPCR (water R2  = 0.81, p < .001, biofouling R2  = 0.68, p < .001); however, qPCR copy numbers were on average 125-fold lower than those measured using ddPCR. Using metabarcoding there was higher detection in water samples when targeting the COI (40%) compared to 18S rRNA (5.4%). The difference was less pronounced in biofouling samples (25% COI, 29% 18S rRNA). Occupancy modelling showed that although the occupancy estimate was higher for biofouling samples (ψ = 1.0), higher probabilities of detection were derived for water samples. Detection probabilities of ddPCR (1.0) and qPCR (0.93) were nearly double metabarcoding (0.57 to 0.27 marker dependent). Studies that aim to detect specific invasive or rare species in environmental samples should consider using targeted approaches until a detailed understanding of how community and matrix complexity, and primer biases affect metabarcoding data.

Preliminary analysis of New Zealand scampi (Metanephrops challengeri) diet using metabarcoding.

Deep sea lobsters are highly valued for seafood and provide the basis of important commercial fisheries in many parts of the world. Despite their economic significance, relatively little is known about their natural diets. Microscopic analyses of foregut content in some species have suffered from low taxonomic resolution, with many of the dietary items difficult to reliably identify as their tissue is easily digested. DNA metabarcoding has the potential to provide greater taxonomic resolution of the diet of the New Zealand scampi (Metanephrops challengeri) through the identification of gut contents, but a number of methodological concerns need to be overcome first to ensure optimum DNA metabarcoding results. In this study, a range of methodological parameters were tested to determine the optimum protocols for DNA metabarcoding, and provide a first view of M. challengeri diet. Several PCR protocols were tested, using two universal primer pairs targeting the 18S rRNA and COI genes, on DNA extracted from both frozen and ethanol preserved samples for both foregut and hindgut digesta. The selection of appropriate DNA polymerases, buffers and methods for reducing PCR inhibitors (including the use of BSA) were found to be critical. Amplification from frozen or ethanol preserved gut contents appeared similarly dependable. The COI gene was found to be more effective than 18S rRNA gene for identifying large eukaryotic taxa from the digesta; however, it was less successfully amplified. The 18S rRNA gene was more easily amplified, but identified mostly smaller marine organisms such as plankton and parasites. This preliminary analysis of the diet of M. challengeri identified a range of species (13,541 reads identified as diet), which included the ghost shark (Hydrolagus novaezealandiae), silver warehou (Seriolella punctata), tall sea pen (Funiculina quadrangularis) and the salp (Ihlea racovitzai), suggesting that they have a varied diet, with a high reliance on scavenging a diverse range of pelagic and benthic species from the seafloor.

Incorporating molecular-based functional and co-occurrence network properties into benthic marine impact assessments.

Taxonomic and functional community structures may respond differently to anthropogenic stressors. Used in combination they can provide an estimate of functional redundancy, a key component of ecosystem resilience. In this study, the utility of incorporating functional community structure and co-occurrence network properties into impact assessments of offshore oil and gas (O&G) operations on benthic bacterial communities was investigated. Sediment samples and physico-chemical data were collected along a transect at increasing distances from one exploratory drilling (ED), and one gas production and drilling (GPD) field. Bacterial community composition was determined by 16S rRNA metabarcoding. A hidden-state prediction method (PAPRICA) was used to characterize bacterial metabolic community functions. At both sites, diversity differed significantly between near-field (impacted) and far-field (non-impacted) stations, with both taxonomic and functional alpha-diversity positively affected in near-field stations at the GPD site. The opposite pattern was observed in the near-field samples of ED with lower and higher values respectively. Overall, impacted stations displayed a distinct network signature, with a lower ratio of positive interactions and signs of higher community cohesion. Community profiles from metabolic inference and co-occurrence network topology provided complementary information to taxonomic indices, which may assist with assessing the effects of O&G activities on benthic communities.

Combining morpho-taxonomy and metabarcoding enhances the detection of non-indigenous marine pests in biofouling communities.

Marine infrastructure can favor the spread of non-indigenous marine biofouling species by providing a suitable habitat for them to proliferate. Cryptic organisms or those in early life stages can be difficult to distinguish by conventional morphological taxonomy. Molecular tools, such as metabarcoding, may improve their detection. In this study, the ability of morpho-taxonomy and metabarcoding (18S rRNA and COI) using three reference databases (PR2, BOLD and NCBI) to characterize biodiversity and detect non-indigenous species (NIS) in biofouling was compared on 60 passive samplers deployed over summer and winter in a New Zealand marina. Highest resolution of metazoan taxa was identified using 18S rRNA assigned to PR2. There were higher assignment rates to NCBI reference sequences, but poorer taxonomic identification. Using all methods, 48 potential NIS were identified. Metabarcoding detected the largest proportion of those NIS: 77% via 18S rRNA/PR2 and NCBI and 35% via COI/BOLD and NCBI. Morpho-taxonomy detected an additional 14% of all identified NIS comprising mainly of bryozoan taxa. The data highlight several on-going challenges, including: differential marker resolution, primer biases, incomplete sequence reference databases, and variations in bioinformatic pipelines. Combining morpho-taxonomy and molecular analysis methods will likely enhance the detection of NIS from complex biofouling.