Cultivation-independent genomes greatly expand taxonomic-profiling capabilities of mOTUs across various environments

Machine learning-based meta-analysis reveals gut microbiome alterations associated with Parkinson's disease

There is strong interest in using the gut microbiome for Parkinson's disease (PD) diagnosis and treatment. However, a consensus on PD-associated microbiome features and a multi-study assessment of their diagnostic value is lacking. Here, we present a machine learning meta-analysis of PD microbiome studies of unprecedented scale (4489 samples). Within most studies, microbiome-based machine learning models accurately classify PD patients (average AUC 71.9%). However, these models are study-specific and do not generalise well across other studies (average AUC 61%). Training models on multiple datasets improves their generalizability (average LOSO AUC 68%) and disease specificity as assessed against microbiomes from other neurodegenerative diseases. Moreover, meta-analysis of shotgun metagenomes delineates PD-associated microbial pathways potentially contributing to gut health deterioration and favouring the translocation of pathogenic molecules along the gut-brain axis. Strikingly, microbial pathways for solvent and pesticide biotransformation are enriched in PD. These results align with epidemiological evidence that exposure to these molecules increases PD risk and raise the question of whether gut microbes modulate their toxicity. Here, we offer the most comprehensive overview to date about the PD gut microbiome and provide future reference for its diagnostic and functional potential.

CAMI Benchmarking Portal: online evaluation and ranking of metagenomic software

Finding appropriate software and parameter settings to process shotgun metagenome data is essential for meaningful metagenomic analyses. To enable objective and comprehensive benchmarking of metagenomic software, the community-led initiative for the Critical Assessment of Metagenome Interpretation (CAMI) promotes standards and best practices. Since 2015, CAMI has provided comprehensive datasets, benchmarking guidelines, and challenges. However, benchmarking had to be conducted offline, requiring substantial time and technical expertise and leading to gaps in results between challenges. We introduce the CAMI Benchmarking Portal-a central repository of CAMI resources and web server for the evaluation and ranking of metagenome assembly, binning, and taxonomic profiling software. The portal simplifies evaluation, enabling users to easily compare their results with previous and other users' submissions through a variety of metrics and visualizations. As a demonstration, we benchmark software performance on the marine dataset of the CAMI II challenge. The portal currently hosts 28 675 results and is freely available at https://cami-challenge.org/.

Microtubules in Asgard archaea

Microtubules are a hallmark of eukaryotes. Archaeal and bacterial homologs of tubulins typically form homopolymers and non-tubular superstructures. The origin of heterodimeric tubulins assembling into microtubules remains unclear. Here, we report the discovery of microtubule-forming tubulins in Asgard archaea, the closest known relatives of eukaryotes. These Asgard tubulins (AtubA/B) are closely related to eukaryotic α/β-tubulins and the enigmatic bacterial tubulins BtubA/B. Proteomics of Candidatus Lokiarchaeum ossiferum showed that AtubA/B were highly expressed. Cryoelectron microscopy structures demonstrate that AtubA/B form eukaryote-like heterodimers, which assembled into 5-protofilament bona fide microtubules in vitro. The additional paralog AtubB2 lacks a nucleotide-binding site and competitively displaced AtubB. These AtubA/B2 heterodimers polymerized into 7-protofilament non-canonical microtubules. In a sub-population of Ca. Lokiarchaeum ossiferum cells, cryo-tomography revealed tubular structures, while expansion microscopy identified AtubA/B cytoskeletal assemblies. Our findings suggest a pre-eukaryotic origin of microtubules and provide a framework for understanding the fundamental principles of microtubule assembly.

Multiple extracellular polymeric substance pathways transcribed by Accumulibacter and the flanking community during aerobic granule formation and after influent modification

Aerobic granular sludge is a biological wastewater treatment process in which a microbial community forms a granular biofilm. The role of Candidatus Accumulibacter in the production of a biofilm matrix composed of extracellular polymeric substances was studied in a sequencing batch reactor enriched with polyphosphate-accumulating organisms. The metabolisms of the microbial populations were investigated using de novo metatranscriptomics analysis. Finally, the effect of decreasing the influent phosphate concentration on the granule stability and microbial activity was investigated. A few weeks after the reactor start-up, the microbial community was dominated by Accumulibacter with up to nine species active in parallel. However, the most active species differed according to sampling time. Decreasing drastically the influent phosphate concentration led to a dominance of the glycogen-accumulating organism Propionivibrio, with some Accumulibacter species still abundant. De novo metatranscriptomics analysis indicated a high diversity of potential extracellular substances produced mainly by Accumulibacter, Azonexus, Candidatus Contendobacter, and Propionivibrio. Moreover, the results suggest that Azonexus, Contendobacter, and Propionivibrio recycle the neuraminic acids produced by Accumulibacter. Changes in the microbial community did not cause the granules to disintegrate, indicating that a Propionivibrio-dominated community can maintain stable granules.IMPORTANCEOne of the main advantages of the aerobic granular sludge wastewater treatment process is the higher settling velocities compared to the conventional activated sludge-based process. In aerobic granular sludge, the biomass is concentrated into a biofilm matrix composed of biopolymers, providing micro-niches to different types of microbial populations. We demonstrate with the help of de novo metatranscriptomics analysis that the formation of granules is a highly dynamic microbial process, even when enriching for a microbial guild, such as phosphate-accumulating organisms. Often underestimated, the flanking community of the main phosphate-accumulating organisms population enriched in the reactor is nonetheless active and transcribing genes related to different extracellular polymeric substance pathways. The multiplicity of the extracellular polymeric substances produced probably helped the matrix to remain stable, thanks to their specific properties. Moreover, the results suggest microbial interactions in extracellular polymeric substance recycling between different microbial populations that can be helpful to prevent a disruption of the granules while stressing out the microbial community.

Environmental drivers of the resistome across the Baltic Sea

BACKGROUND

Antimicrobial resistance is a major global health concern, with the environment playing a key role in its emergence and spread. Understanding the relationships between environmental factors, microbial communities, and resistance mechanisms is vital for elucidating environmental resistome dynamics. In this study, we characterized the environmental resistome of the Baltic Sea and evaluated how environmental gradients and spatial variability, alongside its microbial communities and associated functional genes, influence resistome diversity and composition across geographic regions.

RESULTS

We analyzed the metagenomes of benthic sediments from 59 monitoring stations across a 1,150 km distance of the Baltic Sea, revealing an environmental resistome comprised of predicted antimicrobial resistance genes (ARGs) associated with resistance against 26 antibiotic classes. We observed spatial variation in its resistance profile, with higher resistome diversity in the northern regions and a decline in the dead zones and the southern areas. The combined effects of salinity and temperature gradients, alongside nutrient availability, created a complex environmental landscape that shaped the diversity and distribution of the predicted ARGs. Salinity predominantly influenced microbial communities and predicted ARG composition, leading to clear distinctions between high-saline regions and those with lower to mid-level salinity. Furthermore, our analysis suggests that microbial community composition and mobile genetic elements might be crucial in shaping ARG diversity and composition.

CONCLUSIONS

We presented that salinity and temperature were identified as the primary environmental factors influencing resistome diversity and distribution across geographic regions, with nutrient availability further shaping these patterns in the Baltic Sea. Our study also highlighted the interplay between microbial communities, resistance, and associated functional genes in the benthic ecosystem, underscoring the potential role of microbial and mobile genetic element composition in ARG distribution. Understanding how environmental factors and microbial communities modulate environmental resistomes will help predict the impact of future environmental changes on resistance mechanisms in complex aquatic ecosystems. Video Abstract.

TIPP3 and TIPP3-fast: Improved abundance profiling in metagenomics

We present TIPP3 and TIPP3-fast, new tools for abundance profiling in metagenomic datasets. Like its predecessor, TIPP2, the TIPP3 pipeline uses a maximum likelihood approach to place reads into labeled taxonomies using marker genes, but it achieves superior accuracy to TIPP2 by enabling the use of much larger taxonomies through improved algorithmic techniques. We show that TIPP3 is generally more accurate than leading methods for abundance profiling in two important contexts: when reads come from genomes not already in a public database (i.e., novel genomes) and when reads contain sequencing errors. We also show that TIPP3-fast has slightly lower accuracy than TIPP3, but is also generally more accurate than other leading methods and uses a small fraction of TIPP3's runtime. Additionally, we highlight the potential benefits of restricting abundance profiling methods to those reads that map to marker genes (i.e., using a filtered marker-gene based analysis), which we show typically improves accuracy. TIPP3 is freely available at https://github.com/c5shen/TIPP3.

Heterologous Expression of a Cryptic BGC from Bilophila sp. Provides Access to a Novel Family of Antibacterial Thiazoles

Human health is greatly influenced by the gut microbiota and microbiota imbalance can lead to the development of diseases. It is widely acknowledged that the interaction of bacteria within competitive ecosystems is influenced by their specialized metabolites, which act, e.g., as antibacterials or siderophores. However, our understanding of the occurrence and impact of such natural products in the human gut microbiome remains very limited. As arylthiazole siderophores are an emerging family of growth-promoting molecules in pathogenic bacteria, we analyzed a metagenomic data set from the human microbiome and thereby identified the bil-BGC, which originates from an uncultured Bilophila strain. Through gene synthesis and BGC assembly, heterologous expression and mutasynthetic experiments, we discovered the arylthiazole natural products bilothiazoles A-F. While established activities of related molecules indicate their involvement in metal-binding and -uptake, which could promote the growth of pathogenic strains, we also found antibiotic activity for some bilothiazoles. This is supported by biosensor-experiments, where bilothiazoles C and E show PrecA-suppressing activity, while bilothiazole F induces PblaZ, a biosensor characteristic for β-lactam antibiotics. These findings serve as a starting point for investigating the role of bilothiazoles in the pathogenicity of Bilophila species in the gut.

Adaptive sequence alignment for metagenomic data analysis

With advances in sequencing technologies, the use of high-throughput sequencing to characterize microbial communities is becoming increasingly feasible. However, metagenomic assembly poses computational challenges in reconstructing genes and organisms from complex samples. To address this issue, we introduce a new concept called Adaptive Sequence Alignment (ASA) for analyzing metagenomic DNA sequence data. By iteratively adapting a set of partial alignments of reference sequences to match the sample data, the approach can be applied in multiple scenarios, from taxonomic identification to assembly of target regions of interest. To demonstrate the benefits of ASA, we present two application scenarios and compare the results with state-of-the-art methods conventionally used for the same tasks. In the first, ASA accurately detected microorganisms from a sequenced metagenomic sample with a known composition. The second illustrated the utility of ASA in assembling target genetic regions of the microorganisms. An example implementation of the ASA concept is available at https://github.com/elolab/ASA.

Newly identified species from the dog dental plaque microbiome highlight little overlap with humans

Understudied pet-associated microbiomes represent a rich source for the discovery of microbial taxa important for pet and human health. From a cohort of 23 dogs, we sampled and metagenomically sequenced 64 dental plaque microbiomes, generating 1945 metagenome-assembled genomes spanning 347 microbial species, including 277 undercharacterized species without cultivated representatives. Integration with human microbiome data revealed the dog plaque microbiome is more diverse than - and shows little overlap (5.9% species in common) with - the human plaque microbiome, even though some shared periodontal pathobionts arise as a potential concern.

Virulence factor discovery identifies associations between the Fic gene family and Fap2+ fusobacteria in colorectal cancer microbiomes

Fusobacterium is a bacterium associated with colorectal cancer (CRC) tumorigenesis, progression, and metastasis. Fap2 is a fusobacteria-specific outer membrane galactose-binding lectin that mediates Fusobacterium adherence to and invasion of CRC tumors. Advances in omics analyses provide an opportunity to profile and identify microbial genomic features that correlate with the cancer-associated bacterial virulence factor Fap2. Here, we analyze genomes of Fusobacterium colon tumor isolates and find that a family of post-translational modification enzymes containing Fic domains is associated with Fap2 positivity in these strains. We demonstrate that Fic family genes expand with the presence of Fap2 in the fusobacterial pangenome. Through comparative genomic analysis, we find that Fap2+ Fusobacteriota are highly enriched with Fic gene families compared to other cancer-associated and human gut microbiome bacterial taxa. Using a global data set of CRC shotgun metagenomes, we show that fusobacterial Fic and Fap2 genes frequently co-occur in the fecal microbiomes of individuals with late-stage CRC. We further characterize specific Fic gene families harbored by Fap2+ Fusobacterium animalis genomes and detect recombination events and elements of horizontal gene transfer via synteny analysis of Fic gene loci. Exposure of a F. animalis strain to a colon adenocarcinoma cell line increases gene expression of fusobacterial Fic and virulence-associated adhesins. Finally, we demonstrate that Fic proteins are synthesized by F. animalis as Fic peptides are detectable in F. animalis monoculture supernatants. Taken together, our study uncovers Fic genes as potential virulence factors in Fap2+ fusobacterial genomes.IMPORTANCEAccumulating data support that bacterial members of the intra-tumoral microbiota critically influence colorectal cancer progression. Yet, relatively little is known about non-adhesin fusobacterial virulence factors that may influence carcinogenesis. Our genomic analysis and expression assays in fusobacteria identify Fic domain-containing genes, well-studied virulence factors in pathogenic bacteria, as potential fusobacterial virulence features. The Fic family proteins that we find are encoded by fusobacteria and expressed by Fusobacterium animalis merit future investigation to assess their roles in colorectal cancer development and progression.

Dynamics of Gut Microbiota After Fecal Microbiota Transplantation in Ulcerative Colitis: Success Linked to Control of Prevotellaceae

BACKGROUND

Fecal microbiota transplantation (FMT) is an experimental treatment for ulcerative colitis (UC). We aimed to study microbial families associated with FMT treatment success.

METHODS

We analyzed stools from 24 UC patients treated with 4 FMTs weekly after randomization for pretreatment during 3 weeks with budesonide (n = 12) or placebo (n = 12). Stool samples were collected 9 times pre-, during, and post-FMT. Clinical and endoscopic response was assessed 14 weeks after initiation of the study using the full Mayo score. Early withdrawal due to worsening of UC symptoms was classified as non-response.

RESULTS

Nine patients (38%) reached remission at week 14, and 15 patients had a partial response or non-response at or before week 14. With a Dirichlet multinomial mixture model, we identified 5 distinct clusters based on the microbiota composition of 180 longitudinally collected patient samples and 27 donor samples. A Prevotellaceae-dominant cluster was associated with poor response to FMT treatment. Conversely, the families Ruminococcaceae and Lachnospiraceae were associated with a successful clinical response. These associations were already visible at the start of the treatment for a subgroup of patients and were retained in repeated measures analyses of family-specific abundance over time. Responders were also characterized by a significantly lower Simpson dominance compared to non-responders.

CONCLUSIONS

The success of FMT treatment of UC patients appears to be associated with specific gut microbiota families, such as control of Prevotellaceae. Monitoring the dynamics of these microbial families could potentially be used to inform treatment success early during FMT.

CLINICAL TRIAL REGISTRATION NUMBER

The study was registered in the Netherlands Trial Register, with reference number NL9858.

Assessing environmental gradients in relation to dark CO2 fixation in estuarine wetland microbiomes

The rising atmospheric concentration of CO2 is a major concern to society due to its global warming potential. In soils, CO2-fixing microorganisms are preventing some of the CO2 from entering the atmosphere. Yet, the controls of dark CO2 fixation are rarely studied in situ. Here, we examined the gene and transcript abundance of key genes involved in microbial CO2 fixation along major environmental gradients within estuarine wetlands. A combined multi-omics approach incorporating metabarcoding, deep metagenomic, and metatranscriptomic analyses confirmed that wetland microbiota harbor four out of seven known CO2 fixation pathways, namely, the Calvin cycle, reverse tricarboxylic acid cycle, Wood-Ljungdahl pathway, and reverse glycine pathway. These pathways are transcribed at high frequencies along several environmental gradients, albeit at different levels depending on the environmental niche. Notably, the transcription of the key genes for the reverse tricarboxylic acid cycle was associated with high nitrate concentration, while the transcription of key genes for the Wood-Ljungdahl pathway was favored by reducing, O2-poor conditions. The transcript abundance of the Calvin cycle was favored by niches high in organic matter. Taxonomic assignment of transcripts implied that dark CO2 fixation was mainly linked to a few bacterial phyla, namely, Desulfobacterota, Methylomirabilota, Nitrospirota, Chloroflexota, and Pseudomonadota.

IMPORTANCE

The increasing concentration of atmospheric CO2 has been identified as the primary driver of climate change and poses a major threat to human society. This work explores the mostly overlooked potential of light-independent CO2 fixation by soil microbes (a.k.a. dark CO2 fixation) in climate change mitigation efforts. Applying a combination of molecular microbial tools, our research provides new insights into the ecological niches where CO2-fixing pathways are most active. By identifying how environmental factors, like oxygen, salinity and organic matter availability, influence these pathways in an estuarine wetland environment, potential strategies for enhancing natural carbon sinks can be developed. The importance of our research is in advancing the understanding of microbial CO2 fixation and its potential role in the global climate system.

Metagenomic global survey and in-depth genomic analyses of Ruminococcus gnavus reveal differences across host lifestyle and health status

Ruminococcus gnavus is a gut bacterium found in > 90% of healthy individuals, but its increased abundance is also associated with chronic inflammatory diseases, particularly Crohn's disease. Nevertheless, its global distribution and intraspecies genomic variation remain understudied. By surveying 12,791 gut metagenomes, we recapitulated known associations with metabolic diseases and inflammatory bowel disease. We uncovered a higher prevalence and abundance of R. gnavus in Westernized populations and observed bacterial relative abundances up to 83% in newborns. Next, we built a resource of R. gnavus isolates (N = 45) from healthy individuals and Crohn's disease patients and generated complete R. gnavus genomes using PacBio circular consensus sequencing. Analysis of these genomes and publicly available high-quality draft genomes (N = 333 genomes) revealed multiple clades which separated Crohn's-derived isolates from healthy-derived isolates. Presumed R. gnavus virulence factors could not explain this separation. Bacterial genome-wide association study revealed that Crohn's-derived isolates were enriched in genes related to mobile elements and mucin foraging. Together, we present a large R. gnavus resource that will be available to the scientific community and provide novel biological insights into the global distribution and genomic variation of R. gnavus.

Ribosomal protein phylogeography offers quantitative insights into the efficacy of genome-resolved surveys of microbial communities

The increasing availability of microbial genomes is essential to gain insights into microbial ecology and evolution that can propel biotechnological and biomedical advances. Recent advances in genome recovery have significantly expanded the catalogue of microbial genomes from diverse habitats. However, the ability to explain how well a set of genomes account for the diversity in a given environment remains challenging for individual studies or biome-specific databases. Here we present EcoPhylo, a computational workflow to characterize the phylogeography of any gene family through integrated analyses of genomes and metagenomes, and our application of this approach to ribosomal proteins to quantify phylogeny-aware genome recovery rates across three biomes. Our findings show that genome recovery rates vary widely across taxa and biomes, and that single amplified genomes, metagenome-assembled genomes, and isolate genomes have non-uniform yet quantifiable representation of environmental microbes. EcoPhylo reveals highly resolved, reference-free, multi-domain phylogenies in conjunction with distribution patterns of individual clades across environments, providing a means to assess genome recovery in individual studies and benchmark biome-level genome collections.

The mOTUs online database provides web-accessible genomic context to taxonomic profiling of microbial communities

Determining the taxonomic composition (taxonomic profiling) is a fundamental task in studying environmental and host-associated microbial communities. However, genome-resolved microbial diversity on Earth remains undersampled, and accessing the genomic context of taxa detected during taxonomic profiling remains a challenging task. Here, we present the mOTUs online database (mOTUs-db), which is consistent with and interfaces with the mOTUs taxonomic profiling tool. It comprises 2.83 million metagenome-assembled genomes (MAGs) and 919 090 single-cell and isolate genomes from 124 295 species-level taxonomic units. In addition to being one of the largest prokaryotic genome resources to date, all MAGs in the mOTUs-db were reconstructed de novo in 117 902 individual samples by abundance correlation of scaffolds across multiple samples for improved quality metrics. The database complements the Genome Taxonomy Database, with over 50% of its species-level taxonomic groups being unique. It also offers interactive querying, enabling users to explore and download genomes at various taxonomic levels. The mOTUs-db is accessible at https://motus-db.org.

Genetic and species rearrangements in microbial consortia impact biodegradation potential

Genomic reorganisation between species and horizontal gene transfer have been considered the most important mechanism of biological adaptation under selective pressure. Still, the impact of mobile genes in microbial ecology is far from being completely understood. Here we present the collection and characterisation of microbial consortia enriched from environments contaminated with emerging pollutants, such as non-steroidal anti-inflammatory drugs. We have obtained and further enriched two ibuprofen-degrading microbial consortia from two unrelated wastewater treatment plants. We have also studied their ability to degrade the drug and the dynamics of the re-organisations of the genetic information responsible for its biodegradation among the species within the consortium. Our results show that genomic reorganisation within microorganisms and species rearrangements occur rapidly and efficiently during the selection process, which may be facilitated by plasmids and/or transposable elements located within the sequences. We show the evolution of at least two different plasmid backbones on samples from different locations, showing rearrangements of genomic information, including genes encoding activities for IBU degradation. As a result, we found variations in the expression pattern of the consortia after evolution under selective pressure, as an adaptation process to the new conditions. This work provides evidence for changes in the metagenomes of microbial communities that allow adaptation under a selective constraint -ibuprofen as a sole carbon source- and represents a step forward in knowledge that can inspire future biotechnological developments for drug bioremediation.

A conserved pilin from uncultured gut bacterial clade TANB77 enhances cancer immunotherapy

Immune checkpoint blockade (ICB) has become a standard anti-cancer treatment, offering durable clinical benefits. However, the limited response rate of ICB necessitates biomarkers to predict and modulate the efficacy of the therapy. The gut microbiome's influence on ICB efficacy is of particular interest due to its modifiability through various interventions. However, gut microbiome biomarkers for ICB response have been inconsistent across different studies. Here, we identify TANB77, an uncultured and distinct bacterial clade, as the most consistent responder-enriched taxon through meta-analysis of ten independent ICB recipient cohorts. Traditional taxonomy fails to distinguish TANB77 from unrelated taxa, leading to its oversight. Mice with higher gut TANB77 abundance, either naturally or through transplantation, show improved response to anti-PD-1 therapy. Additionally, mice injected with TANB77-derived pilin-like protein exhibit improved anti-PD-1 therapy response, providing in vivo evidence for the beneficial role of the pilin-like protein. These findings suggest that pilins from the TANB77 order may enhance responses to ICB therapy across diverse cohorts of cancer patients.

Metagenomic approach reveals the role of bioagents in the environmental dissemination risk of rhizosphere soil antibiotic resistance genes pollution

Antibiotic resistance genes (ARGs) have been identified as emerging contaminants, raising concerns around the world. As environmentally friendly bioagents (BA), plant growth-promoting rhizobacteria (PGPR) have been used in agricultural systems. The introduction of BA will lead to the turnover of the microbial communities structure. Nevertheless, it is still unclear how the colonization of the invaded microorganisms could affects the rhizosphere resistome. Consequently, 190 ARGs and 25 integrative and conjugative elements (ICEs) were annotated using the metagenomic approach in 18 samples from the Solanaceae crop rhizosphere soil under BA and conventional treatment (CK) groups. Our study found that, after 90 days of treatment, ARG abundance was lower in the CK group than in the BA group. The results showed that aminoglycoside antibiotic resistance (OprZ), phenicol antibiotic resistance (OprN), aminoglycoside antibiotic resistance (ceoA/B), aminocoumarin antibiotic resistance (mdtB) and phenicol antibiotic resistance (MexW) syntenic with ICEs. Moreover, in 11 sequences, OprN (phenicol antibiotic resistance) was observed to have synteny with ICEPaeLESB58-1, indicating that the ICEs could contribute to the spread of ARGs. Additionally, the binning result showed that the potential bacterial hosts of the ARGs were beneficial bacteria which could promote the nutrition cycle, such as Haliangium, Nitrospira, Sideroxydans, Burkholderia, etc, suggesting that bacterial hosts have a great influence on ARG profiles. According to the findings, considering the dissemination of ARGs, BA should be applied with caution, especially the use of beneficial bacteria in BA. In a nutshell, this study offers valuable insights into ARGs pollution control from the perspective of the development and application of BA, to make effective strategies for blocking pollution risk migration in the ecological environment.

Constructing phylogenetic trees for microbiome data analysis: A mini-review

As next-generation sequencing technologies advance rapidly and the cost of metagenomic sequencing continues to decrease, researchers now face an unprecedented volume of microbiome data. This surge has stimulated the development of scalable microbiome data analysis methods and necessitated the incorporation of phylogenetic information into microbiome analysis for improved accuracy. Tools for constructing phylogenetic trees from 16S rRNA sequencing data are well-established, as the highly conserved regions of the 16S gene are limited, simplifying the identification of marker genes. In contrast, metagenomic and whole genome shotgun (WGS) sequencing involve sequencing from random fragments of the entire gene, making identification of consistent marker genes challenging owing to the vast diversity of genomic regions, resulting in a scarcity of robust tools for constructing phylogenetic trees. Although bacterial sequence tree construction tools exist for upstream bioinformatics, many downstream researchers-those integrating these trees into statistical models or machine learning-are either unaware of these tools or find them difficult to use due to the steep learning curve of processing raw sequences. This is compounded by the fact that public datasets often lack phylogenetic trees, providing only abundance tables and taxonomic classifications. To address this, we present a comprehensive review of phylogenetic tree construction techniques for microbiome data (16S rRNA or whole-genome shotgun sequencing). We outline the strengths and limitations of current methods, offering expert insights and step-by-step guidance to make these tools more accessible and widely applicable in quantitative microbiome data analysis.

Multi-biome analysis identifies distinct gut microbial signatures and their crosstalk in ulcerative colitis and Crohn's disease

The integrative multi-kingdom interaction of the gut microbiome in ulcerative colitis (UC) and Crohn's disease (CD) remains underinvestigated. Here, we perform shotgun metagenomic sequencing of feces from patients with UC and CD, and healthy controls in the Japanese 4D cohort, profiling bacterial taxa, gene functions, and antibacterial genes, bacteriophages, and fungi. External metagenomic datasets from the US, Spain, the Netherlands, and China were analyzed to validate our multi-biome findings. We found that Enterococcus faecium and Bifidobacterium spp. were enriched in both diseases. Enriched Escherichia coli was characteristic of CD and was linked to numerous antibiotic resistance genes involved in efflux pumps and adherent-invasive Escherichia coli virulence factors. Virome changes correlated with shifts in the bacteriome, including increased abundances of phages encoding pathogenic genes. Saccharomyces paradoxus and Saccharomyces cerevisiae were enriched in UC and CD, respectively. Saccharomyces cerevisiae and Escherichia coli had negative associations with short-chain fatty acid (SCFA)-producing bacteria in CD. Multi-biome signatures and their interactions in UC and CD showed high similarities between Japan and other countries. Since bacteria, phages, and fungi formed multiple hubs of intra- or trans-kingdom networks with SCFA producers and pathobionts in UC and CD, an approach targeting the interaction network may hold therapeutic promise.

Evaluating metagenomic analyses for undercharacterized environments: what's needed to light up the microbial dark matter?

Non-human-associated microbial communities play important biological roles, but they remain less understood than human-associated communities. Here, we assess the impact of key environmental sample properties on a variety of state-of-the-art metagenomic analysis methods. In simulated datasets, all methods performed similarly at high taxonomic ranks, but newer marker-based methods incorporating metagenomic assembled genomes outperformed others at lower taxonomic levels. In real environmental data, taxonomic profiles assigned to the same sample by different methods showed little agreement at lower taxonomic levels, but the methods agreed better on community diversity estimates and estimates of the relationships between environmental parameters and microbial profiles.

Emergence of community behaviors in the gut microbiota upon drug treatment

Pharmaceuticals can directly inhibit the growth of gut bacteria, but the degree to which such interactions manifest in complex community settings is an open question. Here, we compared the effects of 30 drugs on a 32-species synthetic community with their effects on each community member in isolation. While most individual drug-species interactions remained the same in the community context, communal behaviors emerged in 26% of all tested cases. Cross-protection during which drug-sensitive species were protected in community was 6 times more frequent than cross-sensitization, the converse phenomenon. Cross-protection decreased and cross-sensitization increased at higher drug concentrations, suggesting that the resilience of microbial communities can collapse when perturbations get stronger. By metabolically profiling drug-treated communities, we showed that both drug biotransformation and bioaccumulation contribute mechanistically to communal protection. As a proof of principle, we molecularly dissected a prominent case: species expressing specific nitroreductases degraded niclosamide, thereby protecting both themselves and sensitive community members.

Surface microlayer-mediated virome dissemination in the Central Arctic

BACKGROUND

Aquatic viruses act as key players in shaping microbial communities. In polar environments, they face significant challenges such as limited host availability and harsh conditions. However, due to the restricted accessibility of these ecosystems, our understanding of viral diversity, abundance, adaptations, and host interactions remains limited.

RESULTS

To fill this knowledge gap, we studied viruses from atmosphere-close aquatic ecosystems in the Central Arctic and Northern Greenland. Aquatic samples for virus-host analysis were collected from ~60 cm depth and the submillimeter surface microlayer (SML) during the Synoptic Arctic Survey 2021 on icebreaker Oden in the Arctic summer. Water was sampled from a melt pond and open water before undergoing size-fractioned filtration, followed by genome-resolved metagenomic and cultivation investigations. The prokaryotic diversity in the melt pond was considerably lower compared to that of open water. The melt pond was dominated by a Flavobacterium sp. and Aquiluna sp., the latter having a relatively small genome size of 1.2 Mb and the metabolic potential to generate ATP using the phosphate acetyltransferase-acetate kinase pathway. Viral diversity on the host fraction (0.2-5 µm) of the melt pond was strikingly limited compared to that of open water. From the 1154 viral operational taxonomic units (vOTUs), of which two-thirds were predicted bacteriophages, 17.2% encoded for auxiliary metabolic genes (AMGs) with metabolic functions. Some AMGs like glycerol-3-phosphate cytidylyltransferase and ice-binding like proteins might serve to provide cryoprotection for the host. Prophages were often associated with SML genomes, and two active prophages of new viral genera from the Arctic SML strain Leeuwenhoekiella aequorea Arc30 were induced. We found evidence that vOTU abundance in the SML compared to that of ~60 cm depth was more positively correlated with the distribution of a vOTU across five different Arctic stations.

CONCLUSIONS

The results indicate that viruses employ elaborate strategies to endure in extreme, host-limited environments. Moreover, our observations suggest that the immediate air-sea interface serves as a platform for viral distribution in the Central Arctic. Video Abstract.

CHAMP delivers accurate taxonomic profiles of the prokaryotes, eukaryotes, and bacteriophages in the human microbiome

Introduction

Accurate taxonomic profiling of the human microbiome composition is crucial for linking microbial species to health outcomes. Therefore, we created the Clinical Microbiomics Human Microbiome Profiler (CHAMP), a comprehensive tool designed for the profiling of prokaryotes, eukaryotes, and viruses across all body sites.

Methods

CHAMP uses a reference database derived from 30,382 human microbiome samples, covering 6,567 prokaryotic and 244 eukaryotic species, as well as 64,003 viruses. We benchmarked CHAMP against established profiling tools (MetaPhlAn 4, Bracken 2, mOTUs 3, and Phanta) using a diverse set of in silico metagenomes and DNA mock communities.

Results

CHAMP demonstrated unparalleled species recall, F1 score, and significantly reduced false positives compared to all other tools benchmarked. The false positive relative abundance (FPRA) for CHAMP was, on average, 50-fold lower than the second-best performing profiler. CHAMP also proved to be more robust than other tools at low sequencing depths, highlighting its application for low biomass samples.

Discussion

Taken together, this establishes CHAMP as a best-in-class human microbiome profiler of prokaryotes, eukaryotes, and viruses in diverse and complex communities across low and high biomass samples. CHAMP profiling is offered as a service by Clinical Microbiomics A/S and is available for a fee at https://cosmosidhub.com.

Rapid species-level metagenome profiling and containment estimation with sylph

Profiling metagenomes against databases allows for the detection and quantification of microorganisms, even at low abundances where assembly is not possible. We introduce sylph, a species-level metagenome profiler that estimates genome-to-metagenome containment average nucleotide identity (ANI) through zero-inflated Poisson k-mer statistics, enabling ANI-based taxa detection. On the Critical Assessment of Metagenome Interpretation II (CAMI2) Marine dataset, sylph was the most accurate profiling method of seven tested. For multisample profiling, sylph took >10-fold less central processing unit time compared to Kraken2 and used 30-fold less memory. Sylph's ANI estimates provided an orthogonal signal to abundance, allowing for an ANI-based metagenome-wide association study for Parkinson disease (PD) against 289,232 genomes while confirming known butyrate-PD associations at the strain level. Sylph took <1 min and 16 GB of random-access memory to profile metagenomes against 85,205 prokaryotic and 2,917,516 viral genomes, detecting 30-fold more viral sequences in the human gut compared to RefSeq. Sylph offers precise, efficient profiling with accurate containment ANI estimation even for low-coverage genomes.

Profiling the fecal microbiome and its modulators across the lifespan in the Netherlands

Defining what constitutes a healthy microbiome throughout our lives remains an ongoing challenge. Understanding to what extent host and environmental factors can influence it has been the primary motivation for large population studies worldwide. Here, we describe the fecal microbiome of 3,746 individuals (0-87 years of age) in a nationwide study in the Netherlands, in association with extensive questionnaires. We validate previous findings, such as infant-adult trajectories, and explore the collective impact of our variables, which explain over 40% of the variation in microbiome composition. We identify associations with less explored factors, particularly those ethnic related, which show the largest impact on the adult microbiome composition, diversity, metabolic profiles, and CAZy (carbohydrate-active enzyme) repertoires. Understanding the sources of microbiome variability is crucial, given its potential as a modifiable target with therapeutic possibilities. With this work, we aim to serve as a foundational element for the design of health interventions and fundamental research.

Trait-based study predicts glycerol/diol dehydratases as a key function of the gut microbiota of hindgut-fermenting carnivores

BACKGROUND

Microbial pdu and cob-cbi-hem gene clusters encode the key enzyme glycerol/diol dehydratase (PduCDE), which mediates the transformation of dietary nutrients glycerol and 1,2-propanediol (1,2-PD) to a variety of metabolites, and enzymes for cobalamin synthesis, a co-factor and shared good of microbial communities. It was the aim of this study to relate pdu as a multipurpose functional trait to environmental conditions and microbial community composition. We collected fecal samples from wild animal species living in captivity with different gut physiology and diet (n = 55, in total 104 samples), determined occurrence and diversity of pdu and cob-cbi-hem using a novel approach combining metagenomics with quantification of metabolic and genetic biomarkers, and conducted in vitro fermentations to test for trait-based activity.

RESULTS

Fecal levels of the glycerol transformation product 1,3-propanediol (1,3-PD) were higher in hindgut than foregut fermenters. Gene-based analyses indicated that pduC harboring taxa are common feature of captive wild animal fecal microbiota that occur more frequently and at higher abundance in hindgut fermenters. Phylogenetic analysis of genomes reconstructed from metagenomic sequences identified captive wild animal fecal microbiota as taxonomically rich with a total of 4150 species and > 1800 novel species but pointed at only 56 species that at least partially harbored pdu and cbi-cob-hem. While taxonomic diversity was highest in fecal samples of foregut-fermenting herbivores, higher pduC abundance and higher diversity of pdu/cbi-cob-hem related to higher potential for glycerol and 1,2-PD utilization of the less diverse microbiota of hindgut-fermenting carnivores in vitro.

CONCLUSION

Our approach combining metabolite and gene biomarker analysis with metagenomics and phenotypic characterization identified Pdu as a common function of fecal microbiota of captive wild animals shared by few taxa and stratified the potential of fecal microbiota for glycerol/1,2-PD utilization and cobalamin synthesis depending on diet and physiology of the host. This trait-based study suggests that the ability to utilize glycerol/1,2-PD is a key function of hindgut-fermenting carnivores, which does not relate to overall community diversity but links to the potential for cobalamin formation. Video Abstract.

The NEREA Augmented Observatory: an integrative approach to marine coastal ecology

The NEREA (Naples Ecological REsearch for Augmented observatories) initiative aims to establish an augmented observatory in the Gulf of Naples (GoN), designed to advance the understanding of marine ecosystems through a holistic approach. Inspired by the Tara Oceans expedition and building on the scientific legacy of the MareChiara Long-Term Ecological Research (LTER-MC) site, NEREA integrates traditional physical, chemical, and biological measurements with state-of-the-art methodologies such as metabarcoding and metagenomics. Here we present the first 10 months of NEREA data, collected from April 2019 to January 2020, encompassing physico-chemical parameters, plankton biodiversity (e.g., microscopy and flow cytometry), prokaryotic and eukaryotic metabarcoding, a prokaryotic gene catalogue, and a collection of 3818 prokaryotic Metagenome-Assembled Genomes (MAGs). NEREA's efforts produce a significant volume of multifaceted data, which enhances our understanding of marine ecosystems and promotes the development of scientific hypotheses and ideas.

Biocontrol agents modulate phyllosphere microbiota interactions against pathogen Pseudomonas syringae

The pathogen Pseudomonas syringae, responsible for a variety of diseases, poses a considerable threat to global crop yields. Emerging biocontrol strategies employ antagonistic microorganisms, utilizing phyllosphere microecology and systemic resistance to combat this disease. However, the interactions between phyllosphere microbial dynamics and the activation of the plant defense system remain poorly understood. Here we show significant alterations in phyllosphere microbiota structure and plant gene expression following the application of biocontrol agents. We reveal enhanced collaboration and integration of Sphingomonas and Methylobacterium within the microbial co-occurrence network. Notably, Sphingomonas inhibits P. syringae by disrupting pathogen chemotaxis and virulence. Additionally, both Sphingomonas and Methylobacterium activate plant defenses by upregulating pathogenesis-related gene expression through abscisic acid, ethylene, jasmonate acid, and salicylic acid signaling pathways. Our results highlighted that biocontrol agents promote plant health, from reconstructing beneficial microbial consortia to enhancing plant immunity. The findings enrich our comprehension of the synergistic interplays between phyllosphere microbiota and plant immunity, offering potential enhancements in biocontrol efficacy for crop protection.

Planning and Analyzing a Low-Biomass Microbiome Study: A Data Analysis Perspective

As investigations of low-biomass microbial communities have become more common, so too has the recognition of major challenges affecting these analyses. These challenges have been shown to compromise biological conclusions and have contributed to several controversies. Here, we review some of the most common and influential challenges in low-biomass microbiome research. We highlight key approaches to alleviate these potential pitfalls, combining experimental planning strategies and data analysis methods.

Melon: metagenomic long-read-based taxonomic identification and quantification using marker genes

Long-read sequencing holds great potential for characterizing complex microbial communities, yet taxonomic profiling tools designed specifically for long reads remain lacking. We introduce Melon, a novel marker-based taxonomic profiler that capitalizes on the unique attributes of long reads. Melon employs a two-stage classification scheme to reduce computational time and is equipped with an expectation-maximization-based post-correction module to handle ambiguous reads. Melon achieves superior performance compared to existing tools in both mock and simulated samples. Using wastewater metagenomic samples, we demonstrate the applicability of Melon by showing it provides reliable estimates of overall genome copies, and species-level taxonomic profiles.

What role do biocontrol agents with Mg2+ play in the fate of antibiotic resistome and pathogenic bacteria in the phyllosphere?

The contamination of the plant phyllosphere with antibiotics and antibiotic resistance genes (ARGs), caused by application of antibiotics, is a significant environmental issue in agricultural management. Alternatively, biocontrol agents are environmentally friendly and have attracted a lot of interest. However, the influence of biocontrol agents on the phyllosphere resistome remains unknown. In this study, we applied biocontrol agents to control the wildfire disease in the Solanaceae crops and investigated their effects on the resistome and the pathogen in the phyllosphere by using metagenomics. A total of 250 ARGs were detected from 15 samples, which showed a variation in distribution across treatments of biocontrol agents (BA), BA with Mg2+ (T1), BA with Mn2+ (T2), and kasugamycin (T3) and nontreated (CK). The results showed that the abundance of ARGs under the treatment of BA-Mg2+ was lower than that in the CK group. The abundance of cphA3 (carbapenem resistance), PME-1 (carbapenem resistance), tcr3 (tetracycline antibiotic resistance), and AAC (3)-VIIIa (aminoglycoside antibiotic resistance) in BA-Mg2+ was significantly higher than that in BA-Mn2+ (P < 0.05). The abundance of cphA3, PME_1, and tcr3 was significantly negatively related to the abundance of the phyllosphere pathogen Pseudomonas syringae (P < 0.05). We also found that the upstream and downstream regions of cphA3 were relatively conserved, in which rpl, rpm, and rps gene families were identified in most sequences (92%). The Ka/Ks of cphA3 was 0 in all observed sequences, indicating that under the action of purifying selection, nonsynonymous substitutions are often gradually eliminated in the population. Overall, this study clarifies the effect of biocontrol agents with Mg2+ on the distribution of the phyllosphere resistome and provides evolutionary insights into the biocontrol process.

IMPORTANCE

Our study applied metagenomics analysis to examine the impact of biocontrol agents (BAs) on the phyllosphere resistome and the pathogen. Irregular use of antibiotics has led to the escalating dissemination of antibiotic resistance genes (ARGs) in the environment. The majority of BA research has focused on the effect of monospecies on the plant disease control process, the role of the compound BA with nutrition elements in the phyllosphere disease, and the resistome is still unknown. We believe BAs are eco-friendly alternatives for antibiotics to combat the transfer of ARGs. Our results revealed that BA-Mg2+ had a lower relative abundance of ARGs compared to the CK group, and the phyllosphere pathogen Pseudomonas syringae was negatively related to three specific ARGs, cphA3, PME-1, and tcr3. These three genes also present different Ka/Ks. We believe that the identification of the distribution and evolution modes of ARGs further elucidates the ecological role and facilitates the development of BAs, which will attract general interest in this field.

Stability of gut microbiome after COVID-19 vaccination in healthy and immuno-compromised individuals

Bidirectional interactions between the immune system and the gut microbiota are key contributors to various physiological functions. Immune-associated diseases such as cancer and autoimmunity, and efficacy of immunomodulatory therapies, have been linked to microbiome variation. Although COVID-19 infection has been shown to cause microbial dysbiosis, it remains understudied whether the inflammatory response associated with vaccination also impacts the microbiota. Here, we investigate the temporal impact of COVID-19 vaccination on the gut microbiome in healthy and immuno-compromised individuals; the latter included patients with primary immunodeficiency and cancer patients on immunomodulating therapies. We find that the gut microbiome remained remarkably stable post-vaccination irrespective of diverse immune status, vaccine response, and microbial composition spanned by the cohort. The stability is evident at all evaluated levels including diversity, phylum, species, and functional capacity. Our results indicate the resilience of the gut microbiome to host immune changes triggered by COVID-19 vaccination and suggest minimal, if any, impact on microbiome-mediated processes. These findings encourage vaccine acceptance, particularly when contrasted with the significant microbiome shifts observed during COVID-19 infection.

ARGprofiler-a pipeline for large-scale analysis of antimicrobial resistance genes and their flanking regions in metagenomic datasets

MOTIVATION

Analyzing metagenomic data can be highly valuable for understanding the function and distribution of antimicrobial resistance genes (ARGs). However, there is a need for standardized and reproducible workflows to ensure the comparability of studies, as the current options involve various tools and reference databases, each designed with a specific purpose in mind.

RESULTS

In this work, we have created the workflow ARGprofiler to process large amounts of raw sequencing reads for studying the composition, distribution, and function of ARGs. ARGprofiler tackles the challenge of deciding which reference database to use by providing the PanRes database of 14 078 unique ARGs that combines several existing collections into one. Our pipeline is designed to not only produce abundance tables of genes and microbes but also to reconstruct the flanking regions of ARGs with ARGextender. ARGextender is a bioinformatic approach combining KMA and SPAdes to recruit reads for a targeted de novo assembly. While our aim is on ARGs, the pipeline also creates Mash sketches for fast searching and comparisons of sequencing runs.

AVAILABILITY AND IMPLEMENTATION

The ARGprofiler pipeline is a Snakemake workflow that supports the reuse of metagenomic sequencing data and is easily installable and maintained at https://github.com/genomicepidemiology/ARGprofiler.

A cryptic plasmid is among the most numerous genetic elements in the human gut

Plasmids are extrachromosomal genetic elements that often encode fitness-enhancing features. However, many bacteria carry "cryptic" plasmids that do not confer clear beneficial functions. We identified one such cryptic plasmid, pBI143, which is ubiquitous across industrialized gut microbiomes and is 14 times as numerous as crAssphage, currently established as the most abundant extrachromosomal genetic element in the human gut. The majority of mutations in pBI143 accumulate in specific positions across thousands of metagenomes, indicating strong purifying selection. pBI143 is monoclonal in most individuals, likely due to the priority effect of the version first acquired, often from one's mother. pBI143 can transfer between Bacteroidales, and although it does not appear to impact bacterial host fitness in vivo, it can transiently acquire additional genetic content. We identified important practical applications of pBI143, including its use in identifying human fecal contamination and its potential as an alternative approach to track human colonic inflammatory states.

SPIRE: a Searchable, Planetary-scale mIcrobiome REsource

Meta'omic data on microbial diversity and function accrue exponentially in public repositories, but derived information is often siloed according to data type, study or sampled microbial environment. Here we present SPIRE, a Searchable Planetary-scale mIcrobiome REsource that integrates various consistently processed metagenome-derived microbial data modalities across habitats, geography and phylogeny. SPIRE encompasses 99 146 metagenomic samples from 739 studies covering a wide array of microbial environments and augmented with manually-curated contextual data. Across a total metagenomic assembly of 16 Tbp, SPIRE comprises 35 billion predicted protein sequences and 1.16 million newly constructed metagenome-assembled genomes (MAGs) of medium or high quality. Beyond mapping to the high-quality genome reference provided by proGenomes3 (http://progenomes.embl.de), these novel MAGs form 92 134 novel species-level clusters, the majority of which are unclassified at species level using current tools. SPIRE enables taxonomic profiling of these species clusters via an updated, custom mOTUs database (https://motu-tool.org/) and includes several layers of functional annotation, as well as crosslinks to several (micro-)biological databases. The resource is accessible, searchable and browsable via http://spire.embl.de.

Bacteriophages from treatment-naïve type 2 diabetes individuals drive an inflammatory response in human co-cultures of dendritic cells and T cells

Individuals with type 2 diabetes (T2D) show signs of low-grade inflammation, which is related to the development of insulin resistance and beta-cell dysfunction. However, the underlying triggers remain unknown. The gut microbiota is a plausible source as it comprises pro-inflammatory bacteria, bacterial metabolites and viruses, including (bacterio)phages. These prokaryotic viruses have been shown to mediate inflammatory responses in gastrointestinal disease. Given the differences in phage populations in healthy individuals versus those with cardiometabolic diseases such as T2D, we here questioned whether phages from T2D individuals would have increased immunogenic potential. To address this, we isolated intestinal phages from a fresh stool sample of healthy controls and individuals with newly diagnosed, treatment-naive T2D. Phages were purified using cesium chloride ultracentrifugation and incubated with healthy donor dendritic cells (DCs) and autologous T cells. Donors with T2D had slightly higher free viral particle numbers compared to healthy controls (p = .1972), which has been previously associated with disease states. Further, phages from T2D induced a higher inflammatory response in DCs and T cells than phages from HC. For example, the expression of the co-stimulatory molecule CD86 on DCs (p < .001) and interferon-y secretion from T cells (p < .01) were increased when comparing the two groups. These results suggest that phages might play a role in low-grade inflammation in T2D individuals.

A metatranscriptomics strategy for efficient characterization of the microbiome in human tissues with low microbial biomass

The high background of host RNA poses a major challenge to metatranscriptome analysis of human samples. Hence, metatranscriptomics has been mainly applied to microbe-rich samples, while its application in human tissues with low ratio of microbial to host cells has yet to be explored. Since there is no computational workflow specifically designed for the taxonomic and functional analysis of this type of samples, we propose an effective metatranscriptomics strategy to accurately characterize the microbiome in human tissues with a low ratio of microbial to host content. We experimentally generated synthetic samples with well-characterized bacterial and host cell compositions, and mimicking human samples with high and low microbial loads. These synthetic samples were used for optimizing and establishing the workflow in a controlled setting. Our results show that the integration of the taxonomic analysis of optimized Kraken 2/Bracken with the functional analysis of HUMAnN 3 in samples with low microbial content, enables the accurate identification of a large number of microbial species with a low false-positive rate, while improving the detection of microbial functions. The effectiveness of our metatranscriptomics workflow was demonstrated in synthetic samples, simulated datasets, and most importantly, human gastric tissue specimens, thus providing a proof of concept for its applicability on mucosal tissues of the gastrointestinal tract. The use of an accurate and reliable metatranscriptomics approach for human tissues with low microbial content will expand our understanding of the functional activity of the mucosal microbiome, uncovering critical interactions between the microbiome and the host in health and disease.

Metagenomic and -transcriptomic analyses of microbial nitrogen transformation potential, and gene expression in Swiss lake sediments

The global nitrogen (N) cycle has been strongly altered by anthropogenic activities, including increased input of bioavailable N into aquatic ecosystems. Freshwater sediments are hotspots with regards to the turnover and elimination of fixed N, yet the environmental controls on the microbial pathways involved in benthic N removal are not fully understood. Here, we analyze the abundance and expression of microbial genes involved in N transformations using metagenomics and -transcriptomics across sediments of 12 Swiss lakes that differ in sedimentation rates and trophic regimes. Our results indicate that microbial N loss in these sediments is primarily driven by nitrification coupled to denitrification. N-transformation gene compositions indicated three groups of lakes: agriculture-influenced lakes characterized by rapid depletion of oxidants in the sediment porewater, pristine-alpine lakes with relatively deep sedimentary penetration of oxygen and nitrate, and large, deep lakes with intermediate porewater hydrochemical properties. Sedimentary organic matter (OM) characteristics showed the strongest correlations with the community structure of microbial N-cycling communities. Most transformation pathways were expressed, but expression deviated from gene abundance and did not correlate with benthic geochemistry. Cryptic N-cycling may maintain transcriptional activity even when substrate levels are below detection. Sediments of large, deep lakes generally showed lower in-situ N gene expression than agriculture-influenced lakes, and half of the pristine-alpine lakes. This implies that prolonged OM mineralization in the water column can lead to the suppression of benthic N gene expression.

From microbiome composition to functional engineering, one step at a time

SUMMARYCommunities of microorganisms (microbiota) are present in all habitats on Earth and are relevant for agriculture, health, and climate. Deciphering the mechanisms that determine microbiota dynamics and functioning within the context of their respective environments or hosts (the microbiomes) is crucially important. However, the sheer taxonomic, metabolic, functional, and spatial complexity of most microbiomes poses substantial challenges to advancing our knowledge of these mechanisms. While nucleic acid sequencing technologies can chart microbiota composition with high precision, we mostly lack information about the functional roles and interactions of each strain present in a given microbiome. This limits our ability to predict microbiome function in natural habitats and, in the case of dysfunction or dysbiosis, to redirect microbiomes onto stable paths. Here, we will discuss a systematic approach (dubbed the N+1/N-1 concept) to enable step-by-step dissection of microbiome assembly and functioning, as well as intervention procedures to introduce or eliminate one particular microbial strain at a time. The N+1/N-1 concept is informed by natural invasion events and selects culturable, genetically accessible microbes with well-annotated genomes to chart their proliferation or decline within defined synthetic and/or complex natural microbiota. This approach enables harnessing classical microbiological and diversity approaches, as well as omics tools and mathematical modeling to decipher the mechanisms underlying N+1/N-1 microbiota outcomes. Application of this concept further provides stepping stones and benchmarks for microbiome structure and function analyses and more complex microbiome intervention strategies.

Narrow host range phages infect essential bacteria for water purification reactions in groundwater-fed rapid sand filters

Biofiltration is used worldwide to provide safe potable water due to its low energy demand and excellent treatment performance. For instance, in Denmark, over 95% of drinking water is supplied through groundwater-fed rapid sand filters (RSF). Bacteriophages, viruses that infect bacteria, have been shown to shape the taxonomic and functional composition of microbial communities across a range of natural and engineering systems. However, phages in the biofiltration systems are rarely studied, despite the central role microbes play in water purification. To probe this, metagenomic data from surface water, groundwater and mixed source water biofiltration units (n = 26 from China, Europe and USA) for drinking water production were analysed to characterize prokaryotic viruses and to identify their potential microbial hosts. The source water type and geographical location are found to exert influence on the composition of the phageome in biofilters. Although the viral abundance (71,676 ± 17,841 RPKM) in biofilters is only 14.4% and 17.0% lower than those of the nutrient-rich wastewater treatment plants and fresh surface waters, the richness (1,441 ± 1,046) and diversity (Inverse Simpson: 91 ± 61) in biofiltration units are significantly less by a factor of 2-5 and 3-4, respectively. In depth analysis of data from 24 groundwater-fed RSFs in Denmark revealed a core phageome shared by most RSFs, which was consistently linked to dominant microbial hosts involved in key biological reactions for water purification. Finally, the high number of specific links detected between phages and bacterial species and the large proportion of lytic phages (77%) led to the conjecture that phages regulate bacterial populations through predation, preventing the proliferation of dominant species and contributing to the established functional redundancy among the dominant microbial groups. In conclusion, bacteriophages are likely to play a significant role in water treatment within biofilters, particularly through interactions with key bacterial species.

Ecogenomics and cultivation reveal distinctive viral-bacterial communities in the surface microlayer of a Baltic Sea slick

Visible surface films, termed slicks, can extensively cover freshwater and marine ecosystems, with coastal regions being particularly susceptible to their presence. The sea-surface microlayer (SML), the upper 1-mm at the air-water interface in slicks (herein slick SML) harbors a distinctive bacterial community, but generally little is known about SML viruses. Using flow cytometry, metagenomics, and cultivation, we characterized viruses and bacteria in a brackish slick SML in comparison to non-slick SML as well as seawater below slick and non-slick areas (subsurface water = SSW). Size-fractionated filtration of all samples distinguished viral attachment to hosts and particles. The slick SML contained higher abundances of virus-like particles, prokaryotic cells, and dissolved organic carbon compared to non-slick SML and SSW. The community of 428 viral operational taxonomic units (vOTUs), 426 predicted as lytic, distinctly differed across all size fractions in the slick SML compared to non-slick SML and SSW. Specific metabolic profiles of bacterial metagenome-assembled genomes and isolates in the slick SML included a prevalence of genes encoding motility and carbohydrate-active enzymes (CAZymes). Several vOTUs were enriched in slick SML, and many virus variants were associated with particles. Nine vOTUs were only found in slick SML, six of them being targeted by slick SML-specific clustered-regularly interspaced short palindromic repeats (CRISPR) spacers likely originating from Gammaproteobacteria. Moreover, isolation of three previously unknown lytic phages for Alishewanella sp. and Pseudoalteromonas tunicata, abundant and actively replicating slick SML bacteria, suggests that viral activity in slicks contributes to biogeochemical cycling in coastal ecosystems.

Removal of false positives in metagenomics-based taxonomy profiling via targeting Type IIB restriction sites

Accurate species identification and abundance estimation are critical for the interpretation of whole metagenome sequencing (WMS) data. Yet, existing metagenomic profilers suffer from false-positive identifications, which can account for more than 90% of total identified species. Here, by leveraging species-specific Type IIB restriction endonuclease digestion sites as reference instead of universal markers or whole microbial genomes, we present a metagenomic profiler, MAP2B (MetAgenomic Profiler based on type IIB restriction sites), to resolve those issues. We first illustrate the pitfalls of using relative abundance as the only feature in determining false positives. We then propose a feature set to distinguish false positives from true positives, and using simulated metagenomes from CAMI2, we establish a false-positive recognition model. By benchmarking the performance in metagenomic profiling using a simulation dataset with varying sequencing depth and species richness, we illustrate the superior performance of MAP2B over existing metagenomic profilers in species identification. We further test the performance of MAP2B using real WMS data from an ATCC mock community, confirming its superior precision against sequencing depth. Finally, by leveraging WMS data from an IBD cohort, we demonstrate the taxonomic features generated by MAP2B can better discriminate IBD and predict metabolomic profiles.

MGnify Genomes: A Resource for Biome-specific Microbial Genome Catalogues

An increasingly common output arising from the analysis of shotgun metagenomic datasets is the generation of metagenome-assembled genomes (MAGs), with tens of thousands of MAGs now described in the literature. However, the discovery and comparison of these MAG collections is hampered by the lack of uniformity in their generation, annotation and storage. To address this, we have developed MGnify Genomes, a growing collection of biome-specific non-redundant microbial genome catalogues generated using MAGs and publicly available isolate genomes. Genomes within a biome-specific catalogue are organised into species clusters. For species that contain multiple conspecific genomes, the highest quality genome is selected as the representative, always prioritising an isolate genome over a MAG. The species representative sequences and annotations can be visualised on the MGnify website and the full catalogue and associated analysis outputs can be downloaded from MGnify servers. A suite of online search tools is provided allowing users to compare their own sequences, ranging from a gene to sets of genomes, against the catalogues. Seven biomes are available currently, comprising over 300,000 genomes that represent 11,048 non-redundant species, and include 36 taxonomic classes not currently represented by cultured genomes. MGnify Genomes is available at https://www.ebi.ac.uk/metagenomics/browse/genomes/.

KMCP: accurate metagenomic profiling of both prokaryotic and viral populations by pseudo-mapping

MOTIVATION

The growing number of microbial reference genomes enables the improvement of metagenomic profiling accuracy but also imposes greater requirements on the indexing efficiency, database size and runtime of taxonomic profilers. Additionally, most profilers focus mainly on bacterial, archaeal and fungal populations, while less attention is paid to viral communities.

RESULTS

We present KMCP (K-mer-based Metagenomic Classification and Profiling), a novel k-mer-based metagenomic profiling tool that utilizes genome coverage information by splitting the reference genomes into chunks and stores k-mers in a modified and optimized Compact Bit-Sliced Signature Index for fast alignment-free sequence searching. KMCP combines k-mer similarity and genome coverage information to reduce the false positive rate of k-mer-based taxonomic classification and profiling methods. Benchmarking results based on simulated and real data demonstrate that KMCP, despite a longer running time than all other methods, not only allows the accurate taxonomic profiling of prokaryotic and viral populations but also provides more confident pathogen detection in clinical samples of low depth.

AVAILABILITY AND IMPLEMENTATION

The software is open-source under the MIT license and available at https://github.com/shenwei356/kmcp.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.