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.

Diverse and specialized metabolic capabilities of microbes in oligotrophic built environments

BACKGROUND

Built environments (BEs) are typically considered to be oligotrophic and harsh environments for microbial communities under normal, non-damp conditions. However, the metabolic functions of microbial inhabitants in BEs remain poorly understood. This study aimed to shed light on the functional capabilities of microbes in BEs by analyzing 860 representative metagenome-assembled genomes (rMAGs) reconstructed from 738 samples collected from BEs across the city of Hong Kong and from the skin surfaces of human occupants. The study specifically focused on the metabolic functions of rMAGs that are either phylogenetically novel or prevalent in BEs.

RESULTS

The diversity and composition of BE microbiomes were primarily shaped by the sample type, with Micrococcus luteus and Cutibacterium acnes being prevalent. The metabolic functions of rMAGs varied significantly based on taxonomy, even at the strain level. A novel strain affiliated with the Candidatus class Xenobia in the Candidatus phylum Eremiobacterota and two novel strains affiliated with the superphylum Patescibacteria exhibited unique functions compared with their close relatives, potentially aiding their survival in BEs and on human skins. The novel strains in the class Xenobia possessed genes for transporting nitrate and nitrite as nitrogen sources and nitrosative stress mitigation induced by nitric oxide during denitrification. The two novel Patescibacteria strains both possessed a broad array of genes for amino acid and trace element transport, while one of them carried genes for carotenoid and ubiquinone biosynthesis. The globally prevalent M. luteus in BEs displayed a large and open pangenome, with high infraspecific genomic diversity contributed by 11 conspecific strains recovered from BEs in a single geographic region. The versatile metabolic functions encoded in the large accessory genomes of M. luteus may contribute to its global ubiquity and specialization in BEs.

CONCLUSIONS

This study illustrates that the microbial inhabitants of BEs possess metabolic potentials that enable them to tolerate and counter different biotic and abiotic conditions. Additionally, these microbes can efficiently utilize various limited residual resources from occupant activities, potentially enhancing their survival and persistence within BEs. A better understanding of the metabolic functions of BE microbes will ultimately facilitate the development of strategies to create a healthy indoor microbiome. Video Abstract.

Small amounts of misassembly can have disproportionate effects on pangenome-based metagenomic analyses

Individual genes from microbiomes can drive host-level phenotypes. To help identify such candidate genes, several recent tools estimate microbial gene copy numbers directly from metagenomes. These tools rely on alignments to pangenomes, which in turn are derived from the set of all individual genomes from one species. While large-scale metagenomic assembly efforts have made pangenome estimates more complete, mixed communities can also introduce contamination into assemblies, and it is unknown how robust pangenome-based metagenomic analyses are to these errors. To gain insight into this problem, we re-analyzed a case-control study of the gut microbiome in cirrhosis, focusing on commensal Clostridia previously implicated in this disease. We tested for differentially prevalent genes in the Lachnospiraceae , then investigated which were likely to be contaminants using sequence similarity searches. Out of 86 differentially prevalent genes, we found that 33 (38%) were probably contaminants originating in taxa such as Veillonella and Haemophilus , unrelated genera that were independently correlated with disease status. Our results demonstrate that even small amounts of contamination in metagenome assemblies, below typical quality thresholds, can threaten to overwhelm gene-level metagenomic analyses. However, we also show that such contaminants can be accurately identified using a method based on gene-to-species correlation. After removing these contaminants, we observe that several flagellar motility gene clusters in the Lachnospira eligens pangenome are associated with cirrhosis status. We have integrated our analyses into an analysis and visualization pipeline, PanSweep, that can automatically identify cases where pangenome contamination may bias the results of gene-resolved analyses.

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.

Biodiversity of mudflat intertidal viromes along the Chinese coasts

Viruses constitute the most diverse and abundant biological entities on Earth. However, our understanding of this tiniest life form in complex ecosystems remains limited. Here, we recover 20,102 viral OTUs from twelve intertidal zones along the Chinese coasts. Our analysis demonstrates high viral diversity and functional potential in intertidal zones, encoding important functional genes that can be potentially transferred to microbial hosts and mediate elemental biogeochemical cycles, especially carbon, phosphate and sulfur. Virus-host abundance dynamics vary among different microbial lineages. Viral community composition is closely associated with environmental conditions, including dissolved organic matter. Concordant biogeographic patterns are observed for viruses and microbes. Viral communities are generally habitat specific with low overlaps between intertidal and other habitats. Environmental factors and geographic distance dominate the compositional variation of intertidal viromes. Overall, these findings expand our understanding of intertidal viromes within an ecological framework, providing insights into the virus-host coevolutionary arms race.

Comprehensive evaluation of primer pairs targeting the ammonia monooxygenase subunit A gene of complete ammonia-oxidizing Nitrospira

Since the discovery of complete ammonia oxidizers (comammox) within the genus Nitrospira, their distribution and abundance across habitats have been intensively studied to better understand their ecological significance. Many primers targeting their ammonia monooxygenase subunit A gene (amoA) have been designed to detect and quantify comammox bacteria and to describe their community structure. We identified 38 published primers, but only few had high coverage and specificity for all known comammox Nitrospira or one of the two described subclades. For each target group, we comprehensively evaluated selected primer pairs using in silico analyses, endpoint PCRs, qPCRs, and amplicon sequencing on samples from various environments. Endpoint PCRs and qPCRs showed that the most commonly used primer pairs (comaA-244F/659R, comaB-244F/659R, and Ntsp-amoA162F/359R) produced several bands, which likely inflated quantifications via qPCR. In contrast, the recently published primer combinations CA377F/C576R, CB377F/C576R, and CA-CB377F/C576R resulted mostly in a single band. Furthermore, amplicon sequencing demonstrated that these primer combinations also captured the highest richness of comammox Nitrospira. Taken together, our results indicate that few existing comammox amoA primer combinations have both high specificity and coverage and that the choice of these high-specificity and high-coverage primer pairs substantially impacts the accurate detection, quantification, and community description of comammox bacteria. We, therefore, recommend using the CA377F/C576R, CB377F/C576R, and CA-CB377F/C576R primer pairs.IMPORTANCEBacteria that can fully convert ammonia via nitrite to nitrate, the complete ammonia oxidizers (comammox), were recently discovered and are found in many natural and engineered environments. PCR-based tools to study their abundance and diversity were rapidly developed, resulting in a plethora of primers available, many of which are widely used. The presence of comammox bacteria in an environment can, however, only be correctly determined if the used primers detect all members of this group while not detecting any other guilds. This study assesses the coverage and specificity of existing primers targeting comammox bacteria using both computational and standard molecular techniques, revealing large differences in their performance. The uniform usage of well-performing primers across studies could aid in generating comparable and generalizable data to better understand the importance of comammox bacteria in the environment.

A single amplified genome catalog reveals the dynamics of mobilome and resistome in the human microbiome

BACKGROUND

The increase in metagenome-assembled genomes (MAGs) has advanced our understanding of the functional characterization and taxonomic assignment within the human microbiome. However, MAGs, as population consensus genomes, often aggregate heterogeneity among species and strains, thereby obfuscating the precise relationships between microbial hosts and mobile genetic elements (MGEs). In contrast, single amplified genomes (SAGs) derived via single-cell genome sequencing can capture individual genomic content, including MGEs.

RESULTS

We introduce the first substantial SAG dataset (bbsag20) from the human oral and gut microbiome, comprising 17,202 SAGs above medium-quality without co-assembly. This collection unveils a diversity of bacterial lineages across 312 oral and 647 gut species, demonstrating different taxonomic compositions from MAGs. Moreover, the SAGs showed cellular-level evidence of the translocation of oral bacteria to the gut. We also identified broad-host-range MGEs harboring antibiotic resistance genes (ARGs), which were not detected in the MAGs.

CONCLUSIONS

The difference in taxonomic composition between SAGs and MAGs indicates that combining both methods would be effective in expanding the genome catalog. By connecting mobilomes and resistomes in individual samples, SAGs could meticulously chart a dynamic network of ARGs on MGEs, pinpointing potential ARG reservoirs and their spreading patterns in the microbial community. Video Abstract.

Plant growth promoting endophyte modulates soil ecological characteristics during the enhancement process of cadmium phytoremediation

Endophyte assisted phytoremediation of cadmium (Cd) contaminated soil represents a promising strategy. However, the precise soil ecological regulatory mechanisms by which endophyte enhance the Cd phytoextraction remain unclear. Here, we employed the plant growth promoting endophyte (PGPE) Pseudomonas sp. E3, which has been validated to effectively enhance Cd extraction in Solanum nigrum L., to investigate its regulatory mechanism on soil ecology. The results demonstrated that while PGPE inoculation resulted in minimal alterations to the physicochemical properties of the bulk soil, it led to a notable increase in acid phosphatase activity by 17.86% and urease activity by 24.85% in the rhizosphere soil. This, in turn, significantly raised the available nitrogen and phosphorus contents by 16.93% and 21.27%, respectively, in the rhizosphere soil. Additionally, PGPE inoculation effectively replenished the bioavailable fractions of Fe and Cd, which had been depleted due to root uptake. Importantly, the inoculation specifically augmented the abundance of biomarkers p_Patescibacteria, f_Saccharimonadales, and g_Saccharimonadales in the rhizosphere soil. These biomarkers exhibited a significant positive correlation with the available nutrient and metal element contents. Moreover, the co-occurrence network analysis demonstrated that the inoculation resulted in a simplified bacterial community network, which may have facilitated community synergism by displacing bacteria with a negative association. This regulation appears to occur independently of PGPE colonization. Overall, our findings suggested that PGPE also exerts a regulatory influence on soil ecological features, significantly aiding hyperaccumulators in nutrient acquisition and heavy metal accumulation.

Taxometer: Improving taxonomic classification of metagenomics contigs

For taxonomy based classification of metagenomics assembled contigs, current methods use sequence similarity to identify their most likely taxonomy. However, in the related field of metagenomic binning, contigs are routinely clustered using information from both the contig sequences and their abundance. We introduce Taxometer, a neural network based method that improves the annotations and estimates the quality of any taxonomic classifier using contig abundance profiles and tetra-nucleotide frequencies. We apply Taxometer to five short-read CAMI2 datasets and find that it increases the average share of correct species-level contig annotations of the MMSeqs2 tool from 66.6% to 86.2%. Additionally, it reduce the share of wrong species-level annotations in the CAMI2 Rhizosphere dataset by an average of two-fold for Metabuli, Centrifuge, and Kraken2. Futhermore, we use Taxometer for benchmarking taxonomic classifiers on two complex long-read metagenomics data sets where ground truth is not known. Taxometer is available as open-source software and can enhance any taxonomic annotation of metagenomic contigs.

Potential applications of microbial genomics in nuclear non-proliferation

As nuclear technology evolves in response to increased demand for diversification and decarbonization of the energy sector, new and innovative approaches are needed to effectively identify and deter the proliferation of nuclear arms, while ensuring safe development of global nuclear energy resources. Preventing the use of nuclear material and technology for unsanctioned development of nuclear weapons has been a long-standing challenge for the International Atomic Energy Agency and signatories of the Treaty on the Non-Proliferation of Nuclear Weapons. Environmental swipe sampling has proven to be an effective technique for characterizing clandestine proliferation activities within and around known locations of nuclear facilities and sites. However, limited tools and techniques exist for detecting nuclear proliferation in unknown locations beyond the boundaries of declared nuclear fuel cycle facilities, representing a critical gap in non-proliferation safeguards. Microbiomes, defined as "characteristic communities of microorganisms" found in specific habitats with distinct physical and chemical properties, can provide valuable information about the conditions and activities occurring in the surrounding environment. Microorganisms are known to inhabit radionuclide-contaminated sites, spent nuclear fuel storage pools, and cooling systems of water-cooled nuclear reactors, where they can cause radionuclide migration and corrosion of critical structures. Microbial transformation of radionuclides is a well-established process that has been documented in numerous field and laboratory studies. These studies helped to identify key bacterial taxa and microbially-mediated processes that directly and indirectly control the transformation, mobility, and fate of radionuclides in the environment. Expanding on this work, other studies have used microbial genomics integrated with machine learning models to successfully monitor and predict the occurrence of heavy metals, radionuclides, and other process wastes in the environment, indicating the potential role of nuclear activities in shaping microbial community structure and function. Results of this previous body of work suggest fundamental geochemical-microbial interactions occurring at nuclear fuel cycle facilities could give rise to microbiomes that are characteristic of nuclear activities. These microbiomes could provide valuable information for monitoring nuclear fuel cycle facilities, planning environmental sampling campaigns, and developing biosensor technology for the detection of undisclosed fuel cycle activities and proliferation concerns.

Diverse non-canonical electron bifurcating [FeFe]-hydrogenases of separate evolutionary origins in Hydrogenedentota

Hydrogenedentota, a globally distributed bacterial phylum-level lineage, is poorly understood. Here, we established a comprehensive genomic catalog of Hydrogenedentota, including a total of seven clades (or families) with 179 genomes, and explored the metabolic potential and evolutionary history of these organisms. We show that a single genome, especially those belonging to Clade 6, often encodes multiple hydrogenases with genomes in Clade 2, which rarely encode hydrogenases being the exception. Notably, most members of Hydrogenedentota contain a group A3 [FeFe]-hydrogenase (BfuABC) with a non-canonical electron bifurcation mechanism, in addition to substrate-level phosphorylation and electron transport-linked phosphorylation pathways, in energy conservation. Furthermore, we show that BfuABC from Hydrogenedentota fall into five sub-types. Phylogenetic analysis reveals five independent routes for the evolution of BfuABC homologs in Hydrogenedentota. We speculate that the five sub-types of BfuABC might be acquired from Bacillota (synonym Firmicutes) through separate horizontal gene transfer events. These data shed light on the diversity and evolution of bifurcating [FeFe]-hydrogenases and provide insight into the strategy of Hydrogenedentota to adapt to survival in various habitats.

IMPORTANCE

The phylum Hydrogenedentota is widely distributed in various environments. However, their physiology, ecology, and evolutionary history remain unknown, primarily due to the limited availability of the genomes and the lack of cultured representatives of the phylum. Our results have increased the knowledge of the genetic and metabolic diversity of these organisms and shed light on their diverse energy conservation strategies, especially those involving electron bifurcation with a non-canonical mechanism, which are likely responsible for their wide distribution. Besides, the organization and phylogenetic relationships of gene clusters coding for BfuABC in Hydrogenedentota provide valuable clues to the evolutionary history of group A3 electron bifurcating [FeFe]-hydrogenases.

Advancing Source Tracking: Systematic Review and Source-Specific Genome Database Curation of Fecally Shed Prokaryotes

Advancements within fecal source tracking (FST) studies are complicated by a lack of knowledge regarding the genetic content and distribution of fecally shed microbial populations. To address this gap, we performed a systematic literature review and curated a large collection of genomes (n = 26,018) representing fecally shed prokaryotic species across broad and narrow source categories commonly implicated in FST studies of recreational waters (i.e., cats, dogs, cows, seagulls, chickens, pigs, birds, ruminants, human feces, and wastewater). We find that across these sources the total number of prokaryotic genomes recovered from materials meeting our initial inclusion criteria varied substantially across fecal sources: from none in seagulls to 9,085 in pigs. We examined genome sequences recovered from these metagenomic and isolation-based studies extensively via comparative genomic approaches to characterize trends across source categories and produce a finalized genome database for each source category which is available online (n = 12,730). On average, 81% of the genomes representing species-level populations occur only within a single source. Using fecal slurries to test the performance of each source database, we report read capture rates that vary with fecal source alpha diversity and database size. We expect this resource to be useful to FST-related objectives, One Health research, and sanitation efforts globally.

Unravelling the secrets of soil microbiome and climate change for sustainable agroecosystems

The soil microbiota exhibits an important function in the ecosystem, and its response to climate change is of paramount importance for sustainable agroecosystems. The macronutrients, micronutrients, and additional constituents vital for the growth of plants are cycled biogeochemically under the regulation of the soil microbiome. Identifying and forecasting the effect of climate change on soil microbiomes and ecosystem services is the need of the hour to address one of the biggest global challenges of the present time. The impact of climate change on the structure and function of the soil microbiota is a major concern, explained by one or more sustainability factors around resilience, reluctance, and rework. However, the past research has revealed that microbial interventions have the potential to regenerate soils and improve crop resilience to climate change factors. The methods used therein include using soil microbes' innate capacity for carbon sequestration, rhizomediation, bio-fertilization, enzyme-mediated breakdown, phyto-stimulation, biocontrol of plant pathogens, antibiosis, inducing the antioxidative defense pathways, induced systemic resistance response (ISR), and releasing volatile organic compounds (VOCs) in the host plant. Microbial phytohormones have a major role in altering root shape in response to exposure to drought, salt, severe temperatures, and heavy metal toxicity and also have an impact on the metabolism of endogenous growth regulators in plant tissue. However, shelf life due to the short lifespan and storage time of microbial formulations is still a major challenge, and efforts should be made to evaluate their effectiveness in crop growth based on climate change. This review focuses on the influence of climate change on soil physico-chemical status, climate change adaptation by the soil microbiome, and its future implications.

GSearch: ultra-fast and scalable genome search by combining K-mer hashing with hierarchical navigable small world graphs

Genome search and/or classification typically involves finding the best-match database (reference) genomes and has become increasingly challenging due to the growing number of available database genomes and the fact that traditional methods do not scale well with large databases. By combining k-mer hashing-based probabilistic data structures (i.e. ProbMinHash, SuperMinHash, Densified MinHash and SetSketch) to estimate genomic distance, with a graph based nearest neighbor search algorithm (Hierarchical Navigable Small World Graphs, or HNSW), we created a new data structure and developed an associated computer program, GSearch, that is orders of magnitude faster than alternative tools while maintaining high accuracy and low memory usage. For example, GSearch can search 8000 query genomes against all available microbial or viral genomes for their best matches (n = ∼318 000 or ∼3 000 000, respectively) within a few minutes on a personal laptop, using ∼6 GB of memory (2.5 GB via SetSketch). Notably, GSearch has an O(log(N)) time complexity and will scale well with billions of genomes based on a database splitting strategy. Further, GSearch implements a three-step search strategy depending on the degree of novelty of the query genomes to maximize specificity and sensitivity. Therefore, GSearch solves a major bottleneck of microbiome studies that require genome search and/or classification.

Annotation-free prediction of microbial dioxygen utilization

Aerobes require dioxygen (O2) to grow; anaerobes do not. However, nearly all microbes-aerobes, anaerobes, and facultative organisms alike-express enzymes whose substrates include O2, if only for detoxification. This presents a challenge when trying to assess which organisms are aerobic from genomic data alone. This challenge can be overcome by noting that O2 utilization has wide-ranging effects on microbes: aerobes typically have larger genomes encoding distinctive O2-utilizing enzymes, for example. These effects permit high-quality prediction of O2 utilization from annotated genome sequences, with several models displaying ≈80% accuracy on a ternary classification task for which blind guessing is only 33% accurate. Since genome annotation is compute-intensive and relies on many assumptions, we asked if annotation-free methods also perform well. We discovered that simple and efficient models based entirely on genomic sequence content-e.g., triplets of amino acids-perform as well as intensive annotation-based classifiers, enabling rapid processing of genomes. We further show that amino acid trimers are useful because they encode information about protein composition and phylogeny. To showcase the utility of rapid prediction, we estimated the prevalence of aerobes and anaerobes in diverse natural environments cataloged in the Earth Microbiome Project. Focusing on a well-studied O2 gradient in the Black Sea, we found quantitative correspondence between local chemistry (O2:sulfide concentration ratio) and the composition of microbial communities. We, therefore, suggest that statistical methods like ours might be used to estimate, or "sense," pivotal features of the chemical environment using DNA sequencing data.IMPORTANCEWe now have access to sequence data from a wide variety of natural environments. These data document a bewildering diversity of microbes, many known only from their genomes. Physiology-an organism's capacity to engage metabolically with its environment-may provide a more useful lens than taxonomy for understanding microbial communities. As an example of this broader principle, we developed algorithms that accurately predict microbial dioxygen utilization directly from genome sequences without annotating genes, e.g., by considering only the amino acids in protein sequences. Annotation-free algorithms enable rapid characterization of natural samples, highlighting quantitative correspondence between sequences and local O2 levels in a data set from the Black Sea. This example suggests that DNA sequencing might be repurposed as a multi-pronged chemical sensor, estimating concentrations of O2 and other key facets of complex natural settings.

Acidic proteomes are linked to microbial alkaline preference in African lakes

Microbial amino acid composition (AA) reflects adaptive strategies of cellular and molecular regulations such as a high proportion of acidic AAs, including glutamic and aspartic acids in alkaliphiles. It remains understudied how microbial AA content is linked to their pH adaptation especially in natural environments. Here we examined prokaryotic communities and their AA composition of genes with metagenomics for 39 water and sediments of East African lakes along a gradient of pH spanning from 7.2 to 10.1. We found that Shannon diversity declined with the increasing pH and that species abundance were either positively or negatively associated with pH, indicating their distinct habitat preference in lakes. Microbial communities showed higher acidic proteomes in alkaline than neutral lakes. Species acidic proteomes were also positively correlated with their pH preference, which was consistent across major bacterial lineages. These results suggest selective pressure associated with high pH likely shape microbial amino acid composition both at the species and community levels. Comparative genome analyses further revealed that alkaliphilic microbes contained more functional genes with higher acidic AAs when compared to those in neutral conditions. These traits included genes encoding diverse classes of cation transmembrane transporters, antiporters, and compatible solute transporters, which are involved in cytoplasmic pH homeostasis and osmotic stress defense under high pH conditions. Our results provide the field evidence for the strong relationship between prokaryotic AA composition and their habitat preference and highlight amino acid optimization as strategies for environmental adaptation.

SeqCode: A Nomenclatural Code for Prokaryotes

SeqCode is a nomenclatural code for naming prokaryotes based on genetic information. With the majority of prokaryotes being inaccessible as pure cultures, they are not eligible for naming under the International Code of Nomenclature of Prokaryotes. To address this challenge, a new concept that is SeqCode, which assign names to prokaryotes on the basis of genome sequence, has been announced in 2022. The valid publication of names for prokaryotes based on isolated genome, metagenome-assembled genomes, or single-amplified genome sequences. It operates through a registration portal, SeqCode Registry, where metadata is linked to names and nomenclatural types. This code provides a framework for reproducible nomenclature for all prokaryotes, either culturable or not and facilitates communication across all microbiological disciplines. Additionally, the SeqCode includes provisions for updating and revising names as new data becomes available. By providing a standardized system for naming and classifying these microorganisms based on their genetic information, the SeqCode will facilitate the discovery, understanding and comparison of these microorganisms, helping us to understand their role in the environment and how they contribute to the functioning of the Earth.

Atacama desert is a source of new Micromonospora strains: description of Micromonospora sicca sp. nov

Several strains were isolated from subsurface soil of the Atacama Desert and were previously assigned to the Micromonospora genus. A polyphasic study was designed to determine the taxonomic affiliation of isolates 4G51T, 4G53, and 4G57. All the strains showed chemotaxonomic properties in line with their classification in the genus Micromonospora, including meso-diaminopimelic acid in the cell wall peptidoglycan, MK-9(H4) as major respiratory quinone, iso-C15:0 and iso-C16:0 as major fatty acids and diphosphatidylglycerol, phosphatidylethanolamine and phosphatidylinositol as major polar lipids. The 16S rRNA gene sequences of strains 4G51T, 4G53, and 4G57 showed the highest similarity (97.9 %) with the type strain of Micromonospora costi CS1-12T, forming an independent branch in the phylogenetic gene tree. Their independent position was confirmed with genome phylogenies, being most closely related to the type strain of Micromonospora kangleipakensis. Digital DNA-DNA hybridization and average nucleotide identity analyses between the isolates and their closest phylogenomic neighbours confirmed that they should be assigned to a new species within the genus Micromonospora for which the name Micromonospora sicca sp. nov. (4G51T=PCM 3031T=LMG 30756T) is proposed.

Soil keystone viruses are regulators of ecosystem multifunctionality

Ecosystem multifunctionality reflects the capacity of ecosystems to simultaneously maintain multiple functions which are essential bases for human sustainable development. Whereas viruses are a major component of the soil microbiome that drive ecosystem functions across biomes, the relationships between soil viral diversity and ecosystem multifunctionality remain under-studied. To address this critical knowledge gap, we employed a combination of amplicon and metagenomic sequencing to assess prokaryotic, fungal and viral diversity, and to link viruses to putative hosts. We described the features of viruses and their potential hosts in 154 soil samples from 29 farmlands and 25 forests distributed across China. Although 4,460 and 5,207 viral populations (vOTUs) were found in the farmlands and forests respectively, the diversity of specific vOTUs rather than overall soil viral diversity was positively correlated with ecosystem multifunctionality in both ecosystem types. Furthermore, the diversity of these keystone vOTUs, despite being 10-100 times lower than prokaryotic or fungal diversity, was a better predictor of ecosystem multifunctionality and more strongly associated with the relative abundances of prokaryotic genes related to soil nutrient cycling. Gemmatimonadota and Actinobacteria dominated the host community of soil keystone viruses in the farmlands and forests respectively, but were either absent or showed a significantly lower relative abundance in that of soil non-keystone viruses. These findings provide novel insights into the regulators of ecosystem multifunctionality and have important implications for the management of ecosystem functioning.

Global marine microbial diversity and its potential in bioprospecting

The past two decades has witnessed a remarkable increase in the number of microbial genomes retrieved from marine systems1,2. However, it has remained challenging to translate this marine genomic diversity into biotechnological and biomedical applications3,4. Here we recovered 43,191 bacterial and archaeal genomes from publicly available marine metagenomes, encompassing a wide range of diversity with 138 distinct phyla, redefining the upper limit of marine bacterial genome size and revealing complex trade-offs between the occurrence of CRISPR-Cas systems and antibiotic resistance genes. In silico bioprospecting of these marine genomes led to the discovery of a novel CRISPR-Cas9 system, ten antimicrobial peptides, and three enzymes that degrade polyethylene terephthalate. In vitro experiments confirmed their effectiveness and efficacy. This work provides evidence that global-scale sequencing initiatives advance our understanding of how microbial diversity has evolved in the oceans and is maintained, and demonstrates how such initiatives can be sustainably exploited to advance biotechnology and biomedicine.

Metagenomic clustering links specific metabolic functions to globally relevant ecosystems

Metagenomic sequencing has advanced our understanding of biogeochemical processes by providing an unprecedented view into the microbial composition of different ecosystems. While the amount of metagenomic data has grown rapidly, simple-to-use methods to analyze and compare across studies have lagged behind. Thus, tools expressing the metabolic traits of a community are needed to broaden the utility of existing data. Gene abundance profiles are a relatively low-dimensional embedding of a metagenome's functional potential and are, thus, tractable for comparison across many samples. Here, we compare the abundance of KEGG Ortholog Groups (KOs) from 6,539 metagenomes from the Joint Genome Institute's Integrated Microbial Genomes and Metagenomes (JGI IMG/M) database. We find that samples cluster into terrestrial, aquatic, and anaerobic ecosystems with marker KOs reflecting adaptations to these environments. For instance, functional clusters were differentiated by the metabolism of antibiotics, photosynthesis, methanogenesis, and surprisingly GC content. Using this functional gene approach, we reveal the broad-scale patterns shaping microbial communities and demonstrate the utility of ortholog abundance profiles for representing a rapidly expanding body of metagenomic data.

IMPORTANCE

Metagenomics, or the sequencing of DNA from complex microbiomes, provides a view into the microbial composition of different environments. Metagenome databases were created to compile sequencing data across studies, but it remains challenging to compare and gain insight from these large data sets. Consequently, there is a need to develop accessible approaches to extract knowledge across metagenomes. The abundance of different orthologs (i.e., genes that perform a similar function across species) provides a simplified representation of a metagenome's metabolic potential that can easily be compared with others. In this study, we cluster the ortholog abundance profiles of thousands of metagenomes from diverse environments and uncover the traits that distinguish them. This work provides a simple to use framework for functional comparison and advances our understanding of how the environment shapes microbial communities.

Genomic characterization of the bacterial phylum Candidatus Effluviviacota, a cosmopolitan member of the global seep microbiome

The microbial communities of marine seep sediments contain unexplored physiological and phylogenetic diversity. Here, we examined 30 bacterial metagenome-assembled genomes (MAGs) from cold seeps in the South China Sea, the Indian Ocean, the Scotian Basin, and the Gulf of Mexico, as well as from deep-sea hydrothermal sediments in the Guaymas Basin, Gulf of California. Phylogenetic analyses of these MAGs indicate that they form a distinct phylum-level bacterial lineage, which we propose as a new phylum, Candidatus Effluviviacota, in reference to its preferential occurrence at diverse seep areas. Based on tightly clustered high-quality MAGs, we propose two new genus-level candidatus taxa, Candidatus Effluvivivax and Candidatus Effluvibates. Genomic content analyses indicate that Candidatus Effluviviacota are chemoheterotrophs that harbor the Embden-Meyerhof-Parnas glycolysis pathway. They gain energy by fermenting organic substrates. Additionally, they display potential capabilities for the degradation of cellulose, hemicellulose, starch, xylan, and various peptides. Extracellular anaerobic respiration appears to rely on metals as electron acceptors, with electron transfer primarily mediated by multiheme cytochromes and by a flavin-based extracellular electron transfer (EET) mechanism that involves NADH-quinone oxidoreductase-demethylmenaquinone-synthesizing enzymes, uncharacterized membrane proteins, and flavin-binding proteins, also known as the NUO-DMK-EET-FMN complex. The heterogeneity within the Ca. Effluviviacota phylum suggests varying roles in energy metabolism among different genera. While NUO-DMK-EET-FMN electron transfer has been reported predominantly in Gram-positive bacteria, it is now identified in Ca. Effluviviacota as well. We detected the presence of genes associated with bacterial microcompartments in Ca. Effluviviacota, which can promote specific metabolic processes and protect the cytosol from toxic intermediates.

IMPORTANCE

The newly discovered bacterial phylum Candidatus Effluviviacota is widespread across diverse seepage ecosystems, marine environments, and freshwater environments, with a notable preference for cold seeps. While maintaining an average abundance of approximately 1% in the global gene catalog of cold seep habitats, it has not hitherto been characterized. The metabolic versatility of Ca. Effluviviacota in anaerobic carbon, hydrogen, and metal cycling aligns with its prevalence in anoxic niches, with a preference for cold seep environments. Variations in metabolic potential between Ca. Effluvivivax and Ca. Effluvibates may contribute to shaping their respective habitat distributions.

MICROPHERRET: MICRObial PHEnotypic tRait ClassifieR using Machine lEarning Techniques

BACKGROUND

In recent years, there has been a rapid increase in the number of microbial genomes reconstructed through shotgun sequencing, and obtained by newly developed approaches including metagenomic binning and single-cell sequencing. However, our ability to functionally characterize these genomes by experimental assays is orders of magnitude less efficient. Consequently, there is a pressing need for the development of swift and automated strategies for the functional classification of microbial genomes.

RESULTS

The present work leverages a suite of supervised machine learning algorithms to establish a range of 86 metabolic and other ecological functions, such as methanotrophy and plastic degradation, starting from widely obtainable microbial genome annotations. Tests performed on independent datasets demonstrated robust performance across complete, fragmented, and incomplete genomes above a 70% completeness level for most of the considered functions. Application of the algorithms to the Biogas Microbiome database yielded predictions broadly consistent with current biological knowledge and correctly detecting functionally-related nuances of archaeal genomes. Finally, a case study focused on acetoclastic methanogenesis demonstrated how the developed machine learning models can be refined or expanded with models describing novel functions of interest.

CONCLUSIONS

The resulting tool, MICROPHERRET, incorporates a total of 86 models, one for each tested functional class, and can be applied to high-quality microbial genomes as well as to low-quality genomes derived from metagenomics and single-cell sequencing. MICROPHERRET can thus aid in understanding the functional role of newly generated genomes within their micro-ecological context.

From soil to sequence: filling the critical gap in genome-resolved metagenomics is essential to the future of soil microbial ecology

Soil microbiomes are heterogeneous, complex microbial communities. Metagenomic analysis is generating vast amounts of data, creating immense challenges in sequence assembly and analysis. Although advances in technology have resulted in the ability to easily collect large amounts of sequence data, soil samples containing thousands of unique taxa are often poorly characterized. These challenges reduce the usefulness of genome-resolved metagenomic (GRM) analysis seen in other fields of microbiology, such as the creation of high quality metagenomic assembled genomes and the adoption of genome scale modeling approaches. The absence of these resources restricts the scale of future research, limiting hypothesis generation and the predictive modeling of microbial communities. Creating publicly available databases of soil MAGs, similar to databases produced for other microbiomes, has the potential to transform scientific insights about soil microbiomes without requiring the computational resources and domain expertise for assembly and binning.

The assembly and ecological roles of biofilms attached to plastic debris of Ashmore reef

Plastic pollution in the ocean is a global environmental hazard aggravated by poor management of plastic waste and growth of annual plastic consumption. Microbial communities colonizing the plastic's surface, the plastisphere, has gained global interest resulting in numerous efforts to characterize the plastisphere. However, there are insufficient studies deciphering the underlying metabolic processes governing the function of the plastisphere and the plastic they reside upon. Here, we collected plastic and seawater samples from Ashmore Reef in Australia to examine the planktonic microbes and plastic associated biofilm (PAB) to investigate the ecological impact, pathogenic potential, and plastic degradation capabilities of PAB in Ashmore Reef, as well as the role and impact of bacteriophages on PAB. Using high-throughput metagenomic sequencing, we demonstrated distinct microbial communities between seawater and PAB. Similar numbers of pathogenic bacteria were found in both sample types, yet plastic and seawater select for different pathogen populations. Virulence Factor analysis further illustrated stronger pathogenic potential in PAB, highlighting the pathogenicity of environmental PAB. Furthermore, functional analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways revealed xenobiotic degradation and fatty acid degradation to be enriched in PABs. In addition, construction of metagenome-assembled genomes (MAG) and functional analysis further demonstrated the presence of a complete Polyethylene (PE) degradation pathway in multiple Proteobacteria MAGs, especially in Rhodobacteriaceae sp. Additionally, we identified viral population presence in PAB, revealing the key role of bacteriophages in shaping these communities within the PAB. Our result provides a comprehensive overview of the various ecological processes shaping microbial community on marine plastic debris.

A dual-scale fused hypergraph convolution-based hyperedge prediction model for predicting missing reactions in genome-scale metabolic networks

Genome-scale metabolic models (GEMs) are powerful tools for predicting cellular metabolic and physiological states. However, there are still missing reactions in GEMs due to incomplete knowledge. Recent gaps filling methods suggest directly predicting missing responses without relying on phenotypic data. However, they do not differentiate between substrates and products when constructing the prediction models, which affects the predictive performance of the models. In this paper, we propose a hyperedge prediction model that distinguishes substrates and products based on dual-scale fused hypergraph convolution, DSHCNet, for inferring the missing reactions to effectively fill gaps in the GEM. First, we model each hyperedge as a heterogeneous complete graph and then decompose it into three subgraphs at both homogeneous and heterogeneous scales. Then we design two graph convolution-based models to, respectively, extract features of the vertices in two scales, which are then fused via the attention mechanism. Finally, the features of all vertices are further pooled to generate the representative feature of the hyperedge. The strategy of graph decomposition in DSHCNet enables the vertices to engage in message passing independently at both scales, thereby enhancing the capability of information propagation and making the obtained product and substrate features more distinguishable. The experimental results show that the average recovery rate of missing reactions obtained by DSHCNet is at least 11.7% higher than that of the state-of-the-art methods, and that the gap-filled GEMs based on our DSHCNet model achieve the best prediction performance, demonstrating the superiority of our method.

SonicParanoid2: fast, accurate, and comprehensive orthology inference with machine learning and language models

Accurate inference of orthologous genes constitutes a prerequisite for comparative and evolutionary genomics. SonicParanoid is one of the fastest tools for orthology inference; however, its scalability and accuracy have been hampered by time-consuming all-versus-all alignments and the existence of proteins with complex domain architectures. Here, we present a substantial update of SonicParanoid, where a gradient boosting predictor halves the execution time and a language model doubles the recall. Application to empirical large-scale and standardized benchmark datasets shows that SonicParanoid2 is much faster than comparable methods and also the most accurate. SonicParanoid2 is available at https://gitlab.com/salvo981/sonicparanoid2 and https://zenodo.org/doi/10.5281/zenodo.11371108 .

Large-scale investigation of species-specific orphan genes in the human gut microbiome elucidates their evolutionary origins

Species-specific genes, also known as orphans, are ubiquitous across life's domains. In prokaryotes, species-specific orphan genes (SSOGs) are mostly thought to originate in external elements such as viruses followed by horizontal gene transfer, whereas the scenario of native origination, through rapid divergence or de novo, is mostly dismissed. However, quantitative evidence supporting either scenario is lacking. Here, we systematically analyzed genomes from 4644 human gut microbiome species and identified more than 600,000 unique SSOGs, representing an average of 2.6% of a given species' pangenome. These sequences are mostly rare within each species yet show signs of purifying selection. Overall, SSOGs use optimal codons less frequently, and their proteins are more disordered than those of conserved genes (i.e., non-SSOGs). Importantly, across species, the GC content of SSOGs closely matches that of conserved ones. In contrast, the ∼5% of SSOGs that share similarity to known viral sequences have distinct characteristics, including lower GC content. Thus, SSOGs with similarity to viruses differ from the remaining SSOGs, contrasting an external origination scenario for most of them. By examining the orthologous genomic region in closely related species, we show that a small subset of SSOGs likely evolved natively de novo and find that these genes also differ in their properties from the remaining SSOGs. Our results challenge the notion that external elements are the dominant source of prokaryotic genetic novelty and will enable future studies into the biological role and relevance of species-specific genes in the human gut.

Distinct microbial nitrogen cycling processes in the deepest part of the ocean

The Mariana Trench (MT) is the deepest part of the ocean on Earth. Previous studies have described the microbial community structures and functional potential in the seawater and surface sediment of MT. Still, the metabolic features and adaptation strategies of the microorganisms involved in nitrogen cycling processes are poorly understood. In this study, comparative metagenomic approaches were used to study microbial nitrogen cycling in three MT habitats, including hadal seawater [9,600-10,500 m below sea level (mbsl)], surface sediments [0-46 cm below seafloor (cmbsf) at a water depth between 7,143 and 8,638 mbsl], and deep sediments (200-306 cmbsf at a water depth of 8,300 mbsl). We identified five new nitrite-oxidizing bacteria (NOB) lineages that had adapted to the oligotrophic MT slope sediment, via their CO2 fixation capability through the reductive tricarboxylic acid (rTCA) or Calvin-Benson-Bassham (CBB) cycle; an anammox bacterium might perform aerobic respiration and utilize sedimentary carbohydrates for energy generation because it contains genes encoding type A cytochrome c oxidase and complete glycolysis pathway. In seawater, abundant alkane-oxidizing Ketobacter species can fix inert N2 released from other denitrifying and/or anammox bacteria. This study further expands our understanding of microbial life in the largely unexplored deepest part of the ocean.

IMPORTANCE

The metabolic features and adaptation strategies of the nitrogen cycling microorganisms in the deepest part of the ocean are largely unknown. This study revealed that anammox bacteria might perform aerobic respiration in response to nutrient limitation or O2 fluctuations in the Mariana Trench sediments. Meanwhile, an abundant alkane-oxidizing Ketobacter species could fix N2 in hadal seawater. This study provides new insights into the roles of hadal microorganisms in global nitrogen biogeochemical cycles. It substantially expands our understanding of the microbial life in the largely unexplored deepest part of the ocean.

Distributions, interactions, and dynamics of prokaryotes and phages in a hybrid biological wastewater treatment system

BACKGROUND

Understanding the interactions and dynamics of microbiotas within biological wastewater treatment systems is essential for ensuring their stability and long-term sustainability. In this study, we developed a systematic framework employing multi-omics and Hi-C sequencing to extensively investigate prokaryotic and phage communities within a hybrid biofilm and activated sludge system.

RESULTS

We uncovered distinct distribution patterns, metabolic capabilities, and activities of functional prokaryotes through the analysis of 454 reconstructed prokaryotic genomes. Additionally, we reconstructed a phage catalog comprising 18,645 viral operational taxonomic units (vOTUs) with high length and contiguity using hybrid assembly, and a distinct distribution of phages was depicted between activated sludge (AS) and biofilm. Importantly, 1340 host-phage pairs were established using Hi-C and conventional in silico methods, unveiling the host-determined phage prevalence. The majority of predicted hosts were found to be involved in various crucial metabolic processes, highlighting the potential vital roles of phages in influencing substance metabolism within this system. Moreover, auxiliary metabolic genes (AMGs) related to various categories (e.g., carbohydrate degradation, sulfur metabolism, transporter) were predicted. Subsequent activity analysis emphasized their potential ability to mediate host metabolism during infection. We also profiled the temporal dynamics of phages and their associated hosts using 13-month time-series metagenomic data, further demonstrating their tight interactions. Notably, we observed lineage-specific infection patterns, such as potentially host abundance- or phage/host ratio-driven phage population changes.

CONCLUSIONS

The insights gained from this research contribute to the growing body of knowledge surrounding interactions and dynamics of host-phage and pave the way for further exploration and potential applications in the field of microbial ecology. Video Abstract.

Genomic representativeness and chimerism in large collections of SAGs and MAGs of marine prokaryoplankton

BACKGROUND

Single amplified genomes (SAGs) and metagenome-assembled genomes (MAGs) are the predominant sources of information about the coding potential of uncultured microbial lineages, but their strengths and limitations remain poorly understood. Here, we performed a direct comparison of two previously published collections of thousands of SAGs and MAGs obtained from the same, global environment.

RESULTS

We found that SAGs were less prone to chimerism and more accurately reflected the relative abundance and the pangenome content of microbial lineages inhabiting the epipelagic of the tropical and subtropical ocean, as compared to MAGs. SAGs were also better suited to link genome information with taxa discovered through 16S rRNA amplicon analyses. Meanwhile, MAGs had the advantage of more readily recovering genomes of rare lineages.

CONCLUSIONS

Our analyses revealed the relative strengths and weaknesses of the two most commonly used genome recovery approaches in environmental microbiology. These considerations, as well as the need for better tools for genome quality assessment, should be taken into account when designing studies and interpreting data that involve SAGs or MAGs. Video Abstract.

VirRep: a hybrid language representation learning framework for identifying viruses from human gut metagenomes

Identifying viruses from metagenomes is a common step to explore the virus composition in the human gut. Here, we introduce VirRep, a hybrid language representation learning framework, for identifying viruses from human gut metagenomes. VirRep combines a context-aware encoder and an evolution-aware encoder to improve sequence representation by incorporating k-mer patterns and sequence homologies. Benchmarking on both simulated and real datasets with varying viral proportions demonstrates that VirRep outperforms state-of-the-art methods. When applied to fecal metagenomes from a colorectal cancer cohort, VirRep identifies 39 high-quality viral species associated with the disease, many of which cannot be detected by existing methods.

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 global atlas of soil viruses reveals unexplored biodiversity and potential biogeochemical impacts

Historically neglected by microbial ecologists, soil viruses are now thought to be critical to global biogeochemical cycles. However, our understanding of their global distribution, activities and interactions with the soil microbiome remains limited. Here we present the Global Soil Virus Atlas, a comprehensive dataset compiled from 2,953 previously sequenced soil metagenomes and composed of 616,935 uncultivated viral genomes and 38,508 unique viral operational taxonomic units. Rarefaction curves from the Global Soil Virus Atlas indicate that most soil viral diversity remains unexplored, further underscored by high spatial turnover and low rates of shared viral operational taxonomic units across samples. By examining genes associated with biogeochemical functions, we also demonstrate the viral potential to impact soil carbon and nutrient cycling. This study represents an extensive characterization of soil viral diversity and provides a foundation for developing testable hypotheses regarding the role of the virosphere in the soil microbiome and global biogeochemistry.

Sequencing-based analysis of microbiomes

Microbiomes occupy a range of niches and, in addition to having diverse compositions, they have varied functional roles that have an impact on agriculture, environmental sciences, and human health and disease. The study of microbiomes has been facilitated by recent technological and analytical advances, such as cheaper and higher-throughput DNA and RNA sequencing, improved long-read sequencing and innovative computational analysis methods. These advances are providing a deeper understanding of microbiomes at the genomic, transcriptional and translational level, generating insights into their function and composition at resolutions beyond the species level.

Resistance to freezing conditions of endemic Antarctic polychaetes is enhanced by cryoprotective proteins produced by their microbiome

The microbiome plays a key role in the health of all metazoans. Whether and how the microbiome favors the adaptation processes of organisms to extreme conditions, such as those of Antarctica, which are incompatible with most metazoans, is still unknown. We investigated the microbiome of three endemic and widespread species of Antarctic polychaetes: Leitoscoloplos geminus, Aphelochaeta palmeri, and Aglaophamus trissophyllus. We report here that these invertebrates contain a stable bacterial core dominated by Meiothermus and Anoxybacillus, equipped with a versatile genetic makeup and a unique portfolio of proteins useful for coping with extremely cold conditions as revealed by pangenomic and metaproteomic analyses. The close phylosymbiosis between Meiothermus and Anoxybacillus and these Antarctic polychaetes indicates a connection with their hosts that started in the past to support holobiont adaptation to the Antarctic Ocean. The wide suite of bacterial cryoprotective proteins found in Antarctic polychaetes may be useful for the development of nature-based biotechnological applications.

Persistent activity of aerobic methane-oxidizing bacteria in anoxic lake waters due to metabolic versatility

Lacustrine methane emissions are strongly mitigated by aerobic methane-oxidizing bacteria (MOB) that are typically most active at the oxic-anoxic interface. Although oxygen is required by the MOB for the first step of methane oxidation, their occurrence in anoxic lake waters has raised the possibility that they are capable of oxidizing methane further anaerobically. Here, we investigate the activity and growth of MOB in Lake Zug, a permanently stratified freshwater lake. The rates of anaerobic methane oxidation in the anoxic hypolimnion reached up to 0.2 µM d-1. Single-cell nanoSIMS measurements, together with metagenomic and metatranscriptomic analyses, linked the measured rates to MOB of the order Methylococcales. Interestingly, their methane assimilation activity was similar under hypoxic and anoxic conditions. Our data suggest that these MOB use fermentation-based methanotrophy as well as denitrification under anoxic conditions, thus offering an explanation for their widespread presence in anoxic habitats such as stratified water columns. Thus, the methane sink capacity of anoxic basins may have been underestimated by not accounting for the anaerobic MOB activity.

The vast landscape of carbohydrate fermentation in prokaryotes

Fermentation is a type of metabolism carried out by organisms in environments without oxygen. Despite being studied for over 185 years, the diversity and complexity of this metabolism are just now becoming clear. Our review starts with the definition of fermentation, which has evolved over the years and which we help further refine. We then examine the range of organisms that carry out fermentation and their traits. Over one-fourth of all prokaryotes are fermentative, use more than 40 substrates, and release more than 50 metabolic end products. These insights come from studies analyzing records of thousands of organisms. Next, our review examines the complexity of fermentation at the biochemical level. We map out pathways of glucose fermentation in unprecedented detail, covering over 120 biochemical reactions. We also review recent studies coupling genomics and enzymology to reveal new pathways and enzymes. Our review concludes with practical applications for agriculture, human health, and industry. All these areas depend on fermentation and could be improved through manipulating fermentative microbes and enzymes. We discuss potential approaches for manipulation, including genetic engineering, electrofermentation, probiotics, and enzyme inhibitors. We hope our review underscores the importance of fermentation research and stimulates the next 185 years of study.

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.

Highly accurate classification and discovery of microbial protein-coding gene functions using FunGeneTyper: an extensible deep learning framework

High-throughput DNA sequencing technologies decode tremendous amounts of microbial protein-coding gene sequences. However, accurately assigning protein functions to novel gene sequences remain a challenge. To this end, we developed FunGeneTyper, an extensible framework with two new deep learning models (i.e., FunTrans and FunRep), structured databases, and supporting resources for achieving highly accurate (Accuracy > 0.99, F1-score > 0.97) and fine-grained classification of antibiotic resistance genes (ARGs) and virulence factor genes. Using an experimentally confirmed dataset of ARGs comprising remote homologous sequences as the test set, our framework achieves by-far-the-best performance in the discovery of new ARGs from human gut (F1-score: 0.6948), wastewater (0.6072), and soil (0.5445) microbiomes, beating the state-of-the-art bioinformatics tools and sequence alignment-based (F1-score: 0.0556-0.5065) and domain-based (F1-score: 0.2630-0.5224) annotation approaches. Furthermore, our framework is implemented as a lightweight, privacy-preserving, and plug-and-play neural network module, facilitating its versatility and accessibility to developers and users worldwide. We anticipate widespread utilization of FunGeneTyper (https://github.com/emblab-westlake/FunGeneTyper) for precise classification of protein-coding gene functions and the discovery of numerous valuable enzymes. This advancement will have a significant impact on various fields, including microbiome research, biotechnology, metagenomics, and bioinformatics.

The past, present and future of polymicrobial infection research: Modelling, eavesdropping, terraforming and other stories

Over the last two centuries, great advances have been made in microbiology as a discipline. Much of this progress has come about as a consequence of studying the growth and physiology of individual microbial species in well-defined laboratory media; so-called "axenic growth". However, in the real world, microbes rarely live in such "splendid isolation" (to paraphrase Foster) and more often-than-not, share the niche with a plethora of co-habitants. The resulting interactions between species (and even between kingdoms) are only very poorly understood, both on a theoretical and experimental level. Nevertheless, the last few years have seen significant progress, and in this review, we assess the importance of polymicrobial infections, and show how improved experimental traction is advancing our understanding of these. A particular focus is on developments that are allowing us to capture the key features of polymicrobial infection scenarios, especially as those associated with the human airways (both healthy and diseased).

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.