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19 pages, 6 figures, 4 tables, supporting information https://doi.org/10.1111/1462-2920.16153.-- Data Availability Statement: The data that support the findings of this study are openly available in GitHub at http://github.com/lanzen/Garate_et_al_2022_data. Raw sequences are available from the INSDC Sequence Read Archive with BioProject number PRJEB54766, Pico- and nanoplankton are key players in the marine ecosystems due to their implication in the biogeochemical cycles, nutrient recycling and the pelagic food webs. However, the specific dynamics and niches of most bacterial, archaeal and eukaryotic plankton remain unknown, as well as the interactions between them. Better characterization of these is critical for understanding and predicting ecosystem functioning under anthropogenic pressures. We used environmental DNA metabarcoding across a 6-year time series to explore the structure and seasonality of pico- and nanoplankton communities in two sites of the Bay of Biscay, one coastal and one offshore, and construct association networks to reveal potential keystone and connector taxa. Temporal trends in alpha diversity were similar between the two sites, and concurrent communities more similar than within the same site at different times. However, we found differences between the network topologies of the two sites, with both shared and site-specific keystones and connectors. For example, Micromonas, with lower abundance in the offshore site is a keystone here, indicating a stronger effect of associations such as resource competition. This study provides an example of how time series and association network analysis can reveal how similar communities may function differently despite being geographically close, This study was financed by a ‘Retos Investigación: Proyectos I + D + i 2018’ grant (RTI2018-101018-A-I00) from the Spanish government. Laura Alonso-Sáez was supported by a ‘Ramon y Cajal’ Grant from the Spanish Government. The environmental data for this study were obtained from the project ‘Program for the monitoring and assessment of the ecological status of transitional and coastal waters of the Basque Country’ funded by URA, the Basque Water Agency, through a convention with AZTI. Anders Lanzén is further supported by a Research Fellow contract from IKERBASQUE (Basque Foundation for Science), With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)

Metabarcoding of environmental DNA (eDNA) is an attractive complement to morphological methods for surveys and routine monitoring of marine sediment benthic communities. However, metabarcoding and other genetic techniques are heavily affected by choices made during sampling, processing, and analysis. Here, we investigated the effect of different eDNA extraction protocols on observed alpha- and beta diversity of replicates from the same grab. Specifically, we compared (A) homogenization intensity during sediment DNA extraction, (B) extraction replicates vs larger sediment extraction volume, and (C) pre- and post-PCR extract pooling. Using the 18S V1-V2 region marker, we show that a Precellys homogenizer protocol during DNA extraction can significantly improve sediment metabarcoding results in terms of captured diversity and inter-replicate homogeneity compared to vortexing only. This effect superseded that of increased sediment extract volume. Pre-PCR pooling of DNA extraction replicates increased observed rarefied richness compared to data from single extracts only, but not to the extent of sample extract replicates amplified individually before pooling. We argue that this discrepancy was due to a reduction both in recovered sample diversity, but also the number of PCR artifacts and PCR drift. Our results demonstrate that extraction replicates of smaller sediment volumes, in combination with moderate Precellys homogenization and pre-PCR pooling, are a cost-effective way to increase the amount of organism diversity that is recovered from sediment eDNA metabarcoding samples. publishedVersion

Routine monitoring of benthic biodiversity is critical for managing and understanding the anthropogenic impacts on marine, transitional and freshwater ecosystems. However, traditional reliance on morphological identification generally makes it cost-prohibitive to increase the scale of monitoring programmes. Metabarcoding of environmental DNA has clear potential to overcome many of the problems associated with traditional monitoring, with prokaryotes and other microorganisms showing particular promise as bioindicators. However, due to the limited knowledge regarding the ecological roles and responses of environmental microorganisms to different types of pressure, the use of de novo approaches is necessary. Here, we use two such approaches for the prediction of multiple impacts present in estuaries and coastal areas of the Bay of Biscay based on microbial communities. The first (Random Forests) is a machine learning method while the second (Threshold Indicator Taxa Analysis and quantile regression splines) is based on de novo identification of bioindicators. Our results show that both methods overlap considerably in the indicator taxa identified, but less for sequence variants. Both methods also perform well in spite of the complexity of the studied ecosystem, providing predictive models with strong correlation to reference values and fair to good agreement with ecological status groups. The ability to predict several specific types of pressure is especially appealing. The cross-validated models and biotic indices developed can be directly applied to predict the environmental status of estuaries in the same geographical region, although more work is needed to evaluate and improve them for use in new regions or habitats.

Supplementary data to this article can be found online at https://doi. org/10.1016/j.scitotenv.2021.151783, Environmental DNA (eDNA) metabarcoding (parallel sequencing of DNA/RNA for identification of whole communities within a targeted group) is revolutionizing the field of aquatic biomonitoring. To date, most metabarcoding studies aiming to assess the ecological status of aquatic ecosystems have focused on water eDNA and macroinvertebrate bulk samples. However, the eDNA metabarcoding has also been applied to soft sediment samples, mainly for assessing microbial or meiofaunal biota. Compared to classical methodologies based on manual sorting and morphological identification of benthic taxa, eDNA metabarcoding offers potentially important advantages for assessing the environmental quality of sediments. The methods and protocols utilized for sediment eDNA metabarcoding can vary considerably among studies, and standardization efforts are needed to improve their robustness, comparability and use within regulatory frameworks. Here, we review the available information on eDNA metabarcoding applied to sediment samples, with a focus on sampling, preservation, and DNA extraction steps. We discuss challenges specific to sediment eDNA analysis, including the variety of different sources and states of eDNA and its persistence in the sediment. This paper aims to identify good-practice strategies and facilitate method harmonization for routine use of sediment eDNA in future benthic monitoring., The work is the result of the DNAqua-Net workshop held in Rome, on June 10–12, 2019, organised by IRSA-CNR and supported by European Cooperation in Science and Technology (COST) grant CA15219 (DNAqua-Net). It largely benefited from the discussions with DNAqua-Net members during this event as well as other DNAqua-Net conferences.This study was carried out within the UNIVPM VIRIDE Project (n. 2017EKFA98) funded by the Ministry of University and Research of Italy (MUR) and the Italian National Project on the use of environmental DNA for the identification of marine non-indigenous species funded by the Istituto Superiore per la Protezione e la Ricerca Ambientale (ISPRA). JP, TC, and LAPG were supported by the Swiss National Science Foundation (grant 31003A_179125) as well as FL with an Early Postdoc.Mobility grant (P2GEP3_171829). MS-M was supported by the Ministry of Education, Youth and Sports of the Czech Republic, European Regional Development Fund-Project CZ.02.1.01/0.0/0.0/16_019/0000845 and LTC 20063. KP was supported by the European Regional Development Fund within National Programme for Addressing Socio-Economic Challenges through R&D (L190003VLVI RITA1/02-60-05) and base financed project P190250PKKH of Estonian University of Life Sciences, IM was supported by the Slovenian Research Agency (ARRS) programme P4-0085. SD was supported by the Portuguese Foundation for Science and Technology (FCT) (CEECIND/00667/2017). LC was supported by the PON AIM 1854833 – PON Ricerca e Innovazione 2014–2020 – Azione I.2 – D.D. n. 407, 27/02/2018 – Attraction and International Mobility.VK was supported by grants PUT1389 (ETAg) and Institute of Technology, University of Tartu basic funding grant.

Technosols can be used to rehabilitate degraded land and reuse wastes. Ideally, these newly formed soils should also fulfil the main soil functions. In this study, initially, we characterized the physicochemical and microbial properties of different formulations and their ingredients (i.e., dirt from a waste recovery plant, recycled bentonite, sewage sludge). When these technosols were then used for the rehabilitation of a quarry, the evolution of such properties was monitored for three consecutive years. Physicochemical and microbial properties were compared to those of a reference soil from a nearby forest. Diversity and composition of prokaryotes and eukaryotes were determined using 16S and 18S rRNA amplicon sequencing. Three years after establishment, as much as 78.8% and 63.9% of the prokaryotic and eukaryotic orders, respectively, were shared between the technosols and the reference forest soil. Although technosols initially showed lower values of CO2 emission, compaction and functional diversity (Biolog EcoPlates™), at the end of the study these values were similar to those observed in the reference forest soil. It was concluded that the microbiota of the studied technosols resembles that of the nearby forest soil after just three years of establishment.

Livestock manure-derived amendments can be beneficial for agricultural soil quality, as they can increase the content of soil organic matter and nutrients, stimulate microbial activity and biomass, and enhance crop yield. Here, we studied the impact of six different manure-derived amendments, according to the origin (horse manure-derived vs. chicken manure-derived) and type of amendment (fresh vs. composted vs. bokashi), on agricultural soil quality. To this purpose, an experiment was conducted with lettuce plants, paying special attention to amendment-induced changes in soil microbial properties and the abundance and risk of dissemination of antibiotic resistance genes (ARGs) through horizontal gene transfer (HGT). Soils amended with fresh manure showed higher values of microbial biomass and activity. In particular, fresh chicken manure yielded the highest crop yield of lettuce, but also increased the abundance of ARGs considerably. Genes encoding mobile genetic elements (tnpA, intI1) were positively correlated with ARGs, suggesting a risk of dissemination of antibiotic resistance via HGT in agricultural soils, as a result of the application of livestock manure-derived amendments. In order to minimize this risk, we therefore suggest that manure-derived amendments be properly treated and managed prior to their application to agricultural soil.

Estuarine and coastal ecosystems play a fundamental role in human activities. Since millions of people depend on the numerous resources they offer (i.e., fisheries, transportation, and recreational activities), these ecosystems are also exposed to a high anthropogenic pressure. In order to better monitor and regulate such pressures, it is critical to improve our understanding of the functioning of these ecosystems. This is especially important for microorganisms, considering, for instance, their important roles in biogeochemical cycles. In this study we investigate estuarine and coastal microbial communities along the coast of the Basque Country using eDNA metabarcoding of bacterioplankton and microbenthos samples along a time series, from locations that present different degrees of disturbance. Metabarcoding of the 16S and 18S rRNA gene was carried out, and the OTU and taxa tables generated were used to reconstruct ecological networks, representing potential biological interactions. These ecological networks were used to identify on one hand the species that play a major role in the maintenance of the whole community structure (keystones), and on the other, complex network modules affected by environmental impacts. Here, we define keystone taxa as those that presented the highest ratio between the degree of connectivity (number of associations they established within the network) and their relative abundance. The underlying aim of this study is to develop novel “bioindicators” based on taxa that are both sensitive to impacts and important for community structure. Results of two seawater communities, one from offshore waters and the other from the coast, showed similar bacterial composition at family level, dominated by Flavobacteraceae and Rhodobacteraceae. Nevertheless, their ecological network properties differed strongly: for a similar number of taxa that established associations, the conectance was similar in both communities, but the number of associations in the coastal community was twice as high as for the offshore one, resulting in a higher modularity. Identified keystone taxa were taxonomically different between both communities: those from the coastal community belonged to Protobacteria, Bacteroidetes, Firmicutes, and Fusobacteria phyla, while the keystones from the offshore community belonged to Proteobacteria, Actinobacteria, Chloroflexi, Thaumarchaeota, PAUC34f and Verrucomicrobia. Moreover, we identified “connector” taxa that presented the highest values of betweenness centrality. These taxa, without having a high degree of connectivity, may be important for the interaction structure because they connect modules, i.e., highly connected subnetworks within the whole network. Further, hierarchical clustering was performed to identify seasonal trends and to better understand the associations retrieved. Taxa with different seasonal preference often grouped together in the same modules, which indicates that modularity was not caused primarily by seasonality.

Routine biological monitoring of the areas affected by offshore oil drilling and extraction is critical for ensuring proper environmental management. In addition to sufficient knowledge of the ecosystem affected, formalised e.g. as biotic indices of indicator species, adequate temporal and spatial resolution is also required, to provide accurate information. As already demonstrated in several types of environments, environmental DNA (eDNA) metabarcoding offers an attractive alternative to current morphology-based assessments, including for impacts of oil extraction or spills. We have recently studied the influence of different experimental strategies on the accuracy of marine sediment metabarcoding, suggesting minimum criteria for technical and spatial replication (Hestetun et al. 2020). Here, we aim to evaluate the predictive power of this strategy, through agreement with assessments based on physicochemical measurements and current bioindicators. To this end, we targeted the metazoan, and total eukaryotic benthic communities, using COI and 18S V1-V2 markers, respectively. Sampled sites ranged from high to low impacts. The studied areas were located near active production installations and reference sites on the Norwegian continental shelf, in the North Sea and Barents Sea. As a proxy for accumulated impact, we developed a simple physicochemical pressure index (PI) based on total hydrocarbons, PAH16, barium and copper, all of which agreed well with impact reported from recent routine monitoring. Alpha diversity of both molecular datasets, as well as of morphology data, correlated strongly with this PI. However, the correlation was stronger yet with the macroinvertebrate-based Norwegian Sensitivity Index (NSI) derived from COI metabarcoding data, which also agreed well with NSI values derived from morphology-based monitoring. We also identified a set of bioindicator taxa from each of the two metabarcoding datasets, used to develop two novel metabarcoding-based biotic indeces. Using cross-validation, we demonstrated that predictions based on these indeces agreed well with PI. Predictive performance was better, and similar to NSI, for the COI-based index, but also high for the 18S-based version. In conclusion, this study demonstrates how de novo biotic indices can be developed, that perform comparably to existing biotic indices. We are confident that, using a larger set of samples, performance can be improved beyond that of current monitoring practices. Thanks to the reduced costs of eDNA analysis in comparison to morphological identifiation, this would also pave the way for improved spatial and temporal resolution employed in routine environmental monitoring. In doing so, it can also provide valuable raw data for improving our understanding of benthic ecology, biodiversity and its sensitivity to anthropogenic pressures.

Monitoring and assessment of benthic communities have been routinely undertaken using morphology-based benthic indices, among which AZTI’s Marine Biotic Index (AMBI) and multivariate-AMBI (M-AMBI), are the most successful worldwide (Borja et al., 2019). They are used officially in routine monitoring in many European countries, where they have been intercalibrated (European Commission, 2018). AMBI has been mirrored by metabarcoding, and the genomic version (gAMBI; Aylagas et al., 2014) has demonstrated to yield results comparable to the morphological version. However, we have so far failed to develop a reliable genomic version of M-AMBI (M-gAMBI), which includes gAMBI, richness and diversity (Aylagas et al., 2018). This is because richness and diversity present very different results in morphological and genomic analyses. Since the multivariate method needs reference conditions, these must be set specifically for M-gAMBI to make its results comparable to those obtained with M-AMBI. To this aim, we started annual surveys in 2018, in 22 sampling locations, in Basque estuaries and coast. We present the results from the first three years of these surveys and discuss the problems faced when developing genomic reference conditions for M-gAMBI. The findings are of paramount importance for managers, since any new method or modification of an existing assessment method, needs to demonstrate that the results obtained when assessing the status are similar to those morphological-based methods, already approved and intercalibrated. Aylagas, E., Á. Borja, N. Rodríguez-Ezpeleta, 2014. Environmental Status Assessment Using DNA Metabarcoding: Towards a Genetics Based Marine Biotic Index (gAMBI). PLoS ONE, 9: e90529. Aylagas, E., Á. Borja, I. Muxika, N. Rodríguez-Ezpeleta, 2018. Adapting metabarcoding-based benthic biomonitoring into routine marine ecological status assessment networks. Ecological Indicators, 95: 194-202. Borja, A., G. Chust, I. Muxika, 2019. Chapter Three - Forever young: The successful story of a marine biotic index. Advances in Marine Biology, 82: 93-127. European Commission, 2018. Commission Decision (EU) 2018/229 of 12 February 2018 establishing, pursuant to Directive 2000/60/EC of the European Parliament and of the Council, the values of the Member State monitoring system classifications as a result of the intercalibration exercise and repealing Commission Decision 2013/480/EU. Official Journal of the European Communities, L47: 1-91.

Crop harvest followed by a fallow period can act as a disturbance on soil microbial communities. Cropping systems intended to improve alpha-diversity of communities may also confer increased compositional stability during succeeding growing seasons. Over a single growing season in a long-term (18 year) agricultural field experiment incorporating conventional (CON), conservation (CA), organic (ORG) and integrated (INT) cropping systems, temporal changes in prokaryote, fungal and arbuscular mycorrhizal fungi (AMF) communities were investigated overwinter, during crop growth and at harvest. While certain prokaryote phyla were influenced by cropping system (e.g. Acidobacteria), the community as a whole was primarily driven by temporal changes over the growing season as distinct overwinter and crop-associated communities, with the same trend observed regardless of cropping system. Species- rich prokaryote communities were most stable over the growing season. Cropping system exerted a greater effect on fungal communities, with alpha-diversity highest and temporal changes most stable under CA. CON was particularly detrimental for alpha-diversity in AMF communities, with AMF alpha-diversity and stability improved under all other cropping systems. Practices that promoted alpha-diversity tended to also increase the similarity and temporal stability of soil fungal (and AMF) communities during a growing season, while prokaryote communities were largely insensitive to management.

Microbial communities inhabiting soil-water-sediment continuum in coastal areas provide important ecosystem services. Their adaptation in response to environmental stressors, particularly mitigating the impact of pollutants discharged from human activities, has been considered for the development of microbial biomonitoring tools, but their use is still in the infancy. Here, chemical and molecular (16S rRNA gene metabarcoding) approaches were combined in order to determine the impact of pollutants on microbial assemblages inhabiting the aquatic network of a soil-water-sediment continuum around the Ichkeul Lake (Tunisia), an area highly impacted by human activities. Samples were collected within the soil-river-lake continuum at three stations in dry (summer) and wet (winter) seasons. The contaminant pressure index (PI), which integrates Polycyclic aromatic hydrocarbons (PAHs), alkanes, Organochlorine pesticides (OCPs) and metal contents, and the microbial pressure index microgAMBI, based on bacterial community structure, showed significant correlation with contamination level and differences between seasons. The comparison of prokaryotic communities further revealed specific assemblages for soil, river and lake sediments. Correlation analyses identified potential "specialist" genera for the different compartments, whose abundances were correlated with the pollutant type found. Additionally, PICRUSt analysis revealed the metabolic potential for pollutant transformation or degradation of the identified "specialist" species, providing information to estimate the recovery capacity of the ecosystem. Such findings offer the possibility to define a relevant set of microbial indicators for assessing the effects of human activities on aquatic ecosystems. Microbial indicators, including the detection of “specialist” and sensitive taxa, and their functional capacity, might be useful, in combination with integrative microbial indices, to constitute accurate biomonitoring tools for the management and restoration of complex coastal aquatic systems.

Studying the dynamics of nitrogen and sulphur cycling bacteria in river surface sediments is essential to better understand their contribution to global biogeochemical cycles. Evaporitic rocks settled at the headwater of the Deba River catchment (northern Spain) lead to high values of sulphate concentration in its waters. Besides, the discharge of effluents from untreated and treated residual (urban and industrial) wastewaters increases the concentration of metals, nutrients and organic compounds in its mid- and low-water courses. The aim of this study was to assess the impact of anthropogenic contamination from untreated and treated residual and industrial wastewaters on the structure and function of bacterial communities present in surface sediments of the Deba River catchment. The application of a quantitative functional approach (qPCR) based on denitrification genes (nir: nirS+nirK; and nosZ), together with a 16S rRNA gene metabarcoding structural analysis, revealed (i) the high relevance of the sulphur cycle at headwater surface sediments (as reflected by the abundance of members of the Syntrophobacterales order, and the Sulfuricurvum and Thiobacillus genera) and (ii) the predominance of sulphide-driven autotrophic denitrification over heterotrophic denitrification. Incomplete heterotrophic denitrification appeared to be predominant in surface sediments strongly impacted by treated and untreated effluents, as reflected by the lower values of the nosZ/nir ratio, thus favouring N2O emissions. Understanding nitrogen and sulphur cycling pathways has profound implications for the management of river ecosystems, since this knowledge can help us determine whether a specific river is acting or not as a source of greenhouse gases (i.e., N2O).

In many urban catchments, the discharge of effluents from wastewater treatment plants (WWTPs), as well as untreated wastewaters (UWWs), presents a major challenge for the maintenance of river sediment and water quality. The discharge of these effluents cannot only increase the concentration of metals, nutrients and organic compounds in fluvial ecosystems, but also alter the abundance, structure and function of river bacterial communities. Here, we present data on chemical and biological quality parameters in wastewater-impacted and non-impacted river surface sediment and water samples. Overall, the concentration of nutrients (inorganic nitrogen) and some heavy metals (Zn, Ni and Cr) was positively correlated with the nirS/16S rRNA ratio, while nirK- and nosZ-denitrifier populations were negatively affected by the presence of ammonium in sediments. Bacterial community structure was significantly correlated with the (i) combined influence of nutrient and metal concentrations, (ii) the contamination level (non-impacted vs. impacted sites), (iii) type of contamination (WWTP or UWW), and (iv) location of the sampling sites. Moreover, the higher abundance of five genera of the family Rhodocyclaceae detected in wastewater-impacted sites is also likely to be an effect of effluent discharge. The data presented here complement a broader study (Martínez-Santos et al., 2018) [1] and they are particularly useful for those interested in understanding the impact of wastewater effluents on the abundance, structure and function of river bacterial communities involved in nitrogen cycling. Keywords: Wastewater, River sediment, Nutrients, Metals, Denitrifying genes, Rhodocyclaceae

The incorporation of stover into soil can bring beneficial effects in terms of soil fertility, stabilization of soil structure, maintenance of soil organic carbon, etc. We evaluated the effects, after 6 years of consecutive treatment, of corn stover incorporation versus corn stover removal on soil quality, using physicochemical and biological parameters as indicators of soil quality. Throughout the experimental period, soil organic carbon decreased as a result of stover removal (from 20.1 to 14.7 g kg−1). Substrate-induced respiration and bacterial gene abundance decreased by stover removal over the same period (24.0 and 47.6%, respectively). Biolog EcoPlates™ data showed faster rates of d -xylose and D-mannitol utilization by the soil bacterial communities under stover incorporation. 16 S and 18 S rRNA Illumina sequencing data did not show significant differences in terms of microbial diversity and composition between stover incorporation and stover removal treatments. Finally, the incorporation of stover resulted in higher values (27.2% higher) of soil quality, as reflected by the value of a Soil Quality Index, which integrates the values of a variety of microbial indicators of soil quality. In conclusion, incorporation of stover after corn harvest is a beneficial agronomic practice which enhances soil N and C pools and stimulates microbial communities, leading to an increase in soil quality.

To avoid loss of genetic information in environmental DNA (eDNA) field samples, the preservation of nucleic acids during field sampling is a critical step. In the development of standard operating procedures (SOPs) for eDNA-based compliance monitoring, the effect of different routinely used sediment preservations on biological community structures serving as bioindicators has gone untested. We compared eDNA metabarcoding results of marine bacterial communities from sample aliquots that were treated with a nucleic acid preservation solution (treated samples) and aliquots that were frozen without further treatment (non-treated samples). Sediment samples were obtained from coastal locations subjected to different stressors (aquaculture, urbanization, industry). DNA extraction efficiency, bacterial community profiles, and measures of alpha- and beta-diversity were highly congruent between treated and non-treated samples. As both preservation methods provide the same relevant information to environmental managers and regulators, we recommend the inclusion of both methods into SOPs for biomonitoring in marine coastal environments.

International audience; 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 programs that leverage recent analytical advancements, while pointing out current limitations and future research needs.

Meromictic lakes are permanently stratified lakes that display steep gradients in salinity, oxygen and sulphur compounds tightly linked to bacterial community structure and diversity. Lake S&aelig, lenvannet is a meromictic lake located south of Bergen, Norway. The 26 m deep lake is connected to the open sea and permanently stratified into two layers separated by a chemocline. The upper water layer is brackish with major input from water runoff from the surroundings. The bottom layer consists of old saline water with low or no oxygen concentrations. Bacteria from phylum Planctomycetes are reported to be ubiquitous in lake environments. They are involved in the degradation of complex carbon sources in aquatic environments and are also linked to anaerobic processes such as fermentation and sulphur reduction. To study Planctomycete distribution along a chemical gradient, we sampled the water column throughout Lake S&aelig, lenvannet in 2012 and profiled the microbial community using 16S rRNA amplicon sequencing (metabarcoding) with 454 pyrosequencing. Planctomycete-related 16S rRNA gene sequences were found to be present both in the oxic and anoxic parts of the lake and showed an uneven distribution throughout the water column, with the highest relative abundance of 10% found in the saline anoxic layer at 15 m depth. In a follow-up study in 2014, samples from eight different depths were collected for enrichment and isolation of novel Planctomycetes. This study resulted in successful isolation in pure culture of 10 isolates affiliated to four different genera from the family Planctomycetaceae. One strain closely related to Blastopirellula cremea was isolated from 9 m depth, and two novel strains affiliated to the genera Stieleria and Gimesia were isolated at 7 and 9 m depths, respectively. Furthermore, seven isolates with identical 16S rRNA gene sequences were retrieved from seven different depths which varied greatly in salinity and chemical composition. These isolates likely represent a new species affiliated to Rubinisphaera. The adaptation of this novel Planctomycete to water depths spanning the entire chemical gradient could indicate a high phenotypic plasticity and/or a very efficient survival strategy. Overall, our results show the presence of a diverse group of Planctomycetes in Lake S&aelig, lenvannet, with a strong potential for novel adaptations to chemical stress factors.

Increased exploitation of resources in sensitive marine ecosystems emphasizes the importance of knowledge regarding ecological impacts. However, current bio-monitoring practices are limited in terms of target-organisms and temporal resolution. Hence, developing new technologies is vital for enhanced ecosystem understanding. In this study, we have applied a prototype version of a phylogenetic microarray to assess the eukaryote community structures of marine sediments from an area with ongoing oil and gas drilling activity. The results were compared with data from both sequencing (metabarcoding) and morphology-based monitoring to evaluate whether microarrays were capable of detecting ecosystem disturbances. A significant correlation between microarray data and chemical pollution indicators, as well as sequencing-based results, was demonstrated, and several potential indicator organisms for pollution-associated parameters were identified, among them a large fraction of microorganisms not covered by traditional morphology-based monitoring. This suggests that microarrays have a potential in future environmental monitoring. acceptedVersion

Background Metatranscriptomics has been used widely for investigation and quantification of microbial communities’ activity in response to external stimuli. By assessing the genes expressed, metatranscriptomics provides an understanding of the interactions between different major functional guilds and the environment. Here, we present a de novo assembly-based Comparative Metatranscriptomics Workflow (CoMW) implemented in a modular, reproducible structure. Metatranscriptomics typically uses short sequence reads, which can either be directly aligned to external reference databases (“assembly-free approach”) or first assembled into contigs before alignment (“assembly-based approach”). We also compare CoMW (assembly-based implementation) with an assembly-free alternative workflow, using simulated and real-world metatranscriptomes from Arctic and temperate terrestrial environments. We evaluate their accuracy in precision and recall using generic and specialized hierarchical protein databases. Results CoMW provided significantly fewer false-positive results, resulting in more precise identification and quantification of functional genes in metatranscriptomes. Using the comprehensive database M5nr, the assembly-based approach identified genes with only 0.6% false-positive results at thresholds ranging from inclusive to stringent compared with the assembly-free approach, which yielded up to 15% false-positive results. Using specialized databases (carbohydrate-active enzyme and nitrogen cycle), the assembly-based approach identified and quantified genes with 3–5 times fewer false-positive results. We also evaluated the impact of both approaches on real-world datasets. Conclusions We present an open source de novo assembly-based CoMW. Our benchmarking findings support assembling short reads into contigs before alignment to a reference database because this provides higher precision and minimizes false-positive results.

Recycling of wood ash from energy production may counteract soil acidification and return essential nutrients to soils. However, wood ash amendment affects soil physicochemical parameters that control composition and functional expression of the soil microbial community. Here, we applied total RNA sequencing to simultaneously assess the impact of wood ash amendment on the active soil microbial communities and the expression of functional genes from all microbial taxa. Wood ash significantly affected the taxonomic (rRNA) as well as functional (mRNA) profiles of both agricultural and forest soil. Increase in pH, electrical conductivity, dissolved organic carbon and phosphate were the most important physicochemical drivers for the observed changes. Wood ash amendment increased the relative abundance of the copiotrophic groups Chitinonophagaceae (Bacteroidetes) and Rhizobiales (Alphaproteobacteria) and resulted in higher expression of genes involved in metabolism and cell growth. Finally, total RNA sequencing allowed us to show that some groups of bacterial feeding protozoa increased concomitantly to the enhanced bacterial growth, which shows their pivotal role in the regulation of bacterial abundance in soil., We applied total RNA sequencing to simultaneously assess the impact of wood ash amendment on the active soil microbial communities and the expression of functional genes from all microbial taxa.

As global exploitation of available resources increases, operations extend towards sensitive and previously protected ecosystems. It is important to monitor such areas in order to detect, understand and remediate environmental responses to stressors. The natural heterogeneity and complexity of communities means that accurate monitoring requires high resolution, both temporally and spatially, as well as more complete assessments of taxa. Increased resolution and taxonomic coverage is economically challenging using current microscopy-based monitoring practices. Alternatively, DNA sequencing-based methods have been suggested for cost-efficient monitoring, offering additional insights into ecosystem function and disturbance. Here, we applied DNA metabarcoding of eukaryotic communities in marine sediments, in areas of offshore drilling on the Norwegian continental shelf. Forty-five samples, collected from seven drilling sites in the Troll/Oseberg region, were assessed, using the small subunit ribosomal RNA gene as a taxonomic marker. In agreement with results based on classical morphology-based monitoring, we were able to identify changes in sediment communities surrounding oil platforms. In addition to overall changes in community structure, we identified several potential indicator taxa, responding to pollutants associated with drilling fluids. These included the metazoan orders Macrodasyida, Macrostomida and Ceriantharia, as well as several ciliates and other protist taxa, typically not targeted by environmental monitoring programmes. Analysis of a co-occurrence network to study the distribution of taxa across samples provided a framework for better understanding the impact of anthropogenic activities on the benthic food web, generating novel, testable hypotheses of trophic interactions structuring benthic communities. publishedVersion

Genomics is fast becoming a routine tool in medical diagnostics and cutting-edge biotechnologies. Yet, its use for environmental biomonitoring is still considered a futuristic ideal. Until now, environmental genomics was mainly used as a replacement of the burdensome morphological identification, to screen known morphologically distinguishable bioindicator taxa. While prokaryotic and eukaryotic microbial diversity is of key importance in ecosystem functioning, its implementation in biomonitoring programs is still largely unappreciated, mainly because of difficulties in identifying microbes and limited knowledge of their ecological functions. Here, we argue that the combination of massive environmental genomics microbial data with machine learning algorithms can be extremely powerful for biomonitoring programs and pave the way to fill important gaps in our understanding of microbial ecology.

Svalbard, situated in the high Arctic, is an important past and present coal mining area. Dozens of abandoned waste rock piles can be found in the proximity of Longyearbyen. This environment offers a unique opportunity for studying the biological control over the weathering of sulphide rocks at low temperatures. Although the extension and impact of acid mine drainage (AMD) in this area is known, the native microbial communities involved in this process are still scarcely studied and uncharacterized. Several abandoned mining areas were explored in the search for active AMD and a culture-independent approach was applied with samples from two different runoffs for the identification and quantification of the native microbial communities. The results obtained revealed two distinct microbial communities. One of the runoffs was more extreme with regards to pH and higher concentration of soluble iron and heavy metals. These conditions favored the development of algal-dominated microbial mats. Typical AMD microorganisms related to known iron-oxidizing bacteria (Acidithiobacillus ferrivorans, Acidobacteria and Actinobacteria) dominated the bacterial community although some unexpected populations related to Chloroflexi were also significant. No microbial mats were found in the second area. The geochemistry here showed less extreme drainage, most likely in direct contact with the ore under the waste pile. Large deposits of secondary minerals were found and the presence of iron stalks was revealed by microscopy analysis. Although typical AMD microorganisms were also detected here, the microbial community was dominated by other populations, some of them new to this type of system (Saccharibacteria, Gallionellaceae). These were absent or lowered in numbers the farther from the spring source and they could represent native populations involved in the oxidation of sulphide rocks within the waste rock pile. This environment appears thus as a highly interesting field of potential novelty in terms of both phylogenetic/taxonomic and functional diversity., We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI).

Mountain grasslands in the Iberian Peninsula are the result of extensive grazing. However, a progressive abandonment of grazing activity is currently observed in the study region. The objective of this work was to evaluate the short-term (2 years) effects of non-grazing on the diversity and composition of plants, soil microorganisms (prokaryotes, fungi, arbuscular mycorrhiza), mesofauna, macrofauna and aboveground-belowground links, through the study of 16 grazed vs. non-grazed areas in Atlantic grasslands located in the Basque Country (Spain). Sites were divided between 4 habitat types with different elevation, pasture productivity, vegetation type and parent material. Herbivores appeared to influence plant community composition, contributing to increase aboveground diversity, while having unequal effects on belowground communities depending on the organisms analysed. This may be explained by the different habitat and trophic level of each soil organism, which may be more or less affected by the predominating negative effects of grazing, such as soil compaction, and only partially compensated by other positive effects. Finally, habitat type appeared to be the strongest influence on both above- and belowground communities, also influencing the effect of the absence of grazing.

Metal resistance has been associated with antibiotic resistance due to co- or cross-resistance mechanisms. Here, metal contaminated mine soil treated with organic wastes was screened for the presence of mobile genetic elements (MGEs). The occurrence of conjugative IncP-1 and mobilizable IncQ plasmids, as well as of class 1 integrons, was confirmed by PCR and Southern blot hybridization, suggesting that bacteria from these soils have gene-mobilizing capacity with implications for the dissemination of resistance factors. Moreover, exogenous isolation of MGEs from the soil bacterial community was attempted under antibiotic selection pressure by using Escherichia coli as recipient. Seventeen putative transconjugants were identified based on increased antibiotic resistance. Metabolic traits and metal resistance of putative transconjugants were investigated, and whole genome sequencing was carried out for two of them. Most putative transconjugants displayed a multi-resistant phenotype for a broad spectrum of antibiotics. They also displayed changes regarding the ability to metabolise different carbon sources, RNA: DNA ratio, growth rate and biofilm formation. Genome sequencing of putative transconjugants failed to detect genes acquired by horizontal gene transfer, but instead revealed a number of nonsense mutations, including in ubiH, whose inactivation was linked to the observed resistance to aminoglycosides. Our results confirm that mine soils contain MGEs encoding antibiotic resistance. Moreover, they point out the role of spontaneous mutations in achieving low-level antibiotic resistance in a short time, which was associated with a trade-off in the capability to metabolise specific carbon sources.

The microbial diversity associated with diffuse venting deep-sea hydrothermal deposits is tightly coupled to the geochemistry of the hydrothermal fluids. Previous 16S rRNA gene amplicon sequencing (metabarcoding) of marine iron-hydroxide deposits along the Arctic Mid Ocean Ridge, revealed the presence of diverse bacterial communities associated with these deposits (Storesund and Ovreas in Antonie van Leeuwenhoek 104:569-584, 2013). One of the most abundant and diverse phyla detected was the enigmatic Planctomycetes. Here we report on the comparative analyses of the diversity and distribution patterns of Planctomycetes associated with metalliferous deposits from two diffuse-flow hydrothermal vent fields (Mariner and Vai Lili) from the Valu Fa Ridge in the Southwestern Pacific. Metabarcoding of 16S rRNA genes showed that the major prokaryotic phyla were Proteobacteria (51-73% of all 16S rRNA gene reads), Epsilonbacteraeota (0.5-19%), Bacteriodetes (5-17%), Planctomycetes (0.4-11%), Candidatus Latescibacteria (0-5%) and Marine Benthic Group E (Hydrothermarchaeota) (0-5%). The two different sampling sites differed considerably in overall community composition. The abundance of Planctomycetes also varied substantially between the samples and the sites, with the majority of the sequences affiliated with uncultivated members of the classes Planctomycetacia and Phycisphaerae, and other deep branching lineages. Seven different strains affiliated with the order Planctomycetales were isolated, mostly from the Vai Lili samples, where also the highest Planctomycetales diversity was seen. Most of the isolates were affiliated with the genera Gimesia, Rhodopirellula and Blastopirellula. One isolate was only distantly related to known cultured, but uncharacterized species within the Pir4 group. This study shows that the deep-sea Planctomycetes represent a very heterogeneous group with a high phylogenetic diversity and a substantial potential for novel organism discovery in these deep ocean environments.

Human impact on marine benthic communities has traditionally been assessed using visible morphological traits and has focused on the macrobenthos, whereas the ecologically important organisms of the meio- and microbenthos have received less attention. DNA metabarcoding offers an alternative to this approach and enables a larger fraction of the biodiversity in marine sediments to be monitored in a cost-efficient manner. Although this methodology remains poorly standardised and challenged by biases inherent to rRNA copy number variation, DNA extraction, PCR, and limitations related to taxonomic identification, it has been shown to be semi-quantitative and useful for comparing taxon abundances between samples. Here, we evaluate the effect of replicating genomic DNA extraction in order to counteract small scale spatial heterogeneity and improve diversity and community structure estimates in metabarcoding-based monitoring. For this purpose, we used ten technical replicates from three different marine sediment samples. The effect of sequence depth was also assessed, and in silico pooling of DNA extraction replicates carried out in order to maintain the number of reads constant. Our analyses demonstrated that both sequencing depth and DNA extraction replicates could improve diversity estimates as well as the ability to separate samples with different characteristics. We could not identify a "sufficient" replicate number or sequence depth, where further improvements had a less significant effect. Based on these results, we consider replication an attractive alternative to directly increasing the amount of sample used for DNA extraction and strongly recommend it for future metabarcoding studies and routine assessments of sediment biodiversity.

Toxicity of metals released from mine tailings may cause severe damage to ecosystems. A diversity of microorganisms, however, have successfully adapted to such sites. In this study, our objective was to advance the understanding of the indigenous microbial communities of mining-impacted soils. To this end, a metatranscriptomic approach was used to study a heavily metal-contaminated site along a metal concentration gradient (up to 3220 000 and 97 000 mg kg(-1) of Cd, Pb and Zn, respectively) resulting from previous mining. Metal concentration, soil pH and amount of clay were the most important factors determining the structure of soil microbial communities. Interestingly, evenness of the microbial communities, but not its richness, increased with contamination level. Taxa with high metabolic plasticity like Ktedonobacteria and Chloroflexi were found with higher relative abundance in more contaminated samples. However, several taxa belonging to the phyla Actinobacteria and Acidobacteria followed opposite trends in relation to metal pollution. Besides, functional transcripts related to transposition or transfer of genetic material and membrane transport, potentially involved in metal resistance mechanisms, had a higher expression in more contaminated samples. Our results provide an insight into microbial communities in long-term metal-contaminated environments and how they contrast to nearby sites with lower contamination.

Deep-sea hydrothermal vents are unique environments on Earth, as they host chemosynthetic ecosystems fuelled by geochemical energy with chemolithoautotrophic microorganisms at the basis of the food webs. Whereas discrete high-temperature venting systems have been studied extensively, the microbiotas associated with low-temperature diffuse venting are not well understood. We analysed the structure and functioning of microbial communities in two diffuse venting sediments from the Jan Mayen vent fields in the Norwegian-Greenland Sea, applying an integrated 'omics' approach combining metatranscriptomics, metaproteomics and metagenomics. Polymerase chain reaction-independent three-domain community profiling showed that the two sediments hosted highly similar communities dominated by Epsilonproteobacteria, Deltaproteobacteria and Gammaproteobacteria, besides ciliates, nematodes and various archaeal taxa. Active metabolic pathways were identified through transcripts and peptides, with genes of sulphur and methane oxidation, and carbon fixation pathways highly expressed, in addition to genes of aerobic and anaerobic (nitrate and sulphate) respiratory chains. High expression of chemotaxis and flagella genes reflected a lifestyle in a dynamic habitat rich in physico-chemical gradients. The major metabolic pathways could be assigned to distinct taxonomic groups, thus enabling hypotheses about the function of the different prokaryotic and eukaryotic taxa. This study advances our understanding of the functioning of microbial communities in diffuse hydrothermal venting sediments.

Naphthalene, the smallest polycyclic aromatic hydrocarbon (PAH), is found in abundance in crude oil, its major source in marine environments. PAH removal occurs via biodegradation, a key process determining their fate in the sea. Adequate estimation of PAH biodegradation rates is essential for environmental risk assessment and response planning using numerical models such as the oil spill contingency and response (OSCAR) model. Using naphthalene as a model compound, biodegradation rate, temperature response and bacterial community composition of seawaters from two climatically different areas (North Sea and Arctic Ocean) were studied and compared. Naphthalene degradation was followed by measuring oxygen consumption in closed bottles using the OxiTop(®) system. Microbial communities of untreated and naphthalene exposed samples were analysed by polymerase chain reaction denaturing gradient gel electrophoresis (PCR-DGGE) and pyrosequencing. Three times higher naphthalene degradation rate coefficients were observed in arctic seawater samples compared to temperate, at all incubation temperatures. Rate coefficients at in situ temperatures were however, similar (0.048 day(-1) for temperate and 0.068 day(-1) for arctic). Naphthalene biodegradation rates decreased with similar Q10 ratios (3.3 and 3.5) in both seawaters. Using the temperature compensation method implemented in the OSCAR model, Q10 = 2, biodegradation in arctic seawater was underestimated when calculated from the measured temperate k1 value, showing that temperature difference alone could not predict biodegradation rates adequately. Temperate and arctic untreated seawater communities were different as revealed by pyrosequencing. Geographic origin of seawater affected the community composition of exposed samples.

8 pages, 1 table, The incursion of High-Throughput Sequencing (HTS) in environmental microbiology brings unique opportunities and challenges. HTS now allows a high-resolution exploration of the vast taxonomic and metabolic diversity present in the microbial world, which can provide an exceptional insight on global ecosystem functioning, ecological processes and evolution. This exploration has also economic potential, as we will have access to the evolutionary innovation present in microbial metabolisms, which could be used for biotechnological development. HTS is also challenging the research community, and the current bottleneck is present in the data analysis side. At the moment, researchers are in a sequence data deluge, with sequencing throughput advancing faster than the computer power needed for data analysis. However, new tools and approaches are being developed constantly and the whole process could be depicted as a fast co-evolution between sequencing technology, informatics and microbiologists. In this work, we examine the most popular and recently commercialized HTS platforms as well as bioinformatics methods for data handling and analysis used in microbial metagenomics. This non-exhaustive review is intended to serve as a broad state-of-the-art guide to researchers expanding into this rapidly evolving field. © 2012 Elsevier B.V., The Department of Biology, University of Oslo, MLSUIO (Molecular Life Science) and ForBio (Norwegian–Swedish Research School in Biosystematics) are acknowledged for financial support, enabling the preparation of this work. R.L. has been financed by a Marie Curie Intra-European Fellowship grant PIEF-GA-2009-235365. T.H.A.H. has been supported with a VISTA/Statoil grant project number 6503