Coupling biogeochemical process rates and metagenomic blueprints of coastal bacterial assemblages in the context of environmental change.

Bacteria are major drivers of biogeochemical nutrient cycles and energy fluxes in marine environments, yet how bacterial communities respond to environmental change is not well known. Metagenomes allow examination of genetic responses of the entire microbial community to environmental change. However, it is challenging to link metagenomes directly to biogeochemical process rates. Here, we investigate metagenomic responses in natural bacterioplankton communities to simulated environmental stressors in the Baltic Sea, including increased river water input, increased nutrient concentration, and reduced oxygen level. This allowed us to identify informative prokaryotic gene markers, responding to environmental perturbation. Our results demonstrate that metagenomic and metabolic changes in bacterial communities in response to environmental stressors are influenced both by the initial community composition and by the biogeochemical factors shaping the functional response. Furthermore, the different sources of dissolved organic matter (DOM) had the largest impact on metagenomic blueprint. Most prominently, changes in DOM loads influenced specific transporter types reflecting the substrate availability and DOC assimilation and consumption pathways. The results provide new knowledge for developing models of ecosystem structure and biogeochemical cycling in future climate change scenarios and advance our exploration of the potential use of marine microorganisms as markers for environmental conditions.

Binning metagenomic contigs by coverage and composition.

Shotgun sequencing enables the reconstruction of genomes from complex microbial communities, but because assembly does not reconstruct entire genomes, it is necessary to bin genome fragments. Here we present CONCOCT, a new algorithm that combines sequence composition and coverage across multiple samples, to automatically cluster contigs into genomes. We demonstrate high recall and precision on artificial as well as real human gut metagenome data sets.

Active anaerobic methane oxidation and sulfur disproportionation in the deep terrestrial subsurface.

Microbial life is widespread in the terrestrial subsurface and present down to several kilometers depth, but the energy sources that fuel metabolism in deep oligotrophic and anoxic environments remain unclear. In the deep crystalline bedrock of the Fennoscandian Shield at Olkiluoto, Finland, opposing gradients of abiotic methane and ancient seawater-derived sulfate create a terrestrial sulfate-methane transition zone (SMTZ). We used chemical and isotopic data coupled to genome-resolved metaproteogenomics to demonstrate active life and, for the first time, provide direct evidence of active anaerobic oxidation of methane (AOM) in a deep terrestrial bedrock. Proteins from Methanoperedens (formerly ANME-2d) are readily identifiable despite the low abundance (≤1%) of this genus and confirm the occurrence of AOM. This finding is supported by 13C-depleted dissolved inorganic carbon. Proteins from Desulfocapsaceae and Desulfurivibrionaceae, in addition to 34S-enriched sulfate, suggest that these organisms use inorganic sulfur compounds as both electron donor and acceptor. Zerovalent sulfur in the groundwater may derive from abiotic rock interactions, or from a non-obligate syntrophy with Methanoperedens, potentially linking methane and sulfur cycles in Olkiluoto groundwater. Finally, putative episymbionts from the candidate phyla radiation (CPR) and DPANN archaea represented a significant diversity in the groundwater (26/84 genomes) with roles in sulfur and carbon cycling. Our results highlight AOM and sulfur disproportionation as active metabolisms and show that methane and sulfur fuel microbial activity in the deep terrestrial subsurface.

Ecologically coherent population structure of uncultivated bacterioplankton.

Bacterioplankton are main drivers of biogeochemical cycles and important components of aquatic food webs. While sequencing-based studies have revealed how bacterioplankton communities are structured in time and space, relatively little is known about intraspecies diversity patterns and their ecological relevance. Here, we use the newly developed software POGENOM (POpulation GENomics from Metagenomes) to investigate genomic diversity and differentiation in metagenome-assembled genomes from the Baltic Sea, and investigate their genomic variation using metagenome data spanning a 1700 km transect and covering seasonal variation at one station. The majority of the investigated species, representing several major bacterioplankton clades, displayed population structures correlating significantly with environmental factors such as salinity and temperature. Population differentiation was more pronounced over spatial than temporal scales. We discovered genes that have undergone adaptation to different salinity regimes, potentially responsible for the populations' existence along with the salinity range. This in turn implies the broad existence of ecotypes that may remain undetected by rRNA gene sequencing. Our findings emphasize the importance of physiological barriers, and highlight the role of adaptive divergence as a structuring mechanism of bacterioplankton species.

Machine Learning Predicts the Presence of 2,4,6-Trinitrotoluene in Sediments of a Baltic Sea Munitions Dumpsite Using Microbial Community Compositions.

Bacteria are ubiquitous and live in complex microbial communities. Due to differences in physiological properties and niche preferences among community members, microbial communities respond in specific ways to environmental drivers, potentially resulting in distinct microbial fingerprints for a given environmental state. As proof of the principle, our goal was to assess the opportunities and limitations of machine learning to detect microbial fingerprints indicating the presence of the munition compound 2,4,6-trinitrotoluene (TNT) in southwestern Baltic Sea sediments. Over 40 environmental variables including grain size distribution, elemental composition, and concentration of munition compounds (mostly at pmol⋅g-1 levels) from 150 sediments collected at the near-to-shore munition dumpsite Kolberger Heide by the German city of Kiel were combined with 16S rRNA gene amplicon sequencing libraries. Prediction was achieved using Random Forests (RFs); the robustness of predictions was validated using Artificial Neural Networks (ANN). To facilitate machine learning with microbiome data we developed the R package phyloseq2ML. Using the most classification-relevant 25 bacterial genera exclusively, potentially representing a TNT-indicative fingerprint, TNT was predicted correctly with up to 81.5% balanced accuracy. False positive classifications indicated that this approach also has the potential to identify samples where the original TNT contamination was no longer detectable. The fact that TNT presence was not among the main drivers of the microbial community composition demonstrates the sensitivity of the approach. Moreover, environmental variables resulted in poorer prediction rates than using microbial fingerprints. Our results suggest that microbial communities can predict even minor influencing factors in complex environments, demonstrating the potential of this approach for the discovery of contamination events over an integrated period of time. Proven for a distinct environment future studies should assess the ability of this approach for environmental monitoring in general.

Active sulfur cycling in the terrestrial deep subsurface.

The deep terrestrial subsurface remains an environment where there is limited understanding of the extant microbial metabolisms. At Olkiluoto, Finland, a deep geological repository is under construction for the final storage of spent nuclear fuel. It is therefore critical to evaluate the potential impact microbial metabolism, including sulfide generation, could have upon the safety of the repository. We investigated a deep groundwater where sulfate is present, but groundwater geochemistry suggests limited microbial sulfate-reducing activity. Examination of the microbial community at the genome-level revealed microorganisms with the metabolic capacity for both oxidative and reductive sulfur transformations. Deltaproteobacteria are shown to have the genetic capacity for sulfate reduction and possibly sulfur disproportionation, while Rhizobiaceae, Rhodocyclaceae, Sideroxydans, and Sulfurimonas oxidize reduced sulfur compounds. Further examination of the proteome confirmed an active sulfur cycle, serving for microbial energy generation and growth. Our results reveal that this sulfide-poor groundwater harbors an active microbial community of sulfate-reducing and sulfide-oxidizing bacteria, together mediating a sulfur cycle that remained undetected by geochemical monitoring alone. The ability of sulfide-oxidizing bacteria to limit the accumulation of sulfide was further demonstrated in groundwater incubations and highlights a potential sink for sulfide that could be beneficial for geological repository safety.

Ecosystem-wide metagenomic binning enables prediction of ecological niches from genomes.

The genome encodes the metabolic and functional capabilities of an organism and should be a major determinant of its ecological niche. Yet, it is unknown if the niche can be predicted directly from the genome. Here, we conduct metagenomic binning on 123 water samples spanning major environmental gradients of the Baltic Sea. The resulting 1961 metagenome-assembled genomes represent 352 species-level clusters that correspond to 1/3 of the metagenome sequences of the prokaryotic size-fraction. By using machine-learning, the placement of a genome cluster along various niche gradients (salinity level, depth, size-fraction) could be predicted based solely on its functional genes. The same approach predicted the genomes' placement in a virtual niche-space that captures the highest variation in distribution patterns. The predictions generally outperformed those inferred from phylogenetic information. Our study demonstrates a strong link between genome and ecological niche and provides a conceptual framework for predictive ecology based on genomic data.

AFISsys - An autonomous instrument for the preservation of brackish water samples for microbial metatranscriptome analysis.

Microbial communities are the main drivers of biogeochemical cycling of multiple elements sustaining life in the ocean. The rapidity of their response to stressors and abrupt environmental changes implies that even fast and infrequent events can affect local transformations of organic matter and nutrients. Modern molecular techniques now allow for monitoring of microbial activities and functions in the environment through the analysis of genes and expressed genes contained in natural microbial assemblages. However, messenger RNA turnover in cells can be as short as 30 seconds and stability varies greatly between transcripts. Sampling of in situ communities involves an inevitable delay between the collection of seawater and the extraction of its RNA, leaving the bacterial communities plenty of time to alter their gene expression. The characteristics of microbial RNA turnover make time-series very difficult because samples need to be processed immediately to limit alterations to the metatranscriptomes. To address these challenges we designed an autonomous in situ fixation multi-sampler (AFISsys) for the reliable sampling of microbial metatranscriptomes at frequent intervals, for refined temporal resolution. To advance the development of this instrument, we examined the minimal seawater volume necessary for adequate coverage of community gene expression, and the suitability of phenol/ethanol fixation for immediate and long-term preservation of transcripts from a microbial community. We then evaluated the field eligibility of the instrument itself, with two case studies in a brackish system. AFISsys is able to collect, fix, and store water samples independently at a predefined temporal resolution. Phenol/ethanol fixation can conserve metatranscriptomes directly in the environment for up to a week, for later analysis in the laboratory. Thus, the AFISsys constitutes an invaluable tool for the integration of molecular functional analyses in environmental monitoring in brackish waters and in aquatic environments in general.

Effects of allochthonous dissolved organic matter input on microbial composition and nitrogen-cycling genes at two contrasting estuarine sites.

Heterotrophic bacteria are important drivers of nitrogen (N) cycling and the processing of dissolved organic matter (DOM). Projected increases in precipitation will potentially cause increased loads of riverine DOM to the Baltic Sea and likely affect the composition and function of bacterioplankton communities. To investigate this, the effects of riverine DOM from two different catchment areas (agricultural and forest) on natural bacterioplankton assemblages from two contrasting sites in the Baltic Sea were examined. Two microcosm experiments were carried out, where the community composition (16S rRNA gene sequencing), the composition of a suite of N-cycling genes (metagenomics) and the abundance and transcription of ammonia monooxygenase (amoA) genes involved in nitrification (quantitative PCR) were investigated. The river water treatments evoked a significant response in bacterial growth, but the effects on overall community composition and the representation of N-cycling genes were limited. Instead, treatment effects were reflected in the prevalence of specific taxonomic families, specific N-related functions and in the transcription of amoA genes. The study suggests that bacterioplankton responses to changes in the DOM pool are constrained to part of the bacterial community, whereas most taxa remain relatively unaffected.

Genomes from uncultivated prokaryotes: a comparison of metagenome-assembled and single-amplified genomes.

BACKGROUND: Prokaryotes dominate the biosphere and regulate biogeochemical processes essential to all life. Yet, our knowledge about their biology is for the most part limited to the minority that has been successfully cultured. Molecular techniques now allow for obtaining genome sequences of uncultivated prokaryotic taxa, facilitating in-depth analyses that may ultimately improve our understanding of these key organisms. RESULTS: We compared results from two culture-independent strategies for recovering bacterial genomes: single-amplified genomes and metagenome-assembled genomes. Single-amplified genomes were obtained from samples collected at an offshore station in the Baltic Sea Proper and compared to previously obtained metagenome-assembled genomes from a time series at the same station. Among 16 single-amplified genomes analyzed, seven were found to match metagenome-assembled genomes, affiliated with a diverse set of taxa. Notably, genome pairs between the two approaches were nearly identical (average 99.51% sequence identity; range 98.77-99.84%) across overlapping regions (30-80% of each genome). Within matching pairs, the single-amplified genomes were consistently smaller and less complete, whereas the genetic functional profiles were maintained. For the metagenome-assembled genomes, only on average 3.6% of the bases were estimated to be missing from the genomes due to wrongly binned contigs. CONCLUSIONS: The strong agreement between the single-amplified and metagenome-assembled genomes emphasizes that both methods generate accurate genome information from uncultivated bacteria. Importantly, this implies that the research questions and the available resources are allowed to determine the selection of genomics approach for microbiome studies.

BARM and BalticMicrobeDB, a reference metagenome and interface to meta-omic data for the Baltic Sea.

The Baltic Sea is one of the world's largest brackish water bodies and is characterised by pronounced physicochemical gradients where microbes are the main biogeochemical catalysts. Meta-omic methods provide rich information on the composition of, and activities within, microbial ecosystems, but are computationally heavy to perform. We here present the Baltic Sea Reference Metagenome (BARM), complete with annotated genes to facilitate further studies with much less computational effort. The assembly is constructed using 2.6 billion metagenomic reads from 81 water samples, spanning both spatial and temporal dimensions, and contains 6.8 million genes that have been annotated for function and taxonomy. The assembly is useful as a reference, facilitating taxonomic and functional annotation of additional samples by simply mapping their reads against the assembly. This capability is demonstrated by the successful mapping and annotation of 24 external samples. In addition, we present a public web interface, BalticMicrobeDB, for interactive exploratory analysis of the dataset.

Stationary and portable sequencing-based approaches for tracing wastewater contamination in urban stormwater systems.

Urban sewer systems consist of wastewater and stormwater sewers, of which only wastewater is processed before being discharged. Occasionally, misconnections or damages in the network occur, resulting in untreated wastewater entering natural water bodies via the stormwater system. Cultivation of faecal indicator bacteria (e.g. Escherichia coli; E. coli) is the current standard for tracing wastewater contamination. This method is cheap but has limited specificity and mobility. Here, we compared the E. coli culturing approach with two sequencing-based methodologies (Illumina MiSeq 16S rRNA gene amplicon sequencing and Oxford Nanopore MinION shotgun metagenomic sequencing), analysing 73 stormwater samples collected in Stockholm. High correlations were obtained between E. coli culturing counts and frequencies of human gut microbiome amplicon sequences, indicating E. coli is indeed a good indicator of faecal contamination. However, the amplicon data further holds information on contamination source or alternatively how much time has elapsed since the faecal matter has entered the system. Shotgun metagenomic sequencing on a subset of the samples using a portable real-time sequencer, MinION, correlated well with the amplicon sequencing data. This study demonstrates the use of DNA sequencing to detect human faecal contamination in stormwater systems and the potential of tracing faecal contamination directly in the field.

Biogeochemical Cycling by a Low-Diversity Microbial Community in Deep Groundwater.

Olkiluoto, an island on the south-west coast of Finland, will host a deep geological repository for the storage of spent nuclear fuel. Microbially induced corrosion from the generation of sulphide is therefore a concern as it could potentially compromise the longevity of the copper waste canisters. Groundwater at Olkiluoto is geochemically stratified with depth and elevated concentrations of sulphide are observed when sulphate-rich and methane-rich groundwaters mix. Particularly high sulphide is observed in methane-rich groundwater from a fracture at 530.6 mbsl, where mixing with sulphate-rich groundwater occurred as the result of an open drill hole connecting two different fractures at different depths. To determine the electron donors fuelling sulphidogenesis, we combined geochemical, isotopic, metagenomic and metaproteomic analyses. This revealed a low diversity microbial community fuelled by hydrogen and organic carbon. Sulphur and carbon isotopes of sulphate and dissolved inorganic carbon, respectively, confirmed that sulphate reduction was ongoing and that CO2 came from the degradation of organic matter. The results demonstrate the impact of introducing sulphate to a methane-rich groundwater with limited electron acceptors and provide insight into extant metabolisms in the terrestrial subsurface.

DESMAN: a new tool for de novo extraction of strains from metagenomes.

We introduce DESMAN for De novo Extraction of Strains from Metagenomes. Large multi-sample metagenomes are being generated but strain variation results in fragmentary co-assemblies. Current algorithms can bin contigs into metagenome-assembled genomes but are unable to resolve strain-level variation. DESMAN identifies variants in core genes and uses co-occurrence across samples to link variants into haplotypes and abundance profiles. These are then searched for against non-core genes to determine the accessory genome of each strain. We validated DESMAN on a complex 50-species 210-genome 96-sample synthetic mock data set and then applied it to the Tara Oceans microbiome.

Ninety-nine de novo assembled genomes from the moose (Alces alces) rumen microbiome provide new insights into microbial plant biomass degradation.

The moose (Alces alces) is a ruminant that harvests energy from fiber-rich lignocellulose material through carbohydrate-active enzymes (CAZymes) produced by its rumen microbes. We applied shotgun metagenomics to rumen contents from six moose to obtain insights into this microbiome. Following binning, 99 metagenome-assembled genomes (MAGs) belonging to 11 prokaryotic phyla were reconstructed and characterized based on phylogeny and CAZyme profile. The taxonomy of these MAGs reflected the overall composition of the metagenome, with dominance of the phyla Bacteroidetes and Firmicutes. Unlike in other ruminants, Spirochaetes constituted a significant proportion of the community and our analyses indicate that the corresponding strains are primarily pectin digesters. Pectin-degrading genes were also common in MAGs of Ruminococcus, Fibrobacteres and Bacteroidetes and were overall overrepresented in the moose microbiome compared with other ruminants. Phylogenomic analyses revealed several clades within the Bacteriodetes without previously characterized genomes. Several of these MAGs encoded a large numbers of dockerins, a module usually associated with cellulosomes. The Bacteroidetes dockerins were often linked to CAZymes and sometimes encoded inside polysaccharide utilization loci, which has never been reported before. The almost 100 CAZyme-annotated genomes reconstructed in this study provide an in-depth view of an efficient lignocellulose-degrading microbiome and prospects for developing enzyme technology for biorefineries.

Metagenome-assembled genomes uncover a global brackish microbiome.

BACKGROUND: Microbes are main drivers of biogeochemical cycles in oceans and lakes. Although the genome is a foundation for understanding the metabolism, ecology and evolution of an organism, few bacterioplankton genomes have been sequenced, partly due to difficulties in cultivating them. RESULTS: We use automatic binning to reconstruct a large number of bacterioplankton genomes from a metagenomic time-series from the Baltic Sea, one of world's largest brackish water bodies. These genomes represent novel species within typical freshwater and marine clades, including clades not previously sequenced. The genomes' seasonal dynamics follow phylogenetic patterns, but with fine-grained lineage-specific variations, reflected in gene-content. Signs of streamlining are evident in most genomes, and estimated genome sizes correlate with abundance variation across filter size fractions. Comparing the genomes with globally distributed metagenomes reveals significant fragment recruitment at high sequence identity from brackish waters in North America, but little from lakes or oceans. This suggests the existence of a global brackish metacommunity whose populations diverged from freshwater and marine relatives over 100,000 years ago, long before the Baltic Sea was formed (8000 years ago). This markedly contrasts to most Baltic Sea multicellular organisms, which are locally adapted populations of freshwater or marine counterparts. CONCLUSIONS: We describe the gene content, temporal dynamics and biogeography of a large set of new bacterioplankton genomes assembled from metagenomes. We propose that brackish environments exert such strong selection that lineages adapted to them flourish globally with limited influence from surrounding aquatic communities.