Functional prediction of proteins from the human gut archaeome.

The human gastrointestinal tract contains diverse microbial communities, including archaea. Among them, Methanobrevibacter smithii represents a highly active and clinically relevant methanogenic archaeon, being involved in gastrointestinal disorders, such as inflammatory bowel disease and obesity. Herein, we present an integrated approach using sequence and structure information to improve the annotation of M. smithii proteins using advanced protein structure prediction and annotation tools, such as AlphaFold2, trRosetta, ProFunc, and DeepFri. Of an initial set of 873 481 archaeal proteins, we found 707 754 proteins exclusively present in the human gut. Having analysed archaeal proteins together with 87 282 994 bacterial proteins, we identified unique archaeal proteins and archaeal-bacterial homologs. We then predicted and characterized functional domains and structures of 73 unique and homologous archaeal protein clusters linked the human gut and M. smithii. We refined annotations based on the predicted structures, extending existing sequence similarity-based annotations. We identified gut-specific archaeal proteins that may be involved in defense mechanisms, virulence, adhesion, and the degradation of toxic substances. Interestingly, we identified potential glycosyltransferases that could be associated with N-linked and O-glycosylation. Additionally, we found preliminary evidence for interdomain horizontal gene transfer between Clostridia species and M. smithii, which includes sporulation Stage V proteins AE and AD. Our study broadens the understanding of archaeal biology, particularly M. smithii, and highlights the importance of considering both sequence and structure for the prediction of protein function.

Autotrophic biofilms sustained by deeply sourced groundwater host diverse bacteria implicated in sulfur and hydrogen metabolism.

BACKGROUND: Biofilms in sulfide-rich springs present intricate microbial communities that play pivotal roles in biogeochemical cycling. We studied chemoautotrophically based biofilms that host diverse CPR bacteria and grow in sulfide-rich springs to investigate microbial controls on biogeochemical cycling. RESULTS: Sulfide springs biofilms were investigated using bulk geochemical analysis, genome-resolved metagenomics, and scanning transmission X-ray microscopy (STXM) at room temperature and 87 K. Chemolithotrophic sulfur-oxidizing bacteria, including Thiothrix and Beggiatoa, dominate the biofilms, which also contain CPR Gracilibacteria, Absconditabacteria, Saccharibacteria, Peregrinibacteria, Berkelbacteria, Microgenomates, and Parcubacteria. STXM imaging revealed ultra-small cells near the surfaces of filamentous bacteria that may be CPR bacterial episymbionts. STXM and NEXAFS spectroscopy at carbon K and sulfur L2,3 edges show that filamentous bacteria contain protein-encapsulated spherical elemental sulfur granules, indicating that they are sulfur oxidizers, likely Thiothrix. Berkelbacteria and Moranbacteria in the same biofilm sample are predicted to have a novel electron bifurcating group 3b [NiFe]-hydrogenase, putatively a sulfhydrogenase, potentially linked to sulfur metabolism via redox cofactors. This complex could potentially contribute to symbioses, for example, with sulfur-oxidizing bacteria such as Thiothrix that is based on cryptic sulfur cycling. One Doudnabacteria genome encodes adjacent sulfur dioxygenase and rhodanese genes that may convert thiosulfate to sulfite. We find similar conserved genomic architecture associated with CPR bacteria from other sulfur-rich subsurface ecosystems. CONCLUSIONS: Our combined metagenomic, geochemical, spectromicroscopic, and structural bioinformatics analyses of biofilms growing in sulfide-rich springs revealed consortia that contain CPR bacteria and sulfur-oxidizing Proteobacteria, including Thiothrix, and bacteria from a new family within Beggiatoales. We infer roles for CPR bacteria in sulfur and hydrogen cycling. Video Abstract.

MuDoGeR: Multi-Domain Genome recovery from metagenomes made easy.

Several computational frameworks and workflows that recover genomes from prokaryotes, eukaryotes and viruses from metagenomes exist. Yet, it is difficult for scientists with little bioinformatics experience to evaluate quality, annotate genes, dereplicate, assign taxonomy and calculate relative abundance and coverage of genomes belonging to different domains. MuDoGeR is a user-friendly tool tailored for those familiar with Unix command-line environment that makes it easy to recover genomes of prokaryotes, eukaryotes and viruses from metagenomes, either alone or in combination. We tested MuDoGeR using 24 individual-isolated genomes and 574 metagenomes, demonstrating the applicability for a few samples and high throughput. While MuDoGeR can recover eukaryotic viral sequences, its characterization is predominantly skewed towards bacterial and archaeal viruses, reflecting the field's current state. However, acting as a dynamic wrapper, the MuDoGeR is designed to constantly incorporate updates and integrate new tools, ensuring its ongoing relevance in the rapidly evolving field. MuDoGeR is open-source software available at https://github.com/mdsufz/MuDoGeR. Additionally, MuDoGeR is also available as a Singularity container.

Dancing the Nanopore limbo - Nanopore metagenomics from small DNA quantities for bacterial genome reconstruction.

BACKGROUND: While genome-resolved metagenomics has revolutionized our understanding of microbial and genetic diversity in environmental samples, assemblies of short-reads often result in incomplete and/or highly fragmented metagenome-assembled genomes (MAGs), hampering in-depth genomics. Although Nanopore sequencing has increasingly been used in microbial metagenomics as long reads greatly improve the assembly quality of MAGs, the recommended DNA quantity usually exceeds the recoverable amount of DNA of environmental samples. Here, we evaluated lower-than-recommended DNA quantities for Nanopore library preparation by determining sequencing quality, community composition, assembly quality and recovery of MAGs. RESULTS: We generated 27 Nanopore metagenomes using the commercially available ZYMO mock community and varied the amount of input DNA from 1000 ng (the recommended minimum) down to 1 ng in eight steps. The quality of the generated reads remained stable across all input levels. The read mapping accuracy, which reflects how well the reads match a known reference genome, was consistently high across all libraries. The relative abundance of the species in the metagenomes was stable down to input levels of 50 ng. High-quality MAGs (> 95% completeness, ≤ 5% contamination) could be recovered from metagenomes down to 35 ng of input material. When combined with publicly available Illumina reads for the mock community, Nanopore reads from input quantities as low as 1 ng improved the quality of hybrid assemblies. CONCLUSION: Our results show that the recommended DNA amount for Nanopore library preparation can be substantially reduced without any adverse effects to genome recovery and still bolster hybrid assemblies when combined with short-read data. We posit that the results presented herein will enable studies to improve genome recovery from low-biomass environments, enhancing microbiome understanding.

Marine viruses disperse bidirectionally along the natural water cycle.

Marine viruses in seawater have frequently been studied, yet their dispersal from neuston ecosystems at the air-sea interface towards the atmosphere remains a knowledge gap. Here, we show that 6.2% of the studied virus population were shared between air-sea interface ecosystems and rainwater. Virus enrichment in the 1-mm thin surface microlayer and sea foams happened selectively, and variant analysis proved virus transfer to aerosols collected at ~2 m height above sea level and rain. Viruses detected in rain and these aerosols showed a significantly higher percent G/C base content compared to marine viruses. CRISPR spacer matches of marine prokaryotes to foreign viruses from rainwater prove regular virus-host encounters at the air-sea interface. Our findings on aerosolization, adaptations, and dispersal support transmission of viruses along the natural water cycle.

Exploring the efficacy of metabarcoding and non-target screening for detecting treated wastewater.

Wastewater treatment processes can eliminate many pollutants, yet remainder pollutants contain organic compounds and microorganisms released into ecosystems. These remainder pollutants have the potential to adversely impact downstream ecosystem processes, but their presence is currently not being monitored. This study was set out with the aim of investigating the effectiveness and sensitivity of non-target screening of chemical compounds, 18S V9 rRNA gene, and full-length 16S rRNA gene metabarcoding techniques for detecting treated wastewater in receiving waters. We aimed at assessing the impact of introducing 33 % treated wastewater into a triplicated large-scale mesocosm setup during a 10-day exposure period. Discharge of treated wastewater significantly altered the chemical signature as well as the microeukaryotic and prokaryotic diversity of the mesocosms. Non-target screening, 18S V9 rRNA gene, and full-length 16S rRNA gene metabarcoding detected these changes with significant covariation of the detected pattern between methods. The 18S V9 rRNA gene metabarcoding exhibited superior sensitivity immediately following the introduction of treated wastewater and remained one of the top-performing methods throughout the study. Full-length 16S rRNA gene metabarcoding demonstrated sensitivity only in the initial hour, but became insignificant thereafter. The non-target screening approach was effective throughout the experiment and in contrast to the metabarcoding methods the signal to noise ratio remained similar during the experiment resulting in an increasing relative strength of this method. Based on our findings, we conclude that all methods employed for monitoring environmental disturbances from various sources are suitable. The distinguishing factor of these methods is their ability to detect unknown pollutants and organisms, which sets them apart from previously utilized approaches and allows for a more comprehensive perspective. Given their diverse strengths, particularly in terms of temporal resolution, these methods are best suited as complementary approaches.

A predicted CRISPR-mediated symbiosis between uncultivated archaea.

CRISPR-Cas systems defend prokaryotic cells from invasive DNA of viruses, plasmids and other mobile genetic elements. Here, we show using metagenomics, metatranscriptomics and single-cell genomics that CRISPR systems of widespread, uncultivated archaea can also target chromosomal DNA of archaeal episymbionts of the DPANN superphylum. Using meta-omics datasets from Crystal Geyser and Horonobe Underground Research Laboratory, we find that CRISPR spacers of the hosts Candidatus Altiarchaeum crystalense and Ca. A. horonobense, respectively, match putative essential genes in their episymbionts' genomes of the genus Ca. Huberiarchaeum and that some of these spacers are expressed in situ. Metabolic interaction modelling also reveals complementation between host-episymbiont systems, on the basis of which we propose that episymbionts are either parasitic or mutualistic depending on the genotype of the host. By expanding our analysis to 7,012 archaeal genomes, we suggest that CRISPR-Cas targeting of genomes associated with symbiotic archaea evolved independently in various archaeal lineages.

Spatio-functional organization in virocells of small uncultivated archaea from the deep biosphere.

Despite important ecological roles posited for virocells (i.e., cells infected with viruses), studying individual cells in situ is technically challenging. We introduce here a novel correlative microscopic approach to study the ecophysiology of virocells. By conducting concerted virusFISH, 16S rRNA FISH, and scanning electron microscopy interrogations of uncultivated archaea, we linked morphologies of various altiarchaeal cells to corresponding phylogenetic signals and indigenous virus infections. While uninfected cells exhibited moderate separation between fluorescence signals of ribosomes and DNA, virocells displayed complete cellular segregation of chromosomal DNA from viral DNA, the latter co-localizing with host ribosome signals. A similar spatial separation was observed in dividing cells, with viral signals congregating near ribosomes at the septum. These observations suggest that replication of these uncultivated viruses occurs alongside host ribosomes, which are used to generate the required proteins for virion assembly. Heavily infected cells sometimes displayed virus-like particles attached to their surface, which agree with virus structures in cells observed via transmission electron microscopy. Consequently, this approach is the first to link genomes of uncultivated viruses to their respective structures and host cells. Our findings shed new light on the complex ecophysiology of archaeal virocells in deep subsurface biofilms and provide a solid framework for future in situ studies of virocells.

Temporal disturbance of a model stream ecosystem by high microbial diversity from treated wastewater.

Microbial communities in freshwater streams play an essential role in ecosystem functioning via biogeochemical cycling. Yet, the impacts of treated wastewater influx into stream ecosystems on microbial strain diversity remain mostly unexplored. Here, we coupled full-length 16S ribosomal RNA gene Nanopore sequencing and strain-resolved metagenomics to investigate the impact of treated wastewater on a mesocosm system (AquaFlow) run with restored river water. Over 10 days, community Bray-Curtis dissimilarities between treated and control mesocosm decreased (0.57 ± 0.058 to 0.26 ± 0.046) based on ribosomal protein S3 gene clustering, finally converging to nearly identical communities. Similarly, strain-resolved metagenomics revealed a high diversity of bacteria and viruses after the introduction of treated wastewater; these microbes also decreased over time resulting in the same strain clusters in control and treatment at the end of the experiment. Specifically, 39.2% of viral strains detected in all samples were present after the introduction of treated wastewater only. Although bacteria present at low abundance in the treated wastewater introduced additional antibiotic resistance genes, signals of naturally occurring ARG-encoding organisms resembled the resistome at the endpoint. Our results suggest that the previously stressed freshwater stream and its microbial community are resilient to a substantial introduction of treated wastewater.

Virus-Host Dynamics in Archaeal Groundwater Biofilms and the Associated Bacterial Community Composition.

Spatial and temporal distribution of lytic viruses in deep groundwater remains unexplored so far. Here, we tackle this gap of knowledge by studying viral infections of Altivir_1_MSI in biofilms dominated by the uncultivated host Candidatus Altiarchaeum hamiconexum sampled from deep anoxic groundwater over a period of four years. Using virus-targeted direct-geneFISH (virusFISH) whose detection efficiency for individual viral particles was 15%, we show a significant and steady increase of virus infections from 2019 to 2022. Based on fluorescence micrographs of individual biofilm flocks, we determined different stages of viral infections in biofilms for single sampling events, demonstrating the progression of infection of biofilms in deep groundwater. Biofilms associated with many host cells undergoing lysis showed a substantial accumulation of filamentous microbes around infected cells probably feeding off host cell debris. Using 16S rRNA gene sequencing across ten individual biofilm flocks from one sampling event, we determined that the associated bacterial community remains relatively constant and was dominated by sulfate-reducing members affiliated with Desulfobacterota. Given the stability of the virus-host interaction in these deep groundwater samples, we postulate that the uncultivated virus-host system described herein represents a suitable model system for studying deep biosphere virus-host interactions in future research endeavors.

uBin: A manual refining tool for genomes from metagenomes.

Resolving bacterial and archaeal genomes from metagenomes has revolutionized our understanding of Earth's biomes yet producing high-quality genomes from assembled fragments has been an ever-standing problem. While automated binning software and their combination produce prokaryotic bins in high throughput, their manual refinement has been slow, sometimes difficult or missing entirely facilitating error propagation in public databases. Here, we present uBin, a GUI-based, standalone bin refiner that runs on all major operating platforms and was additionally designed for educational purposes. When applied to the public CAMI dataset, refinement of bins using GC content, coverage and taxonomy was able to improve 78.9% of bins by decreasing their contamination. We also applied the bin refiner as a standalone binner to public metagenomes from the International Space Station and demonstrate the recovery of near-complete genomes, whose replication indices indicate the active proliferation of microbes in Earth's lower orbit. uBin is an easy to instal software for bin refinement, binning of simple metagenomes and communication of metagenomic results to other scientists and in classrooms. The software and its helper scripts are open source and available under https://github.com/ProbstLab/uBin.

The Asymmetric Response Concept explains ecological consequences of multiple stressor exposure and release.

Our capacity to predict trajectories of ecosystem degradation and recovery is limited, especially when impairments are caused by multiple stressors. Recovery may be fast or slow and either complete or partial, sometimes result in novel ecosystem states or even fail completely. Here, we introduce the Asymmetric Response Concept (ARC) that provides a basis for exploring and predicting the pace and magnitude of ecological responses to, and release from, multiple stressors. The ARC holds that three key mechanisms govern population, community and ecosystem trajectories. Stress tolerance is the main mechanism determining responses to increasing stressor intensity, whereas dispersal and biotic interactions predominantly govern responses to the release from stressors. The shifting importance of these mechanisms creates asymmetries between the ecological trajectories that follow increasing and decreasing stressor intensities. This recognition helps to understand multiple stressor impacts and to predict which measures will restore communities that are resistant to restoration.

Selective enrichment, identification, and isolation of diclofenac, ibuprofen, and carbamazepine degrading bacteria from a groundwater biofilm.

Diclofenac, ibuprofen, and carbamazepine are three of the most widely detected and most concerning pharmaceutical residues in aquatic ecosystems. The aim of this study was to identify bacteria that may be involved in their degradation from a bacterial biofilm. Selective enrichment cultures in mineral salt solution containing pharmaceutical compounds as sole source of carbon and energy were set up, and population dynamics were monitored using shotgun metagenome sequencing. Bacterial genomes were reconstructed using genome-resolved metagenomics. Thirty bacterial isolates were obtained, identified at species level, and tested regarding pharmaceutical biodegradation at an initial concentration of 1.5 mg l-1. The results indicated that most probably diclofenac biodegrading cultures consisted of members of genera Ferrovibrio, Hydrocarboniphaga, Zavarzinia, and Sphingopyxis, while in ibuprofen biodegradation Nocardioides and Starkeya, and in carbamazepine biodegradation Nocardioides, Pseudonocardia, and Sphingopyxis might be involved. During the enrichments, compared to the initial state the percentage relative abundance of these genera increased up to three orders of magnitude. Except Starkeya, the genomes of these bacteria were reconstructed and annotated. Metabolic analyses of the annotated genomes indicated that these bacteria harbored genes associated with pharmaceutical biodegradation. Stenotrophomonas humi DIC_5 and Rhizobium daejeonense IBU_18 isolates eliminated diclofenac and ibuprofen during the tests in the presence of either glucose (3 g l-1) or in R2A broth. Higher than 90% concentration reduction was observed in the case of both compounds.

Genomic remnants of ancestral methanogenesis and hydrogenotrophy in Archaea drive anaerobic carbon cycling.

Anaerobic methane metabolism is among the hallmarks of Archaea, originating very early in their evolution. Here, we show that the ancestor of methane metabolizers was an autotrophic CO2-reducing hydrogenotrophic methanogen that possessed the two main complexes, methyl-CoM reductase (Mcr) and tetrahydromethanopterin-CoM methyltransferase (Mtr), the anaplerotic hydrogenases Eha and Ehb, and a set of other genes collectively called "methanogenesis markers" but could not oxidize alkanes. Overturning recent inferences, we demonstrate that methyl-dependent hydrogenotrophic methanogenesis has emerged multiple times independently, either due to a loss of Mtr while Mcr is inherited vertically or from an ancient lateral acquisition of Mcr. Even if Mcr is lost, Mtr, Eha, Ehb, and the markers can persist, resulting in mixotrophic metabolisms centered around the Wood-Ljungdahl pathway. Through their methanogenesis remnants, Thorarchaeia and two newly reconstructed order-level lineages in Archaeoglobi and Bathyarchaeia act as metabolically versatile players in carbon cycling of anoxic environments across the globe.

Development of the SeqCode: A proposed nomenclatural code for uncultivated prokaryotes with DNA sequences as type.

Over the last fifteen years, genomics has become fully integrated into prokaryotic systematics. The genomes of most type strains have been sequenced, genome sequence similarity is widely used for delineation of species, and phylogenomic methods are commonly used for classification of higher taxonomic ranks. Additionally, environmental genomics has revealed a vast diversity of as-yet-uncultivated taxa. In response to these developments, a new code of nomenclature, the Code of Nomenclature of Prokaryotes Described from Sequence Data (SeqCode), has been developed over the last two years to allow naming of Archaea and Bacteria using DNA sequences as the nomenclatural types. The SeqCode also allows naming of cultured organisms, including fastidious prokaryotes that cannot be deposited into culture collections. Several simplifications relative to the International Code of Nomenclature of Prokaryotes (ICNP) are implemented to make nomenclature more accessible, easier to apply and more readily communicated. By simplifying nomenclature with the goal of a unified classification, inclusive of both cultured and uncultured taxa, the SeqCode will facilitate the naming of taxa in every biome on Earth, encourage the isolation and characterization of as-yet-uncultivated taxa, and promote synergies between the ecological, environmental, physiological, biochemical, and molecular biological disciplines to more fully describe prokaryotes.

SeqCode: a nomenclatural code for prokaryotes described from sequence data.

Most prokaryotes are not available as pure cultures and therefore ineligible for naming under the rules and recommendations of the International Code of Nomenclature of Prokaryotes (ICNP). Here we summarize the development of the SeqCode, a code of nomenclature under which genome sequences serve as nomenclatural types. This code enables valid publication of names of prokaryotes based upon isolate genome, metagenome-assembled genome or single-amplified genome sequences. Otherwise, it is similar to the ICNP with regard to the formation of names and rules of priority. It operates through the SeqCode Registry ( https://seqco.de/ ), a registration portal through which names and nomenclatural types are registered, validated and linked to metadata. We describe the two paths currently available within SeqCode to register and validate names, including Candidatus names, and provide examples for both. Recommendations on minimal standards for DNA sequences are provided. Thus, the SeqCode provides a reproducible and objective framework for the nomenclature of all prokaryotes regardless of cultivability and facilitates communication across microbiological disciplines.

Progress and Challenges in Studying the Ecophysiology of Archaea.

It has been less than two decades since the study of archaeal ecophysiology has become unshackled from the limitations of cultivation and amplicon sequencing through the advent of metagenomics. As a primer to the guide on producing archaeal genomes from metagenomes, we briefly summarize here how different meta'omics, imaging, and wet lab methods have contributed to progress in understanding the ecophysiology of Archaea. We then peer into the history of how our knowledge on two particularly important lineages was assembled: the anaerobic methane and alkane oxidizers, encountered primarily among Euryarchaeota, and the nanosized, mainly parasitic, members of the DPANN superphylum.

Reconstruction of Archaeal Genomes from Short-Read Metagenomes.

As the majority of biological diversity remains unexplored and uncultured, investigating it requires culture-independent approaches. Archaea in particular suffer from a multitude of issues that make their culturing problematic, from them being frequently members of the rare biosphere, to low growth rates, to them thriving under very specific and often extreme environmental and community conditions that are difficult to replicate. OMICs techniques are state of the art approaches that allow direct high-throughput investigations of environmental samples at all levels from nucleic acids to proteins, lipids, and secondary metabolites. Metagenomics, as the foundation for other OMICs techniques, facilitates the identification and functional characterization of the microbial community members and can be combined with other methods to provide insights into the microbial activities, both on the RNA and protein levels. In this chapter, we provide a step-by-step workflow for the recovery of archaeal genomes from metagenomes, starting from raw short-read sequences. This workflow can be applied to recover bacterial genomes as well.