MetaQUAST: evaluation of metagenome assemblies

Decomposing a San Francisco estuary microbiome using long-read metagenomics reveals species- and strain-level dominance from picoeukaryotes to viruses

Although long-read sequencing has enabled obtaining high-quality and complete genomes from metagenomes, many challenges still remain to completely decompose a metagenome into its constituent prokaryotic and viral genomes. This study focuses on decomposing an estuarine metagenome to obtain a more accurate estimate of microbial diversity. To achieve this, we developed a new bead-based DNA extraction method, a novel bin refinement method, and obtained 150 Gbp of Nanopore sequencing. We estimate that there are ~500 bacterial and archaeal species in our sample and obtained 68 high-quality bins (>90% complete, <5% contamination, ≤5 contigs, contig length of >100 kbp, and all ribosomal and tRNA genes). We also obtained many contigs of picoeukaryotes, environmental DNA of larger eukaryotes such as mammals, and complete mitochondrial and chloroplast genomes and detected ~40,000 viral populations. Our analysis indicates that there are only a few strains that comprise most of the species abundances.

IMPORTANCE

Ocean and estuarine microbiomes play critical roles in global element cycling and ecosystem function. Despite the importance of these microbial communities, many species still have not been cultured in the lab. Environmental sequencing is the primary way the function and population dynamics of these communities can be studied. Long-read sequencing provides an avenue to overcome limitations of short-read technologies to obtain complete microbial genomes but comes with its own technical challenges, such as needed sequencing depth and obtaining high-quality DNA. We present here new sampling and bioinformatics methods to attempt decomposing an estuarine microbiome into its constituent genomes. Our results suggest there are only a few strains that comprise most of the species abundances from viruses to picoeukaryotes, and to fully decompose a metagenome of this diversity requires 1 Tbp of long-read sequencing. We anticipate that as long-read sequencing technologies continue to improve, less sequencing will be needed.

Contrasting fertilization and phenological stages shape microbial-mediated phosphorus cycling in a maize agroecosystem

Phosphorus (P) is essential for plants but often limited in soils, with microbes playing a key role in its cycling. P deficiency in crops can be mitigated by applying by-products like sludge and struvite to enhance yield and sustainability. Here, we evaluated the contribution of four different types of fertilizers: i) conventional NPK; ii) sludge; iii) struvite; and iv) struvite+sludge in a semiarid maize plantation to the availability of P and the responses of the soil microbiome. We investigated the effects of these treatments on the relative abundance of bacterial and archaeal genes and proteins related to organic P mineralization, inorganic P solubilization, and the P starvation response regulation through a multi-omic approach. Moreover, we explored the impact of maize phenology by collecting samples at germination and flowering stages. Our findings suggest that the phenological stage has a notable impact on the abundance of P cycle genes within bacterial and archaeal communities, particularly regarding the solubilization of inorganic P. Furthermore, significant variations were observed in the relative abundance of genes associated with different P cycles in response to various fertilizer treatments. Sludge and struvite application improved P availability, which was related to an increase in the relative abundance of Sphingomonas (Proteobacteria) and Luteitalea (Acidobacteria) respectively, and genes related to inorganic P solubilization. Furthermore, we observed a substantial taxonomic clustering of functional processes associated with the P cycle. Among the dominant bacterial populations containing P-related genes, those microbes possessing genes linked to the solubilization of inorganic P typically did not harbor genes associated with the mineralization of organic P. This phenomenon was particularly evident among members of Actinobacteria. Overall, we reveal important shifts in bacterial and archaeal communities and associated molecular processes, stressing the intricate interplay between fertilization, phenology, and P cycling in agroecosystems.

Microbial metabolic potential of hydrothermal vent chimneys along the submarine ring of fire

Hydrothermal vents host a diverse community of microorganisms that utilize chemical gradients from the venting fluid for their metabolisms. The venting fluid can solidify to form chimney structures that these microbes adhere to and colonize. These chimney structures are found throughout many different locations in the world's oceans. In this study, comparative metagenomic analyses of microbial communities on five chimney structures from around the Pacific Ocean were elucidated focusing on the core taxa and genes that are characteristic of each of these hydrothermal vent chimneys. The differences among the taxa and genes found at each chimney due to parameters such as physical characteristics, chemistry, and activity of the vents were highlighted. DNA from the chimneys was sequenced, assembled into contigs, and annotated for gene function. Genes used for carbon, oxygen, sulfur, nitrogen, iron, and arsenic metabolisms were found at varying abundances at each of the chimneys, largely from either Gammaproteobacteria or Campylobacteria. Many taxa shared an overlap of these functional metabolic genes, indicating that functional redundancy is critical for life at these hydrothermal vents. A high relative abundance of oxygen metabolism genes coupled with a low abundance of carbon fixation genes could be used as a unique identifier for inactive chimneys. Genes used for DNA repair, chemotaxis, and transposases were found at high abundances at each of these hydrothermal chimneys allowing for enhanced adaptations to the ever-changing chemical and physical conditions encountered.

Exploring viral diversity and metagenomics in livestock: insights into disease emergence and spillover risks in cattle

Cattle have a significant impact on human societies in terms of both economics and health. Viral infections pose a relevant problem as they directly or indirectly disrupt the balance within cattle populations. This has negative consequences at the economic level for producers and territories, and also jeopardizes human health through the transmission of zoonotic diseases that can escalate into outbreaks or pandemics. To establish prevention strategies and control measures at various levels (animal, farm, region, or global), it is crucial to identify the viral agents present in animals. Various techniques, including virus isolation, serological tests, and molecular techniques like PCR, are typically employed for this purpose. However, these techniques have two major drawbacks: they are ineffective for non-culturable viruses, and they only detect a small fraction of the viruses present. In contrast, metagenomics offers a promising approach by providing a comprehensive and unbiased analysis for detecting all viruses in a given sample. It has the potential to identify rare or novel infectious agents promptly and establish a baseline of healthy animals. Nevertheless, the routine application of viral metagenomics for epidemiological surveillance and diagnostics faces challenges related to socioeconomic variables, such as resource availability and space dedicated to metagenomics, as well as the lack of standardized protocols and resulting heterogeneity in presenting results. This review aims to provide an overview of the current knowledge and prospects for using viral metagenomics to detect and identify viruses in cattle raised for livestock, while discussing the epidemiological and clinical implications.

'Candidatus Phytoplasma vignae', assigning a species description to a long-known phytoplasma occurring in northern Australia

Gene- and genome-based approaches were used to determine whether Vigna little leaf (ViLL) phytoplasma, which occurs in northern Australia, is a distinct 'Candidatus Phytoplasma' species. The ViLL 16S rRNA gene sequences exhibited the highest known similarity to species in the 16SrXXIX-A and 16SrIX-D subgroups, namely 'Candidatus Phytoplasma omanense' (98.03-98.10%) and 'Candidatus Phytoplasma phoenicium' (96.87-97.20%), respectively. A total of 48 single-copy orthologue genes were identified to be shared among the two draft ViLL phytoplasma genomes, 30 publicly available phytoplasma genomes, and one Acholeplasma laidlawii genome as the outgroup taxon. Phylogenomic assessments using the 48 shared single-copy orthologue genes supported that ViLL and 'Ca. Phytoplasma phoenicium' were closely related yet distinct species. The 16S rRNA gene sequence analysis and phylogenomic assessment indicate that ViLL phytoplasmas are a distinct taxon. As such, a novel species, 'Candidatus Phytoplasma vignae', is proposed. Strain BAWM-336 (genome accession number JAUZLI000000000) detected in Momordica charantia (bitter melon) serves as the reference strain of this species, with infected plant material deposited in the Victorian Plant Pathology Herbarium (VPRI) as VPRI 44369.

Solving genomic puzzles: computational methods for metagenomic binning

Metagenomics involves the study of genetic material obtained directly from communities of microorganisms living in natural environments. The field of metagenomics has provided valuable insights into the structure, diversity and ecology of microbial communities. Once an environmental sample is sequenced and processed, metagenomic binning clusters the sequences into bins representing different taxonomic groups such as species, genera, or higher levels. Several computational tools have been developed to automate the process of metagenomic binning. These tools have enabled the recovery of novel draft genomes of microorganisms allowing us to study their behaviors and functions within microbial communities. This review classifies and analyzes different approaches of metagenomic binning and different refinement, visualization, and evaluation techniques used by these methods. Furthermore, the review highlights the current challenges and areas of improvement present within the field of research.

Setu: a pipeline for the robust assembly of SARS-CoV-2 genomes

Setu is an efficient pipeline integrating currently available open source bioinformatic tools to perform rapid de novo assembly to assist tracking of severe acute respiratory syndrome coronavirus 2 genome evolution in clinical data, being particularly useful for institutions with limited computing resources or personnel not familiar with bioinformatic pipelines.

Microbial Sulfur and Arsenic Oxidation Facilitate the Establishment of Biocrusts during Reclamation of Degraded Mine Tailings

Degraded tailings generated by the mining of metal ores are major environmental threats to the surrounding ecosystems. Tailing reclamation, however, is often impeded due to adverse environmental conditions, with depleted key nutrients (i.e., nitrogen (N) and phosphorus (P)) and elevated sulfur and metal(loid) concentrations. Formation of biocrusts may significantly accelerate nutrient accumulation and is therefore an essential stage for tailing reclamation. Although suggested to play an important role, the microbial community composition and key metabolisms in biocrusts remain largely unknown and are therefore investigated in the current study. The results suggested that sulfur and arsenic oxidation are potential energy sources utilized by members of predominant biocrust bacterial families, including Beijerinckiaceae, Burkholderiaceae, Hyphomicrobiaceae, and Rhizobiaceae. Accordingly, the S and As oxidation potentials are elevated in biocrusts compared to those in their adjacent tailings. Biocrust growth, as proxied by chlorophyll concentrations, is enhanced in treatments supplemented with S and As. The elevated biocrust growth might benefit from nutrient acquisition services (i.e., nitrogen fixation and phosphorus solubilization) fueled by microbial sulfur and arsenic oxidation. The current study suggests that sulfur- and arsenic-oxidizing microorganisms may play important ecological roles in promoting biocrust formation and facilitating tailing reclamation.

Unified metagenomic method for rapid detection of microorganisms in clinical samples

BACKGROUND

Clinical metagenomics involves the genomic sequencing of all microorganisms in clinical samples ideally after depletion of human DNA to increase sensitivity and reduce turnaround times. Current human DNA depletion methods preferentially preserve either DNA or RNA containing microbes, but not both simultaneously. Here we describe and present data using a practical and rapid mechanical host-depletion method allowing simultaneous detection of RNA and DNA microorganisms linked with nanopore sequencing.

METHODS

The human cells from respiratory samples are lysed mechanically using 1.4 mm zirconium-silicate spheres and the human DNA is depleted using a nonspecific endonuclease. The RNA is converted to dsDNA to allow the simultaneous sequencing of DNA and RNA.

RESULTS

The method decreases human DNA concentration by a median of eight Ct values while detecting a broad range of RNA & DNA viruses, bacteria, including atypical pathogens (Legionella, Chlamydia, Mycoplasma) and fungi (Candida, Pneumocystis, Aspergillus). The first automated reports are generated after 30 min sequencing from a 7 h end-to-end workflow. Sensitivity and specificity for bacterial detection are 90% and 100%, respectively, and viral detection are 92% and 100% after 2 h of sequencing. Prospective validation on 33 consecutive lower respiratory tract samples from ventilated patients with suspected pneumonia shows 60% concordance with routine testing, detection of additional pathogens in 21% of samples and pathogen genomic assembly achieve for 42% of viruses and 33% of bacteria.

CONCLUSIONS

Although further workflow refinement and validation on samples containing a broader range of pathogens is required, it holds promise as a clinically deployable workflow suitable for evaluation in routine microbiology laboratories.

Protocol for the construction and functional profiling of metagenome-assembled genomes for microbiome analyses

Constructing metagenome-assembled genomes (MAGs) from complex metagenomic samples involves a series of bioinformatics operations, each requiring deep bioinformatics knowledge. Here, we present a protocol for constructing MAGs and conducting functional profiling to address biological questions. We describe steps for system configuration, data downloads, read processing, removal of human DNA contamination, metagenomic assembly, and statistical quality assessment of the final assembly. Additionally, we detail procedures for the construction and refinement of MAGs, as well as the functional profiling of MAGs.

Longitudinal multi-omics analysis of host microbiome architecture and immune responses during short-term spaceflight

Maintenance of astronaut health during spaceflight will require monitoring and potentially modulating their microbiomes. However, documenting microbial shifts during spaceflight has been difficult due to mission constraints that lead to limited sampling and profiling. Here we executed a six-month longitudinal study to quantify the high-resolution human microbiome response to three days in orbit for four individuals. Using paired metagenomics and metatranscriptomics alongside single-nuclei immune cell profiling, we characterized time-dependent, multikingdom microbiome changes across 750 samples and 10 body sites before, during and after spaceflight at eight timepoints. We found that most alterations were transient across body sites; for example, viruses increased in skin sites mostly during flight. However, longer-term shifts were observed in the oral microbiome, including increased plaque-associated bacteria (for example, Fusobacteriota), which correlated with immune cell gene expression. Further, microbial genes associated with phage activity, toxin-antitoxin systems and stress response were enriched across multiple body sites. In total, this study reveals in-depth characterization of microbiome and immune response shifts experienced by astronauts during short-term spaceflight and the associated changes to the living environment, which can help guide future missions, spacecraft design and space habitat planning.

Strain dynamics of contaminating bacteria modulate the yield of ethanol biorefineries

Bioethanol is a sustainable energy alternative and can contribute to global greenhouse-gas emission reductions by over 60%. Its industrial production faces various bottlenecks, including sub-optimal efficiency resulting from bacteria. Broad-spectrum removal of these contaminants results in negligible gains, suggesting that the process is shaped by ecological interactions within the microbial community. Here, we survey the microbiome across all process steps at two biorefineries, over three timepoints in a production season. Leveraging shotgun metagenomics and cultivation-based approaches, we identify beneficial bacteria and find improved outcome when yeast-to-bacteria ratios increase during fermentation. We provide a microbial gene catalogue which reveals bacteria-specific pathways associated with performance. We also show that Limosilactobacillus fermentum overgrowth lowers production, with one strain reducing yield by ~5% in laboratory fermentations, potentially due to its metabolite profile. Temperature is found to be a major driver for strain-level dynamics. Improved microbial management strategies could unlock environmental and economic gains in this US $ 60 billion industry enabling its wider adoption.

Database selection for shotgun metaproteomic of low-diversity dairy microbiomes

The metaproteomics field has recently gained more and more interest as a valuable tool for studying both the taxonomy and function of microbiomes, including those used in food fermentations. One crucial step in the metaproteomics pipeline is selecting a database to obtain high-quality taxonomical and functional information from microbial communities. One of the best strategies described for building protein databases is using sample-specific or study-specific protein databases obtained from metagenomic sequencing. While this is true for high-diversity microbiomes (such as gut and soil), there is still a lack of validation for different database construction strategies in low-diversity microbiomes, such as those found in fermented dairy products where starter cultures containing few species are used. In this study, we assessed the performance of various database construction strategies applied to metaproteomics on two low-diversity microbiomes obtained from cheese production using commercial starter cultures and analyzed by LC-MS/MS. Substantial differences were detected between the strategies, and the best performance in terms of the number of peptides and proteins identified from the spectra was achieved by metagenomic-derived databases. However, extensive databases constructed from a high number of available online genomes obtained a similar taxonomical and functional annotation of the metaproteome compared to the metagenomic-derived databases. Our results indicate that, in the case of low-diversity dairy microbiomes, the use of publically available genomes to construct protein databases can be considered as an alternative to metagenome-derived databases.

Plastiome: Plastisphere-enriched mobile resistome in aquatic environments

Aquatic microplastics (MPs) act as reservoirs for microbial communities, fostering the formation of a mobile resistome encompassing diverse antibiotic (ARGs) and biocide/metal resistance genes (BMRGs), and mobile genetic elements (MGEs). This collective genetic repertoire, referred to as the "plastiome," can potentially perpetuate environmental antimicrobial resistance (AMR). Our study examining two Japanese rivers near Tokyo revealed that waterborne MPs are primarily composed of polyethylene and polypropylene fibers and sheets of diverse origin. Clinically important genera like Exiguobacterium and Eubacterium were notably enriched on MPs. Metagenomic analysis uncovered a 3.46-fold higher enrichment of ARGs on MPs than those in water, with multidrug resistance genes (MDRGs) and BMRGs prevailing, particularly within MPs. Specific ARG and BMRG subtypes linked to resistance to vancomycin, beta-lactams, biocides, arsenic, and mercury showed selective enrichment on MPs. Network analysis revealed intense associations between host genera with ARGs, BMRGs, and MGEs on MPs, emphasizing their role in coselection. In contrast, river water exhibited weaker associations. This study underscores the complex interactions shaping the mobile plastiome in aquatic environments and emphasizes the global imperative for research to comprehend and effectively control AMR within the One Health framework.

Unlocking the biosynthetic potential and taxonomy of the Antarctic microbiome along temporal and spatial gradients

Extreme environments, such as Antarctica, select microbial communities that display a range of evolutionary strategies to survive and thrive under harsh environmental conditions. These include a diversity of specialized metabolites, which have the potential to be a source for new natural product discovery. Efforts using (meta)genome mining approaches to identify and understand biosynthetic gene clusters in Antarctica are still scarce, and the extent of their diversity and distribution patterns in the environment have yet to be discovered. Herein, we investigated the biosynthetic gene diversity of the biofilm microbial community of Whalers Bay, Deception Island, in the Antarctic Peninsula and revealed its distribution patterns along spatial and temporal gradients by applying metagenome mining approaches and multivariable analysis. The results showed that the Whalers Bay microbial community harbors a great diversity of biosynthetic gene clusters distributed into seven classes, with terpene being the most abundant. The phyla Proteobacteria and Bacteroidota were the most abundant in the microbial community and contributed significantly to the biosynthetic gene abundances in Whalers Bay. Furthermore, the results highlighted a significant correlation between the distribution of biosynthetic genes and taxonomic diversity, emphasizing the intricate interplay between microbial taxonomy and their potential for specialized metabolite production.IMPORTANCEThis research on antarctic microbial biosynthetic diversity in Whalers Bay, Deception Island, unveils the hidden potential of extreme environments for natural product discovery. By employing metagenomic techniques, the research highlights the extensive diversity of biosynthetic gene clusters and identifies key microbial phyla, Proteobacteria and Bacteroidota, as significant contributors. The correlation between taxonomic diversity and biosynthetic gene distribution underscores the intricate interplay governing specialized metabolite production. These findings are crucial for understanding microbial adaptation in extreme environments and hold significant implications for bioprospecting initiatives. The study opens avenues for discovering novel bioactive compounds with potential applications in medicine and industry, emphasizing the importance of preserving and exploring these polyextreme ecosystems to advance biotechnological and pharmaceutical research.

Advancing metagenome-assembled genome-based pathogen identification: unraveling the power of long-read assembly algorithms in Oxford Nanopore sequencing

Oxford Nanopore sequencing is one of the high-throughput sequencing technologies that facilitates the reconstruction of metagenome-assembled genomes (MAGs). This study aimed to assess the potential of long-read assembly algorithms in Oxford Nanopore sequencing to enhance the MAG-based identification of bacterial pathogens using both simulated and mock communities. Simulated communities were generated to mimic those on fresh spinach and in surface water. Long reads were produced using R9.4.1+SQK-LSK109 and R10.4 + SQK-LSK112, with 0.5, 1, and 2 million reads. The simulated bacterial communities included multidrug-resistant Salmonella enterica serotypes Heidelberg, Montevideo, and Typhimurium in the fresh spinach community individually or in combination, as well as multidrug-resistant Pseudomonas aeruginosa in the surface water community. Real data sets of the ZymoBIOMICS HMW DNA Standard were also studied. A bioinformatic pipeline (MAGenie, freely available at https://github.com/jackchen129/MAGenie) that combines metagenome assembly, taxonomic classification, and sequence extraction was developed to reconstruct draft MAGs from metagenome assemblies. Five assemblers were evaluated based on a series of genomic analyses. Overall, Flye outperformed the other assemblers, followed by Shasta, Raven, and Unicycler, while Canu performed least effectively. In some instances, the extracted sequences resulted in draft MAGs and provided the locations and structures of antimicrobial resistance genes and mobile genetic elements. Our study showcases the viability of utilizing the extracted sequences for precise phylogenetic inference, as demonstrated by the consistent alignment of phylogenetic topology between the reference genome and the extracted sequences. R9.4.1+SQK-LSK109 was more effective in most cases than R10.4+SQK-LSK112, and greater sequencing depths generally led to more accurate results.IMPORTANCEBy examining diverse bacterial communities, particularly those housing multiple Salmonella enterica serotypes, this study holds significance in uncovering the potential of long-read assembly algorithms to improve metagenome-assembled genome (MAG)-based pathogen identification through Oxford Nanopore sequencing. Our research demonstrates that long-read assembly stands out as a promising avenue for boosting precision in MAG-based pathogen identification, thus advancing the development of more robust surveillance measures. The findings also support ongoing endeavors to fine-tune a bioinformatic pipeline for accurate pathogen identification within complex metagenomic samples.

Benchmarking short-, long- and hybrid-read assemblers for metagenome sequencing of complex microbial communities

Metagenome community analyses, driven by the continued development in sequencing technology, is rapidly providing insights in many aspects of microbiology and becoming a cornerstone tool. Illumina, Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio) are the leading technologies, each with their own advantages and drawbacks. Illumina provides accurate reads at a low cost, but their length is too short to close bacterial genomes. Long reads overcome this limitation, but these technologies produce reads with lower accuracy (ONT) or with lower throughput (PacBio high-fidelity reads). In a critical first analysis step, reads are assembled to reconstruct genomes or individual genes within the community. However, to date, the performance of existing assemblers has never been challenged with a complex mock metagenome. Here, we evaluate the performance of current assemblers that use short, long or both read types on a complex mock metagenome consisting of 227 bacterial strains with varying degrees of relatedness. We show that many of the current assemblers are not suited to handle such a complex metagenome. In addition, hybrid assemblies do not fulfil their potential. We conclude that ONT reads assembled with CANU and Illumina reads assembled with SPAdes offer the best value for reconstructing genomes and individual genes of complex metagenomes, respectively.

Exploring high-quality microbial genomes by assembling short-reads with long-range connectivity

Although long-read sequencing enables the generation of complete genomes for unculturable microbes, its high cost limits the widespread adoption of long-read sequencing in large-scale metagenomic studies. An alternative method is to assemble short-reads with long-range connectivity, which can be a cost-effective way to generate high-quality microbial genomes. Here, we develop Pangaea, a bioinformatic approach designed to enhance metagenome assembly using short-reads with long-range connectivity. Pangaea leverages connectivity derived from physical barcodes of linked-reads or virtual barcodes by aligning short-reads to long-reads. Pangaea utilizes a deep learning-based read binning algorithm to assemble co-barcoded reads exhibiting similar sequence contexts and abundances, thereby improving the assembly of high- and medium-abundance microbial genomes. Pangaea also leverages a multi-thresholding algorithm strategy to refine assembly for low-abundance microbes. We benchmark Pangaea on linked-reads and a combination of short- and long-reads from simulation data, mock communities and human gut metagenomes. Pangaea achieves significantly higher contig continuity as well as more near-complete metagenome-assembled genomes (NCMAGs) than the existing assemblers. Pangaea also generates three complete and circular NCMAGs on the human gut microbiomes.

Easing genomic surveillance: A comprehensive performance evaluation of long-read assemblers across multi-strain mixture data of HIV-1 and Other pathogenic viruses for constructing a user-friendly bioinformatic pipeline

Background

Determining the appropriate computational requirements and software performance is essential for efficient genomic surveillance. The lack of standardized benchmarking complicates software selection, especially with limited resources.

Methods

We developed a containerized benchmarking pipeline to evaluate seven long-read assemblers-Canu, GoldRush, MetaFlye, Strainline, HaploDMF, iGDA, and RVHaplo-for viral haplotype reconstruction, using both simulated and experimental Oxford Nanopore sequencing data of HIV-1 and other viruses. Benchmarking was conducted on three computational systems to assess each assembler's performance, utilizing QUAST and BLASTN for quality assessment.

Results

Our findings show that assembler choice significantly impacts assembly time, with CPU and memory usage having minimal effect. Assembler selection also influences the size of the contigs, with a minimum read length of 2,000 nucleotides required for quality assembly. A 4,000-nucleotide read length improves quality further. Canu was efficient among de novo assemblers but not suitable for multi-strain mixtures, while GoldRush produced only consensus assemblies. Strainline and MetaFlye were suitable for metagenomic sequencing data, with Strainline requiring high memory and MetaFlye operable on low-specification machines. Among reference-based assemblers, iGDA had high error rates, RVHaplo showed the best runtime and accuracy but became ineffective with similar sequences, and HaploDMF, utilizing machine learning, had fewer errors with a slightly longer runtime.

Conclusions

The HIV-64148 pipeline, containerized using Docker, facilitates easy deployment and offers flexibility to select from a range of assemblers to match computational systems or study requirements. This tool aids in genome assembly and provides valuable information on HIV-1 sequences, enhancing viral evolution monitoring and understanding.

Identification of carbohydrate gene clusters obtained from in vitro fermentations as predictive biomarkers of prebiotic responses

BACKGROUND

Prebiotic fibers are non-digestible substrates that modulate the gut microbiome by promoting expansion of microbes having the genetic and physiological potential to utilize those molecules. Although several prebiotic substrates have been consistently shown to provide health benefits in human clinical trials, responder and non-responder phenotypes are often reported. These observations had led to interest in identifying, a priori, prebiotic responders and non-responders as a basis for personalized nutrition. In this study, we conducted in vitro fecal enrichments and applied shotgun metagenomics and machine learning tools to identify microbial gene signatures from adult subjects that could be used to predict prebiotic responders and non-responders.

RESULTS

Using short chain fatty acids as a targeted response, we identified genetic features, consisting of carbohydrate active enzymes, transcription factors and sugar transporters, from metagenomic sequencing of in vitro fermentations for three prebiotic substrates: xylooligosacharides, fructooligosacharides, and inulin. A machine learning approach was then used to select substrate-specific gene signatures as predictive features. These features were found to be predictive for XOS responders with respect to SCFA production in an in vivo trial.

CONCLUSIONS

Our results confirm the bifidogenic effect of commonly used prebiotic substrates along with inter-individual microbial responses towards these substrates. We successfully trained classifiers for the prediction of prebiotic responders towards XOS and inulin with robust accuracy (≥ AUC 0.9) and demonstrated its utility in a human feeding trial. Overall, the findings from this study highlight the practical implementation of pre-intervention targeted profiling of individual microbiomes to stratify responders and non-responders.

Key energy metabolisms in modern living microbialites from hypersaline Andean lagoons of the Salar de Atacama, Chile

Microbialites are organosedimentary structures formed mainly due to the precipitation of carbonate minerals, although they can also incorporate siliceous, phosphate, ferric, and sulfate minerals. The minerals' precipitation occurs because of local chemical changes triggered by changes in pH and redox transformations catalyzed by the microbial energy metabolisms. Here, geochemistry, metagenomics, and bioinformatics tools reveal the key energy metabolisms of microbial mats, stromatolites and an endoevaporite distributed across four hypersaline lagoons from the Salar de Atacama. Chemoautotrophic and chemoheterotrophic microorganisms seem to coexist and influence microbialite formation. The microbialite types of each lagoon host unique microbial communities and metabolisms that influence their geochemistry. Among them, photosynthetic, carbon- and nitrogen- fixing and sulfate-reducing microorganisms appear to control the main biogeochemical cycles. Genes associated with non-conventional energy pathways identified in MAGs, such as hydrogen production/consumption, arsenic oxidation/reduction, manganese oxidation and selenium reduction, also contribute to support life in microbialites. The presence of genes encoding for enzymes associated with ureolytic processes in the Cyanobacteria phylum and Gammaproteobacteria class might induce carbonate precipitation in hypersaline environments, contributing to the microbialites formation. To the best of our knowledge, this is the first study characterizing metagenomically microbialites enriched in manganese and identifying metabolic pathways associated with manganese oxidation, selenium reduction, and ureolysis in this ecosystem, which suggests that the geochemistry and bioavailability of energy sources (As, Mn and Se) shapes the microbial metabolisms in the microbialites.

Integrating metagenomic and isolation strategies revealed high contamination of pathogenies and resistome in market shrimps

This study employs a comprehensive approach combining metagenomic analysis and bacterial isolation to elucidate the microbial composition, antibiotic resistance genes (ARGs), and virulence factors (VFGs) present in shrimps from market and supermarket. Metagenomic analysis of shrimps revealed a dominance of Proteobacteria and Bacteroidetes with Firmicutes notably enriched in some samples. On the other hand, the dominant bacteria isolated included Citrobacter portucalensis, Escherichia coli, Salmonella enterica, Vibrio species and Klebsiella pneumonaie. Metagenomic analysis unveiled a diverse spectrum of 23 main types and 380 subtypes of ARGs in shrimp samples including many clinical significant ARGs such as blaKPC, blaNDM, mcr, tet(X4) etc. Genomic analysis of isolated bacterial strains identified 14 ARG types with 109 subtype genes, which complemented the metagenomic data. Genomic analysis also allowed us to identify a rich amount of MDR plasmids, which provided further insights into the dissemination of resistance genes in different species of bacteria in the same samples. Examination of VFGs and mobile genetic elements (MGEs) in both metagenomic and bacterial genomes revealed a complex landscape of factors contributing to bacterial virulence and genetic mobility. Potential co-occurrence patterns of ARGs and VFGs within human pathogenic bacteria underlined the intricate interplay between antibiotic resistance and virulence. In conclusion, this integrated analysis for the first time provides a comprehensive view and sheds new light on the potential hazards associated with shrimp products in the markets. The findings underscore the necessity of ongoing surveillance and intervention strategies to mitigate risks posed by antibiotic-resistant bacteria in the food supply chain using the novel comprehensive approaches.

Foliar mycobiome remains unaltered under urban air-pollution but differentially express stress-related genes

Air pollution caused by tropospheric ozone contributes to the decline of forest ecosystems; for instance, sacred fir, Abies religiosa (Kunth) Schltdl. & Cham. forests in the peri-urban region of Mexico City. Individual trees within these forests exhibit variation in their response to ozone exposure, including the severity of visible symptoms in needles. Using RNA-Seq metatranscriptomic data and ITS2 metabarcoding, we investigated whether symptom variation correlates with the taxonomic and functional composition of fungal mycobiomes from needles collected in this highly polluted area in the surroundings of Mexico City. Our findings indicate that ozone-related symptoms do not significantly correlate with changes in the taxonomic composition of fungal mycobiomes. However, genes coding for 30 putative proteins were differentially expressed in the mycobiome of asymptomatic needles, including eight genes previously associated with resistance to oxidative stress. These results suggest that fungal communities likely play a role in mitigating the oxidative burst caused by tropospheric ozone in sacred fir. Our study illustrates the feasibility of using RNA-Seq data, accessible from global sequence repositories, for the characterization of fungal communities associated with plant tissues, including their gene expression.

Improving Bacterial Metagenomic Research through Long-Read Sequencing

Metagenomic sequencing analysis is central to investigating microbial communities in clinical and environmental studies. Short-read sequencing remains the primary approach for metagenomic research; however, long-read sequencing may offer advantages of improved metagenomic assembly and resolved taxonomic identification. To compare the relative performance for metagenomic studies, we simulated short- and long-read datasets using increasingly complex metagenomes comprising 10, 20, and 50 microbial taxa. Additionally, we used an empirical dataset of paired short- and long-read data generated from mouse fecal pellets to assess real-world performance. We compared metagenomic assembly quality, taxonomic classification, and metagenome-assembled genome (MAG) recovery rates. We show that long-read sequencing data significantly improve taxonomic classification and assembly quality. Metagenomic assemblies using simulated long reads were more complete and more contiguous with higher rates of MAG recovery. This resulted in more precise taxonomic classifications. Principal component analysis of empirical data demonstrated that sequencing technology affects compositional results as samples clustered by sequence type, not sample type. Overall, we highlight strengths of long-read metagenomic sequencing for microbiome studies, including improving the accuracy of classification and relative abundance estimates. These results will aid researchers when considering which sequencing approaches to use for metagenomic projects.

Meta-transcriptomic identification of groundnut RNA viruses in western Kenya and the novel detection of groundnut as a host for Cauliflower mosaic virus

BACKGROUND

Groundnut (Arachis hypogaea L.) is the 13th most important global crop grown throughout the tropical and subtropical regions of the world. One of the major constraints to groundnut production is viruses, which are also the most economically important and most abundant pathogens among cultivated legumes. Only a few studies have reported the characterization of RNA viruses in cultivated groundnuts in western Kenya, most of which deployed classical methods of detecting known viruses.

METHODS

We sampled twenty-one symptomatic and three asymptomatic groundnut leaf samples from farmers' fields in western Kenya. Total RNA was extracted from the samples followed by First-strand cDNA synthesis and sequencing on the Illumina HiSeq 2500 platform. After removing host and rRNA sequences, high-quality viral RNA sequences were de novo assembled and viral genomes annotated using the publicly available NCBI virus database. Multiple sequence alignment and phylogenetic analysis were done using MEGA X.

RESULTS

Bioinformatics analyses using as low as ∼3.5 million reads yielded complete and partial genomes for Cauliflower mosaic virus (CaMV), Cowpea polerovirus 2 (CPPV2), Groundnut rosette assistor virus (GRAV), Groundnut rosette virus (GRV), Groundnut rosette virus satellite RNA (satRNA) and Peanut mottle virus (PeMoV) falling within the species demarcation criteria. This is the first report of CaMV and the second report of CPPV2 on groundnut hosts in the world. Confirmation of the detected viruses was further verified through phylogenetic analyses alongside reported publicly available highly similar viruses. PeMoV was the only seed-borne virus reported.

CONCLUSION

Our findings demonstrate the power of Next Generation Sequencing in the discovery and identification of novel viruses in groundnuts. The detection of the new viruses indicates the complexity of virus diseases in groundnuts and would require more focus in future studies to establish the effect of the viruses as sole or mixed infections on the crop. The detection of PeMoV with potential origin from Malawi indicates the importance of seed certification and cross-boundary seed health testing.

Potential routes of plastics biotransformation involving novel plastizymes revealed by global multi-omic analysis of plastic associated microbes

Despite increasing efforts across various disciplines, the fate, transport, and impact of synthetic plastics on the environment and public health remain poorly understood. To better elucidate the microbial ecology of plastic waste and its potential for biotransformation, we conducted a large-scale analysis of all publicly available meta-omic studies investigating plastics (n = 27) in the environment. Notably, we observed low prevalence of known plastic degraders throughout most environments, except for substantial enrichment in riverine systems. This indicates rivers may be a highly promising environment for discovery of novel plastic bioremediation products. Ocean samples associated with degrading plastics showed clear differentiation from non-degrading polymers, showing enrichment of novel putative biodegrading taxa in the degraded samples. Regarding plastisphere pathogenicity, we observed significant enrichment of antimicrobial resistance genes on plastics but not of virulence factors. Additionally, we report a co-occurrence network analysis of 10 + million proteins associated with the plastisphere. This analysis revealed a localized sub-region enriched with known and putative plastizymes-these may be useful for deeper investigation of nature's ability to biodegrade man-made plastics. Finally, the combined data from our meta-analysis was used to construct a publicly available database, the Plastics Meta-omic Database (PMDB)-accessible at plasticmdb.org. These data should aid in the integrated exploration of the microbial plastisphere and facilitate research efforts investigating the fate and bioremediation potential of environmental plastic waste.

Metagenomic insights into the impact of litter from poultry Concentrated Animal Feeding Operations (CAFOs) to adjacent soil and water microbial communities

In recent decades, human food consumption has led to an increased demand for animal-based foods, particularly chicken meat production. The state of Georgia, USA is one of the top broiler chicken producers in the United States, where animals are raised in Concentrated Animal Feeding Operations (CAFOs). Without proper management, CAFOs could negatively impact the environment and become a public health risk as a source of water and air pollution and/or by spreading antimicrobial resistance genes. In this study, we used metagenome sequencing to investigate the impact of the application of the CAFO's litter on adjacent soils and downstream creek waters in terms of microbial diversity and antimicrobial resistance profile changes. Our data indicate that while a few microbial groups increased in abundance within a short period of time after litter application, these populations subsequently decreased to levels similar to those found prior to the litter application or to below the detection limit of our metagenome sequencing effort. Microbial taxonomic composition analyses, relative abundance of Metagenome-Assembled Genomes (MAGs) and detection of Antimicrobial Resistance Genes (ARGs) allow us to conclude that this practice of litter application had a negligible effect on the microbiome or resistome profile of these soils and nearby waterways, likely due to its dilution in the field and/or outcompetition by indigenous microbes, revealing a minimal impact of these poultry facilities on the natural microbial communities.

Comprehensive assessment of 11 de novo HiFi assemblers on complex eukaryotic genomes and metagenomes

Pacific Biosciences (PacBio) HiFi sequencing technology generates long reads (>10 kbp) with very high accuracy (<0.01% sequencing error). Although several de novo assembly tools are available for HiFi reads, there are no comprehensive studies on the evaluation of these assemblers. We evaluated the performance of 11 de novo HiFi assemblers on (1) real data for three eukaryotic genomes; (2) 34 synthetic data sets with different ploidy, sequencing coverage levels, heterozygosity rates, and sequencing error rates; (3) one real metagenomic data set; and (4) five synthetic metagenomic data sets with different composition abundance and heterozygosity rates. The 11 assemblers were evaluated using quality assessment tool (QUAST) and benchmarking universal single-copy ortholog (BUSCO). We also used several additional criteria, namely, completion rate, single-copy completion rate, duplicated completion rate, average proportion of largest category, average distance difference, quality value, run-time, and memory utilization. Results show that hifiasm and hifiasm-meta should be the first choice for assembling eukaryotic genomes and metagenomes with HiFi data. We performed a comprehensive benchmarking study of commonly used assemblers on complex eukaryotic genomes and metagenomes. Our study will help the research community to choose the most appropriate assembler for their data and identify possible improvements in assembly algorithms.

Biodegradation of chloroethene compounds under microoxic conditions

The biodegradation of chloroethene compounds under oxic and anoxic conditions is well established. However, the biological reactions that take place under microoxic conditions are unknown. Here, we report the biostimulated (BIOST: addition of lactate) and natural attenuated (NAT) degradation of chloroethene compounds under microoxic conditions by bacterial communities from chloroethene compounds-contaminated groundwater. The degradation of tetrachloroethene was significantly higher in NAT (15.14% on average) than in BIOST (10.13% on average) conditions at the end of the experiment (90 days). Sporomusa, Paracoccus, Sedimentibacter, Pseudomonas, and Desulfosporosinus were overrepresented in NAT and BIOST compared to the source groundwater. The NAT metagenome contains phenol hydrolase P1 oxygenase (dmpL), catechol-1,2-dioxygenase (catA), catechol-2,3-dioxygenases (dmpB, todE, and xylE) genes, which could be involved in the cometabolic degradation of chloroethene compounds; and chlorate reductase (clrA), that could be associated with partial reductive dechlorination of chloroethene compounds. Our data provide a better understanding of the bacterial communities, genes, and pathways potentially implicated in the reductive and cometabolic degradation of chloroethene compounds under microoxic conditions.

A metagenomic investigation of phytoplasma diversity in Australian vegetable growing regions

In this study, metagenomic sequence data was used to investigate the phytoplasma taxonomic diversity in vegetable-growing regions across Australia. Metagenomic sequencing was performed on 195 phytoplasma-positive samples, originating either from historic collections (n=46) or during collection efforts between January 2015 and June 2022 (n=149). The sampled hosts were classified as crop (n=155), weed (n=24), ornamental (n=7), native plant (n=6), and insect (n=3) species. Most samples came from Queensland (n=78), followed by Western Australia (n=46), the Northern Territory (n=32), New South Wales (n=17), and Victoria (n=10). Of the 195 draft phytoplasma genomes, 178 met our genome criteria for comparison using an average nucleotide identity approach. Ten distinct phytoplasma species were identified and could be classified within the 16SrII, 16SrXII (PCR only), 16SrXXV, and 16SrXXXVIII phytoplasma groups, which have all previously been recorded in Australia. The most commonly detected phytoplasma taxa in this study were species and subspecies classified within the 16SrII group (n=153), followed by strains within the 16SrXXXVIII group ('Ca. Phytoplasma stylosanthis'; n=6). Several geographic- and host-range expansions were reported, as well as mixed phytoplasma infections of 16SrII taxa and 'Ca. Phytoplasma stylosanthis'. Additionally, six previously unrecorded 16SrII taxa were identified, including five putative subspecies of 'Ca. Phytoplasma australasiaticum' and a new putative 16SrII species. PCR and sequencing of the 16S rRNA gene was a suitable triage tool for preliminary phytoplasma detection. Metagenomic sequencing, however, allowed for higher-resolution identification of the phytoplasmas, including mixed infections, than was afforded by only direct Sanger sequencing of the 16S rRNA gene. Since the metagenomic approach theoretically obtains sequences of all organisms in a sample, this approach was useful to confirm the host family, genus, and/or species. In addition to improving our understanding of the phytoplasma species that affect crop production in Australia, the study also significantly expands the genomic sequence data available in public sequence repositories to contribute to phytoplasma molecular epidemiology studies, revision of taxonomy, and improved diagnostics.

Genome-Resolved Metagenomics and Denitrifying Strain Isolation Reveal New Insights into Microbial Denitrification in the Deep Vadose Zone

The heavy use of nitrogen fertilizer in intensive agricultural areas often leads to nitrate accumulation in subsurface soil and nitrate contamination in groundwater, which poses a serious risk to public health. Denitrifying microorganisms in the subsoil convert nitrate to gaseous forms of nitrogen, thereby mitigating the leaching of nitrate into groundwater. Here, we investigated denitrifying microorganisms in the deep vadose zone of a typical intensive agricultural area in China through microcosm enrichment, genome-resolved metagenomic analysis, and denitrifying bacteria isolation. A total of 1000 metagenome-assembled genomes (MAGs) were reconstructed, resulting in 98 high-quality, dereplicated MAGs that contained denitrification genes. Among them, 32 MAGs could not be taxonomically classified at the genus or species level, indicating that a broader spectrum of taxonomic groups is involved in subsoil denitrification than previously recognized. A denitrifier isolate library was constructed by using a strategy combining high-throughput and conventional cultivation techniques. Assessment of the denitrification characteristics of both the MAGs and isolates demonstrated the dominance of truncated denitrification. Functional screening revealed the highest denitrification activity in two complete denitrifiers belonging to the genus Pseudomonas. These findings greatly expand the current knowledge of the composition and function of denitrifying microorganisms in subsoils. The constructed isolate library provided the first pool of subsoil-denitrifying microorganisms that could facilitate the development of microbe-based technologies for nitrate attenuation in groundwater.

Recovering high-quality bacterial genomes from cross-contaminated cultures: a case study of marine Vibrio campbellii

BACKGROUND

Environmental monitoring of bacterial pathogens is critical for disease control in coastal marine ecosystems to maintain animal welfare and ecosystem function and to prevent significant economic losses. This requires accurate taxonomic identification of environmental bacterial pathogens, which often cannot be achieved by commonly used genetic markers (e.g., 16S rRNA gene), and an understanding of their pathogenic potential based on the information encoded in their genomes. The decreasing costs of whole genome sequencing (WGS), combined with newly developed bioinformatics tools, now make it possible to unravel the full potential of environmental pathogens, beyond traditional microbiological approaches. However, obtaining a high-quality bacterial genome, requires initial cultivation in an axenic culture, which is a bottleneck in environmental microbiology due to cross-contamination in the laboratory or isolation of non-axenic strains.

RESULTS

We applied WGS to determine the pathogenic potential of two Vibrio isolates from coastal seawater. During the analysis, we identified cross-contamination of one of the isolates and decided to use this dataset to evaluate the possibility of bioinformatic contaminant removal and recovery of bacterial genomes from a contaminated culture. Despite the contamination, using an appropriate bioinformatics workflow, we were able to obtain high quality and highly identical genomes (Average Nucleotide Identity value 99.98%) of one of the Vibrio isolates from both the axenic and the contaminated culture. Using the assembled genome, we were able to determine that this isolate belongs to a sub-lineage of Vibrio campbellii associated with several diseases in marine organisms. We also found that the genome of the isolate contains a novel Vibrio plasmid associated with bacterial defense mechanisms and horizontal gene transfer, which may offer a competitive advantage to this putative pathogen.

CONCLUSIONS

Our study shows that, using state-of-the-art bioinformatics tools and a sufficient sequencing effort, it is possible to obtain high quality genomes of the bacteria of interest and perform in-depth genomic analyses even in the case of a contaminated culture. With the new isolate and its complete genome, we are providing new insights into the genomic characteristics and functional potential of this sub-lineage of V. campbellii. The approach described here also highlights the possibility of recovering complete bacterial genomes in the case of non-axenic cultures or obligatory co-cultures.

The long and short of it: benchmarking viromics using Illumina, Nanopore and PacBio sequencing technologies

Viral metagenomics has fuelled a rapid change in our understanding of global viral diversity and ecology. Long-read sequencing and hybrid assembly approaches that combine long- and short-read technologies are now being widely implemented in bacterial genomics and metagenomics. However, the use of long-read sequencing to investigate viral communities is still in its infancy. While Nanopore and PacBio technologies have been applied to viral metagenomics, it is not known to what extent different technologies will impact the reconstruction of the viral community. Thus, we constructed a mock bacteriophage community of previously sequenced phage genomes and sequenced them using Illumina, Nanopore and PacBio sequencing technologies and tested a number of different assembly approaches. When using a single sequencing technology, Illumina assemblies were the best at recovering phage genomes. Nanopore- and PacBio-only assemblies performed poorly in comparison to Illumina in both genome recovery and error rates, which both varied with the assembler used. The best Nanopore assembly had errors that manifested as SNPs and INDELs at frequencies 41 and 157 % higher than found in Illumina only assemblies, respectively. While the best PacBio assemblies had SNPs at frequencies 12 and 78 % higher than found in Illumina-only assemblies, respectively. Despite high-read coverage, long-read-only assemblies recovered a maximum of one complete genome from any assembly, unless reads were down-sampled prior to assembly. Overall the best approach was assembly by a combination of Illumina and Nanopore reads, which reduced error rates to levels comparable with short-read-only assemblies. When using a single technology, Illumina only was the best approach. The differences in genome recovery and error rates between technology and assembler had downstream impacts on gene prediction, viral prediction, and subsequent estimates of diversity within a sample. These findings will provide a starting point for others in the choice of reads and assembly algorithms for the analysis of viromes.

Host DNA depletion methods and genome-centric metagenomics of bovine hindmilk microbiome

Bovine mastitis is a multi-etiological and complex disease, resulting in serious economic consequences for dairy farmers and industry. In recent years, the microbiological evaluation of raw milk has been investigated in-depth using next-generation sequencing approaches such as metataxonomic analysis. Despite this, host DNA is a major concern in the shotgun metagenomic sequencing of microbial communities in milk samples, and it represents a big challenge. In this study, we aimed to evaluate different methods for host DNA depletion and/or microbial DNA enrichment and assess the use of PCR-based whole genome amplification in milk samples with high somatic cell count (SCC) by using short- and long-read sequencing technologies. Our results evidenced that DNA extraction performed differently in terms of host DNA removal, impacting metagenome composition and functional profiles.. Moreover, the ratio of SCC/bacteria ultimately impacts microbial DNA yield, and samples with low SCC (SCC below 100,000 cells/mL) are the most problematic. When milk samples with high SCC (SCC above 200,000 cells/mL) underwent multiple-displacement amplification (MDA), we successfully recovered high-quality metagenome-assembled genomes (MAGs), and long-read sequencing was feasible even for samples with low DNA concentration. By associating MDA and short-read sequencing, we recovered two times more MAGs than in untreated samples, and an ongoing co-infection not reported by traditional methods was detected for mastitis pathogen. Overall, this new approach will improve the detection of mastitis-associated microorganisms and make it possible to examine host-microbiome interactions in bovine mastitis.IMPORTANCENext-generation sequencing technologies have been widely used to gain new insights into the diversity of the microbial community of milk samples and dairy products for different purposes such as microbial safety, profiling of starter cultures, and host-microbiome interactions. Milk is a complex food matrix, and additionally, the presence of host nucleic acid sequences is considered a contaminant in untargeted high-throughput sequencing studies. Therefore, genomic-centric metagenomic studies of milk samples focusing on the health-disease status in dairy cattle are still scarce, which makes it difficult to evaluate the microbial ecophysiology of bovine hindmilk. This study provides an alternative method for genome-centric metagenome studies applied to hindmilk samples with high somatic cell content, which is indispensable to examining host-microbiome interactions in bovine mastitis.

Impact of Anthropogenic Activities on Microbial Community Structure in Riverbed Sediments of East Kazakhstan

Heavy metal (HMe) pollution in regions with mining and metallurgy activities is known to be a serious environmental problem worldwide. Hydrological processes contribute to the dissemination of HMes (drainage, precipitation, flow rate). The aim of the present study is to investigate the microbial community structure in ten river sediments sampled in different regions of East Kazakhstan, which are contaminated with HMes. The overall degree of sediment contamination with HMes (Cr, Cu, Zn, Pb, and Cd) was assessed using the pollution index Zc, which ranged from 0.43 to 21.6, with the highest in Ridder City (Zc = 21.6) and Ust-Kamenogorsk City, 0.8 km below the dam of the hydroelectric power station (Zc = 19.6). The tested samples considerably differed in organic matter, total carbon, nitrogen, and phosphorus content, as well as in the abundance of HMe-related functional gene families and antibiotic resistance genes. Metagenomic analysis of benthic microorganisms showed the prevalence of Proteobacteria (88.84-97.61%) and Actinobacteria (1.21-5.98%) at the phylum level in all samples. At the class level, Actinobacteria (21.68-57.48%), Betaproteobacteria (19.38-41.17%), and Alphaproteobacteria (10.0-39.78%) were the most common among the classified reads. To the best of our knowledge, this is the first study on the metagenomic characteristics of benthic microbial communities exposed to chronic HMe pressure in different regions of East Kazakhstan.

Panax notoginseng stems and leaves affect microbial community and function in cecum of duzang pigs

Panax notoginseng is a Chinese medicine with a long history in which stems and leaves are the wastes of processing Panax notoginseng and have not been effectively utilized. The effects of diets containing Panax notoginseng stems and leaves on the cecal short-chain fatty acid (SCFA) concentration and microbiome of independent pigs were studied. Diets containing Panax notoginseng stems and leaves did not affect the concentration of SCFA in the cecal contents of Duzang pigs but affected the microbial composition and diversity. Firmicutes, Proteobacteria, and Bacteroidetes dominate in the cecal of Duzang pigs. Feeding Duzang pigs with a 10% Panax notoginseng stems and leaves diet increases the abundance of Lactobacillus, Christensenellaceae R-7 group, and Akkermansia in the cecal. We found 14 genera positively associated with acetate, and they were Lactobacillus, Ruminococcaceae UCG 005, Ruminiclostridium 6; Escherichia Shigella and Family XIII AD3011 group showed negative correlations. Solobacterium, Desulfovibrio, and Erysipelatoclostridium were positively associated with propionate. Campylobacter, Clostridium sensu stricto 11, and Angelakisella were positively associated with butyrate. In conclusion, Panax notoginseng stems and leaves could affect the cecal microbial community and functional composition of Duzang pigs. Panax notoginseng stems and leaves reduce the enrichment of lipopolysaccharide biosynthetic pathway of the cecal microbiome, which may have a positive effect on intestinal health. The higher abundance of GH25 family in Duzang pig's cecal microbiome of fed Panax notoginseng stems and leaves diet. This increase may be the reason for the microbial diversity decrease.

Genome sequences of four colistin-resistant ESKAPE bacterial strains isolated from patients within the same hospital

The genomes of four clinical Gram-negative ESKAPE bacterial strains highly resistant to the last-resort antibiotic colistin were sequenced and analyzed. The strains were found to carry multidrug-resistant genes besides colistin-resistant genes.

Metagenomic insights into novel microbial lineages with distinct ecological functions in the Arctic glacier foreland ecosystems

Land-terminating glaciers are retreating globally, resulting in the expansion of the ice-free glacier forelands (GFs). These GFs act as a natural laboratory to study microbial community succession, soil formation, and ecosystem development. Here, we have employed gene-centric and genome-resolved metagenomic approaches to disseminate microbial diversity, community structure, and their associated biogeochemical processes involved in the carbon, nitrogen, and sulfur cycling across three GF ecosystems. Here, we present a compendium of draft Metagenome Assembled Genomes (MAGs) belonging to bacterial (n = 899) and archaeal (n = 4) domains. These MAGs were reconstructed using a total of 27 shotgun metagenomic datasets obtained from three different GFs, including Midtre Lovénbreen glacier (Svalbard), Russell glacier (Greenland), and Storglaciaren (Sweden). The taxonomic classification revealed that 98% of MAGs remained unclassified at species levels, suggesting the presence of novel microbial lineages. The abundance of metabolic genes associated with carbon, nitrogen, and sulfur cycling pathways varied between and within the samples collected across the three GF ecosystems. Our findings indicate that MAGs from different GFs share close phylogenetic relationships but exhibit significant differences in abundance, distribution patterns, and metabolic functions. This compendium of novel MAGs, encompassing autotrophic, phototrophic, and chemolithoautotrophic microbial groups reconstructed from GF ecosystems, represents a valuable resource for further studies.

Aerobic denitrification as an N2O source from microbial communities

Nitrous oxide (N2O) is a potent greenhouse gas of primarily microbial origin. Oxic and anoxic emissions are commonly ascribed to autotrophic nitrification and heterotrophic denitrification, respectively. Beyond this established dichotomy, we quantitatively show that heterotrophic denitrification can significantly contribute to aerobic nitrogen turnover and N2O emissions in complex microbiomes exposed to frequent oxic/anoxic transitions. Two planktonic, nitrification-inhibited enrichment cultures were established under continuous organic carbon and nitrate feeding, and cyclic oxygen availability. Over a third of the influent organic substrate was respired with nitrate as electron acceptor at high oxygen concentrations (>6.5 mg/L). N2O accounted for up to one-quarter of the nitrate reduced under oxic conditions. The enriched microorganisms maintained a constitutive abundance of denitrifying enzymes due to the oxic/anoxic frequencies exceeding their protein turnover-a common scenario in natural and engineered ecosystems. The aerobic denitrification rates are ascribed primarily to the residual activity of anaerobically synthesised enzymes. From an ecological perspective, the selection of organisms capable of sustaining significant denitrifying activity during aeration shows their competitive advantage over other heterotrophs under varying oxygen availabilities. Ultimately, we propose that the contribution of heterotrophic denitrification to aerobic nitrogen turnover and N2O emissions is currently underestimated in dynamic environments.

Metagenomic assembly is the main bottleneck in the identification of mobile genetic elements

Antimicrobial resistance genes (ARG) are commonly found on acquired mobile genetic elements (MGEs) such as plasmids or transposons. Understanding the spread of resistance genes associated with mobile elements (mARGs) across different hosts and environments requires linking ARGs to the existing mobile reservoir within bacterial communities. However, reconstructing mARGs in metagenomic data from diverse ecosystems poses computational challenges, including genome fragment reconstruction (assembly), high-throughput annotation of MGEs, and identification of their association with ARGs. Recently, several bioinformatics tools have been developed to identify assembled fragments of plasmids, phages, and insertion sequence (IS) elements in metagenomic data. These methods can help in understanding the dissemination of mARGs. To streamline the process of identifying mARGs in multiple samples, we combined these tools in an automated high-throughput open-source pipeline, MetaMobilePicker, that identifies ARGs associated with plasmids, IS elements and phages, starting from short metagenomic sequencing reads. This pipeline was used to identify these three elements on a simplified simulated metagenome dataset, comprising whole genome sequences from seven clinically relevant bacterial species containing 55 ARGs, nine plasmids and five phages. The results demonstrated moderate precision for the identification of plasmids (0.57) and phages (0.71), and moderate sensitivity of identification of IS elements (0.58) and ARGs (0.70). In this study, we aim to assess the main causes of this moderate performance of the MGE prediction tools in a comprehensive manner. We conducted a systematic benchmark, considering metagenomic read coverage, contig length cutoffs and investigating the performance of the classification algorithms. Our analysis revealed that the metagenomic assembly process is the primary bottleneck when linking ARGs to identified MGEs in short-read metagenomics sequencing experiments rather than ARGs and MGEs identification by the different tools.

Community-scale models of microbiomes: Articulating metabolic modelling and metagenome sequencing

Building models is essential for understanding the functions and dynamics of microbial communities. Metabolic models built on genome-scale metabolic network reconstructions (GENREs) are especially relevant as a means to decipher the complex interactions occurring among species. Model reconstruction increasingly relies on metagenomics, which permits direct characterisation of naturally occurring communities that may contain organisms that cannot be isolated or cultured. In this review, we provide an overview of the field of metabolic modelling and its increasing reliance on and synergy with metagenomics and bioinformatics. We survey the means of assigning functions and reconstructing metabolic networks from (meta-)genomes, and present the variety and mathematical fundamentals of metabolic models that foster the understanding of microbial dynamics. We emphasise the characterisation of interactions and the scaling of model construction to large communities, two important bottlenecks in the applicability of these models. We give an overview of the current state of the art in metagenome sequencing and bioinformatics analysis, focusing on the reconstruction of genomes in microbial communities. Metagenomics benefits tremendously from third-generation sequencing, and we discuss the opportunities of long-read sequencing, strain-level characterisation and eukaryotic metagenomics. We aim at providing algorithmic and mathematical support, together with tool and application resources, that permit bridging the gap between metagenomics and metabolic modelling.

Evaluation of multiple displacement amplification for metagenomic analysis of low biomass samples

Combining multiple displacement amplification (MDA) with metagenomics enables the analysis of samples with extremely low DNA concentrations, making them suitable for high-throughput sequencing. Although amplification bias and nonspecific amplification have been reported from MDA-amplified samples, the impact of MDA on metagenomic datasets is not well understood. We compared three MDA methods (i.e. bulk MDA, emulsion MDA, and primase MDA) for metagenomic analysis of two DNA template concentrations (approx. 1 and 100 pg) derived from a microbial community standard "mock community" and two low biomass environmental samples (i.e. borehole fluid and groundwater). We assessed the impact of MDA on metagenome-based community composition, assembly quality, functional profiles, and binning. We found amplification bias against high GC content genomes but relatively low nonspecific amplification such as chimeras, artifacts, or contamination for all MDA methods. We observed MDA-associated representational bias for microbial community profiles, especially for low-input DNA and with the primase MDA method. Nevertheless, similar taxa were represented in MDA-amplified libraries to those of unamplified samples. The MDA libraries were highly fragmented, but similar functional profiles to the unamplified libraries were obtained for bulk MDA and emulsion MDA at higher DNA input and across these MDA libraries for the groundwater sample. Medium to low-quality bins were possible for the high input bulk MDA metagenomes for the most simple microbial communities, borehole fluid, and mock community. Although MDA-based amplification should be avoided, it can still reveal meaningful taxonomic and functional information from samples with extremely low DNA concentration where direct metagenomics is otherwise impossible.

First insight into the natural biodegradation of cyanide in a gold tailings environment enriched in cyanide compounds

The disposal of mining wastes that contain cyanide are dumped in tailings from gold extraction is a public concern in mining countries such as South Africa. Many studies have shown the potential of microorganisms to degrade cyanide. However, no in-situ exploration, in tailings contaminated with cyanide, of the capability of indigenous microorganisms to act as a natural barrier for cyanide attenuation has been performed. Here we aim to combine geochemical and metagenomics techniques to reveal the genomic machinery of indigenous bacteria to degrade cyanide in gold tailings. Indigenous bacteria (i.e., Alicyclobacillus, Sulfobacillus, Acinetobacter, Achromobacter, and among others) pose the genomic machinery to trigger hydrolytic cyanide degradation using enzymes such as nitrilase, nitrile hydratase (Nhase) and thiocyanate. It seems that the lack of nitrogen sources induces the use of cyanide, which would contribute to its natural attenuation in the gold tailings. Therefore, the bacteria identified could represent the first barrier for the detoxification and degradation of cyanide in the outermost layer of the tailings.

Putative novel hydrogen- and iron-oxidizing sheath-producing Zetaproteobacteria thrive at the Fåvne deep-sea hydrothermal vent field

IMPORTANCE

Knowledge on microbial iron oxidation is important for understanding the cycling of iron, carbon, nitrogen, nutrients, and metals. The current study yields important insights into the niche sharing, diversification, and Fe(III) oxyhydroxide morphology of Ghiorsea, an iron- and hydrogen-oxidizing Zetaproteobacteria representative belonging to Zetaproteobacteria operational taxonomic unit 9. The study proposes that Ghiorsea exhibits a more extensive morphology of Fe(III) oxyhydroxide than previously observed. Overall, the results increase our knowledge on potential drivers of Zetaproteobacteria diversity in iron microbial mats and can eventually be used to develop strategies for the cultivation of sheath-forming Zetaproteobacteria.

Disentangling a metabolic cross-feeding in a halophilic archaea-bacteria consortium

Microbial syntrophy, a cooperative metabolic interaction among prokaryotes, serves a critical role in shaping communities, due to the auxotrophic nature of many microorganisms. Syntrophy played a key role in the evolution of life, including the hypothesized origin of eukaryotes. In a recent exploration of the microbial mats within the exceptional and uniquely extreme Cuatro Cienegas Basin (CCB), a halophilic isolate, designated as AD140, emerged as a standout due to its distinct growth pattern. Subsequent genome sequencing revealed AD140 to be a co-culture of a halophilic archaeon from the Halorubrum genus and a marine halophilic bacterium, Marinococcus luteus, both occupying the same ecological niche. This intriguing coexistence hints at an early-stage symbiotic relationship that thrives on adaptability. By delving into their metabolic interdependence through genomic analysis, this study aims to uncover shared characteristics that enhance their symbiotic association, offering insights into the evolution of halophilic microorganisms and their remarkable adaptations to high-salinity environments.

Poultry manure-derived microorganisms as a reservoir and source of antibiotic resistance genes transferred to soil autochthonous microorganisms

Animal husbandry is increasing yearly due to the growing demand for meat and livestock products, among other reasons. To meet these demands, prophylactic antibiotics are used in the livestock industry (i.e., poultry farming) to promote health and stimulate animal growth. However, antibiotics are not fully metabolized by animals, and they are evacuated to the environment with excreta. Animal manure is used as fertilizer to reduce the volume of waste generated in the livestock sector. However, manure often contains microorganisms harboring antibiotic resistance genes (ARGs). Then, the microbiome of manure applicate to the soil may contribute to the spread of antibiotic resistance in the environment, including autochthonous soil-dwelling microorganisms. The present study was conducted during the crops growing season in Poland (May to September 2019) to determine the influence of poultry manure as well as poultry manure supplemented with selected antibiotics on the diversity of the soil microbiome in treatments that had not been previously fertilized with manure and the ability of antibiotic-resistant bacteria to transfer ARGs to other soil bacteria. Antibiotic concentrations were elevated at the beginning of the study and decreased over time. Poultry manure induced significant changes in the structure of microbial communities in soil; the diversity of the soil microbiome decreased, and the abundance of bacterial genera Bradyrhizobium, Streptomyces, and Pseudomonas, which are characteristic of the analyzed manure, increased. Over time, soil microbial diversity was restored to the state observed before the application of manure. Genes conferring resistance to multiple drugs as well as genes encoding resistance to bacitracin and aminoglycosides were the most frequently identified ARGs in the analyzed bacteria, including on mobile genetic elements. Multidrug resistance was observed in 17 bacterial taxa, whereas ARGs were identified in 32 bacterial taxa identified in the soil microbiome. The results of the study conclude that the application of poultry manure supplemented with antibiotics initially affects soil microbiome and resistome diversity but finally, the soil shows resilience and returns to its original state after time, with most antibiotic resistance genes disappearing. This phenomenon is of great importance in sustainable soil health after manure application.

Metagenome-assembled genomes from particle-associated microbial communities in the mesopelagic zone of the Pacific Ocean

We report 10 particle-associated metagenome-assembled genomes (MAGs) from the mesopelagic zone of Pacific Ocean seawaters. MAGs comprise members of Flavobacteria Halomonas, Blastomonas, Brevundimonas, Alteromonas, Shingomonas, Sphingopyxis, Tabrizicola, Proteobacteria, and Gammaproteobacteria. Functional annotation suggests that these bacteria are involved in central particulate organic carbon conversion, nitrogen cycling, and phosphorus cycling.

Viromes vs. mixed community metagenomes: choice of method dictates interpretation of viral community ecology

Background

Viruses, the majority of which are uncultivated, are among the most abundant biological entities on Earth. From altering microbial physiology to driving community dynamics, viruses are fundamental members of microbiomes. While the number of studies leveraging viral metagenomics (viromics) for studying uncultivated viruses is growing, standards for viromics research are lacking. Viromics can utilize computational discovery of viruses from total metagenomes of all community members (hereafter metagenomes) or use physical separation of virus-specific fractions (hereafter viromes). However, differences in the recovery and interpretation of viruses from metagenomes and viromes obtained from the same samples remain understudied.

Results

Here, we compare viral communities from paired viromes and metagenomes obtained from 60 diverse samples across human gut, soil, freshwater, and marine ecosystems. Overall, viral communities obtained from viromes were more abundant and species rich than those obtained from metagenomes, although there were some exceptions. Despite this, metagenomes still contained many viral genomes not detected in viromes. We also found notable differences in the predicted lytic state of viruses detected in viromes vs metagenomes at the time of sequencing. Other forms of variation observed include genome presence/absence, genome quality, and encoded protein content between viromes and metagenomes, but the magnitude of these differences varied by environment.

Conclusions

Overall, our results show that the choice of method can lead to differing interpretations of viral community ecology. We suggest that the choice of whether to target a metagenome or virome to study viral communities should be dependent on the environmental context and ecological questions being asked. However, our overall recommendation to researchers investigating viral ecology and evolution is to pair both approaches to maximize their respective benefits.

Comparative analysis of HiSeq3000 and BGISEQ-500 sequencing platform over whole genome sequencing metagenomics data

Recent advances in sequencing technologies and platforms have enabled to generate metagenomics sequences using different sequencing platforms. In this study, we analyzed and compared shotgun metagenomic sequences generated by HiSeq3000 and BGISEQ-500 platforms from 12 sediment samples collected across the Norwegian coast. Metagenomics DNA sequences were normalized to an equal number of bases for both platforms and further evaluated by using different taxonomic classifiers, reference databases, and assemblers. Normalized BGISEQ-500 sequences retained more reads and base counts after preprocessing, while a slightly higher fraction of HiSeq3000 sequences were taxonomically classified. Kaiju classified a higher percentage of reads relative to Kraken2 for both platforms, and comparison of reference database for taxonomic classification showed that MAR database outperformed RefSeq. Assembly using MEGAHIT produced longer assemblies and higher total contigs count in majority of HiSeq3000 samples than using metaSPAdes, but the assembly statistics notably improved with unprocessed or normalized reads. Our results indicate that both platforms perform comparably in terms of the percentage of taxonomically classified reads and assembled contig statistics for metagenomics samples. This study provides valuable insights for researchers in selecting an appropriate sequencing platform and bioinformatics pipeline for their metagenomics studies.

Diversity at single nucleotide to pangenome scales among sulfur cycling bacteria in salt marshes

IMPORTANCE

Salt marshes are known for their significant carbon storage capacity, and sulfur cycling is closely linked with the ecosystem-scale carbon cycling in these ecosystems. Sulfate reducers are key for the decomposition of organic matter, and sulfur oxidizers remove toxic sulfide, supporting the productivity of marsh plants. To date, the complexity of coastal environments, heterogeneity of the rhizosphere, high microbial diversity, and uncultured majority hindered our understanding of the genomic diversity of sulfur-cycling microbes in salt marshes. Here, we use comparative genomics to overcome these challenges and provide an in-depth characterization of sulfur-cycling microbial diversity in salt marshes. We characterize communities across distinct sites and plant species and uncover extensive genomic diversity at the taxon level and specific genomic features present in MAGs affiliated with uncultivated sulfur-cycling lineages. Our work provides insights into the partnerships in salt marshes and a roadmap for multiscale analyses of diversity in complex biological systems.