A genomic catalog of Earth's microbiomes

Ecological significance of Candidatus ARS69 and Gemmatimonadota in the Arctic glacier foreland ecosystems

The Gemmatimonadota phylum has been widely detected in diverse natural environments, yet their specific ecological roles in many habitats remain poorly investigated. Similarly, the Candidatus ARS69 phylum has been identified only in a few habitats, and literature on their metabolic functions is relatively scarce. In the present study, we investigated the ecological significance of phyla Ca. ARS69 and Gemmatimonadota in the Arctic glacier foreland (GF) ecosystems through genome-resolved metagenomics. We have reconstructed the first high-quality metagenome-assembled genome (MAG) belonging to Ca. ARS69 and 12 other MAGs belonging to phylum Gemmatimonadota from the three different Arctic GF samples. We further elucidated these two groups phylogenetic lineage and their metabolic function through phylogenomic and pangenomic analysis. The analysis showed that all the reconstructed MAGs potentially belonged to novel species. The MAGs belonged to Ca. ARS69 consist about 8296 gene clusters, of which only about 8% of single-copy core genes (n = 980) were shared among them. The study also revealed the potential ecological role of Ca. ARS69 is associated with carbon fixation, denitrification, sulfite oxidation, and reduction biochemical processes in the GF ecosystems. Similarly, the study demonstrates the widespread distribution of different classes of Gemmatimonadota across wide ranges of ecosystems and their metabolic functions, including in the polar region. KEY POINTS: • Glacier foreland ecosystems act as a natural laboratory to study microbial community structure. • We have reconstructed 13 metagenome-assembled genomes from the soil samples. • All the reconstructed MAGs belonged to novel species with different metabolic processes. • Ca. ARS69 and Gemmatimonadota MAGs were found to participate in carbon fixation and denitrification processes.

A systematic comparison of natural product potential, with an emphasis on RiPPs, by mining of bacteria of three large ecosystems

The implementation of several global microbiome studies has yielded extensive insights into the biosynthetic potential of natural microbial communities. However, studies on the distribution of several classes of ribosomally synthesized and post-translationally modified peptides (RiPPs), non-ribosomal peptides (NRPs) and polyketides (PKs) in different large microbial ecosystems have been very limited. Here, we collected a large set of metagenome-assembled bacterial genomes from marine, freshwater and terrestrial ecosystems to investigate the biosynthetic potential of these bacteria. We demonstrate the utility of public dataset collections for revealing the different secondary metabolite biosynthetic potentials among these different living environments. We show that there is a higher occurrence of RiPPs in terrestrial systems, while in marine systems, we found relatively more terpene-, NRP-, and PK encoding gene clusters. Among the many new biosynthetic gene clusters (BGCs) identified, we analyzed various Nif-11-like and nitrile hydratase leader peptide (NHLP) containing gene clusters that would merit further study, including promising products, such as mersacidin-, LAP- and proteusin analogs. This research highlights the significance of public datasets in elucidating the biosynthetic potential of microbes in different living environments and underscores the wide bioengineering opportunities within the RiPP family.

A refined picture of the native amine dehydrogenase family revealed by extensive biodiversity screening

Native amine dehydrogenases offer sustainable access to chiral amines, so the search for scaffolds capable of converting more diverse carbonyl compounds is required to reach the full potential of this alternative to conventional synthetic reductive aminations. Here we report a multidisciplinary strategy combining bioinformatics, chemoinformatics and biocatalysis to extensively screen billions of sequences in silico and to efficiently find native amine dehydrogenases features using computational approaches. In this way, we achieve a comprehensive overview of the initial native amine dehydrogenase family, extending it from 2,011 to 17,959 sequences, and identify native amine dehydrogenases with non-reported substrate spectra, including hindered carbonyls and ethyl ketones, and accepting methylamine and cyclopropylamine as amine donor. We also present preliminary model-based structural information to inform the design of potential (R)-selective amine dehydrogenases, as native amine dehydrogenases are mostly (S)-selective. This integrated strategy paves the way for expanding the resource of other enzyme families and in highlighting enzymes with original features.

Challenges in computational discovery of bioactive peptides in 'omics data

Peptides have a plethora of activities in biological systems that can potentially be exploited biotechnologically. Several peptides are used clinically, as well as in industry and agriculture. The increase in available 'omics data has recently provided a large opportunity for mining novel enzymes, biosynthetic gene clusters, and molecules. While these data primarily consist of DNA sequences, other types of data provide important complementary information. Due to their size, the approaches proven successful at discovering novel proteins of canonical size cannot be naïvely applied to the discovery of peptides. Peptides can be encoded directly in the genome as short open reading frames (smORFs), or they can be derived from larger proteins by proteolysis. Both of these peptide classes pose challenges as simple methods for their prediction result in large numbers of false positives. Similarly, functional annotation of larger proteins, traditionally based on sequence similarity to infer orthology and then transferring functions between characterized proteins and uncharacterized ones, cannot be applied for short sequences. The use of these techniques is much more limited and alternative approaches based on machine learning are used instead. Here, we review the limitations of traditional methods as well as the alternative methods that have recently been developed for discovering novel bioactive peptides with a focus on prokaryotic genomes and metagenomes.

Pro-CRISPR PcrIIC1-associated Cas9 system for enhanced bacterial immunity

The CRISPR system is an adaptive immune system found in prokaryotes that defends host cells against the invasion of foreign DNA1. As part of the ongoing struggle between phages and the bacterial immune system, the CRISPR system has evolved into various types, each with distinct functionalities2. Type II Cas9 is the most extensively studied of these systems and has diverse subtypes. It remains uncertain whether members of this family can evolve additional mechanisms to counter viral invasions3,4. Here we identify 2,062 complete Cas9 loci, predict the structures of their associated proteins and reveal three structural growth trajectories for type II-C Cas9. We found that novel associated genes (NAGs) tended to be present within the loci of larger II-C Cas9s. Further investigation revealed that CbCas9 from Chryseobacterium species contains a novel β-REC2 domain, and forms a heterotetrameric complex with an NAG-encoded CRISPR-Cas-system-promoting (pro-CRISPR) protein of II-C Cas9 (PcrIIC1). The CbCas9-PcrIIC1 complex exhibits enhanced DNA binding and cleavage activity, broader compatibility for protospacer adjacent motif sequences, increased tolerance for mismatches and improved anti-phage immunity, compared with stand-alone CbCas9. Overall, our work sheds light on the diversity and 'growth evolutionary' trajectories of II-C Cas9 proteins at the structural level, and identifies many NAGs-such as PcrIIC1, which serves as a pro-CRISPR factor to enhance CRISPR-mediated immunity.

Comparative genomic analysis of Planctomycetota potential for polysaccharide degradation identifies biotechnologically relevant microbes

BACKGROUND

Members of the Planctomycetota phylum harbour an outstanding potential for carbohydrate degradation given the abundance and diversity of carbohydrate-active enzymes (CAZymes) encoded in their genomes. However, mainly members of the Planctomycetia class have been characterised up to now, and little is known about the degrading capacities of the other Planctomycetota. Here, we present a comprehensive comparative analysis of all available planctomycetotal genome representatives and detail encoded carbohydrolytic potential across phylogenetic groups and different habitats.

RESULTS

Our in-depth characterisation of the available planctomycetotal genomic resources increases our knowledge of the carbohydrolytic capacities of Planctomycetota. We show that this single phylum encompasses a wide variety of the currently known CAZyme diversity assigned to glycoside hydrolase families and that many members encode a versatile enzymatic machinery towards complex carbohydrate degradation, including lignocellulose. We highlight members of the Isosphaerales, Pirellulales, Sedimentisphaerales and Tepidisphaerales orders as having the highest encoded hydrolytic potential of the Planctomycetota. Furthermore, members of a yet uncultivated group affiliated to the Phycisphaerales order could represent an interesting source of novel lytic polysaccharide monooxygenases to boost lignocellulose degradation. Surprisingly, many Planctomycetota from anaerobic digestion reactors encode CAZymes targeting algal polysaccharides - this opens new perspectives for algal biomass valorisation in biogas processes.

CONCLUSIONS

Our study provides a new perspective on planctomycetotal carbohydrolytic potential, highlighting distinct phylogenetic groups which could provide a wealth of diverse, potentially novel CAZymes of industrial interest.

Exploring the roles of ribosomal peptides in prokaryote-phage interactions through deep learning-enabled metagenome mining

BACKGROUND

Microbial secondary metabolites play a crucial role in the intricate interactions within the natural environment. Among these metabolites, ribosomally synthesized and post-translationally modified peptides (RiPPs) are becoming a promising source of therapeutic agents due to their structural diversity and functional versatility. However, their biosynthetic capacity and ecological functions remain largely underexplored.

RESULTS

Here, we aim to explore the biosynthetic profile of RiPPs and their potential roles in the interactions between microbes and viruses in the ocean, which encompasses a vast diversity of unique biomes that are rich in interactions and remains chemically underexplored. We first developed TrRiPP to identify RiPPs from ocean metagenomes, a deep learning method that detects RiPP precursors in a hallmark gene-independent manner to overcome the limitations of classic methods in processing highly fragmented metagenomic data. Applying this method to metagenomes from the global ocean microbiome, we uncover a diverse array of previously uncharacterized putative RiPP families with great novelty and diversity. Through correlation analysis based on metatranscriptomic data, we observed a high prevalence of antiphage defense-related and phage-related protein families that were co-expressed with RiPP families. Based on this putative association between RiPPs and phage infection, we constructed an Ocean Virus Database (OVD) and established a RiPP-involving host-phage interaction network through host prediction and co-expression analysis, revealing complex connectivities linking RiPP-encoding prokaryotes, RiPP families, viral protein families, and phages. These findings highlight the potential of RiPP families involved in prokaryote-phage interactions and coevolution, providing insights into their ecological functions in the ocean microbiome.

CONCLUSIONS

This study provides a systematic investigation of the biosynthetic potential of RiPPs from the ocean microbiome at a global scale, shedding light on the essential insights into the ecological functions of RiPPs in prokaryote-phage interactions through the integration of deep learning approaches, metatranscriptomic data, and host-phage connectivity. This study serves as a valuable example of exploring the ecological functions of bacterial secondary metabolites, particularly their associations with unexplored microbial interactions. Video Abstract.

Phages in different habitats and their ability to carry antibiotic resistance genes

As the most abundant organisms on Earth, phages play a key role in the evolution of bacterial antibiotic resistance. Although previous studies have demonstrated the molecular mechanisms of horizontal gene transfer mediated by mobile genetic elements, our understanding of the intertwined relationships between antibiotic resistance genes (ARGs) and phages is limited. In this study, we analysed 2781 metagenomic samples to reveal the composition and species interactions of phage communities in different habitats as well as their capacity to carry ARGs with health risks. The composition of phage communities varies in different habitats and mainly depends on environmental conditions. Terrestrial habitats display more complex and robust interactions between phages than aquatic and human-associated habitats, resulting in the highest biodiversity of phages. Several types of phages in certain taxa (4.95-7.67%, mainly belonging to Caudoviricetes) have the capacity to carry specific ARGs and display a high potential risk to human health, especially in human-associated habitats. Overall, our results provide insights into the assembly mechanisms of phage communities and their effects on the dissemination of antibiotic resistance.

Predicting metabolic modules in incomplete bacterial genomes with MetaPathPredict

The reconstruction of complete microbial metabolic pathways using 'omics data from environmental samples remains challenging. Computational pipelines for pathway reconstruction that utilize machine learning methods to predict the presence or absence of KEGG modules in incomplete genomes are lacking. Here, we present MetaPathPredict, a software tool that incorporates machine learning models to predict the presence of complete KEGG modules within bacterial genomic datasets. Using gene annotation data and information from the KEGG module database, MetaPathPredict employs deep learning models to predict the presence of KEGG modules in a genome. MetaPathPredict can be used as a command line tool or as a Python module, and both options are designed to be run locally or on a compute cluster. Benchmarks show that MetaPathPredict makes robust predictions of KEGG module presence within highly incomplete genomes.

Critical steps in an environmental metaproteomics workflow

Environmental metaproteomics is a rapidly advancing field that provides insights into the structure, dynamics, and metabolic activity of microbial communities. As the field is still maturing, it lacks consistent workflows, making it challenging for non-expert researchers to navigate. This review aims to introduce the workflow of environmental metaproteomics. It outlines the standard practices for sample collection, processing, and analysis, and offers strategies to overcome the unique challenges presented by common environmental matrices such as soil, freshwater, marine environments, biofilms, sludge, and symbionts. The review also highlights the bottlenecks in data analysis that are specific to metaproteomics samples and provides suggestions for researchers to obtain high-quality datasets. It includes recent benchmarking studies and descriptions of software packages specifically built for metaproteomics analysis. The article is written without assuming the reader's familiarity with single-organism proteomic workflows, making it accessible to those new to proteomics or mass spectrometry in general. This primer for environmental metaproteomics aims to improve accessibility to this exciting technology and empower researchers to tackle challenging and ambitious research questions. While it is primarily a resource for those new to the field, it should also be useful for established researchers looking to streamline or troubleshoot their metaproteomics experiments.

Genomic comparison of deep-sea hydrothermal genera related to Aeropyrum, Thermodiscus and Caldisphaera, and proposed emended description of the family Acidilobaceae

Deep-sea hydrothermal vents host archaeal and bacterial thermophilic communities, including taxonomically and functionally diverse Thermoproteota. Despite their prevalence in high-temperature submarine communities, Thermoproteota are chronically under-represented in genomic databases and issues have emerged regarding their nomenclature, particularly within the Aeropyrum-Thermodiscus-Caldisphaera. To resolve some of these problems, we identified 47 metagenome-assembled genomes (MAGs) within this clade, from 20 previously published deep-sea hydrothermal vent and submarine volcano metagenomes, and 24 MAGs from public databases. Using phylogenomic analysis, Genome Taxonomy Database Toolkit (GTDB-Tk) taxonomic assessment, 16S rRNA gene phylogeny, average amino acid identity (AAI) and functional gene patterns, we re-evaluated of the taxonomy of the Aeropyrum-Thermodiscus-Caldisphaera. At least nine genus-level clades were identified with two or more MAGs. In accordance with SeqCode requirements and recommendations, we propose names for three novel genera, viz. Tiamatella incendiivivens, Hestiella acidicharens and Calypsonella navitae. A fourth genus was also identified related to Thermodiscus maritimus, for which no available sequenced genome exists. We propose the novel species Thermodiscus eudorianus to describe our high-quality Thermodiscus MAG, which represents the type genome for the genus. All three novel genera and T. eudorianus are likely anaerobic heterotrophs, capable of fermenting protein-rich carbon sources, while some Tiamatella, Calypsonella and T. eudorianus may also reduce polysulfides, thiosulfate, sulfur and/or selenite, and the likely acidophile, Hestiella, may reduce nitrate and/or perchlorate. Based on phylogenomic evidence, we also propose the family Acidilobaceae be amended to include Caldisphaera, Aeropyrum, Thermodiscus and Stetteria and the novel genera described here.

A vast repertoire of secondary metabolites potentially influences community dynamics and biogeochemical processes in cold seeps

In deep-sea cold seeps, microbial communities thrive on the geological seepage of hydrocarbons and inorganic compounds, differing from photosynthetically driven ecosystems. However, their biosynthetic capabilities remain largely unexplored. Here, we analyzed 81 metagenomes, 33 metatranscriptomes, and 7 metabolomes derived from nine different cold seep areas to investigate their secondary metabolites. Cold seep microbiomes encode diverse and abundant biosynthetic gene clusters (BGCs). Most BGCs are affiliated with understudied bacteria and archaea, including key mediators of methane and sulfur cycling. The BGCs encode diverse antimicrobial compounds that potentially shape community dynamics and various metabolites predicted to influence biogeochemical cycling. BGCs from key players are widely distributed and highly expressed, with their abundance and expression levels varying with sediment depth. Sediment metabolomics reveals unique natural products, highlighting uncharted chemical potential and confirming BGC activity in these sediments. Overall, these results demonstrate that cold seep sediments serve as a reservoir of hidden natural products and sheds light on microbial adaptation in chemosynthetically driven ecosystems.

Long-duration environmental biosensing by recording analyte detection in DNA using recombinase memory

Microbial biosensors that convert environmental information into real-time visual outputs are limited in their sensing abilities in complex environments, such as soil and wastewater, due to optical inaccessibility. Biosensors that could record transient exposure to analytes within a large time window for later retrieval represent a promising approach to solve the accessibility problem. Here, we test the performance of recombinase-memory biosensors that sense a sugar (arabinose) and a microbial communication molecule (3-oxo-C12-L-homoserine lactone) over 8 days (~70 generations) following analyte exposure. These biosensors sense the analyte and trigger the expression of a recombinase enzyme which flips a segment of DNA, creating a genetic memory, and initiates fluorescent protein expression. The initial designs failed over time due to unintended DNA flipping in the absence of the analyte and loss of the flipped state after exposure to the analyte. Biosensor performance was improved by decreasing recombinase expression, removing the fluorescent protein output, and using quantitative PCR to read out stored information. Application of memory biosensors in wastewater isolates achieved memory of analyte exposure in an uncharacterized Pseudomonas isolate. By returning these engineered isolates to their native environments, recombinase-memory systems are expected to enable longer duration and in situ investigation of microbial signaling, cross-feeding, community shifts, and gene transfer beyond the reach of traditional environmental biosensors.IMPORTANCEMicrobes mediate ecological processes over timescales that can far exceed the half-lives of transient metabolites and signals that drive their collective behaviors. We investigated strategies for engineering microbes to stably record their transient exposure to a chemical over many generations through DNA rearrangements. We identify genetic architectures that improve memory biosensor performance and characterize these in wastewater isolates. Memory biosensors are expected to be useful for monitoring cell-cell signals in biofilms, detecting transient exposure to chemical pollutants, and observing microbial cross-feeding through short-lived metabolites within cryptic methane, nitrogen, and sulfur cycling processes. They will also enable in situ studies of microbial responses to ephemeral environmental changes, or other ecological processes that are currently challenging to monitor non-destructively using real-time biosensors and analytical instruments.

Diversity and distribution of biosynthetic gene clusters in agricultural soil microbiomes

Bacterial secondary metabolites serve as an important source of molecules for drug discovery. They also play an important function in mediating the interactions of microbial producers with their living environment and surrounding organisms. However, little is known about the genetic novelty, distribution, and community-level impacts of soil bacterial biosynthetic potential on a large geographic scale. Here, we constructed the first catalog of 11,149 biosynthetic gene clusters (BGCs) from agricultural soils across China and unearthed hidden biosynthetic potential for new natural product discovery from the not-yet-cultivated soil bacteria. Notably, we revealed soil pH as the strongest environmental driver of BGC biogeography and predicted that soil acidification and global climate change could damage the biosynthetic potential of the soil microbiome. The co-occurrence network of bacterial genomes revealed two BGC-rich species, i.e., Nocardia niigatensis from Actinobacteriota and PSRF01 from Acidobacteriota, as the module hub and connector, respectively, indicating their keystone positions in the soil microbial communities. We also uncovered a dominant role of BGC-inferred biotic interactions over environmental drivers in structuring the soil microbiome. Overall, this study achieved novel insights into the BGC landscape in agricultural soils of China, substantially expanding our understanding of the diversity and novelty of bacterial secondary metabolism and the potential role of secondary metabolites in microbiota assembly.IMPORTANCEBacterial secondary metabolites not only serve as the foundation for numerous therapeutics (e.g., antibiotics and anticancer drugs), but they also play critical ecological roles in mediating microbial interactions (e.g., competition and communication). However, our knowledge of bacterial secondary metabolism is limited to only a small fraction of cultured strains, thus restricting our comprehensive understanding of their diversity, novelty, and potential ecological roles in soil ecosystems. Here, we used culture-independent metagenomics to explore biosynthetic potentials in agricultural soils of China. Our analyses revealed a high degree of genetic diversity and novelty within biosynthetic gene clusters in agricultural soil environments, offering valuable insights for biochemists seeking to synthesize novel bioactive products. Furthermore, we uncovered the pivotal role of BGC-rich species in microbial communities and the significant relationship between BGC richness and microbial phylogenetic turnover. This information emphasizes the importance of biosynthetic potential in the assembly of microbial communities.

Diverse and abundant phages exploit conjugative plasmids

Phages exert profound evolutionary pressure on bacteria by interacting with receptors on the cell surface to initiate infection. While the majority of phages use chromosomally encoded cell surface structures as receptors, plasmid-dependent phages exploit plasmid-encoded conjugation proteins, making their host range dependent on horizontal transfer of the plasmid. Despite their unique biology and biotechnological significance, only a small number of plasmid-dependent phages have been characterized. Here we systematically search for new plasmid-dependent phages targeting IncP and IncF plasmids using a targeted discovery platform, and find that they are common and abundant in wastewater, and largely unexplored in terms of their genetic diversity. Plasmid-dependent phages are enriched in non-canonical types of phages, and all but one of the 65 phages we isolated were non-tailed, and members of the lipid-containing tectiviruses, ssDNA filamentous phages or ssRNA phages. We show that plasmid-dependent tectiviruses exhibit profound differences in their host range which is associated with variation in the phage holin protein. Despite their relatively high abundance in wastewater, plasmid-dependent tectiviruses are missed by metaviromic analyses, underscoring the continued importance of culture-based phage discovery. Finally, we identify a tailed phage dependent on the IncF plasmid, and find related structural genes in phages that use the orthogonal type 4 pilus as a receptor, highlighting the evolutionarily promiscuous use of these distinct contractile structures by multiple groups of phages. Taken together, these results indicate plasmid-dependent phages play an under-appreciated evolutionary role in constraining horizontal gene transfer via conjugative plasmids.

Community Structure, Drivers, and Potential Functions of Different Lifestyle Viruses in Chaohu Lake

Viruses, as the most prolific entities on Earth, constitute significant ecological groups within freshwater lakes, exerting pivotal ecological roles. In this study, we selected Chaohu Lake, a representative eutrophic freshwater lake in China, as our research site to explore the community distribution, driving mechanisms, and potential ecological functions of diverse viral communities, the intricate virus-host interaction systems, and the overarching influence of viruses on global biogeochemical cycling.

A compendium of ruminant gastrointestinal phage genomes revealed a higher proportion of lytic phages than in any other environments

BACKGROUND

Ruminants are important livestock animals that have a unique digestive system comprising multiple stomach compartments. Despite significant progress in the study of microbiome in the gastrointestinal tract (GIT) sites of ruminants, we still lack an understanding of the viral community of ruminants. Here, we surveyed its viral ecology using 2333 samples from 10 sites along the GIT of 8 ruminant species.

RESULTS

We present the Unified Ruminant Phage Catalogue (URPC), a comprehensive survey of phages in the GITs of ruminants including 64,922 non-redundant phage genomes. We characterized the distributions of the phage genomes in different ruminants and GIT sites and found that most phages were organism-specific. We revealed that ~ 60% of the ruminant phages were lytic, which was the highest as compared with those in all other environments and certainly will facilitate their applications in microbial interventions. To further facilitate the future applications of the phages, we also constructed a comprehensive virus-bacteria/archaea interaction network and identified dozens of phages that may have lytic effects on methanogenic archaea.

CONCLUSIONS

The URPC dataset represents a useful resource for future microbial interventions to improve ruminant production and ecological environmental qualities. Phages have great potential for controlling pathogenic bacterial/archaeal species and reducing methane emissions. Our findings provide insights into the virome ecology research of the ruminant GIT and offer a starting point for future research on phage therapy in ruminants. Video Abstract.

Diverse Class 2 CRISPR Effectors as Active Nucleases with Expanded Targeting Capabilities

CRISPR-Cas systems have proven effective in a variety of applications due to their ease of use and relatively high editing efficiency. Yet, any individual CRISPR-Cas system has inherent limitations, necessitating a diversity of RNA-guided nucleases to suit applications with distinct needs. We searched through metagenomic sequences to identify RNA-guided nucleases and found enzymes from diverse CRISPR-Cas types and subtypes, the most promising of which we developed into gene-editing platforms. Based on prior annotations of the metagenomic sequences, we establish the likely taxa and sampling locations where Class 2 CRISPR-Cas systems active in eukaryotes may be found. The newly discovered systems show robust capabilities as gene editors and base editors.

The Microbiome Protocols eBook initiative: Building a bridge to microbiome research

The Microbiome Protocols eBook (MPB) serves as a crucial bridge, filling gaps in microbiome protocols for both wet experiments and data analysis. The first edition, launched in 2020, featured 152 meticulously curated protocols, garnering widespread acclaim. We now extend a sincere invitation to researchers to participate in the upcoming 2nd version of MPB, contributing their valuable protocols to advance microbiome research.

Speciation Features of Ferdinandcohnia quinoae sp. nov to Adapt to the Plant Host

The bacterial strain SECRCQ15T was isolated from seeds of Chenopodium quinoa in Spain. Phylogenetic, chemotaxonomic, and phenotypic analyses, as well as genome similarity indices, support the classification of the strain into a novel species of the genus Ferdinandcohnia, for which we propose the name Ferdinandcohnia quinoae sp. nov. To dig deep into the speciation features of the strain SECRCQ15T, we performed a comparative genomic analysis of the genome of this strain and those of the type strains of species from the genus Ferdinandcohnia. We found several genes related with plant growth-promoting mechanisms within the SECRCQ15T genome. We also found that singletons of F. quinoae SECRCQ15T are mainly related to the use of carbohydrates, which is a common trait of plant-associated bacteria. To further reveal speciation events in this strain, we revealed genes undergoing diversifying selection (e.g., genes encoding ribosomal proteins) and functions likely lost due to pseudogenization. Also, we found that this novel species contains 138 plant-associated gene-cluster functions that are unique within the genus Ferdinandcohnia. These features may explain both the ecological and taxonomical differentiation of this new taxon.

A mixed blessing of influent leachate microbes in downstream biotreatment systems of a full-scale landfill leachate treatment plant

In landfill leachate treatment plants (LLTPs), the microbiome plays a pivotal role in the decomposition of organic compounds, reduction in nutrient levels, and elimination of toxins. However, the effects of microbes in landfill leachate influents on downstream treatment systems remain poorly understood. To address this knowledge gap, we collected 23 metagenomic and 12 metatranscriptomic samples from landfill leachate and activated sludge from various treatment units in a full-scale LLTP. We successfully recovered 1,152 non-redundant metagenome-assembled genomes (MAGs), encompassing a wide taxonomic range, including 48 phyla, 95 classes, 166 orders, 247 families, 238 genera, and 1,152 species. More diverse microbes were observed in the influent leachate than in the downstream biotreatment systems, among which, an unprecedented ∼30 % of microbes with transcriptional expression migrated from the influent to the biological treatment units. Network analysis revealed that 399 shared MAGs across the four units exhibited high node centrality and degree, thus supporting enhanced interactions and increased stability of microbial communities. Functional reconstruction and genome characterization of MAGs indicated that these shared MAGs possessed greater capabilities for carbon, nitrogen, sulfur, and arsenic metabolism compared to non-shared MAGs. We further identified a novel species of Zixibacteria in the leachate influent with discrete lineages from those in other environments that accounted for up to 17 % of the abundance of the shared microbial community and exhibited notable metabolic versatility. Meanwhile, we presented groundbreaking evidence of the involvement of Zixibacteria-encoded genes in the production of harmful gas emissions, such as N2O and H2S, at the transcriptional level, thus suggesting that influent microbes may pose safety risks to downstream treatment systems. In summary, this study revealed the complex impact of the influent microbiome on LLTP and emphasizes the need to consider these microbial characteristics when designing treatment technologies and strategies for landfill leachate management.

Expanded phylogeny of extremely halophilic archaea shows multiple independent adaptations to hypersaline environments

Extremely halophilic archaea (Haloarchaea, Nanohaloarchaeota, Methanonatronarchaeia and Halarchaeoplasmatales) thrive in saturating salt concentrations where they must maintain osmotic equilibrium with their environment. The evolutionary history of adaptations enabling salt tolerance remains poorly understood, in particular because the phylogeny of several lineages is conflicting. Here we present a resolved phylogeny of extremely halophilic archaea obtained using improved taxon sampling and state-of-the-art phylogenetic approaches designed to cope with the strong compositional biases of their proteomes. We describe two uncultured lineages, Afararchaeaceae and Asbonarchaeaceae, which break the long branches at the base of Haloarchaea and Nanohaloarchaeota, respectively. We obtained 13 metagenome-assembled genomes (MAGs) of these archaea from metagenomes of hypersaline aquatic systems of the Danakil Depression (Ethiopia). Our phylogenomic analyses including these taxa show that at least four independent adaptations to extreme halophily occurred during archaeal evolution. Gene-tree/species-tree reconciliation suggests that gene duplication and horizontal gene transfer played an important role in this process, for example, by spreading key genes (such as those encoding potassium transporters) across extremely halophilic lineages.

Biosynthetic potential of the sediment microbial subcommunities of an unexplored karst ecosystem and its ecological implications

Microbial communities from various environments have been studied in the quest for new natural products with a broad range of applications in medicine and biotechnology. We employed an enrichment method and genome mining tools to examine the biosynthetic potential of microbial communities in the sediments of a coastal sinkhole within the karst ecosystem of the Yucatán Peninsula, Mexico. Our investigation led to the detection of 203 biosynthetic gene clusters (BGCs) and 55 secondary metabolites (SMs) within 35 high-quality metagenome-assembled genomes (MAGs) derived from these subcommunities. The most abundant types of BGCs were Terpene, Nonribosomal peptide-synthetase, and Type III polyketide synthase. Some of the in silico identified BGCs and SMs have been previously reported to exhibit biological activities against pathogenic bacteria and fungi. Others could play significant roles in the sinkhole ecosystem, such as iron solubilization and osmotic stress protection. Interestingly, 75% of the BGCs showed no sequence homology with bacterial BGCs previously reported in the MiBIG database. This suggests that the microbial communities in this environment could be an untapped source of genes encoding novel specialized compounds. The majority of the BGCs were identified in pathways found in the genus Virgibacillus, followed by Sporosarcina, Siminovitchia, Rhodococcus, and Halomonas. The latter, along with Paraclostridium and Lysinibacillus, had the highest number of identified BGC types. This study offers fresh insights into the potential ecological role of SMs from sediment microbial communities in an unexplored environment, underscoring their value as a source of novel natural products.

An in-depth evaluation of metagenomic classifiers for soil microbiomes

BACKGROUND

Recent endeavours in metagenomics, exemplified by projects such as the human microbiome project and TARA Oceans, have illuminated the complexities of microbial biomes. A robust bioinformatic pipeline and meticulous evaluation of their methodology have contributed to the success of these projects. The soil environment, however, with its unique challenges, requires a specialized methodological exploration to maximize microbial insights. A notable limitation in soil microbiome studies is the dearth of soil-specific reference databases available to classifiers that emulate the complexity of soil communities. There is also a lack of in-vitro mock communities derived from soil strains that can be assessed for taxonomic classification accuracy.

RESULTS

In this study, we generated a custom in-silico mock community containing microbial genomes commonly observed in the soil microbiome. Using this mock community, we simulated shotgun sequencing data to evaluate the performance of three leading metagenomic classifiers: Kraken2 (supplemented with Bracken, using a custom database derived from GTDB-TK genomes along with its own default database), Kaiju, and MetaPhlAn, utilizing their respective default databases for a robust analysis. Our results highlight the importance of optimizing taxonomic classification parameters, database selection, as well as analysing trimmed reads and contigs. Our study showed that classifiers tailored to the specific taxa present in our samples led to fewer errors compared to broader databases including microbial eukaryotes, protozoa, or human genomes, highlighting the effectiveness of targeted taxonomic classification. Notably, an optimal classifier performance was achieved when applying a relative abundance threshold of 0.001% or 0.005%. The Kraken2 supplemented with bracken, with a custom database demonstrated superior precision, sensitivity, F1 score, and overall sequence classification. Using a custom database, this classifier classified 99% of in-silico reads and 58% of real-world soil shotgun reads, with the latter identifying previously overlooked phyla using a custom database.

CONCLUSION

This study underscores the potential advantages of in-silico methodological optimization in metagenomic analyses, especially when deciphering the complexities of soil microbiomes. We demonstrate that the choice of classifier and database significantly impacts microbial taxonomic profiling. Our findings suggest that employing Kraken2 with Bracken, coupled with a custom database of GTDB-TK genomes and fungal genomes at a relative abundance threshold of 0.001% provides optimal accuracy in soil shotgun metagenome analysis.

Sequence-structure-function characterization of the emerging tetracycline destructase family of antibiotic resistance enzymes

Tetracycline destructases (TDases) are flavin monooxygenases which can confer resistance to all generations of tetracycline antibiotics. The recent increase in the number and diversity of reported TDase sequences enables a deep investigation of the TDase sequence-structure-function landscape. Here, we evaluate the sequence determinants of TDase function through two complementary approaches: (1) constructing profile hidden Markov models to predict new TDases, and (2) using multiple sequence alignments to identify conserved positions important to protein function. Using the HMM-based approach we screened 50 high-scoring candidate sequences in Escherichia coli, leading to the discovery of 13 new TDases. The X-ray crystal structures of two new enzymes from Legionella species were determined, and the ability of anhydrotetracycline to inhibit their tetracycline-inactivating activity was confirmed. Using the MSA-based approach we identified 31 amino acid positions 100% conserved across all known TDase sequences. The roles of these positions were analyzed by alanine-scanning mutagenesis in two TDases, to study the impact on cell and in vitro activity, structure, and stability. These results expand the diversity of TDase sequences and provide valuable insights into the roles of important residues in TDases, and flavin monooxygenases more broadly.

BASALT refines binning from metagenomic data and increases resolution of genome-resolved metagenomic analysis

Metagenomic binning is an essential technique for genome-resolved characterization of uncultured microorganisms in various ecosystems but hampered by the low efficiency of binning tools in adequately recovering metagenome-assembled genomes (MAGs). Here, we introduce BASALT (Binning Across a Series of Assemblies Toolkit) for binning and refinement of short- and long-read sequencing data. BASALT employs multiple binners with multiple thresholds to produce initial bins, then utilizes neural networks to identify core sequences to remove redundant bins and refine non-redundant bins. Using the same assemblies generated from Critical Assessment of Metagenome Interpretation (CAMI) datasets, BASALT produces up to twice as many MAGs as VAMB, DASTool, or metaWRAP. Processing assemblies from a lake sediment dataset, BASALT produces ~30% more MAGs than metaWRAP, including 21 unique class-level prokaryotic lineages. Functional annotations reveal that BASALT can retrieve 47.6% more non-redundant opening-reading frames than metaWRAP. These results highlight the robust handling of metagenomic sequencing data of BASALT.

The defensome of complex bacterial communities

Bacteria have developed various defense mechanisms to avoid infection and killing in response to the fast evolution and turnover of viruses and other genetic parasites. Such pan-immune system (defensome) encompasses a growing number of defense lines that include well-studied innate and adaptive systems such as restriction-modification, CRISPR-Cas and abortive infection, but also newly found ones whose mechanisms are still poorly understood. While the abundance and distribution of defense systems is well-known in complete and culturable genomes, there is a void in our understanding of their diversity and richness in complex microbial communities. Here we performed a large-scale in-depth analysis of the defensomes of 7759 high-quality bacterial population genomes reconstructed from soil, marine, and human gut environments. We observed a wide variation in the frequency and nature of the defensome among large phyla, which correlated with lifestyle, genome size, habitat, and geographic background. The defensome's genetic mobility, its clustering in defense islands, and genetic variability was found to be system-specific and shaped by the bacterial environment. Hence, our results provide a detailed picture of the multiple immune barriers present in environmentally distinct bacterial communities and set the stage for subsequent identification of novel and ingenious strategies of diversification among uncultivated microbes.

Extracellular vesicle formation in Euryarchaeota is driven by a small GTPase

Since their discovery, extracellular vesicles (EVs) have changed our view on how organisms interact with their extracellular world. EVs are able to traffic a diverse array of molecules across different species and even domains, facilitating numerous functions. In this study, we investigate EV production in Euryarchaeota, using the model organism Haloferax volcanii. We uncover that EVs enclose RNA, with specific transcripts preferentially enriched, including those with regulatory potential, and conclude that EVs can act as an RNA communication system between haloarchaea. We demonstrate the key role of an EV-associated small GTPase for EV formation in H. volcanii that is also present across other diverse evolutionary branches of Archaea. We propose the name, ArvA, for the identified family of archaeal vesiculating GTPases. Additionally, we show that two genes in the same operon with arvA (arvB and arvC) are also involved in EV formation. Both, arvB and arvC, are closely associated with arvA in the majority of other archaea encoding ArvA. Our work demonstrates that small GTPases involved in membrane deformation and vesiculation, ubiquitous in Eukaryotes, are also present in Archaea and are widely distributed across diverse archaeal phyla.

Genome-centric analyses of 165 metagenomes show that mobile genetic elements are crucial for the transmission of antimicrobial resistance genes to pathogens in activated sludge and wastewater

Wastewater is considered a reservoir of antimicrobial resistance genes (ARGs), where the abundant antimicrobial-resistant bacteria and mobile genetic elements facilitate horizontal gene transfer. However, the prevalence and extent of these phenomena in different taxonomic groups that inhabit wastewater are still not fully understood. Here, we determined the presence of ARGs in metagenome-assembled genomes (MAGs) and evaluated the risks of MAG-carrying ARGs in potential human pathogens. The potential of these ARGs to be transmitted horizontally or vertically was also determined. A total of 5,916 MAGs (completeness >50%, contamination <10%) were recovered, covering 68 phyla and 279 genera. MAGs were dereplicated into 1,204 genome operational taxonomic units (gOTUs) as a proxy for species ( average nucleotide identity >0.95). The dominant ARG classes detected were bacitracin, multi-drug, macrolide-lincosamide-streptogramin (MLS), glycopeptide, and aminoglycoside, and 10.26% of them were located on plasmids. The main hosts of ARGs belonged to Escherichia, Klebsiella, Acinetobacter, Gresbergeria, Mycobacterium, and Thauera. Our data showed that 253 MAGs carried virulence factor genes (VFGs) divided into 44 gOTUs, of which 45 MAGs were carriers of ARGs, indicating that potential human pathogens carried ARGs. Alarmingly, the MAG assigned as Escherichia coli contained 159 VFGs, of which 95 were located on chromosomes and 10 on plasmids. In addition to shedding light on the prevalence of ARGs in individual genomes recovered from activated sludge and wastewater, our study demonstrates a workflow that can identify antimicrobial-resistant pathogens in complex microbial communities.

IMPORTANCE

Antimicrobial resistance (AMR) threatens the health of humans, animals, and natural ecosystems. In our study, an analysis of 165 metagenomes from wastewater revealed antibiotic-targeted alteration, efflux, and inactivation as the most prevalent AMR mechanisms. We identified several genera correlated with multiple ARGs, including Klebsiella, Escherichia, Acinetobacter, Nitrospira, Ottowia, Pseudomonas, and Thauera, which could have significant implications for AMR transmission. The abundance of bacA, mexL, and aph(3")-I in the genomes calls for their urgent management in wastewater. Our approach could be applied to different ecosystems to assess the risk of potential pathogens containing ARGs. Our findings highlight the importance of managing AMR in wastewater and can help design measures to reduce the transmission and evolution of AMR in these systems.

An optimized culturomics strategy for isolation of human milk microbiota

Viable microorganisms and a diverse microbial ecosystem found in human milk play a crucial role in promoting healthy immune system and shaping the microbial community in the infant's gut. Culturomics is a method to obtain a comprehensive repertoire of human milk microbiota. However, culturomics is an onerous procedure, and needs expertise, making it difficult to be widely implemented. Currently, there is no efficient and feasible culturomics method specifically designed for human milk microbiota yet. Therefore, the aim of this study was to develop a more efficient and feasible culturomics method specifically designed for human milk microbiota. We obtained fresh samples of human milk from healthy Chinese mothers and conducted a 27-day enrichment process using blood culture bottles. Bacterial isolates were harvested at different time intervals and cultured on four different types of media. Using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis, we identified a total of 6601 colonies and successfully obtained 865 strains, representing 4 phyla, 21 genera, and 54 species. By combining CBA and MRS media, we were able to cultivate over 94.4% of bacterial species with high diversity, including species-specific microorganisms. Prolonged pre-incubation in blood culture bottles significantly increased the number of bacterial species by about 33% and improved the isolation efficiency of beneficial bacteria with low abundance in human milk. After optimization, we reduced the pre-incubation time in blood culture bottles and selected optimal picking time-points (0, 3, and 6 days) at 37°C. By testing 6601 colonies using MALDI-TOF MS, we estimated that this new protocol could obtain more than 90% of bacterial species, reducing the workload by 57.0%. In conclusion, our new culturomics strategy, which involves the combination of CBA and MRS media, extended pre-incubation enrichment, and optimized picking time-points, is a feasible method for studying the human milk microbiota. This protocol significantly improves the efficiency of culturomics and allows for the establishment of a comprehensive repertoire of bacterial species and strains in human milk.

Why and how to use the SeqCode

The SeqCode, formally called the Code of Nomenclature of Prokaryotes Described from Sequence Data, is a new code of nomenclature in which genome sequences are the nomenclatural types for the names of prokaryotic species. While similar to the International Code of Nomenclature of Prokaryotes (ICNP) in structure and rules of priority, it does not require the deposition of type strains in international culture collections. Thus, it allows for the formation of permanent names for uncultured prokaryotes whose nearly complete genome sequences have been obtained directly from environmental DNA as well as other prokaryotes that cannot be deposited in culture collections. Because the diversity of uncultured prokaryotes greatly exceeds that of readily culturable prokaryotes, the SeqCode is the only code suitable for naming the majority of prokaryotic species. The start date of the SeqCode was January 1, 2022, and the online Registry (https://seqco.de/) was created to ensure valid publication of names. The SeqCode recognizes all names validly published under the ICNP before 2022. After that date, names validly published under the SeqCode compete with ICNP names for priority. As a result, species can have only one name, either from the SeqCode or ICNP, enabling effective communication and the creation of unified taxonomies of uncultured and cultured prokaryotes. The SeqCode is administered by the SeqCode Committee, which is comprised of the SeqCode Community and elected administrative components. Anyone with an interest in the systematics of prokaryotes is encouraged to join the SeqCode Community and participate in the development of this resource.

Peeling off the layers from microbial dark matter (MDM): recent advances, future challenges, and opportunities

Microbes represent the most common organisms on Earth; however, less than 2% of microbial species in the environment can undergo cultivation for study under laboratory conditions, and the rest of the enigmatic, microbial world remains mysterious, constituting a kind of "microbial dark matter" (MDM). In the last two decades, remarkable progress has been made in culture-dependent and culture-independent techniques. More recently, studies of MDM have relied on culture-independent techniques to recover genetic material through either unicellular genomics or shotgun metagenomics to construct single-amplified genomes (SAGs) and metagenome-assembled genomes (MAGs), respectively, which provide information about evolution and metabolism. Despite the remarkable progress made in the past decades, the functional diversity of MDM still remains uncharacterized. This review comprehensively summarizes the recently developed culture-dependent and culture-independent techniques for characterizing MDM, discussing major challenges, opportunities, and potential applications. These activities contribute to expanding our knowledge of the microbial world and have implications for various fields including Biotechnology, Bioprospecting, Functional genomics, Medicine, Evolutionary and Planetary biology. Overall, this review aims to peel off the layers from MDM, shed light on recent advancements, identify future challenges, and illuminate the exciting opportunities that lie ahead in unraveling the secrets of this intriguing microbial realm.

A genome and gene catalog of the aquatic microbiomes of the Tibetan Plateau

The Tibetan Plateau supplies water to nearly 2 billion people in Asia, but climate change poses threats to its aquatic microbial resources. Here, we construct the Tibetan Plateau Microbial Catalog by sequencing 498 metagenomes from six water ecosystems (saline lakes, freshwater lakes, rivers, hot springs, wetlands and glaciers). Our catalog expands knowledge of regional genomic diversity by presenting 32,355 metagenome-assembled genomes that de-replicated into 10,723 representative genome-based species, of which 88% were unannotated. The catalog contains nearly 300 million non-redundant gene clusters, of which 15% novel, and 73,864 biosynthetic gene clusters, of which 50% novel, thus expanding known functional diversity. Using these data, we investigate the Tibetan Plateau aquatic microbiome's biogeography along a distance of 2,500 km and >5 km in altitude. Microbial compositional similarity and the shared gene count with the Tibetan Plateau microbiome decline along with distance and altitude difference, suggesting a dispersal pattern. The Tibetan Plateau Microbial Catalog stands as a substantial repository for high-altitude aquatic microbiome resources, providing potential for discovering novel lineages and functions, and bridging knowledge gaps in microbiome biogeography.

A metagenomic alpha-diversity index for microbial functional biodiversity

Alpha-diversity indices are an essential tool for describing and comparing biodiversity. Microbial ecologists apply indices originally intended for, or adopted by, macroecology to address questions relating to taxonomy (conserved marker) and function (metagenome-based data). In this Perspective piece, I begin by discussing the nature and mathematical quirks important for interpreting routinely employed alpha-diversity indices. Secondly, I propose a metagenomic alpha-diversity index (MD) that measures the (dis)similarity of protein-encoding genes within a community. MD has defined limits, whereby a community comprised mostly of similar, poorly diverse protein-encoding genes pulls the index to the lower limit, while a community rich in divergent homologs and unique genes drives it toward the upper limit. With data acquired from an in silico and three in situ metagenome studies, I derive MD and typical alpha-diversity indices applied to taxonomic (ribosomal rRNA) and functional (all protein-encoding) genes, and discuss their relationships with each other. Not all alpha-diversity indices detect biological trends, and taxonomic does not necessarily follow functional biodiversity. Throughout, I explain that protein Richness and MD provide complementary and easily interpreted information, while probability-based indices do not. Finally, considerations regarding the unique nature of microbial metagenomic data and its relevance for describing functional biodiversity are discussed.

Metagenomic analysis of carbohydrate-active enzymes and their contribution to marine sediment biodiversity

Marine sediments constitute the world's most substantial long-term carbon repository. The microorganisms dwelling in these sediments mediate the transformation of fixed oceanic carbon, but their contribution to the carbon cycle is not fully understood. Previous culture-independent investigations into sedimentary microorganisms have underscored the significance of carbohydrates in the carbon cycle. In this study, we employ a metagenomic methodology to investigate the distribution and abundance of carbohydrate-active enzymes (CAZymes) in 37 marine sediments sites. These sediments exhibit varying oxygen availability and were isolated in diverse regions worldwide. Our comparative analysis is based on the metabolic potential for oxygen utilisation, derived from genes present in both oxic and anoxic environments. We found that extracellular CAZyme modules targeting the degradation of plant and algal detritus, necromass, and host glycans were abundant across all metagenomic samples. The analysis of these results indicates that the oxic/anoxic conditions not only influence the taxonomic composition of the microbial communities, but also affect the occurrence of CAZyme modules involved in the transformation of necromass, algae and plant detritus. To gain insight into the sediment microbial taxa, we reconstructed metagenome assembled genomes (MAG) and examined the presence of primary extracellular carbohydrate active enzyme (CAZyme) modules. Our findings reveal that the primary CAZyme modules and the CAZyme gene clusters discovered in our metagenomes were prevalent in the Bacteroidia, Gammaproteobacteria, and Alphaproteobacteria classes. We compared those MAGs to organisms from the same taxonomic classes found in soil, and we found that they were similar in its CAZyme repertoire, but the soil MAG contained a more abundant and diverse CAZyme content. Furthermore, the data indicate that abundant classes in our metagenomic samples, namely Alphaproteobacteria, Bacteroidia and Gammaproteobacteria, play a pivotal role in carbohydrate transformation within the initial few metres of the sediments.

Hydrolytic endonucleolytic ribozyme (HYER) is programmable for sequence-specific DNA cleavage

Ribozymes are catalytic RNAs with diverse functions including self-splicing and polymerization. This work aims to discover natural ribozymes that behave as hydrolytic and sequence-specific DNA endonucleases, which could be repurposed as DNA manipulation tools. Focused on bacterial group II-C introns, we found that many systems without intron-encoded protein propagate multiple copies in their resident genomes. These introns, named HYdrolytic Endonucleolytic Ribozymes (HYERs), cleaved RNA, single-stranded DNA, bubbled double-stranded DNA (dsDNA), and plasmids in vitro. HYER1 generated dsDNA breaks in the mammalian genome. Cryo-electron microscopy analysis revealed a homodimer structure for HYER1, where each monomer contains a Mg2+-dependent hydrolysis pocket and captures DNA complementary to the target recognition site (TRS). Rational designs including TRS extension, recruiting sequence insertion, and heterodimerization yielded engineered HYERs showing improved specificity and flexibility for DNA manipulation.

Tools for microbial single-cell genomics for obtaining uncultured microbial genomes

The advent of next-generation sequencing technologies has facilitated the acquisition of large amounts of DNA sequence data at a relatively low cost, leading to numerous breakthroughs in decoding microbial genomes. Among the various genome sequencing activities, metagenomic analysis, which entails the direct analysis of uncultured microbial DNA, has had a profound impact on microbiome research and has emerged as an indispensable technology in this field. Despite its valuable contributions, metagenomic analysis is a "bulk analysis" technique that analyzes samples containing a wide diversity of microbes, such as bacteria, yielding information that is averaged across the entire microbial population. In order to gain a deeper understanding of the heterogeneous nature of the microbial world, there is a growing need for single-cell analysis, similar to its use in human cell biology. With this paradigm shift in mind, comprehensive single-cell genomics technology has become a much-anticipated innovation that is now poised to revolutionize microbiome research. It has the potential to enable the discovery of differences at the strain level and to facilitate a more comprehensive examination of microbial ecosystems. In this review, we summarize the current state-of-the-art in microbial single-cell genomics, highlighting the potential impact of this technology on our understanding of the microbial world. The successful implementation of this technology is expected to have a profound impact in the field, leading to new discoveries and insights into the diversity and evolution of microbes.

Functional and evolutionary significance of unknown genes from uncultivated taxa

Many of the Earth's microbes remain uncultured and understudied, limiting our understanding of the functional and evolutionary aspects of their genetic material, which remain largely overlooked in most metagenomic studies1. Here we analysed 149,842 environmental genomes from multiple habitats2-6 and compiled a curated catalogue of 404,085 functionally and evolutionarily significant novel (FESNov) gene families exclusive to uncultivated prokaryotic taxa. All FESNov families span multiple species, exhibit strong signals of purifying selection and qualify as new orthologous groups, thus nearly tripling the number of bacterial and archaeal gene families described to date. The FESNov catalogue is enriched in clade-specific traits, including 1,034 novel families that can distinguish entire uncultivated phyla, classes and orders, probably representing synapomorphies that facilitated their evolutionary divergence. Using genomic context analysis and structural alignments we predicted functional associations for 32.4% of FESNov families, including 4,349 high-confidence associations with important biological processes. These predictions provide a valuable hypothesis-driven framework that we used for experimental validatation of a new gene family involved in cell motility and a novel set of antimicrobial peptides. We also demonstrate that the relative abundance profiles of novel families can discriminate between environments and clinical conditions, leading to the discovery of potentially new biomarkers associated with colorectal cancer. We expect this work to enhance future metagenomics studies and expand our knowledge of the genetic repertory of uncultivated organisms.

A genomic view of environmental and life history controls on microbial nitrogen acquisition strategies

Microorganisms have evolved diverse strategies to acquire the vital element nitrogen (N) from the environment. Ecological and physiological controls on the distribution of these strategies among microbes remain unclear. In this study, we examine the distribution of 10 major N acquisition strategies in taxonomically and metabolically diverse microbial genomes, including those from the Genomic Catalogue of Earth's Microbiomes dataset. We utilize a marker gene-based approach to assess relationships between N acquisition strategy prevalence and microbial life history strategies. Our results underscore energetic costs of assimilation as a broad control on strategy distribution. The most prevalent strategies are the uptake of ammonium and simple amino acids, which have relatively low energetic costs, while energy-intensive biological nitrogen fixation is the least common. Deviations from the energy-based framework include the higher-than-expected prevalence of the assimilatory pathway for chitin, a large organic polymer. Energy availability is also important, with aerobic chemoorganotrophs  and oxygenic phototrophs notably possessing ~2-fold higher numbers of total strategies compared to anaerobic microbes. Environmental controls are evidenced by the enrichment of inorganic N assimilation strategies among free-living taxa compared to host-associated taxa. Physiological constraints such as pathway incompatibility add complexity to N acquisition strategy distributions. Finally, we discuss the necessity for microbially-relevant spatiotemporal environmental metadata for improving mechanistic and prediction-oriented analyses of genomic data.

Recent advances in the culture-independent discovery of natural products using metagenomic approaches

Natural products derived from bacterial sources have long been pivotal in the discovery of drug leads. However, the cultivation of only about 1% of bacteria in laboratory settings has left a significant portion of biosynthetic diversity hidden within the genomes of uncultured bacteria. Advances in sequencing technologies now enable the exploration of genetic material from these metagenomes through culture-independent methods. This approach involves extracting genetic sequences from environmental DNA and applying a hybrid methodology that combines functional screening, sequence tag-based homology screening, and bioinformatic-assisted chemical synthesis. Through this process, numerous valuable natural products have been identified and synthesized from previously uncharted metagenomic territories. This paper provides an overview of the recent advancements in the utilization of culture-independent techniques for the discovery of novel biosynthetic gene clusters and bioactive small molecules within metagenomic libraries.

scMicrobe PTA: Near Complete Genomes from Single Bacterial Cells

Microbial genomes produced by single-cell amplification are largely incomplete. Here, we show that primary template amplification (PTA), a novel single-cell amplification technique, generated nearly complete genomes from three bacterial isolate species. Furthermore, taxonomically diverse genomes recovered from aquatic and soil microbiomes using PTA had a median completeness of 81%, whereas genomes from standard amplification approaches were usually <30% complete. PTA-derived genomes also included more associated viruses and biosynthetic gene clusters.

Unraveling the phylogenomic diversity of Methanomassiliicoccales and implications for mitigating ruminant methane emissions

BACKGROUND

Methanomassiliicoccales are a recently identified order of methanogens that are diverse across global environments particularly the gastrointestinal tracts of animals; however, their metabolic capacities are defined via a limited number of cultured strains.

RESULTS

Here, we profile and analyze 243 Methanomassiliicoccales genomes assembled from cultured representatives and uncultured metagenomes recovered from various biomes, including the gastrointestinal tracts of different animal species. Our analyses reveal the presence of numerous undefined genera and genetic variability in metabolic capabilities within Methanomassiliicoccales lineages, which is essential for adaptation to their ecological niches. In particular, gastrointestinal tract Methanomassiliicoccales demonstrate the presence of co-diversified members with their hosts over evolutionary timescales and likely originated in the natural environment. We highlight the presence of diverse clades of vitamin transporter BtuC proteins that distinguish Methanomassiliicoccales from other archaeal orders and likely provide a competitive advantage in efficiently handling B12. Furthermore, genome-centric metatranscriptomic analysis of ruminants with varying methane yields reveal elevated expression of select Methanomassiliicoccales genera in low methane animals and suggest that B12 exchanges could enable them to occupy ecological niches that possibly alter the direction of H2 utilization.

CONCLUSIONS

We provide a comprehensive and updated account of divergent Methanomassiliicoccales lineages, drawing from numerous uncultured genomes obtained from various habitats. We also highlight their unique metabolic capabilities involving B12, which could serve as promising targets for mitigating ruminant methane emissions by altering H2 flow.

Structure-guided discovery of anti-CRISPR and anti-phage defense proteins

Bacteria use a variety of defense systems to protect themselves from phage infection. In turn, phages have evolved diverse counter-defense measures to overcome host defenses. Here, we use protein structural similarity and gene co-occurrence analyses to screen >66 million viral protein sequences and >330,000 metagenome-assembled genomes for the identification of anti-phage and counter-defense systems. We predict structures for ~300,000 proteins and perform large-scale, pairwise comparison to known anti-CRISPR (Acr) and anti-phage proteins to identify structural homologs that otherwise may not be uncovered using primary sequence search. This way, we identify a Bacteroidota phage Acr protein that inhibits Cas12a, and an Akkermansia muciniphila anti-phage defense protein, termed BxaP. Gene bxaP is found in loci encoding Bacteriophage Exclusion (BREX) and restriction-modification defense systems, but confers immunity independently. Our work highlights the advantage of combining protein structural features and gene co-localization information in studying host-phage interactions.

Microbial metabolites as modulators of host physiology

The gut microbiota is increasingly recognised as a key player in influencing human health and changes in the gut microbiota have been strongly linked with many non-communicable conditions in humans such as type 2 diabetes, obesity and cardiovascular disease. However, characterising the molecular mechanisms that underpin these associations remains an important challenge for researchers. The gut microbiota is a complex microbial community that acts as a metabolic interface to transform ingested food (and other xenobiotics) into metabolites that are detected in the host faeces, urine and blood. Many of these metabolites are only produced by microbes and there is accumulating evidence to suggest that these microbe-specific metabolites do act as effectors to influence human physiology. For example, the gut microbiota can digest dietary complex polysaccharides (such as fibre) into short-chain fatty acids (SCFA) such as acetate, propionate and butyrate that have a pervasive role in host physiology from nutrition to immune function. In this review we will outline our current understanding of the role of some key microbial metabolites, such as SCFA, indole and bile acids, in human health. Whilst many studies linking microbial metabolites with human health are correlative we will try to highlight examples where genetic evidence is available to support a specific role for a microbial metabolite in host health and well-being.

Genomic profiles of four novel cyanobacteria MAGs from Lake Vanda, Antarctica: insights into photosynthesis, cold tolerance, and the circadian clock

Cyanobacteria in polar environments face environmental challenges, including cold temperatures and extreme light seasonality with small diurnal variation, which has implications for polar circadian clocks. However, polar cyanobacteria remain underrepresented in available genomic data, and there are limited opportunities to study their genetic adaptations to these challenges. This paper presents four new Antarctic cyanobacteria metagenome-assembled genomes (MAGs) from microbial mats in Lake Vanda in the McMurdo Dry Valleys in Antarctica. The four MAGs were classified as Leptolyngbya sp. BulkMat.35, Pseudanabaenaceae cyanobacterium MP8IB2.15, Microcoleus sp. MP8IB2.171, and Leptolyngbyaceae cyanobacterium MP9P1.79. The MAGs contain 2.76 Mbp - 6.07 Mbp, and the bin completion ranges from 74.2-92.57%. Furthermore, the four cyanobacteria MAGs have average nucleotide identities (ANIs) under 90% with each other and under 77% with six existing polar cyanobacteria MAGs and genomes. This suggests that they are novel cyanobacteria and demonstrates that polar cyanobacteria genomes are underrepresented in reference databases and there is continued need for genome sequencing of polar cyanobacteria. Analyses of the four novel and six existing polar cyanobacteria MAGs and genomes demonstrate they have genes coding for various cold tolerance mechanisms and most standard circadian rhythm genes with the Leptolyngbya sp. BulkMat.35 and Leptolyngbyaceae cyanobacterium MP9P1.79 contained kaiB3, a divergent homolog of kaiB.

Precision enzyme discovery through targeted mining of metagenomic data

Metagenomics has opened new avenues for exploring the genetic potential of uncultured microorganisms, which may serve as promising sources of enzymes and natural products for industrial applications. Identifying enzymes with improved catalytic properties from the vast amount of available metagenomic data poses a significant challenge that demands the development of novel computational and functional screening tools. The catalytic properties of all enzymes are primarily dictated by their structures, which are predominantly determined by their amino acid sequences. However, this aspect has not been fully considered in the enzyme bioprospecting processes. With the accumulating number of available enzyme sequences and the increasing demand for discovering novel biocatalysts, structural and functional modeling can be employed to identify potential enzymes with novel catalytic properties. Recent efforts to discover new polysaccharide-degrading enzymes from rumen metagenome data using homology-based searches and machine learning-based models have shown significant promise. Here, we will explore various computational approaches that can be employed to screen and shortlist metagenome-derived enzymes as potential biocatalyst candidates, in conjunction with the wet lab analytical methods traditionally used for enzyme characterization.

Niche differentiation in microbial communities with stable genomic traits over time in engineered systems

Microbial communities in full-scale engineered systems undergo dynamic compositional changes. However, mechanisms governing assembly of such microbes and succession of their functioning and genomic traits under various environmental conditions are unclear. In this study, we used the activated sludge and anaerobic treatment systems of four full-scale industrial wastewater treatment plants as models to investigate the niches of microbes in communities and the temporal succession patterns of community compositions. High-quality representative metagenome-assembled genomes revealed that taxonomic, functional, and trait-based compositions were strongly shaped by environmental selection, with replacement processes primarily driving variations in taxonomic and functional compositions. Plant-specific indicators were associated with system environmental conditions and exhibited strong determinism and trajectory directionality over time. The partitioning of microbes in a co-abundance network according to groups of plant-specific indicators, together with significant between-group differences in genomic traits, indicated the occurrence of niche differentiation. The indicators of the treatment plant with rich nutrient input and high substrate removal efficiency exhibited a faster predicted growth rate, lower guanine-cytosine content, smaller genome size, and higher codon usage bias than the indicators of the other plants. In individual plants, taxonomic composition displayed a more rapid temporal succession than functional and trait-based compositions. The succession of taxonomic, functional, and trait-based compositions was correlated with the kinetics of treatment processes in the activated sludge systems. This study provides insights into ecological niches of microbes in engineered systems and succession patterns of their functions and traits, which will aid microbial community management to improve treatment performance.

Genomic basis of environmental adaptation in the widespread poly-extremophilic Exiguobacterium group

Delineating cohesive ecological units and determining the genetic basis for their environmental adaptation are among the most important objectives in microbiology. In the last decade, many studies have been devoted to characterizing the genetic diversity in microbial populations to address these issues. However, the impact of extreme environmental conditions, such as temperature and salinity, on microbial ecology and evolution remains unclear so far. In order to better understand the mechanisms of adaptation, we studied the (pan)genome of Exiguobacterium, a poly-extremophile bacterium able to grow in a wide range of environments, from permafrost to hot springs. To have the genome for all known Exiguobacterium type strains, we first sequenced those that were not yet available. Using a reverse-ecology approach, we showed how the integration of phylogenomic information, genomic features, gene and pathway enrichment data, regulatory element analyses, protein amino acid composition, and protein structure analyses of the entire Exiguobacterium pangenome allows to sharply delineate ecological units consisting of mesophilic, psychrophilic, halophilic-mesophilic, and halophilic-thermophilic ecotypes. This in-depth study clarified the genetic basis of the defined ecotypes and identified some key mechanisms driving the environmental adaptation to extreme environments. Our study points the way to organizing the vast microbial diversity into meaningful ecologically units, which, in turn, provides insight into how microbial communities adapt and respond to different environmental conditions in a changing world.

IMG/PR: a database of plasmids from genomes and metagenomes with rich annotations and metadata

Plasmids are mobile genetic elements found in many clades of Archaea and Bacteria. They drive horizontal gene transfer, impacting ecological and evolutionary processes within microbial communities, and hold substantial importance in human health and biotechnology. To support plasmid research and provide scientists with data of an unprecedented diversity of plasmid sequences, we introduce the IMG/PR database, a new resource encompassing 699 973 plasmid sequences derived from genomes, metagenomes and metatranscriptomes. IMG/PR is the first database to provide data of plasmid that were systematically identified from diverse microbiome samples. IMG/PR plasmids are associated with rich metadata that includes geographical and ecosystem information, host taxonomy, similarity to other plasmids, functional annotation, presence of genes involved in conjugation and antibiotic resistance. The database offers diverse methods for exploring its extensive plasmid collection, enabling users to navigate plasmids through metadata-centric queries, plasmid comparisons and BLAST searches. The web interface for IMG/PR is accessible at https://img.jgi.doe.gov/pr. Plasmid metadata and sequences can be downloaded from https://genome.jgi.doe.gov/portal/IMG_PR.

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.