Increasing marine trophic web knowledge through DNA analyses of fish stomach content: a step towards an ecosystem-based approach to fisheries research.

Multispecies and ecosystem models, which are key for the implementation of ecosystem-based approaches to fisheries management, require extensive data on the trophic interactions between marine organisms, including changes over time. DNA metabarcoding, by allowing the simultaneous taxonomic identification of the community present in hundreds of samples, could be used for speeding up large-scale stomach content data collection. Yet, for DNA metabarcoding to be routinely implemented, technical challenges should be addressed, such as the potentially complicated sampling logistics, the detection of a high proportion of predator DNA, and the inability to provide reliable abundance estimations. Here, we present a DNA metabarcoding assay developed to examine the diet of five commercially important fish, which can be feasibly incorporated into routinary samplings. The method is devised to speed up the analysis process by avoiding the stomach dissection and content extraction steps, while preventing the amplification of predator DNA by using blocking primers. Tested in mock samples and in real stomach samples, the method has proven effective and shows great effectiveness discerning diet variations due to predator ecology or prey availability. Additionally, by applying our protocol to mackerel stomachs previously analyzed by visual inspection, we showcase how DNA metabarcoding could complement visually based data by detecting overlooked prey by the visual approach. We finally discuss how DNA metabarcoding-based data can contribute to trophic data collection. Our work reinforces the potential of DNA metabarcoding for the study and monitoring of fish trophic interactions and provides a basis for its incorporation into routine monitoring programs, which will be critical for the implementation of ecosystem-based approaches to fisheries management.

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.

Shared and contrasting associations in the dynamic nano- and picoplankton communities of two close but contrasting sites from the Bay of Biscay.

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.

Reconstructing ribosomal genes from large scale total RNA meta-transcriptomic data.

MOTIVATION: Technological advances in meta-transcriptomics have enabled a deeper understanding of the structure and function of microbial communities. 'Total RNA' meta-transcriptomics, sequencing of total reverse transcribed RNA, provides a unique opportunity to investigate both the structure and function of active microbial communities from all three domains of life simultaneously. A major step of this approach is the reconstruction of full-length taxonomic marker genes such as the small subunit ribosomal RNA. However, current tools for this purpose are mainly targeted towards analysis of amplicon and metagenomic data and thus lack the ability to handle the massive and complex datasets typically resulting from total RNA experiments. RESULTS: In this work, we introduce MetaRib, a new tool for reconstructing ribosomal gene sequences from total RNA meta-transcriptomic data. MetaRib is based on the popular rRNA assembly program EMIRGE, together with several improvements. We address the challenge posed by large complex datasets by integrating sub-assembly, dereplication and mapping in an iterative approach, with additional post-processing steps. We applied the method to both simulated and real-world datasets. Our results show that MetaRib can deal with larger datasets and recover more rRNA genes, which achieve around 60 times speedup and higher F1 score compared to EMIRGE in simulated datasets. In the real-world dataset, it shows similar trends but recovers more contigs compared with a previous analysis based on random sub-sampling, while enabling the comparison of individual contig abundances across samples for the first time. AVAILABILITY AND IMPLEMENTATION: The source code of MetaRib is freely available at https://github.com/yxxue/MetaRib. CONTACT: yaxin.xue@uib.no or Inge.Jonassen@uib.no. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A microbial mandala for environmental monitoring: Predicting multiple impacts on estuarine prokaryote communities of the Bay of Biscay.

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.

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.

Diversity patterns and isolation of Planctomycetes associated with metalliferous deposits from hydrothermal vent fields along the Valu Fa Ridge (SW Pacific).

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 Øvreås 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.

The genome sequence of Atlantic cod reveals a unique immune system.

Atlantic cod (Gadus morhua) is a large, cold-adapted teleost that sustains long-standing commercial fisheries and incipient aquaculture. Here we present the genome sequence of Atlantic cod, showing evidence for complex thermal adaptations in its haemoglobin gene cluster and an unusual immune architecture compared to other sequenced vertebrates. The genome assembly was obtained exclusively by 454 sequencing of shotgun and paired-end libraries, and automated annotation identified 22,154 genes. The major histocompatibility complex (MHC) II is a conserved feature of the adaptive immune system of jawed vertebrates, but we show that Atlantic cod has lost the genes for MHC II, CD4 and invariant chain (Ii) that are essential for the function of this pathway. Nevertheless, Atlantic cod is not exceptionally susceptible to disease under natural conditions. We find a highly expanded number of MHC I genes and a unique composition of its Toll-like receptor (TLR) families. This indicates how the Atlantic cod immune system has evolved compensatory mechanisms in both adaptive and innate immunity in the absence of MHC II. These observations affect fundamental assumptions about the evolution of the adaptive immune system and its components in vertebrates.

High-throughput metabarcoding of eukaryotic diversity for environmental monitoring of offshore oil-drilling activities.

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.

Prokaryotic Community Diversity Along an Increasing Salt Gradient in a Soda Ash Concentration Pond.

The effect of salinity on prokaryotic community diversity in Abijata-Shalla Soda Ash Concentration Pond system was investigated by using high-throughput 16S rRNA gene 454 pyrosequencing. Surface water and brine samples from five sites spanning a salinity range of 3.4 % (Lake Abijata) to 32 % (SP230F, crystallizer pond) were analyzed. Overall, 33 prokaryotic phyla were detected, and the dominant prokaryotic phyla accounted for more than 95 % of the reads consisting of Planctomycetes, Bacteroidetes, candidate division TM7, Deinococcus-Thermus, Firmicutes, Actinobacteria, Proteobacteria, and Euryarchaeota. Diversity indices indicated that operational taxonomic unit (OTU) richness decreases drastically with increasing salinity in the pond system. A total of 471 OTUs were found at 3.4 % salinity whereas 49 OTUs were detected in pond SP211 (25 % salinity), and only 19 OTUs in the crystallization pond at 32 % salinity (SP230F). Along the salinity gradient, archaeal community gradually replaced bacterial community. Thus, archaeal community accounted for 0.4 % in Lake Abijata while 99.0 % in pond SP230F. This study demonstrates that salinity appears to be the key environmental parameter in structuring the prokaryotic communities of haloalkaline environments. Further, it confirmed that the prokaryotic diversity in Lake Abijata is high and it harbors taxa with low or no phylogenetic similarities to existing prokaryotic taxa and thus represents novel microorganisms.

Correlating microbial community profiles with geochemical data in highly stratified sediments from the Arctic Mid-Ocean Ridge.

Microbial communities and their associated metabolic activity in marine sediments have a profound impact on global biogeochemical cycles. Their composition and structure are attributed to geochemical and physical factors, but finding direct correlations has remained a challenge. Here we show a significant statistical relationship between variation in geochemical composition and prokaryotic community structure within deep-sea sediments. We obtained comprehensive geochemical data from two gravity cores near the hydrothermal vent field Loki's Castle at the Arctic Mid-Ocean Ridge, in the Norwegian-Greenland Sea. Geochemical properties in the rift valley sediments exhibited strong centimeter-scale stratigraphic variability. Microbial populations were profiled by pyrosequencing from 15 sediment horizons (59,364 16S rRNA gene tags), quantitatively assessed by qPCR, and phylogenetically analyzed. Although the same taxa were generally present in all samples, their relative abundances varied substantially among horizons and fluctuated between Bacteria- and Archaea-dominated communities. By independently summarizing covariance structures of the relative abundance data and geochemical data, using principal components analysis, we found a significant correlation between changes in geochemical composition and changes in community structure. Differences in organic carbon and mineralogy shaped the relative abundance of microbial taxa. We used correlations to build hypotheses about energy metabolisms, particularly of the Deep Sea Archaeal Group, specific Deltaproteobacteria, and sediment lineages of potentially anaerobic Marine Group I Archaea. We demonstrate that total prokaryotic community structure can be directly correlated to geochemistry within these sediments, thus enhancing our understanding of biogeochemical cycling and our ability to predict metabolisms of uncultured microbes in deep-sea sediments.

Microbial community structure and functioning in marine sediments associated with diffuse hydrothermal venting assessed by integrated meta-omics.

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 biodegradation in temperate and arctic marine microcosms.

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.

Revisiting the mercury cycle in marine sediments: A potential multifaceted role for Desulfobacterota.

Marine sediments impacted by urban and industrial pollutants are typically exposed to reducing conditions and represent major reservoirs of toxic mercury species. Mercury methylation mediated by anaerobic microorganisms is favored under such conditions, yet little is known about potential microbial mechanisms for mercury detoxification. We used culture-independent (metagenomics, metabarcoding) and culture-dependent approaches in anoxic marine sediments to identify microbial indicators of mercury pollution and analyze the distribution of genes involved in mercury reduction (merA) and demethylation (merB). While none of the isolates featured merB genes, 52 isolates, predominantly affiliated with Gammaproteobacteria, were merA positive. In contrast, merA genes detected in metagenomes were assigned to different phyla, including Desulfobacterota, Actinomycetota, Gemmatimonadota, Nitrospirota, and Pseudomonadota. This indicates a widespread capacity for mercury reduction in anoxic sediment microbiomes. Notably, merA genes were predominately identified in Desulfobacterota, a phylum previously associated only with mercury methylation. Marker genes involved in the latter process (hgcAB) were also mainly assigned to Desulfobacterota, implying a potential central and multifaceted role of this phylum in the mercury cycle. Network analysis revealed that Desulfobacterota were associated with anaerobic fermenters, methanogens and sulfur-oxidizers, indicating potential interactions between key players of the carbon, sulfur and mercury cycling in anoxic marine sediments.

Integrated metagenomic and metaproteomic analyses of an ANME-1-dominated community in marine cold seep sediments.

Sulfate-reducing methanotrophy by anaerobic methanotrophic archaea (ANME) and sulfate-reducing bacteria (SRB) is a major biological sink of methane in anoxic methane-enriched marine sediments. The physiology of a microbial community dominated by free-living ANME-1 at 14-16 cm below the seafloor in the G11 pockmark at Nyegga was investigated by integrated metagenomic and metaproteomic approaches. Total DNA was subjected to 454-pyrosequencing (829 527 reads), and 16.6 Mbp of sequence information was assembled into 27352 contigs. Taxonomic analysis supported a high abundance of Euryarchaea (70%) with 66% of the assembled metagenome belonging to ANME-1. Extracted sediment proteins were separated in two dimensions and subjected to mass spectrometry (LTQ-Orbitrap XL). Of 356 identified proteins, 245 were expressed by ANME-1. These included proteins for cold-adaptation and production of gas vesicles, reflecting both the adaptation of the ANME-1 community to a permanently cold environment and its potential for positioning in specific sediment depths respectively. In addition, key metabolic enzymes including the enzymes in the reverse methanogenesis pathway (except N(5) ,N(10) -methylene-tetrahydromethanopterin reductase), heterodisulfide reductases and the F(420) H(2) :quinone oxidoreductase (Fqo) complex were identified. A complete dissimilatory sulfate reduction pathway was expressed by sulfate-reducing Deltaproteobacteria. Interestingly, an APS-reductase comprising Gram-positive SRB and related sequences were identified in the proteome. Overall, the results demonstrated that our approach was effective in assessing in situ metabolic processes in cold seep sediments.

Metatranscriptomics of the marine sponge Geodia barretti: tackling phylogeny and function of its microbial community.

Geodia barretti is a marine cold-water sponge harbouring high numbers of microorganisms. Significant rates of nitrification have been observed in this sponge, indicating a substantial contribution to nitrogen turnover in marine environments with high sponge cover. In order to get closer insights into the phylogeny and function of the active microbial community and the interaction with its host G. barretti, a metatranscriptomic approach was employed, using the simultaneous analysis of rRNA and mRNA. Of the 262 298 RNA-tags obtained by pyrosequencing, 92% were assigned to ribosomal RNA (ribo-tags). A total of 109 325 SSU rRNA ribo-tags revealed a detailed picture of the community, dominated by group SAR202 of Chloroflexi, candidate phylum Poribacteria and Acidobacteria, which was different in its composition from that obtained in clone libraries prepared form the same samples. Optimized assembly strategies allowed the reconstruction of full-length rRNA sequences from the short ribo-tags for more detailed phylogenetic studies of the dominant taxa. Cells of several phyla were visualized by FISH analyses for confirmation. Of the remaining 21 325 RNA-tags, 10 023 were assigned to mRNA-tags, based on similarities to genes in the databases. A wide range of putative functional gene transcripts from over 10 different phyla were identified among the bacterial mRNA-tags. The most abundant mRNAs were those encoding key metabolic enzymes of nitrification from ammonia-oxidizing archaea as well as candidate genes involved in related processes. Our analysis demonstrates the potential and limits of using a combined rRNA and mRNA approach to explore the microbial community profile, phylogenetic assignments and metabolic activities of a complex, but little explored microbial community.

Accurate determination of microbial diversity from 454 pyrosequencing data.

We present an algorithm, PyroNoise, that clusters the flowgrams of 454 pyrosequencing reads using a distance measure that models sequencing noise. This infers the true sequences in a collection of amplicons. We pyrosequenced a known mixture of microbial 16S rDNA sequences extracted from a lake and found that without noise reduction the number of operational taxonomic units is overestimated but using PyroNoise it can be accurately calculated.

Microbial diversity alteration reveals biomarkers of contamination in soil-river-lake continuum.

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.

Removing noise from pyrosequenced amplicons.

BACKGROUND: In many environmental genomics applications a homologous region of DNA from a diverse sample is first amplified by PCR and then sequenced. The next generation sequencing technology, 454 pyrosequencing, has allowed much larger read numbers from PCR amplicons than ever before. This has revolutionised the study of microbial diversity as it is now possible to sequence a substantial fraction of the 16S rRNA genes in a community. However, there is a growing realisation that because of the large read numbers and the lack of consensus sequences it is vital to distinguish noise from true sequence diversity in this data. Otherwise this leads to inflated estimates of the number of types or operational taxonomic units (OTUs) present. Three sources of error are important: sequencing error, PCR single base substitutions and PCR chimeras. We present AmpliconNoise, a development of the PyroNoise algorithm that is capable of separately removing 454 sequencing errors and PCR single base errors. We also introduce a novel chimera removal program, Perseus, that exploits the sequence abundances associated with pyrosequencing data. We use data sets where samples of known diversity have been amplified and sequenced to quantify the effect of each of the sources of error on OTU inflation and to validate these algorithms. RESULTS: AmpliconNoise outperforms alternative algorithms substantially reducing per base error rates for both the GS FLX and latest Titanium protocol. All three sources of error lead to inflation of diversity estimates. In particular, chimera formation has a hitherto unrealised importance which varies according to amplification protocol. We show that AmpliconNoise allows accurate estimates of OTU number. Just as importantly AmpliconNoise generates the right OTUs even at low sequence differences. We demonstrate that Perseus has very high sensitivity, able to find 99% of chimeras, which is critical when these are present at high frequencies. CONCLUSIONS: AmpliconNoise followed by Perseus is a very effective pipeline for the removal of noise. In addition the principles behind the algorithms, the inference of true sequences using Expectation-Maximization (EM), and the treatment of chimera detection as a classification or 'supervised learning' problem, will be equally applicable to new sequencing technologies as they appear.

Characteristics of 454 pyrosequencing data--enabling realistic simulation with flowsim.

MOTIVATION: The commercial launch of 454 pyrosequencing in 2005 was a milestone in genome sequencing in terms of performance and cost. Throughout the three available releases, average read lengths have increased to approximately 500 base pairs and are thus approaching read lengths obtained from traditional Sanger sequencing. Study design of sequencing projects would benefit from being able to simulate experiments. RESULTS: We explore 454 raw data to investigate its characteristics and derive empirical distributions for the flow values generated by pyrosequencing. Based on our findings, we implement Flowsim, a simulator that generates realistic pyrosequencing data files of arbitrary size from a given set of input DNA sequences. We finally use our simulator to examine the impact of sequence lengths on the results of concrete whole-genome assemblies, and we suggest its use in planning of sequencing projects, benchmarking of assembly methods and other fields. AVAILABILITY: Flowsim is freely available under the General Public License from http://blog.malde.org/index.php/flowsim/.