BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification.

The accurate classification of non-coding RNA (ncRNA) sequences is pivotal for advanced non-coding genome annotation and analysis, a fundamental aspect of genomics that facilitates understanding of ncRNA functions and regulatory mechanisms in various biological processes. While traditional machine learning approaches have been employed for distinguishing ncRNA, these often necessitate extensive feature engineering. Recently, deep learning algorithms have provided advancements in ncRNA classification. This study presents BioDeepFuse, a hybrid deep learning framework integrating convolutional neural networks (CNN) or bidirectional long short-term memory (BiLSTM) networks with handcrafted features for enhanced accuracy. This framework employs a combination of k-mer one-hot, k-mer dictionary, and feature extraction techniques for input representation. Extracted features, when embedded into the deep network, enable optimal utilization of spatial and sequential nuances of ncRNA sequences. Using benchmark datasets and real-world RNA samples from bacterial organisms, we evaluated the performance of BioDeepFuse. Results exhibited high accuracy in ncRNA classification, underscoring the robustness of our tool in addressing complex ncRNA sequence data challenges. The effective melding of CNN or BiLSTM with external features heralds promising directions for future research, particularly in refining ncRNA classifiers and deepening insights into ncRNAs in cellular processes and disease manifestations. In addition to its original application in the context of bacterial organisms, the methodologies and techniques integrated into our framework can potentially render BioDeepFuse effective in various and broader domains.

Viral Communities Contribute More to the Lysis of Antibiotic-Resistant Bacteria than the Transduction of Antibiotic Resistance Genes in Anaerobic Digestion Revealed by Metagenomics.

Ecological role of the viral community on the fate of antibiotic resistance genes (ARGs) (reduction vs proliferation) remains unclear in anaerobic digestion (AD). Metagenomics revealed a dominance of Siphoviridae and Podoviridae among 13,895 identified viral operational taxonomic units (vOTUs) within AD, and only 21 of the vOTUs carried ARGs, which only accounted for 0.57 ± 0.43% of AD antibiotic resistome. Conversely, ARGs locating on plasmids and integrative and conjugative elements accounted for above 61.0%, indicating a substantial potential for conjugation in driving horizontal gene transfer of ARGs within AD. Virus-host prediction based on CRISPR spacer, tRNA, and homology matches indicated that most viruses (80.2%) could not infect across genera. Among 480 high-quality metagenome assembly genomes, 95 carried ARGs and were considered as putative antibiotic-resistant bacteria (pARB). Furthermore, lytic phages of 66 pARBs were identified and devoid of ARGs, and virus/host abundance ratios with an average value of 71.7 indicated extensive viral activity and lysis. The infectivity of lytic phage was also elucidated through laboratory experiments concerning changes of the phage-to-host ratio, pH, and temperature. Although metagenomic evidence for dissemination of ARGs by phage transduction was found, the higher proportion of lytic phages infecting pARBs suggested that the viral community played a greater role in reducing ARB numbers than spreading ARGs in AD.

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.

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

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

Identification of Huge Phages from Wastewater Metagenomes.

Huge phages have genomes larger than 200 kilobases, which are particularly interesting for their genetic inventory and evolution. We screened 165 wastewater metagenomes for the presence of viral sequences. After identifying over 600 potential huge phage genomes, we reduced the dataset using manual curation by excluding viral contigs that did not contain viral protein-coding genes or consisted of concatemers of several small phage genomes. This dataset showed seven fully annotated huge phage genomes. The phages grouped into distinct phylogenetic clades, likely forming new genera and families. A phylogenomic analysis between our huge phages and phages with smaller genomes, i.e., less than 200 kb, supported the hypothesis that huge phages have undergone convergent evolution. The genomes contained typical phage protein-coding genes, sequential gene cassettes for metabolic pathways, and complete inventories of tRNA genes covering all standard and rare amino acids. Our study showed a pipeline for huge phage analyses that may lead to new enzymes for therapeutic or biotechnological applications.

Natural product biosynthetic potential reflects macroevolutionary diversification within a widely distributed bacterial taxon.

IMPORTANCE: This is the most comprehensive study performed thus far on the biosynthetic potential within the Flavobacteriaceae family. Our findings reveal intertwined taxonomic and natural product biosynthesis diversification within the family. We posit that the carbohydrate, peptide, and secondary metabolism triad synergistically shaped the evolution of this keystone bacterial taxon, acting as major forces underpinning the broad host range and opportunistic-to-pathogenic behavior encompassed by species in the family. This study further breaks new ground for future research on select Flavobacteriaceae spp. as reservoirs of novel drug leads.

The AnimalAssociatedMetagenomeDB reveals a bias towards livestock and developed countries and blind spots in functional-potential studies of animal-associated microbiomes.

BACKGROUND: Metagenomic data can shed light on animal-microbiome relationships and the functional potential of these communities. Over the past years, the generation of metagenomics data has increased exponentially, and so has the availability and reusability of data present in public repositories. However, identifying which datasets and associated metadata are available is not straightforward. We created the Animal-Associated Metagenome Metadata Database (AnimalAssociatedMetagenomeDB - AAMDB) to facilitate the identification and reuse of publicly available non-human, animal-associated metagenomic data, and metadata. Further, we used the AAMDB to (i) annotate common and scientific names of the species; (ii) determine the fraction of vertebrates and invertebrates; (iii) study their biogeography; and (iv) specify whether the animals were wild, pets, livestock or used for medical research. RESULTS: We manually selected metagenomes associated with non-human animals from SRA and MG-RAST.  Next, we standardized and curated 51 metadata attributes (e.g., host, compartment, geographic coordinates, and country). The AAMDB version 1.0 contains 10,885 metagenomes associated with 165 different species from 65 different countries. From the collected metagenomes, 51.1% were recovered from animals associated with medical research or grown for human consumption (i.e., mice, rats, cattle, pigs, and poultry). Further, we observed an over-representation of animals collected in temperate regions (89.2%) and a lower representation of samples from the polar zones, with only 11 samples in total. The most common genus among invertebrate animals was Trichocerca (rotifers). CONCLUSION: Our work may guide host species selection in novel animal-associated metagenome research, especially in biodiversity and conservation studies. The data available in our database will allow scientists to perform meta-analyses and test new hypotheses (e.g., host-specificity, strain heterogeneity, and biogeography of animal-associated metagenomes), leveraging existing data. The AAMDB WebApp is a user-friendly interface that is publicly available at https://webapp.ufz.de/aamdb/ .

Improved recovery and annotation of genes in metagenomes through the prediction of fungal introns.

Metagenomics provides a tool to assess the functional potential of environmental and host-associated microbiomes based on the analysis of environmental DNA: assembly, gene prediction and annotation. While gene prediction is straightforward for most bacterial and archaeal taxa, it has limited applicability in the majority of eukaryotic organisms, including fungi that contain introns in gene coding sequences. As a consequence, eukaryotic genes are underrepresented in metagenomics datasets and our understanding of the contribution of fungi and other eukaryotes to microbiome functioning is limited. Here, we developed a machine intelligence-based algorithm that predicts fungal introns in environmental DNA with reasonable precision and used it to improve the annotation of environmental metagenomes. Intron removal increased the number of predicted genes by up to 9.1% and improved the annotation of several others. The proportion of newly predicted genes increased with the share of eukaryotic genes in the metagenome and-within fungal taxa-increased with the number of introns per gene. Our approach provides a tool named SVMmycointron for improved metagenome annotation, especially of microbiomes with a high proportion of eukaryotes. The scripts described in the paper are made publicly available and can be readily utilized by microbiome researchers analysing metagenomics data.

StandEnA: a customizable workflow for standardized annotation and generating a presence-absence matrix of proteins.

Motivation: Several genome annotation tools standardize annotation outputs for comparability. During standardization, these tools do not allow user-friendly customization of annotation databases; limiting their flexibility and applicability in downstream analysis. Results: StandEnA is a user-friendly command-line tool for Linux that facilitates the generation of custom databases by retrieving protein sequences from multiple databases. Directed by a user-defined list of standard names, StandEnA retrieves synonyms to search for corresponding sequences in a set of public databases. Custom databases are used in prokaryotic genome annotation to generate standardized presence-absence matrices and reference files containing standard database identifiers. To showcase StandEnA, we applied it to six metagenome-assembled genomes to analyze three different pathways. Availability and implementation: StandEnA is an open-source software available at https://github.com/mdsufz/StandEnA. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

Corrigendum: The fate of sulfonamide resistance genes and anthropogenic pollution marker intI1 after discharge of wastewater into a pristine river stream.

[This corrects the article DOI: 10.3389/fmicb.2023.1058350.].

Functional Redundancy Secures Resilience of Chain Elongation Communities upon pH Shifts in Closed Bioreactor Ecosystems.

For anaerobic mixed cultures performing microbial chain elongation, it is unclear how pH alterations affect the abundance of key players, microbial interactions, and community functioning in terms of medium-chain carboxylate yields. We explored pH effects on mixed cultures enriched in continuous anaerobic bioreactors representing closed model ecosystems. Gradual pH increase from 5.5 to 6.5 induced dramatic shifts in community composition, whereas product range and yields returned to previous states after transient fluctuations. To understand community responses to pH perturbations over long-term reactor operation, we applied Aitchison PCA clustering, linear mixed-effects models, and random forest classification on 16S rRNA gene amplicon sequencing and process data. Different pH preferences of two key chain elongation species─one Clostridium IV species related to Ruminococcaceae bacterium CPB6 and one Clostridium sensu stricto species related to Clostridium luticellarii─were determined. Network analysis revealed positive correlations of Clostridium IV with lactic acid bacteria, which switched from Olsenella to Lactobacillus along the pH increase, illustrating the plasticity of the food web in chain elongation communities. Despite long-term cultivation in closed systems over the pH shift experiment, the communities retained functional redundancy in fermentation pathways, reflected by the emergence of rare species and concomitant recovery of chain elongation functions.

Recovery of 197 eukaryotic bins reveals major challenges for eukaryote genome reconstruction from terrestrial metagenomes.

As most eukaryotic genomes are yet to be sequenced, the mechanisms underlying their contribution to different ecosystem processes remain untapped. Although approaches to recovering Prokaryotic genomes have become common in genome biology, few studies have tackled the recovery of eukaryotic genomes from metagenomes. This study assessed the reconstruction of microbial eukaryotic genomes using 6000 metagenomes from terrestrial and some transition environments using the EukRep pipeline. Only 215 metagenomic libraries yielded eukaryotic bins. From a total of 447 eukaryotic bins recovered 197 were classified at the phylum level. Streptophytes and fungi were the most represented clades with 83 and 73 bins, respectively. More than 78% of the obtained eukaryotic bins were recovered from samples whose biomes were classified as host-associated, aquatic, and anthropogenic terrestrial. However, only 93 bins were taxonomically assigned at the genus level and 17 bins at the species level. Completeness and contamination estimates were obtained for a total of 193 bins and consisted of 44.64% (σ = 27.41%) and 3.97% (σ = 6.53%), respectively. Micromonas commoda was the most frequent taxon found while Saccharomyces cerevisiae presented the highest completeness, probably because more reference genomes are available. Current measures of completeness are based on the presence of single-copy genes. However, mapping of the contigs from the recovered eukaryotic bins to the chromosomes of the reference genomes showed many gaps, suggesting that completeness measures should also include chromosome coverage. Recovering eukaryotic genomes will benefit significantly from long-read sequencing, development of tools for dealing with repeat-rich genomes, and improved reference genomes databases.

Metagenome-assembled genomes indicate that antimicrobial resistance genes are highly prevalent among urban bacteria and multidrug and glycopeptide resistances are ubiquitous in most taxa.

Introduction: Every year, millions of deaths are associated with the increased spread of antimicrobial resistance genes (ARGs) in bacteria. With the increasing urbanization of the global population, the spread of ARGs in urban bacteria has become a more severe threat to human health. Methods: In this study, we used metagenome-assembled genomes (MAGs) recovered from 1,153 urban metagenomes in multiple urban locations to investigate the fate and occurrence of ARGs in urban bacteria. Additionally, we analyzed the occurrence of these ARGs on plasmids and estimated the virulence of the bacterial species. Results: Our results showed that multidrug and glycopeptide ARGs are ubiquitous among urban bacteria. Additionally, we analyzed the deterministic effects of phylogeny on the spread of these ARGs and found ARG classes that have a non-random distribution within the phylogeny of our recovered MAGs. However, few ARGs were found on plasmids and most of the recovered MAGs contained few virulence factors. Discussion: Our results suggest that the observed non-random spreads of ARGs are not due to the transfer of plasmids and that most of the bacteria observed in the study are unlikely to be virulent. Additional research is needed to evaluate whether the ubiquitous and widespread ARG classes will become entirely prevalent among urban bacteria and how they spread among phylogenetically distinct species.

The fate of sulfonamide resistance genes and anthropogenic pollution marker intI1 after discharge of wastewater into a pristine river stream.

Introduction: Currently there are sparse regulations regarding the discharge of antibiotics from wastewater treatment plants (WWTP) into river systems, making surface waters a latent reservoir for antibiotics and antibiotic resistance genes (ARGs). To better understand factors that influence the fate of ARGs in the environment and to foster surveillance of antibiotic resistance spreading in such habitats, several indicator genes have been proposed, including the integrase gene intI1 and the sulfonamide resistance genes sul1 and sul2. Methods: Here we used quantitative PCR and long-read nanopore sequencing to monitor the abundance of these indicator genes and ARGs present as class 1 integron gene cassettes in a river system from pristine source to WWTP-impacted water. ARG abundance was compared with the dynamics of the microbial communities determined via 16S rRNA gene amplicon sequencing, conventional water parameters and the concentration of sulfamethoxazole (SMX), sulfamethazine (SMZ) and sulfadiazine (SDZ). Results: Our results show that WWTP effluent was the principal source of all three sulfonamides with highest concentrations for SMX (median 8.6 ng/l), and of the indicator genes sul1, sul2 and intI1 with median relative abundance to 16S rRNA gene of 0.55, 0.77 and 0.65%, respectively. Downstream from the WWTP, water quality improved constantly, including lower sulfonamide concentrations, decreasing abundances of sul1 and sul2 and lower numbers and diversity of ARGs in the class 1 integron. The riverine microbial community partially recovered after receiving WWTP effluent, which was consolidated by a microbiome recovery model. Surprisingly, the relative abundance of intI1 increased 3-fold over 13 km of the river stretch, suggesting an internal gene multiplication. Discussion: We found no evidence that low amounts of sulfonamides in the aquatic environment stimulate the maintenance or even spread of corresponding ARGs. Nevertheless, class 1 integrons carrying various ARGs were still present 13 km downstream from the WWTP. Therefore, limiting the release of ARG-harboring microorganisms may be more crucial for restricting the environmental spread of antimicrobial resistance than attenuating ng/L concentrations of antibiotics.

Combining Flow Cytometry and Metagenomics Improves Recovery of Metagenome-Assembled Genomes in a Cell Culture from Activated Sludge.

The recovery of metagenome-assembled genomes is biased towards the most abundant species in a given community. To improve the identification of species, even if only dominant species are recovered, we investigated the integration of flow cytometry cell sorting with bioinformatics tools to recover metagenome-assembled genomes. We used a cell culture of a wastewater microbial community as our model system. Cells were separated based on fluorescence signals via flow cytometry cell sorting into sub-communities: dominant gates, low abundant gates, and outer gates into subsets of the original community. Metagenome sequencing was performed for all groups. The unsorted community was used as control. We recovered a total of 24 metagenome-assembled genomes (MAGs) representing 11 species-level genome operational taxonomic units (gOTUs). In addition, 57 ribosomal operational taxonomic units (rOTUs) affiliated with 29 taxa at species level were reconstructed from metagenomic libraries. Our approach suggests a two-fold increase in the resolution when comparing sorted and unsorted communities. Our results also indicate that species abundance is one determinant of genome recovery from metagenomes as we can recover taxa in the sorted libraries that are not present in the unsorted community. In conclusion, a combination of cell sorting and metagenomics allows the recovery of MAGs undetected without cell sorting.

Exploring the Potential Molecular Mechanisms of Interactions between a Probiotic Consortium and Its Coral Host.

Beneficial microorganisms for corals (BMCs) have been demonstrated to be effective probiotics to alleviate bleaching and mitigate coral mortality in vivo. The selection of putative BMCs is traditionally performed manually, using an array of biochemical and molecular tests for putative BMC traits. We present a comprehensive genetic survey of BMC traits using a genome-based framework for the identification of alternative mechanisms that can be used for future in silico selection of BMC strains. We identify exclusive BMC traits associated with specific strains and propose new BMC mechanisms, such as the synthesis of glycine betaine and ectoines. Our roadmap facilitates the selection of BMC strains while increasing the array of genetic targets that can be included in the selection of putative BMC strains to be tested as coral probiotics. IMPORTANCE Probiotics are currently the main hope as a potential medicine for corals, organisms that are considered the marine "canaries of the coal mine" and that are threatened with extinction. Our experiments have proved the concept that probiotics mitigate coral bleaching and can also prevent coral mortality. Here, we present a comprehensive genetic survey of probiotic traits using a genome-based framework. The main outcomes are a roadmap that facilitates the selection of coral probiotic strains while increasing the array of mechanisms that can be included in the selection of coral probiotics.

Genome Mining Reveals High Biosynthetic Potential of Biocontrol Agent Bacillus velezensis B.BV10.

The present study demonstrates the biocontrol potential of a plant growth-promoting bacterial strain using three different approaches: (i) an in vitro evaluation of antagonistic activity against important phytopathogenic fungi; (ii) an evaluation under greenhouse conditions with strawberry plants to assess the control of gray mold; and (iii) an in silico whole genome sequence mining to assign genetic features such as gene clusters or isolated genes to the strain activity. The in vitro assay showed that the B.BV10 strain presented antagonistic activity, inhibiting the mycelial growth in all the phytopathogenic fungi evaluated. The application of the Bacillus velezensis strain B.BV10 under greenhouse conditions reduced the presence of Botrytis cinerea and increased the mean fruit biomass. The genome of B.BV10 was estimated at 3,917,533 bp, with a GC content of 46.6% and 4088 coding DNA sequences, and was identified as B. velezensis. Biosynthetic gene clusters related to the synthesis of the molecules with antifungal activity were found in its genome. Genes related to the regulation/formation of biofilms, motility, and the important properties for the rhizospheric colonization were also found in the genome. The current study offers a comprehensive understanding of the genomic architecture and control activity of phytopathogenic fungi by the B. velezensis strain B.BV10 that may substantiate the industrialization of this strain in the future.

Whole-genome sequence of the filamentous diazotrophic cyanobacterium Tolypothrix sp. PCC 7712 and its comparison with non-diazotrophic Tolypothrix sp. PCC 7601.

Cyanobacteria are highly promising microorganisms in forthcoming biotechnologies. Besides the systematic development of molecular tools for genetic engineering, the design of chassis strains and novel reactor concepts are in focus. The latter includes capillary biofilm reactors (CBR), which offer a high surface area-to-volume ratio and very high cell densities. In this context, Tolypothrix sp. PCC 7712 was found to be highly suited for this reactor system due to maximal surface coverage, extraordinarily strong biofilm attachment, and high biomass formation. Here, we provide the genome sequence of Tolypothrix sp. PCC 7712 to potentially allow targeted strain engineering. Surprisingly, it was almost identical to an available incomplete genome draft of Tolypothrix sp. PCC 7601. Thus, we completely sequenced this strain as well and compared it in detail to strain PCC 7712. Comparative genome analysis revealed 257 and 80 unique protein-coding sequences for strains PCC 7601 and PCC 7712, respectively. Clustering genomes based on average nucleotide identity (ANI) and 16S rRNA homology showed 99.98% similarity and only minor distance, respectively, between the two strains in contrast to 21 other cyanobacterial genomes. Despite these high similarities, both strains differ in the ability to fix atmospheric nitrogen and show specific sequence variations, which are discussed in the paper.

MarineMetagenomeDB: a public repository for curated and standardized metadata for marine metagenomes.

BACKGROUND: Metagenomics is an expanding field within microbial ecology, microbiology, and related disciplines. The number of metagenomes deposited in major public repositories such as Sequence Read Archive (SRA) and Metagenomic Rapid Annotations using Subsystems Technology (MG-RAST) is rising exponentially. However, data mining and interpretation can be challenging due to mis-annotated and misleading metadata entries. In this study, we describe the Marine Metagenome Metadata Database (MarineMetagenomeDB) to help researchers identify marine metagenomes of interest for re-analysis and meta-analysis. To this end, we have manually curated the associated metadata of several thousands of microbial metagenomes currently deposited at SRA and MG-RAST. RESULTS: In total, 125 terms were curated according to 17 different classes (e.g., biome, material, oceanic zone, geographic feature and oceanographic phenomena). Other standardized features include sample attributes (e.g., salinity, depth), sample location (e.g., latitude, longitude), and sequencing features (e.g., sequencing platform, sequence count). MarineMetagenomeDB version 1.0 contains 11,449 marine metagenomes from SRA and MG-RAST distributed across all oceans and several seas. Most samples were sequenced using Illumina sequencing technology (84.33%). More than 55% of the samples were collected from the Pacific and the Atlantic Oceans. About 40% of the samples had their biomes assigned as 'ocean'. The 'Quick Search' and 'Advanced Search' tabs allow users to use different filters to select samples of interest dynamically in the web app. The interactive map allows the visualization of samples based on their location on the world map. The web app is also equipped with a novel download tool (on both Windows and Linux operating systems), that allows easy download of raw sequence data of selected samples from their respective repositories. As a use case, we demonstrated how to use the MarineMetagenomeDB web app to select estuarine metagenomes for potential large-scale microbial biogeography studies. CONCLUSION: The MarineMetagenomeDB is a powerful resource for non-bioinformaticians to find marine metagenome samples with curated metadata and stimulate meta-studies involving marine microbiomes. Our user-friendly web app is publicly available at https://webapp.ufz.de/marmdb/ .

Global Distribution of Carbohydrate Utilization Potential in the Prokaryotic Tree of Life.

Microorganisms dominate all ecosystems on Earth and play a key role in the turnover of organic matter. By producing enzymes, they degrade complex carbohydrates, facilitating the recycling of nutrients and controlling the carbon cycle. Despite their importance, our knowledge regarding microbial carbohydrate utilization has been limited to genome-sequenced taxa and thus heavily biased to specific groups and environments. Here, we used the Genomes from Earth's Microbiomes (GEM) catalog to describe the carbohydrate utilization potential in >7000 bacterial and archaeal taxa originating from a range of terrestrial, marine and host-associated habitats. We show that the production of carbohydrate-active enzymes (CAZymes) is phylogenetically conserved and varies significantly among microbial phyla. High numbers of carbohydrate-active enzymes were recorded in phyla known for their versatile use of carbohydrates, such as Firmicutes, Fibrobacterota, and Armatimonadota, but also phyla without cultured representatives whose carbohydrate utilization potential was so far unknown, such as KSB1, Hydrogenedentota, Sumerlaeota, and UBP3. Carbohydrate utilization potential reflected the specificity of various habitats: the richest complements of CAZymes were observed in MAGs of plant microbiomes, indicating the structural complexity of plant biopolymers. IMPORTANCE This study expanded our knowledge of the phylogenetic distribution of carbohydrate-active enzymes across prokaryotic tree of life, including new phyla where the carbohydrate-active enzymes composition have not been described until now and demonstrated the potential for carbohydrate utilization of numerous yet uncultured phyla. Profiles of carbohydrate-active enzymes are largely habitat-specific and reflect local carbohydrate availability by selecting taxa with appropriate complements of these enzymes. This information should aid in the prediction of functions in microbiomes of known taxonomic composition and helps to identify key components of habitat-specific carbohydrate pools. In addition, these findings have a high relevance for the understanding of carbohydrate utilization and carbon cycling in the environment, the process that is closely link to the carbon storage potential of Earth habitats and the production of greenhouse gasses.