Temporal Bacterial Surveillance of Salmon Aquaculture Sites Indicates a Long Lasting Benthic Impact With Minimal Recovery

Descriptive analyses of bacterial communities in marine sediment microcosms spiked with fish wastes, emamectin benzoate, and oxytetracycline

In marine sediments surrounding salmon aquaculture sites, organic matter (OM) enrichment has been shown to influence resident bacterial community composition; however, additional effects on these communities due to combined use of the sea-lice therapeutant emamectin benzoate (EMB) and the widely used antibiotic oxytetracycline (OTC) are unknown. Here, we use sediment microcosms to assess the influence of OM, EMB, and OTC on benthic bacterial communities. Microcosms consisted of mud or sand sediments enriched with OM (fish and feed wastes) and spiked with EMB and OTC at environmentally-relevant concentrations. Samples were collected from initial matrices at the initiation of the trial and after 110 days for 16 S rRNA gene sequencing of the V3-V4 region and microbiome profiling. The addition of OM in both mud and sand sediments reduced alpha diversities; for example, an average of 1106 amplicon sequence variants (ASVs) were detected in mud with no OM addition, while only 729 and 596 ASVs were detected in mud with low OM and high OM, respectively. Sediments enriched with OM had higher relative abundances of Spirochaetota, Firmicutes, and Bacteroidota. For instance, Spirochaetota were detected in sediments with no OM with a relative abundance range of 0.01-1.2%, while in sediments enriched with OM relative abundance varied from 0.16% to 26.1%. In contrast, the addition of EMB (60 ng/g) or OTC (150 ng/g) did not result in distinct taxonomic shifts in the bacterial communities compared to un-spiked sediments during the timeline of this experiment. EMB and OTC concentrations may have been below effective inhibitor concentrations for taxa in these communities; further work should explore gene content and the presence of antibiotic resistance genes (ARGs) in sediment-dwelling bacteria.

Simultaneous analysis of seven 16S rRNA hypervariable gene regions increases efficiency in marine bacterial diversity detection

Environmental DNA sequencing is the gold standard to reveal microbial community structures. In most applications, a one-fragment PCR approach is applied to amplify a taxonomic marker gene, usually a hypervariable region of the 16S rRNA gene. We used a new reverse complement (RC)-PCR-based assay that amplifies seven out of the nine hypervariable regions of the 16S rRNA gene, to interrogate bacterial communities in sediment samples collected from different coastal marine sites with an impact gradient. In parallel, we employed a traditional one-fragment analysis of the hypervariable V3-V4 region to investigate whether the RC-PCR reveals more of the 'unseen' diversity obtained by the one-fragment approach. As a benchmark for the full deck of diversity, we subjected the samples to PCR-free metagenomic sequencing. None of the two PCR-based approaches recorded the full taxonomic repertoire obtained from the metagenomics datasets. However, the RC-PCR approach detected 2.8 times more bacterial genera compared to the near-saturation sequenced V3-V4 samples. RC-PCR is an ideal compromise between the standard one-fragment approach and metagenomics sequencing and may guide future environmental sequencing studies, in which bacterial diversity is a central subject.

Biogeochemical impacts of fish farming on coastal sediments: Insights into the functional role of cable bacteria

Fish farming in sea cages is a growing component of the global food industry. A prominent ecosystem impact of this industry is the increase in the downward flux of organic matter, which stimulates anaerobic mineralization and sulfide production in underlying sediments. When free sulfide is released to the overlying water, this can have a toxic effect on local marine ecosystems. The microbially-mediated process of sulfide oxidation has the potential to be an important natural mitigation and prevention strategy that has not been studied in fish farm sediments. We examined the microbial community composition (DNA-based 16S rRNA gene) underneath two active fish farms on the Southwestern coast of Iceland and performed laboratory incubations of resident sediment. Field observations confirmed the strong geochemical impact of fish farming on the sediment (up to 150 m away from cages). Sulfide accumulation was evidenced under the cages congruent with a higher supply of degradable organic matter from the cages. Phylogenetically diverse microbes capable of sulfide detoxification were present in the field sediment as well as in lab incubations, including cable bacteria (Candidatus Electrothrix), which display a unique metabolism based on long-distance electron transport. Microsensor profiling revealed that the activity of cable bacteria did not exert a dominant impact on the geochemistry of fish farm sediment at the time of sampling. However, laboratory incubations that mimic the recovery process during fallowing, revealed successful enrichment of cable bacteria within weeks, with concomitant high sulfur-oxidizing activity. Overall our results give insight into the role of microbially-mediated sulfide detoxification in aquaculture impacted sediments.

How elevated nitrogen load affects bacterial community structure and nitrogen cycling services in coastal water

Nutrient pollution in the coastal environment has been accelerated by progressively intensifying aquaculture activities. Excessive nutrients can lead to coastal eutrophication with serious economic and ecological consequences. In this study, we studied coastal planktonic microbial community over a year to understand the aquaculture impact on coastal water quality and function. We observed increased total inorganic nitrogen concentrations in active fish farms to favor the diverse Alpha- and Gammaproteobacteria. Bacterial community alpha diversity in fish farms was positively correlated with total inorganic nitrogen, and active fish farming co-influenced the bacterial structural composition and regional beta diversity. By analyzing the nitrogen cycle-related functional compositions and pathways using PICRUSt2 prediction on inferred genomes, we identified the contribution of over 600 bacterial species to four major pathways. Enhanced nitrogen load in active fish farms was positively correlated with elevated dissimilatory nitrate reduction and denitrification pathway abundances. Fallowed fish farms were characterized by a predicted high abundance of nirA and narB genes contributing to assimilatory nitrate reduction pathway due to the prevalence of Cyanobacteria. Overall, these results suggested active operation and short hiatus in coastal aquaculture practices could rapidly impact planktonic bacterial communities and further influence nitrogen cycling and associated processes. These findings will improve the understanding of the responses and interactions between microbiome and aquaculture activities. In a world of increasing aquaculture demands, this work has important implications for sustainable water resource management and development.

Composition and functionality of bacterioplankton communities in marine coastal zones adjacent to finfish aquaculture

Finfish aquaculture is a fast-growing primary industry and is increasingly common in coastal ecosystems. Bacterioplankton is ubiquitous in marine environment and respond rapidly to environmental changes. Changes in bacterioplankton community are not well understood in semi-enclosed stratified embayments. This study aims to examine aquaculture effects in the composition and functional profiles of the bacterioplankton community using amplicon sequencing along a distance gradient from two finfish leases in a marine embayment. Results revealed natural stratification in bacterioplankton associated to NOx, conductivity, salinity, temperature and PO₄. Among the differentially abundant bacteria in leases, we found members associated with nutrient enrichment and aquaculture activities. Abundant predicted functions near leases were assigned to organic matter degradation, fermentation, and antibiotic resistance. This study provides a first effort to describe changes in the bacterioplankton community composition and function due to finfish aquaculture in a semi-enclosed and highly stratified embayment with a significant freshwater input.

Fine-scale differences in eukaryotic communities inside and outside salmon aquaculture cages revealed by eDNA metabarcoding

Aquaculture impacts on marine benthic ecosystems are widely recognized and monitored. However, little is known about the community changes occurring in the water masses surrounding aquaculture sites. In the present study, we studied the eukaryotic communities inside and outside salmonid aquaculture cages through time to assess the community changes in the neighbouring waters of the farm. Water samples were taken biweekly over five months during the production phase from inside the cages and from nearby points located North and South of the salmon farm. Eukaryotic communities were analyzed by eDNA metabarcoding of the partial COI Leray-XT fragment. The results showed that eukaryotic communities inside the cages were significantly different from those in the outside environment, with communities inside the cages having higher diversity values and more indicator species associated with them. This is likely explained by the appearance of fouling species that colonize the artificial structures, but also by other species that are attracted to the cages by other means. Moreover, these effects were highly localized inside the cages, as the communities identified outside the cages, both North and South, had very similar eukaryotic composition at each point in time. Overall, the eukaryotic communities, both inside and outside the cages, showed similar temporal fluctuations through the summer months, with diversity peaks occurring at the end of July, beginning of September, and in the beginning of November, with the latter showing the highest Shannon diversity and richness values. Hence, our study suggests that seasonality, together with salmonid aquaculture, are the main drivers of eukaryotic community structure in surface waters surrounding the farm.

Environmental monitoring tools and strategies in salmon net-pen aquaculture

As global salmon production accelerates in response to higher consumer demand for seafood, so does the need for sophisticated monitoring strategies to enable and maintain ethically sound, productive, and environmentally friendly production of fish. Innovative technologies are needed to ensure proper water quality, react to unfavorable hydrodynamic conditions, monitor for changes in fish health, and minimize ecological interactions with indigenous aquatic life, including fish escapes. Automated sensors connected wirelessly to data stations, visualization aids, and acoustic and physical tagging technologies are emerging tools capable of detecting environmental stress and its associated behavioral changes in farmed fish. Computer modeling of the monitoring data collected from a single salmon farm or collection of farms sharing a data network can be used to spot environmental trends vital for anticipating some of the consequences of climate change. Environmental regulations governing salmon farming in coastal areas are becoming more stringent in response to public pressures to protect coastal and ocean resources and to provide for multipurpose use of marine resources. As net-pen salmon aquaculture expands globally, new technologies will be essential to collect and interpret the anticipated larger volumes of data needed to meet these stringent regulatory requirements and to safeguard the high investment costs inherent in salmon farming. Integr Environ Assess Manag 2022;18:950-963. © SETAC.

Shifts in benthic bacterial communities associated with farming stages and a microbiological proxy for assessing sulfidic sediment conditions at fish farms

To assess the aquaculture-induced sediment conditions associated with sulfur cycles, shifts in bacterial communities across farming stages were investigated. The sulfate reduction rate (SRR), and concentrations of acid volatile sulfide (AVS) and H₂S were significantly higher at the mid- and post-farming stages than at the early stage, indicating that the aquaculture effects persist even after harvest. Incomplete organic carbon-oxidizing sulfate-reducing bacteria (IO-SRB) affiliated with Desulfobulbaceae, and gammaproteobacterial sulfur oxidizing bacteria (SOB) (Thiohalobacter, Thioprofundum, and Thiohalomonas) were dominant during the early stage, whereas fermenting bacteria (Bacteroidetes and Firmicutes) and complete oxidizing SRB (CO-SRB) belonging to Desulfobacteraceae, and epsilonproteobacterial SOB (Sulfurovum) dominated during the mid- and post-stages. The shift in SRB and SOB communities well reflected the anoxic and sulfidic conditions of farm sediment. Especially, the Sulfurovum-like SOB correlated highly and positively with H₂S, AVS, and SRR, suggesting that they could be relevant microbiological proxies to assess sulfidic conditions in farm sediment.

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.

Identifying the minimum amplicon sequence depth to adequately predict classes in eDNA-based marine biomonitoring using supervised machine learning

Environmental DNA metabarcoding is a powerful approach for use in biomonitoring and impact assessments. Amplicon-based eDNA sequence data are characteristically highly divergent in sequencing depth (total reads per sample) as influenced inter alia by the number of samples simultaneously analyzed per sequencing run. The random forest (RF) machine learning algorithm has been successfully employed to accurately classify unknown samples into monitoring categories. To employ RF to eDNA data, and avoid sequencing-depth artifacts, sequence data across samples are normalized using rarefaction, a process that inherently loses information. The aim of this study was to inform future sampling designs in terms of the relationship between sampling depth and RF accuracy. We analyzed three published and one new bacterial amplicon datasets, using a RF, based initially on the maximal rarefied data available (minimum mean of > 30,000 reads across all datasets) to give our baseline performance. We then evaluated the RF classification success based on increasingly rarefied datasets. We found that extreme to moderate rarefaction (50-5000 sequences per sample) was sufficient to achieve prediction performance commensurate to the full data, depending on the classification task. We did not find that the number of classification classes, data balance across classes, or the total number of sequences or samples, were associated with predictive accuracy. We identified the ability of the training data to adequately characterize the classes being mapped as the most important criterion and discuss how this finding can inform future sampling design for eDNA based biomonitoring to reduce costs and computation time.

Local dynamics of a white syndrome outbreak and changes in the microbial community associated with colonies of the scleractinian brain coral Pseudodiploria strigosa

Reef corals in the Mexican Reef System have been severely affected by the emergence of a white syndrome that resembles both White Plague II and SCTLD descriptions. Meandroid scleractinian coral species are among the most severely affected. To gain insight into this affliction we conducted a broad study in the brain coral Pseudodiploria strigosa at a rear reef site in the NE Mexican Caribbean. We describe macro and microscopical signals of the disease, characterize the outbreak dynamics, the tissue histopathology, explore immunological responses in the individuals, and compare microbial assemblages associated with the surface mucus layer of healthy and unhealthy colonies. At the study site, the white syndrome outbreak on P. strigosa showed a high incidence rate in summer-fall and a low one in winter, as well as low survival expectation of diseased colonies at the end of the study. After 306 days of observation, out of 96 tracked colonies, eight remained apparently healthy and seven were diseased. No effective resistance to colony disease progression was observed once white syndrome signs developed. Tissue loss rate during the study varied among colonies (mean = 10.8 cm², s.d. = 7.8 cm²) suggesting a complex relation between causal agents and colony resistance. The deterioration of tissues was evidenced from the basal to the surface body wall of polyps (up to 66% hypertrophy and liquefactive necrosis in unhealthy colonies), implying that microscopic alterations begin before macroscopic signals develop, suggesting this may be a systemic disease. We measured high levels of phenoloxidase (two orders of magnitude higher PO activity than P. strigosa affected by BBD) and antibacterial activity without significant reduction in unhealthy samples from the mucus layer, indicative of an enhanced immunological response. Results showed that opportunistic bacteria dominated damaged colonies, where six genera of the Bacteroidia class were found with significant changes in unhealthy colonies after DeSeq2 analysis. Nevertheless, histological observations did not support infection of the tissues. The opportunistic overload seems to be contained within the mucus layer but may be associated with the mortality of tissues in a yet unclear way. Future research should focus on experimental infections, the tracking of natural infections, and the immunocompetence of corals in the face of environmental pressures due to local, regional, and global impacts. If environmental deterioration is the primary cause of the continuing emergence and re-emergence of lethal coral diseases, as has been proposed by many authors, the only true option to effectively help preserve the coral reef biodiversity and services, is to restore the environmental quality of reef waters at the local scale and reduce greenhouse gases at the global scale.

Enrichment of potential pathogens in marine microbiomes with different degrees of anthropogenic activity

Anthropogenic activities in coastal marine ecosystems can lead to an increase in the abundance of potentially harmful microorganisms in the marine environment. To understand anthropogenic impacts on the marine microbiome, we first used publicly available microbial phylogenetic and functional data to establish a dataset of bacterial genera potentially related to pathogens that cause diseases (BGPRD) in marine organisms. Representatives of low-, medium- and highly impacted marine coastal environments were selected, and the abundance and composition of their microbial communities were determined by quantitative PCR and 16 S rRNA gene sequencing. In total, 72 BGPRD were cataloged, and 11, 36 and 37 BGPRD were found in low-, medium- and highly human-impacted ecosystems, respectively. The absolute abundance of BGPRD and the co-occurrence of antibiotic resistance genes (AGR) increased with the degree of anthropogenic perturbation in these ecosystems. Anthropogenically impacted coastal microbiomes were compositionally and functionally distinct from those of less impacted sites, presenting features that may contribute to adverse outcomes for marine macrobiota in the Anthropocene era.

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.

Supervised machine learning is superior to indicator value inference in monitoring the environmental impacts of salmon aquaculture using eDNA metabarcodes

Increasing anthropogenic impact and global change effects on natural ecosystems has prompted the development of less expensive and more efficient bioassessments methodologies. One promising approach is the integration of DNA metabarcoding in environmental monitoring. A critical step in this process is the inference of ecological quality (EQ) status from identified molecular bioindicator signatures that mirror environmental classification based on standard macroinvertebrate surveys. The most promising approaches to infer EQ from biotic indices (BI) are supervised machine learning (SML) and the calculation of indicator values (IndVal). In this study we compared the performance of both approaches using DNA metabarcodes of bacteria and ciliates as bioindicators obtained from 152 samples collected from seven Norwegian salmon farms. Results from standard macroinvertebrate-monitoring of the same samples were used as reference to compare the accuracy of both approaches. First, SML outperformed the IndVal approach to infer EQ from eDNA metabarcodes. The Random Forest (RF) algorithm appeared to be less sensitive to noisy data (a typical feature of massive environmental sequence data sets) and uneven data coverage across EQ classes (a typical feature of environmental compliance monitoring scheme) compared to a widely used method to infer IndVals for the calculation of a BI. Second, bacteria allowed for a more accurate EQ assessment than ciliate eDNA metabarcodes. For the implementation of DNA metabarcoding into routine monitoring programmes to assess EQ around salmon aquaculture cages, we therefore recommend bacterial DNA metabarcodes in combination with SML to classify EQ categories based on molecular signatures.