Nanopore long-read-only metagenomics enables complete and high-quality genome reconstruction from mock and complex metagenomes

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

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

Benchmarking bacterial taxonomic classification using nanopore metagenomics data of several mock communities

Taxonomic classification is crucial in identifying organisms within diverse microbial communities when using metagenomics shotgun sequencing. While second-generation Illumina sequencing still dominates, third-generation nanopore sequencing promises improved classification through longer reads. However, extensive benchmarking studies on nanopore data are lacking. We systematically evaluated performance of bacterial taxonomic classification for metagenomics nanopore sequencing data for several commonly used classifiers, using standardized reference sequence databases, on the largest collection of publicly available data for defined mock communities thus far (nine samples), representing different research domains and application scopes. Our results categorize classifiers into three categories: low precision/high recall; medium precision/medium recall, and high precision/medium recall. Most fall into the first group, although precision can be improved without excessively penalizing recall with suitable abundance filtering. No definitive 'best' classifier emerges, and classifier selection depends on application scope and practical requirements. Although few classifiers designed for long reads exist, they generally exhibit better performance. Our comprehensive benchmarking provides concrete recommendations, supported by publicly available code for reassessment and fine-tuning by other scientists.

Application of single-cell Raman-deuterium isotope probing to reveal the resistance of marine ammonia-oxidizing archaea SCM1 against common antibiotics

Antimicrobial resistance (AMR) in oceans poses a significant threat to human health through the seafood supply chain. Ammonia-oxidizing archaea (AOA) are important marine microorganisms and play a key role in the biogeochemical nitrogen cycle around the world. However, the AMR of marine AOA to aquicultural antibiotics is poorly explored. Here, Raman-deuterium isotope probing (Raman-DIP), a single-cell tool, was developed to reveal the AMR of a typical marine species of AOA, Nitrosopumilus maritimus (designated SCM1), against six antibiotics, including erythromycin, tetracycline, novobiocin, neomycin, bacitracin, and vancomycin. The D2O concentration (30% v/v) and culture period (9 days) were optimized for the precise detection of metabolic activity in SCM1 cells through Raman-DIP. The relative metabolic activity of SCM1 upon exposure to antibiotics was semi-quantitatively calculated based on single-cell Raman spectra. SCM1 exhibited high resistance to erythromycin, tetracycline, novobiocin, neomycin, and vancomycin, with minimum inhibitory concentration (MIC) values between 100 and 400 mg/L, while SCM1 is very sensitive to bacitracin (MIC: 0.8 mg/L). Notably, SCM1 cells were completely inactive under the metabolic activity minimum inhibitory concentration conditions (MA-MIC: 1.6-800 mg/L) for the six antibiotics. Further genomic analysis revealed the antibiotic resistance genes (ARGs) of SCM1, including 14 types categorized into 33 subtypes. This work increases our knowledge of the AMR of marine AOA by linking the resistant phenome to the genome, contributing to the risk assessment of AMR in the underexplored ocean environment. As antibiotic resistance in marine microorganisms is significantly affected by the concentration of antibiotics in coastal environments, we encourage more studies concentrating on both the phenotypic and genotypic antibiotic resistance of marine archaea. This may facilitate a comprehensive evaluation of the capacity of marine microorganisms to spread AMR and the implementation of suitable control measures to protect environmental safety and human health.

Establishing African genomics and bioinformatics programs through annual regional workshops

The African BioGenome Project (AfricaBP) Open Institute for Genomics and Bioinformatics aims to overcome barriers to capacity building through its distributed African regional workshops and prioritizes the exchange of grassroots knowledge and innovation in biodiversity genomics and bioinformatics. In 2023, we implemented 28 workshops on biodiversity genomics and bioinformatics, covering 11 African countries across the 5 African geographical regions. These regional workshops trained 408 African scientists in hands-on molecular biology, genomics and bioinformatics techniques as well as the ethical, legal and social issues associated with acquiring genetic resources. Here, we discuss the implementation of transformative strategies, such as expanding the regional workshop model of AfricaBP to involve multiple countries, institutions and partners, including the proposed creation of an African digital database with sequence information relating to both biodiversity and agriculture. This will ultimately help create a critical mass of skilled genomics and bioinformatics scientists across Africa.

Dirammox-dominated microbial community for biological nitrogen removal from wastewater

Direct ammonia oxidation (Dirammox) might be of great significance to advance the innovation of biological nitrogen removal process in wastewater treatment systems. However, it remains unknown whether Dirammox bacteria can be selectively enriched in activated sludge. In this study, a lab-scale bioreactor was established and operated for 2 months to treat synthetic wastewater with hydroxylamine as a selection pressure. Three Dirammox strains (Alcaligenes aquatilis SDU_AA1, Alcaligenes aquatilis SDU_AA2, and Alcaligenes sp. SDU_A2) were isolated from the activated sludge, and their capability to perform Dirammox process was confirmed. Although these three Dirammox bacteria were undetectable in the seed sludge (0%), their relative abundances rapidly increased after a month of operation, reaching 12.65%, 0.69%, and 0.69% for SDU_A2, SDU_AA1, and SDU_AA2, respectively. Among them, the most dominant Dirammox (SDU_A2) exhibited higher nitrogen removal rate (32.35%) than the other two strains (13.57% of SDU_AA1 and 14.52% of SDU_AA2). Comparative genomic analysis demonstrated that the most dominant Dirammox bacterium (SDU_A2) possesses fewer complete metabolic modules compared to the other two less abundant Alcaligenes strains. Our findings expanded the understanding of the application of Dirammox bacteria as key functional microorganisms in a novel biological nitrogen and carbon removal process if they could be well stabilized. KEY POINTS: • Dirammox-dominated microbial community was enriched in activated sludge bioreactor. • The addition of hydroxylamine played a role in Dirammox enrichment. • Three Dirammox bacterial strains, including one novel species, were isolated.

How low can you go? Short-read polishing of Oxford Nanopore bacterial genome assemblies

It is now possible to assemble near-perfect bacterial genomes using Oxford Nanopore Technologies (ONT) long reads, but short-read polishing is usually required for perfection. However, the effect of short-read depth on polishing performance is not well understood. Here, we introduce Pypolca (with default and careful parameters) and Polypolish v0.6.0 (with a new careful parameter). We then show that: (1) all polishers other than Pypolca-careful, Polypolish-default and Polypolish-careful commonly introduce false-positive errors at low read depth; (2) most of the benefit of short-read polishing occurs by 25× depth; (3) Polypolish-careful almost never introduces false-positive errors at any depth; and (4) Pypolca-careful is the single most effective polisher. Overall, we recommend the following polishing strategies: Polypolish-careful alone when depth is very low (<5×), Polypolish-careful and Pypolca-careful when depth is low (5-25×), and Polypolish-default and Pypolca-careful when depth is sufficient (>25×).

Metabuli: sensitive and specific metagenomic classification via joint analysis of amino acid and DNA

Metagenomic taxonomic classifiers analyze either DNA or amino acid (AA) sequences. Metabuli ( https://metabuli.steineggerlab.com ), however, jointly analyzes both DNA and AA to leverage AA conservation for sensitive homology detection and DNA mutations for specific differentiation of closely related taxa. In the Critical Assessment of Metagenome Interpretation 2 plant-associated dataset, Metabuli covered 99% and 98% of classifications of state-of-the-art DNA- and AA-based classifiers, respectively.

Nanopore adaptive sampling of a metagenomic sample derived from a human monkeypox case

In 2022, a series of human monkeypox cases in multiple countries led to the largest and most widespread outbreak outside the known endemic areas. Setup of proper genomic surveillance is of utmost importance to control such outbreaks. To this end, we performed Nanopore (PromethION P24) and Illumina (NextSeq. 2000) Whole Genome Sequencing (WGS) of a monkeypox sample. Adaptive sampling was applied for in silico depletion of the human host genome, allowing for the enrichment of low abundance viral DNA without a priori knowledge of sample composition. Nanopore sequencing allowed for high viral genome coverage, tracking of sample composition during sequencing, strain determination, and preliminary assessment of mutational pattern. In addition to that, only Nanopore data allowed us to resolve the entire monkeypox virus genome, with respect to two structural variants belonging to the genes OPG015 and OPG208. These SVs in important host range genes seem stable throughout the outbreak and are frequently misassembled and/or misannotated due to the prevalence of short read sequencing or short read first assembly. Ideally, standalone standard Illumina sequencing should not be used for Monkeypox WGS and de novo assembly, since it will obfuscate the structure of the genome, which has an impact on the quality and completeness of the genomes deposited in public databases and thus possibly on the ability to evaluate the complete genetic reason for the host range change of monkeypox in the current pandemic.

Towards facilitated interpretation of shotgun metagenomics long-read sequencing data analyzed with KMA for the detection of bacterial pathogens and their antimicrobial resistance genes

Metagenomic sequencing is a promising method that has the potential to revolutionize the world of pathogen detection and antimicrobial resistance (AMR) surveillance in food-producing environments. However, the analysis of the huge amount of data obtained requires performant bioinformatics tools and databases, with intuitive and straightforward interpretation. In this study, based on long-read metagenomics data of chicken fecal samples with a spike-in mock community, we proposed confidence levels for taxonomic identification and AMR gene detection, with interpretation guidelines, to help with the analysis of the output data generated by KMA, a popular k-mer read alignment tool. Additionally, we demonstrated that the completeness and diversity of the genomes present in the reference databases are key parameters for accurate and easy interpretation of the sequencing data. Finally, we explored whether KMA, in a two-step procedure, can be used to link the detected AMR genes to their bacterial host chromosome, both detected within the same long-reads. The confidence levels were successfully tested on 28 metagenomics datasets which were obtained with sequencing of real and spiked samples from fecal (chicken, pig, and buffalo) or food (minced beef and food enzyme products) origin. The methodology proposed in this study will facilitate the analysis of metagenomics sequencing datasets for KMA users. Ultimately, this will contribute to improvements in the rapid diagnosis and surveillance of pathogens and AMR genes in food-producing environments, as prioritized by the EU.

Nanopore and Illumina sequencing reveal different viral populations from human gut samples

The advent of viral metagenomics, or viromics, has improved our knowledge and understanding of global viral diversity. High-throughput sequencing technologies enable explorations of the ecological roles, contributions to host metabolism, and the influence of viruses in various environments, including the human intestinal microbiome. However, bacterial metagenomic studies frequently have the advantage. The adoption of advanced technologies like long-read sequencing has the potential to be transformative in refining viromics and metagenomics. Here, we examined the effectiveness of long-read and hybrid sequencing by comparing Illumina short-read and Oxford Nanopore Technology (ONT) long-read sequencing technologies and different assembly strategies on recovering viral genomes from human faecal samples. Our findings showed that if a single sequencing technology is to be chosen for virome analysis, Illumina is preferable due to its superior ability to recover fully resolved viral genomes and minimise erroneous genomes. While ONT assemblies were effective in recovering viral diversity, the challenges related to input requirements and the necessity for amplification made it less ideal as a standalone solution. However, using a combined, hybrid approach enabled a more authentic representation of viral diversity to be obtained within samples.

A CRISPR-based strategy for targeted sequencing in biodiversity science

Many applications in molecular ecology require the ability to match specific DNA sequences from single- or mixed-species samples with a diagnostic reference library. Widely used methods for DNA barcoding and metabarcoding employ PCR and amplicon sequencing to identify taxa based on target sequences, but the target-specific enrichment capabilities of CRISPR-Cas systems may offer advantages in some applications. We identified 54,837 CRISPR-Cas guide RNAs that may be useful for enriching chloroplast DNA across phylogenetically diverse plant species. We tested a subset of 17 guide RNAs in vitro to enrich plant DNA strands ranging in size from diagnostic DNA barcodes of 1,428 bp to entire chloroplast genomes of 121,284 bp. We used an Oxford Nanopore sequencer to evaluate sequencing success based on both single- and mixed-species samples, which yielded mean chloroplast sequence lengths of 2,530-11,367 bp, depending on the experiment. In comparison to mixed-species experiments, single-species experiments yielded more on-target sequence reads and greater mean pairwise identity between contigs and the plant species' reference genomes. But nevertheless, these mixed-species experiments yielded sufficient data to provide ≥48-fold increase in sequence length and better estimates of relative abundance for a commercially prepared mixture of plant species compared to DNA metabarcoding based on the chloroplast trnL-P6 marker. Prior work developed CRISPR-based enrichment protocols for long-read sequencing and our experiments pioneered its use for plant DNA barcoding and chloroplast assemblies that may have advantages over workflows that require PCR and short-read sequencing. Future work would benefit from continuing to develop in vitro and in silico methods for CRISPR-based analyses of mixed-species samples, especially when the appropriate reference genomes for contig assembly cannot be known a priori.

Metagenomic absolute quantification of antibiotic resistance genes and virulence factor genes-carrying bacterial genomes in anaerobic digesters

Sewage treatment works have been considered as hotspots for the dissemination of antibiotic resistance genes (ARGs). Anaerobic digestion (AD) has emerged as a promising approach for controlling the spread of ARGs while destroying biomass in sludge. Evaluating the impact of AD on ARG removal relies on the absolute quantification of ARGs. In this study, we quantified the ARG concentrations in both full-scale and lab-scale AD systems using a cellular spike-ins based absolute quantification approach. Results demonstrated that AD effectively removed 68 ± 18 %, 55 ± 12 %, and 57 ± 19 % of total ARGs in semi-continuous AD digesters, with solid retention times of 15, 20, and 25 days, respectively. The removal efficiency of total ARGs increased as the AD process progressed in the batch digesters over 40 days. A significant negative correlation was observed between digestion time and the concentrations of certain ARG types, such as beta-lactam, sulfonamide, and tetracycline. However, certain potential pathogenic antibiotic resistant bacteria (PARB) and multi-resistant high-risk ARGs-carrying populations robustly persisted throughout the AD process, regardless of the operating conditions. This study highlighted the influence of the AD process and its operating parameters on ARG removal, and revealed the broad spectrum and persistence of PARB in AD systems. These findings provided critical insights for the management of microbial hazards.

Functional traits and health implications of the global household drinking-water microbiome retrieved using an integrative genome-centric approach

The biological safety of drinking water plays a crucial role in public health protection. However, research on the drinking water microbiome remains in its infancy, especially little is known about the potentially pathogenic bacteria in and functional characteristics of the microbiome in household tap water that people are directly exposed to. In this study, we used a genomic-centric approach to construct a genetic catalogue of the drinking water microbiome by analysing 116 metagenomic datasets of household tap water worldwide, spanning nine countries/regions on five continents. We reconstructed 859 high-quality metagenome-assembled genomes (MAGs) spanning 27 bacterial and 2 archaeal phyla, and found that the core MAGs belonging to the phylum Proteobacteria encoded the highest metabolic functional diversity of the 33 key complete metabolic modules. In particular, we found that two core MAGs of Brevibacillus and Methylomona encoded genes for methane metabolism, which may support the growth of heterotrophic organisms observed in the oligotrophic ecosystem. Four MAGs of complete ammonia oxidation (comammox) Nitrospira were identified and functional metabolic analysis suggested these may enable mixotrophic growth and encode genes for reactive oxygen stress defence and arsenite reduction that could aid survival in the environment of oligotrophic drinking water systems. Four MAGs were annotated as potentially pathogenic bacteria (PPB) and thus represented a possible public health concern. They belonged to the genera Acinetobacter (n = 3) and Mycobacterium (n = 1), with a total relative abundance of 1.06 % in all samples. The genomes of PPB A. junii and A. ursingii were discovered to contain antibiotic resistance genes and mobile genetic elements that could contribute to antimicrobial dissemination in drinking water. Further network analysis suggested that symbiotic microbes which support the growth of pathogenic bacteria can be targets for future surveillance and removal.

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

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

High-quality metagenome assembly from long accurate reads with metaMDBG

We introduce metaMDBG, a metagenomics assembler for PacBio HiFi reads. MetaMDBG combines a de Bruijn graph assembly in a minimizer space with an iterative assembly over sequences of minimizers to address variations in genome coverage depth and an abundance-based filtering strategy to simplify strain complexity. For complex communities, we obtained up to twice as many high-quality circularized prokaryotic metagenome-assembled genomes as existing methods and had better recovery of viruses and plasmids.

Metabolically-versatile Ca. Thiodiazotropha symbionts of the deep-sea lucinid clam Lucinoma kazani have the genetic potential to fix nitrogen

Lucinid clams are one of the most diverse and widespread symbiont-bearing animal groups in both shallow and deep-sea chemosynthetic habitats. Lucinids harbor Ca. Thiodiazotropha symbionts that can oxidize inorganic and organic substrates such as hydrogen sulfide and formate to gain energy. The interplay between these key metabolic functions, nutrient uptake and biotic interactions in Ca. Thiodiazotropha is not fully understood. We collected Lucinoma kazani individuals from next to a deep-sea brine pool in the eastern Mediterranean Sea, at a depth of 1150 m and used Oxford Nanopore and Illumina sequencing to obtain high-quality genomes of their Ca. Thiodiazotropha gloverae symbiont. The genomes served as the basis for transcriptomic and proteomic analyses to characterize the in situ gene expression, metabolism and physiology of the symbionts. We found genes needed for N2 fixation in the deep-sea symbiont's genome, which, to date, were only found in shallow-water Ca. Thiodiazotropha. However, we did not detect the expression of these genes and thus the potential role of nitrogen fixation in this symbiosis remains to be determined. We also found the high expression of carbon fixation and sulfur oxidation genes, which indicate chemolithoautotrophy as the key physiology of Ca. Thiodiazotropha. However, we also detected the expression of pathways for using methanol and formate as energy sources. Our findings highlight the key traits these microbes maintain to support the nutrition of their hosts and interact with them.

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.

Dancing the Nanopore limbo - Nanopore metagenomics from small DNA quantities for bacterial genome reconstruction

BACKGROUND

While genome-resolved metagenomics has revolutionized our understanding of microbial and genetic diversity in environmental samples, assemblies of short-reads often result in incomplete and/or highly fragmented metagenome-assembled genomes (MAGs), hampering in-depth genomics. Although Nanopore sequencing has increasingly been used in microbial metagenomics as long reads greatly improve the assembly quality of MAGs, the recommended DNA quantity usually exceeds the recoverable amount of DNA of environmental samples. Here, we evaluated lower-than-recommended DNA quantities for Nanopore library preparation by determining sequencing quality, community composition, assembly quality and recovery of MAGs.

RESULTS

We generated 27 Nanopore metagenomes using the commercially available ZYMO mock community and varied the amount of input DNA from 1000 ng (the recommended minimum) down to 1 ng in eight steps. The quality of the generated reads remained stable across all input levels. The read mapping accuracy, which reflects how well the reads match a known reference genome, was consistently high across all libraries. The relative abundance of the species in the metagenomes was stable down to input levels of 50 ng. High-quality MAGs (> 95% completeness, ≤ 5% contamination) could be recovered from metagenomes down to 35 ng of input material. When combined with publicly available Illumina reads for the mock community, Nanopore reads from input quantities as low as 1 ng improved the quality of hybrid assemblies.

CONCLUSION

Our results show that the recommended DNA amount for Nanopore library preparation can be substantially reduced without any adverse effects to genome recovery and still bolster hybrid assemblies when combined with short-read data. We posit that the results presented herein will enable studies to improve genome recovery from low-biomass environments, enhancing microbiome understanding.

A novel culture-enriched metagenomic sequencing strategy effectively guarantee the microbial safety of drinking water by uncovering the low abundance pathogens

Assessing the presence of waterborne pathogens and antibiotic resistance genes (ARGs) is crucial for managing the environmental quality of drinking water sources. However, detecting low abundance pathogens in such settings is challenging. In this study, a workflow was developed to enrich for broad spectrum pathogens from drinking water samples. A mock community was used to evaluate the effectiveness of various enrichment broths in detecting low-abundance pathogens. Monthly metagenomic surveillance was conducted in a drinking water source from May to September 2021, and water samples were subjected to five enrichment procedures for 6 h to recover the majority of waterborne bacterial pathogens. Oxford Nanopore Technology (ONT) was used for metagenomic sequencing of enriched samples to obtain high-quality pathogen genomes. The results showed that selective enrichment significantly increased the proportions of targeted bacterial pathogens. Compared to direct metagenomic sequencing of untreated water samples, targeted enrichment followed by ONT sequencing significantly improved the detection of waterborne pathogens and the quality of metagenome-assembled genomes (MAGs). Eighty-six high-quality MAGs, including 70 pathogen MAGs, were obtained from ONT sequencing, while only 12 MAGs representing 10 species were obtained from direct metagenomic sequencing of untreated water samples. In addition, ONT sequencing improved the recovery of mobile genetic elements and the accuracy of phylogenetic analysis. This study highlights the urgent need for efficient methodologies to detect and manage microbial risks in drinking water sources. The developed workflow provides a cost-effective approach for environmental management of drinking water sources with microbial risks. The study also uncovered pathogens that were not detected by traditional methods, thereby advancing microbial risk management of drinking water sources.

Comparison of de novo assembly using long-read shotgun metagenomic sequencing of viruses in fecal and serum samples from marine mammals

Introduction

Viral diseases of marine mammals are difficult to study, and this has led to a limited knowledge on emerging known and unknown viruses which are ongoing threats to animal health. Viruses are the leading cause of infectious disease-induced mass mortality events among marine mammals.

Methods

In this study, we performed viral metagenomics in stool and serum samples from California sea lions (Zalophus californianus) and bottlenose dolphins (Tursiops truncates) using long-read nanopore sequencing. Two widely used long-read de novo assemblers, Canu and Metaflye, were evaluated to assemble viral metagenomic sequencing reads from marine mammals.

Results

Both Metaflye and Canu assembled similar viral contigs of vertebrates, such as Parvoviridae, and Poxviridae. Metaflye assembled viral contigs that aligned with one viral family that was not reproduced by Canu, while Canu assembled viral contigs that aligned with seven viral families that was not reproduced by Metaflye. Only Canu assembled viral contigs from dolphin and sea lion fecal samples that matched both protein and nucleotide RefSeq viral databases using BLASTx and BLASTn for Anelloviridae, Parvoviridae and Circoviridae families. Viral contigs assembled with Canu aligned with torque teno viruses and anelloviruses from vertebrate hosts. Viruses associated with invertebrate hosts including densoviruses, Ambidensovirus, and various Circoviridae isolates were also aligned. Some of the invertebrate and vertebrate viruses reported here are known to potentially cause mortality events and/or disease in different seals, sea stars, fish, and bivalve species.

Discussion

Canu performed better by producing the most viral contigs as compared to Metaflye with assemblies aligning to both protein and nucleotide databases. This study suggests that marine mammals can be used as important sentinels to surveil marine viruses that can potentially cause diseases in vertebrate and invertebrate hosts.

Uncultured prokaryotic genomes in the spotlight: An examination of publicly available data from metagenomics and single-cell genomics

Owing to the ineffectiveness of traditional culture techniques for the vast majority of microbial species, culture-independent analyses utilizing next-generation sequencing and bioinformatics have become essential for gaining insight into microbial ecology and function. This mini-review focuses on two essential methods for obtaining genetic information from uncultured prokaryotes, metagenomics and single-cell genomics. We analyzed the registration status of uncultured prokaryotic genome data from major public databases and assessed the advantages and limitations of both the methods. Metagenomics generates a significant quantity of sequence data and multiple prokaryotic genomes using straightforward experimental procedures. However, in ecosystems with high microbial diversity, such as soil, most genes are presented as brief, disconnected contigs, and lack association of highly conserved genes and mobile genetic elements with individual species genomes. Although technically more challenging, single-cell genomics offers valuable insights into complex ecosystems by providing strain-resolved genomes, addressing issues in metagenomics. Recent technological advancements, such as long-read sequencing, machine learning algorithms, and in silico protein structure prediction, in combination with vast genomic data, have the potential to overcome the current technical challenges and facilitate a deeper understanding of uncultured microbial ecosystems and microbial dark matter genes and proteins. In light of this, it is imperative that continued innovation in both methods and technologies take place to create high-quality reference genome databases that will support future microbial research and industrial applications.

Illuminating the oral microbiome and its host interactions: recent advancements in omics and bioinformatics technologies in the context of oral microbiome research

The oral microbiota has an enormous impact on human health, with oral dysbiosis now linked to many oral and systemic diseases. Recent advancements in sequencing, mass spectrometry, bioinformatics, computational biology, and machine learning are revolutionizing oral microbiome research, enabling analysis at an unprecedented scale and level of resolution using omics approaches. This review contains a comprehensive perspective of the current state-of-the-art tools available to perform genomics, metagenomics, phylogenomics, pangenomics, transcriptomics, proteomics, metabolomics, lipidomics, and multi-omics analysis on (all) microbiomes, and then provides examples of how the techniques have been applied to research of the oral microbiome, specifically. Key findings of these studies and remaining challenges for the field are highlighted. Although the methods discussed here are placed in the context of their contributions to oral microbiome research specifically, they are pertinent to the study of any microbiome, and the intended audience of this includes researchers would simply like to get an introduction to microbial omics and/or an update on the latest omics methods. Continued research of the oral microbiota using omics approaches is crucial and will lead to dramatic improvements in human health, longevity, and quality of life.

Guidelines for microbiome studies in renal physiology

Gut microbiome research has increased dramatically in the last decade, including in renal health and disease. The field is moving from experiments showing mere association to causation using both forward and reverse microbiome approaches, leveraging tools such as germ-free animals, treatment with antibiotics, and fecal microbiota transplantations. However, we are still seeing a gap between discovery and translation that needs to be addressed, so that patients can benefit from microbiome-based therapies. In this guideline paper, we discuss the key considerations that affect the gut microbiome of animals and clinical studies assessing renal function, many of which are often overlooked, resulting in false-positive results. For animal studies, these include suppliers, acclimatization, baseline microbiota and its normalization, littermates and cohort/cage effects, diet, sex differences, age, circadian differences, antibiotics and sweeteners, and models used. Clinical studies have some unique considerations, which include sampling, gut transit time, dietary records, medication, and renal phenotypes. We provide best-practice guidance on sampling, storage, DNA extraction, and methods for microbial DNA sequencing (both 16S rRNA and shotgun metagenome). Finally, we discuss follow-up analyses, including tools available, metrics, and their interpretation, and the key challenges ahead in the microbiome field. By standardizing study designs, methods, and reporting, we will accelerate the findings from discovery to translation and result in new microbiome-based therapies that may improve renal health.

Wood-Ljungdahl pathway found in novel marine Korarchaeota groups illuminates their evolutionary history

Korarchaeota, due to its rarity in common environments, is one of the archaeal phyla that has received the least attention from researchers. It was previously thought to consist solely of strict thermophiles. However, our study provides genetic evidence for the presence of korarchaeal members in temperate subsurface seawater. Furthermore, a systematic reclassification of the Korarchaeota based on 16S rRNA genes and genomes has revealed three novel marine groups (Kor-6 to Kor-8) at the root of the Korarchaeota branch. Kor-6 contains microbes that are present in moderate temperatures. All three novel marine phyla possess genes for the Wood-Ljungdahl pathway, and Kor-7 and Kor-8 possess fewer genes encoding oxygen resistance traits than other korarchaeal groups, suggesting a distinct lifestyle for these novel phyla. Our results, together with estimations of Korarchaeota divergence times, suggest that oxygen availability may be one of the important factors that have influenced the evolution of Korarchaeota. IMPORTANCE Korarchaeota were previously thought to inhabit exclusively high-temperature environments. However, our study provides genetic evidence for their unexpected presence in temperate marine waters. Through analysis of publicly available korarchaeal reference data, we have systematically reclassified Korarchaeota and identified the existence of three previously unknown marine groups (Kor-6, Kor-7, and Kor-8) at the root of the Korarchaeota branch. Comparative analysis of their gene content revealed that these novel groups exhibit a lifestyle distinct from other Korarchaeota. Specifically, they have the ability to fix carbon exclusively via the Wood-Ljungdahl (WL) pathway, and the genomes within Kor-7 and Kor-8 contain few genes encoding antioxidant enzymes, indicating their strictly anaerobic lifestyle. Further studies suggest that the genes related to methane metabolism and the WL pathway may have been inherited from a common ancestor of the Korarchaeota and that oxygen availability may be one of the important evolutionary factors that shaped the diversification of this archaeal phylum.

Dwell Time Prolongation and Identification of Single Nucleotides Passing through a Solid-State Nanopore by Using Ammonium Sulfate Aqueous Solution

The ionic current blockades when poly(dT)₆₀ or dNTPs passed through SiN nanopores in an aqueous solution containing (NH₄)₂SO₄ were investigated. The dwell time of poly(dT)₆₀ in the nanopores in an aqueous solution containing (NH₄)₂SO₄ was significantly longer compared to that in an aqueous solution that did not contain (NH₄)₂SO₄. This dwell time prolongation effect due to the aqueous solution containing (NH₄)₂SO₄ was also confirmed when dCTP passed through the nanopores. In addition, when the nanopores were fabricated via dielectric breakdown in the aqueous solution containing (NH₄)₂SO₄, the dwell time prolongation effect for dCTP still occurred even after the aqueous solution was displaced with the aqueous solution without (NH₄)₂SO₄. Furthermore, we measured the ionic current blockades when the four types of dNTPs passed through the same nanopore, and the four types of dNTPs could be statistically identified according to their current blockade values.

Linear time complexity de novo long read genome assembly with GoldRush

Current state-of-the-art de novo long read genome assemblers follow the Overlap-Layout-Consensus paradigm. While read-to-read overlap - its most costly step - was improved in modern long read genome assemblers, these tools still often require excessive RAM when assembling a typical human dataset. Our work departs from this paradigm, foregoing all-vs-all sequence alignments in favor of a dynamic data structure implemented in GoldRush, a de novo long read genome assembly algorithm with linear time complexity. We tested GoldRush on Oxford Nanopore Technologies long sequencing read datasets with different base error profiles sourced from three human cell lines, rice, and tomato. Here, we show that GoldRush achieves assembly scaffold NGA50 lengths of 18.3-22.2, 0.3 and 2.6 Mbp, for the genomes of human, rice, and tomato, respectively, and assembles each genome within a day, using at most 54.5 GB of random-access memory, demonstrating the scalability of our genome assembly paradigm and its implementation.

Viruses of sulfur oxidizing phototrophs encode genes for pigment, carbon, and sulfur metabolisms

Viral infections modulate bacterial metabolism and ecology. Here, we investigated the hypothesis that viruses influence the ecology of purple and green sulfur bacteria in anoxic and sulfidic lakes, analogs of euxinic oceans in the geologic past. By screening metagenomes from lake sediments and water column, in addition to publicly-available genomes of cultured purple and green sulfur bacteria, we identified almost 300 high and medium-quality viral genomes. Viruses carrying the gene psbA, encoding the small subunit of photosystem II protein D1, were ubiquitous, suggesting viral interference with the light reactions of sulfur oxidizing autotrophs. Viruses predicted to infect these autotrophs also encoded auxiliary metabolic genes for reductive sulfur assimilation as cysteine, pigment production, and carbon fixation. These observations show that viruses have the genomic potential to modulate the production of metabolic markers of phototrophic sulfur bacteria that are used to identify photic zone euxinia in the geologic past.

Nanopore-Based Metagenomic Sequencing in Respiratory Tract Infection: A Developing Diagnostic Platform

Respiratory tract infection (RTI) remains a significant cause of morbidity and mortality across the globe. The optimal management of RTI relies upon timely pathogen identification via evaluation of respiratory samples, a process which utilises traditional culture-based methods to identify offending microorganisms. This process can be slow and often prolongs the use of broad-spectrum antimicrobial therapy, whilst also delaying the introduction of targeted therapy as a result. Nanopore sequencing (NPS) of respiratory samples has recently emerged as a potential diagnostic tool in RTI. NPS can identify pathogens and antimicrobial resistance profiles with greater speed and efficiency than traditional sputum culture-based methods. Increased speed to pathogen identification can improve antimicrobial stewardship by reducing the use of broad-spectrum antibiotic therapy, as well as improving overall clinical outcomes. This new technology is becoming more affordable and accessible, with some NPS platforms requiring minimal sample preparation and laboratory infrastructure. However, questions regarding clinical utility and how best to implement NPS technology within RTI diagnostic pathways remain unanswered. In this review, we introduce NPS as a technology and as a diagnostic tool in RTI in various settings, before discussing the advantages and limitations of NPS, and finally what the future might hold for NPS platforms in RTI diagnostics.