Long-read Metagenomics Research Articles

Taxometer: Improving taxonomic classification of metagenomics contigs

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

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

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.

Metagenomic evaluation of bacteria in drinking water using full-length 16S rRNA amplicons.

Escherichia coli and total coliforms are important tools for identifying potential faecal contamination in drinking water. However, metagenomics offers a powerful approach for delving deeper into a bacterial community when E. coli or total coliforms are detected. Metagenomics can identify microbes native to water systems, track community changes and potential pathogens introduced by contamination events, and evaluate the effectiveness of treatment processes. Here, we demonstrate how the dual application of traditional monitoring practices and metagenomics can improve monitoring and surveillance for water resource management. The robustness of long-read metagenomics across replicates is demonstrated by the effect and interaction between manganese filters and bacterial communities, as well as the impact of chlorination after coliform detection. These examples reveal how metagenomics can identify the complex bacterial communities in the distribution system and the source waters used to supply drinking water treatment plants (DWTPs). The knowledge gained increases confidence in identified causes and mitigations of potential contamination events. By exploring bacterial communities, we can gain additional insights into the impact of faecal contamination events and treatment processes. This insight enables more precise remediation actions and enhances confidence in communicating health risks to drinking water operators and the public.

The drainome: longitudinal metagenomic characterization of wastewater from hospital ward sinks to characterize the microbiome and resistome and to assess the effects of decontamination interventions

BackgroundHospital drains and water interfaces are implicated in nosocomial transmission of pathogens. Metagenomics can assess the microbial composition and presence of antimicrobial resistance genes in drains (‘the drainome’) but studies applying these methods longitudinally and to assess infection control interventions are lacking. AimApply long-read metagenomics coupled with microbiological measurements to investigate the drainome and assess the effects of a peracetic acid-containing decontamination product. Methods12-week study in three phases: a baseline phase, an intervention phase of enhanced decontamination with peracetic acid, and a post-intervention phase. Five hospital sink drains on an intensive care unit were sampled twice weekly. Each sample had 1) measurement of total viable count (TVC), 2) metagenomic analyses including i) taxonomic classification of bacteria and fungi ii) antibiotic resistance gene detection iii) plasmid identification, and 3) immunochromatographic detection of antimicrobial residues. FindingsOverall TVCs remain unchanged in the intervention phase (+386 CFU/mL, SE 705, p=0.59). There was a small but significant increase in the microbial diversity in the intervention phase (-0.07 in Simpson’s index, SE 0.03, p=0.007), which was not sustained post-intervention (-0.05, SE 0.03, p=0.08). The intervention was associated with increased relative abundance of the Pseudomonas genus (18.3% to 40.5% [+22.2%], SE 5.7%, p<0.001). Extended spectrum beta-lactamases were found in all samples, with NDM-carbapenemase found in 3 drains in 6 samples. Antimicrobial residues were detected in a large proportion of samples (31/115, 27%), suggesting use of sinks for non-handwashing activities. ConclusionsMetagenomics and other measurements can measure the composition of the drainome and assess the effectiveness of decontamination interventions.

A microbiome survey of contrasting potato terroirs using 16S rRNA long-read sequencing

Abstract Aims As a consequence of the increasing impact of climate change on crop production and food security worldwide, the need to explore agricultural systems in a sustainable manner is also intensified. The improvement of long-read metagenomics approaches might give valuable information not only on soil microbial communities, but also on their potential effects on plant phenotypes. Soil properties, climate conditions, and agricultural techniques are the main factors shaping microbial communities found in the soil and on the surface of the potatoes, influencing plant health and performance. The objective of this study was to decipher the bacterial communities in contrasting potato terroirs using long-read sequencing of the 16S rRNA gene. Methods To do so, 18 soil samples were taken from different potato fields in the island of Naxos (Island Terroir) and Northern Greece (Continental Terroir). Differences in soil properties and climatic conditions were also regarded to explore the possible motif of microbial structure and diversity in each region. Results Our results highlighted that contrasting potato terroirs strongly affected microbial community composition and diversity. A richer microbial composition in the island terroir was evident. A wide range of soil bacteria were identified, including Vicinamibacter, Neobacillus, Povalibacter, Microvirga, Thermoanaerobaculum, Arenimonas, and Rubrobacter, with different distribution patterns that resulted in characteristic microbial footprints. Conclusions In combination with soil analysis, microbial mapping might be a valuable tool, not only for gaining a deeper knowledge of their impact on potato production, but also for developing biomarkers that would uniquely define and characterize each potato habitat.

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.

Sensitivity and consistency of long- and short-read metagenomics and epicPCR for the detection of antibiotic resistance genes and their bacterial hosts in wastewater

Wastewater surveillance is a powerful tool to assess the risks associated with antibiotic resistance in communities. One challenge is selecting which analytical tool to deploy to measure risk indicators, such as antibiotic resistance genes (ARGs) and their respective bacterial hosts. Although metagenomics is frequently used for analyzing ARGs, few studies have compared the performance of long-read and short-read metagenomics in identifying which bacteria harbor ARGs in wastewater. Furthermore, for ARG host detection, untargeted metagenomics has not been compared to targeted methods such as epicPCR. Here, we 1) evaluated long-read and short-read metagenomics as well as epicPCR for detecting ARG hosts in wastewater, and 2) investigated the host range of ARGs across the wastewater treatment plant (WWTP) to evaluate host proliferation. Results highlighted long-read revealed a wider range of ARG hosts compared to short-read metagenomics. Nonetheless, the ARG host range detected by long-read metagenomics only represented a subset of the hosts detected by epicPCR. The ARG-host linkages across the influent and effluent of the WWTP were characterized. Results showed the ARG-host phylum linkages were relatively consistent across the WWTP, whereas new ARG-host species linkages appeared in the WWTP effluent. The ARG-host linkages of several clinically relevant species found in the effluent were identified.

Insights into gut microbiomes in stem cell transplantation by comprehensive shotgun long-read sequencing

The gut microbiome is a diverse ecosystem, dominated by bacteria; however, fungi, phages/viruses, archaea, and protozoa are also important members of the gut microbiota. Exploration of taxonomic compositions beyond bacteria as well as an understanding of the interaction between the bacteriome with the other members is limited using 16S rDNA sequencing. Here, we developed a pipeline enabling the simultaneous interrogation of the gut microbiome (bacteriome, mycobiome, archaeome, eukaryome, DNA virome) and of antibiotic resistance genes based on optimized long-read shotgun metagenomics protocols and custom bioinformatics. Using our pipeline we investigated the longitudinal composition of the gut microbiome in an exploratory clinical study in patients undergoing allogeneic hematopoietic stem cell transplantation (alloHSCT; n = 31). Pre-transplantation microbiomes exhibited a 3-cluster structure, characterized by Bacteroides spp. /Phocaeicola spp., mixed composition and Enterococcus abundances. We revealed substantial inter-individual and temporal variabilities of microbial domain compositions, human DNA, and antibiotic resistance genes during the course of alloHSCT. Interestingly, viruses and fungi accounted for substantial proportions of microbiome content in individual samples. In the course of HSCT, bacterial strains were stable or newly acquired. Our results demonstrate the disruptive potential of alloHSCTon the gut microbiome and pave the way for future comprehensive microbiome studies based on long-read metagenomics.

Spatiotemporal dynamics of giant viruses within a deep freshwater lake reveal a distinct dark-water community.

Giant viruses (GVs) significantly regulate the ecological dynamics of diverse ecosystems. Although metagenomics has expanded our understanding of their diversity and ecological roles played in marine environments, little is known about GVs of freshwater ecosystems. Most previous studies have employed short-read sequencing and therefore resulted in fragmented genomes, hampering accurate assessment of genetic diversity. We sought to bridge this knowledge gap and overcome previous technical limitations. We subjected spatiotemporal (2 depths × 12months) samples from Lake Biwa to metagenome-assembled genome reconstruction enhanced by long-read metagenomics. This yielded 293 GV metagenome-assembled genomes. Of these, 285 included previously unknown species in five orders of nucleocytoviruses and the first representatives of freshwater mirusviruses, which exhibited marked divergence from marine-derived lineages. The good performance of our long-read metagenomic assembly was demonstrated by the detection of 42 (14.3%) genomes composed of single contigs with completeness values >90%. GVs were partitioned across water depths, with most species specific to either the sunlit epilimnion or the dark hypolimnion. Epilimnion-specific members tended to be transient and exhibit short and intense abundance peaks, in line with the fact that they regulate the surface algal blooms. During the spring bloom, mirusviruses and members of three nucleocytovirus families were among the most abundant viruses. In contrast, hypolimnion-specific ones, including a mirusvirus genome, were typically more persistent in the hypolimnion throughout the water-stratified period, suggesting that they infect hosts specific to the hypolimnion and play previously unexplored ecological roles in dark water microbial ecosystems.

Long-Read Metagenomics of Marine Microbes Reveals Diversely Expressed Secondary Metabolites.

Microbial secondary metabolites play crucial roles in microbial competition, communication, resource acquisition, antibiotic production, and a variety of other biotechnological processes. The retrieval of full-length BGC (biosynthetic gene cluster) sequences from uncultivated bacteria is difficult due to the technical constraints of short-read sequencing, making it impossible to determine BGC diversity. Using long-read sequencing and genome mining, 339 mainly full-length BGCs were recovered in this study, illuminating the wide range of BGCs from uncultivated lineages discovered in seawater from Aoshan Bay, Yellow Sea, China. Many extremely diverse BGCs were discovered in bacterial phyla such as Proteobacteria, Bacteroidota, Acidobacteriota, and Verrucomicrobiota as well as the previously uncultured archaeal phylum "Candidatus Thermoplasmatota." The data from metatranscriptomics showed that 30.1% of secondary metabolic genes were being expressed, and they also revealed the expression pattern of BGC core biosynthetic genes and tailoring enzymes. Taken together, our results demonstrate that long-read metagenomic sequencing combined with metatranscriptomic analysis provides a direct view into the functional expression of BGCs in environmental processes. IMPORTANCE Genome mining of metagenomic data has become the preferred method for the bioprospecting of novel compounds by cataloguing secondary metabolite potential. However, the accurate detection of BGCs requires unfragmented genomic assemblies, which have been technically difficult to obtain from metagenomes until recently with new long-read technologies. We used high-quality metagenome-assembled genomes generated from long-read data to determine the biosynthetic potential of microbes found in the surface water of the Yellow Sea. We recovered 339 highly diverse and mostly full-length BGCs from largely uncultured and underexplored bacterial and archaeal phyla. Additionally, we present long-read metagenomic sequencing combined with metatranscriptomic analysis as a potential method for gaining access to the largely underutilized genetic reservoir of specialized metabolite gene clusters in the majority of microbes that are not cultured. The combination of long-read metagenomic and metatranscriptomic analyses is significant because it can more accurately assess the mechanisms of microbial adaptation to the environment through BGC expression based on metatranscriptomic data.

Exploring Long-Read Metagenomics for Full Characterization of Shiga Toxin-Producing Escherichia coli in Presence of Commensal E. coli.

The characterization of Shiga toxin-producing Escherichia coli (STEC) is necessary to assess their pathogenic potential, but isolation of the strain from complex matrices such as milk remains challenging. In previous work, we have shown the potential of long-read metagenomics to characterize eae-positive STEC from artificially contaminated raw milk without isolating the strain. The presence of multiple E. coli strains in the sample was shown to potentially hinder the correct characterization of the STEC strain. Here, we aimed at determining the STEC:commensal ratio that would prevent the characterization of the STEC. We artificially contaminated pasteurized milk with different ratios of an eae-positive STEC and a commensal E. coli and applied the method previously developed. Results showed that the STEC strain growth was better than the commensal E. coli after enrichment in acriflavine-supplemented BPW. The STEC was successfully characterized in all samples with at least 10 times more STEC post-enrichment compared to the commensal E. coli. However, the presence of equivalent proportions of STEC and commensal E. coli prevented the full characterization of the STEC strain. This study confirms the potential of long-read metagenomics for STEC characterization in an isolation-free manner while refining its limit regarding the presence of background E. coli strains.

A novel and diverse group of Candidatus Patescibacteria from bathypelagic Lake Baikal revealed through long-read metagenomics

BackgroundLake Baikal, the world’s deepest freshwater lake, contains important numbers of Candidatus Patescibacteria (formerly CPR) in its deepest reaches. However, previously obtained CPR metagenome-assembled genomes recruited very poorly indicating the potential of other groups being present. Here, we have applied for the first time a long-read (PacBio CCS) metagenomic approach to analyze in depth the Ca. Patescibacteria living in the bathypelagic water column of Lake Baikal at 1600 m.ResultsThe retrieval of nearly complete 16S rRNA genes before assembly has allowed us to detect the presence of a novel and a likely endemic group of Ca. Patescibacteria inhabiting bathypelagic Lake Baikal. This novel group seems to possess extremely high intra-clade diversity, precluding complete genomes' assembly. However, read binning and scaffolding indicate that these microbes are similar to other Ca. Patescibacteria (i.e. parasites or symbionts), although they seem to carry more anabolic pathways, likely reflecting the extremely oligotrophic habitat they inhabit. The novel bins have not been found anywhere, but one of the groups appears in small amounts in an oligotrophic and deep alpine Lake Thun. We propose this novel group be named Baikalibacteria.ConclusionThe recovery of 16S rRNA genes via long-read metagenomics plus the use of long-read binning to uncover highly diverse “hidden” groups of prokaryotes are key strategies to move forward in ecogenomic microbiology. The novel group possesses enormous intraclade diversity akin to what happens with Ca. Patescibacteria at the interclade level, which is remarkable in an environment that has changed little in the last 25 million years.

Long-Read Metagenomics and CAZyme Discovery.

Microorganisms play a primary role in regulating biogeochemical cycles and are a valuable source of enzymes that have biotechnological applications, such as carbohydrate-active enzymes (CAZymes). However, the inability to culture the majority of microorganisms that exist in natural ecosystems restricts access to potentially novel bacteria and beneficial CAZymes. While commonplace molecular-based culture-independent methods such as metagenomics enable researchers to study microbial communities directly from environmental samples, recent progress in long-read sequencing technologies are advancing the field. We outline key methodological stages that are required as well as describe specific protocols that are currently used for long-read metagenomic projects dedicated to CAZyme discovery.

Long-read metagenomics paves the way toward a complete microbial tree of life.

Long-read metagenomics paves the way toward a complete microbial tree of life.

A step forward for Shiga toxin-producing Escherichia coli identification and characterization in raw milk using long-read metagenomics.

Shiga toxin-producing Escherichia coli (STEC) are a cause of severe human illness and are frequently associated with haemolytic uraemic syndrome (HUS) in children. It remains difficult to identify virulence factors for STEC that absolutely predict the potential to cause human disease. In addition to the Shiga-toxin (stx genes), many additional factors have been reported, such as intimin (eae gene), which is clearly an aggravating factor for developing HUS. Current STEC detection methods classically rely on real-time PCR (qPCR) to detect the presence of the key virulence markers (stx and eae). Although qPCR gives an insight into the presence of these virulence markers, it is not appropriate for confirming their presence in the same strain. Therefore, isolation steps are necessary to confirm STEC viability and characterize STEC genomes. While STEC isolation is laborious and time-consuming, metagenomics has the potential to accelerate the STEC characterization process in an isolation-free manner. Recently, short-read sequencing metagenomics have been applied for this purpose, but assembly quality and contiguity suffer from the high proportion of mobile genetic elements occurring in STEC strains. To circumvent this problem, we used long-read sequencing metagenomics for identifying eae-positive STEC strains using raw cow's milk as a causative matrix for STEC food-borne outbreaks. By comparing enrichment conditions, optimizing library preparation for MinION sequencing and generating an easy-to-use STEC characterization pipeline, the direct identification of an eae-positive STEC strain was successful after enrichment of artificially contaminated raw cow's milk samples at a contamination level as low as 5 c.f.u. ml-1. Our newly developed method combines optimized enrichment conditions of STEC in raw milk in combination with a complete STEC analysis pipeline from long-read sequencing metagenomics data. This study shows the potential of the innovative methodology for characterizing STEC strains from complex matrices. Further developments will nonetheless be necessary for this method to be applied in STEC surveillance.

Insights into ecological roles of uncultivated bacteria in Katase hot spring sediment from long-read metagenomics.

Diverse yet-uncultivated bacteria and archaea, i.e., microbial dark matter, are present in terrestrial hot spring environments. Numerous metagenome-assembled genomes (MAGs) of these uncultivated prokaryotes by short-read metagenomics have been reported so far, suggesting their metabolic potential. However, more reliable MAGs, i.e., circularized complete MAGs (cMAGs), have been rarely reported from hot spring environments. Here, we report 61 high-quality (HQ)-MAGs, including 14 cMAGs, of diverse uncultivated bacteria and archaea retrieved from hot spring sediment (52°C, pH 7.2) by highly accurate long-read sequencing using PacBio Sequel II. The HQ MAGs were affiliated with one archaeal and 13 bacterial phyla. Notably, nine of the 14 cMAGs were the first reported cMAGs for the family- to class-level clades that these cMAGs belonged to. The genome information suggests that the bacteria represented by MAGs play a significant role in the biogeochemical cycling of carbon, nitrogen, iron, and sulfur at this site. In particular, the genome analysis of six HQ MAGs including two cMAGs of Armatimonadota, of which members are frequently abundant in hot spring environments, predicts that they are aerobic, moderate thermophilic chemoorganoheterotrophs, and potentially oxidize and/or reduce iron. This prediction is consistent with the environmental conditions where they were detected. Our results expand the knowledge regarding the ecological potential of uncultivated bacteria in moderately-high-temperature environments.

Nanopore-based long-read metagenomics uncover the resistome intrusion by antibiotic resistant bacteria from treated wastewater in receiving water body

Wastewater treatment plant (WWTP) effluent discharge could induce the resistome enrichment in the receiving water environments. However, because of the general lack of a robust antibiotic-resistant bacteria (ARB) identification method, the driving mechanism for resistome accumulation in receiving environment is unclear. Here, we took advantage of the enhanced ARBs recognition by nanopore long reads to distinguish the indigenous ARBs and the accumulation of WWTP-borne ARBs in the receiving water body of a domestic WWTP. A bioinformatic framework (named ARGpore2: https://github.com/sustc-xylab/ARGpore2) was constructed and evaluate to facilitate antibiotic resistance genes (ARGs) and ARBs identification in nanopore reads. ARGs identification by ARGpore2 showed comparable precision and recall to that of the commonly adopt BLASTP-based method, whereas the spectrum of ARBs doubled that of the assembled Illumina dataset. Totally, we identified 33 ARBs genera carrying 65 ARG subtypes in the receiving seawater, whose concentration was in general 10 times higher than clean seawater's. Notably we report a primary resistome intrusion caused by the revival of residual microbes survived from disinfection treatment. These WWTP-borne ARBs, including several animal/human enteric pathogens, contributed up to 85% of the receiving water resistome. Plasmids and class 1 integrons were reckoned as major vehicles facilitating the persistence and dissemination of ARGs. Moreover, our work demonstrated the importance of extensive carrier identification in determining the driving force of multifactor coupled resistome booming in complicated environmental conditions, thereby paving the way for establishing priority for effective ARGs mitigation strategies.

Long-Read Metagenomics Improves the Recovery of Viral Diversity from Complex Natural Marine Samples.

ABSTRACTThe recovery of DNA from viromes is a major obstacle in the use of long-read sequencing to study their genomes. For this reason, the use of cellular metagenomes (>0.2-μm size range) emerges as an interesting complementary tool, since they contain large amounts of naturally amplified viral genomes from prelytic replication. We have applied second-generation (Illumina NextSeq; short reads) and third-generation (PacBio Sequel II; long reads) sequencing to compare the diversity and features of the viral community in a marine sample obtained from offshore waters of the western Mediterranean. We found that a major wedge of the expected marine viral diversity was directly recovered by the raw PacBio circular consensus sequencing (CCS) reads. More than 30,000 sequences were detected only in this data set, with no homologues in the long- and short-read assembly, and ca. 26,000 had no homologues in the large data set of the Global Ocean Virome 2 (GOV2), highlighting the information gap created by the assembly bias. At the level of complete viral genomes, the performance was similar in both approaches. However, the hybrid long- and short-read assembly provided the longest average length of the sequences and improved the host assignment. Although no novel major clades of viruses were found, there was an increase in the intraclade genomic diversity recovered by long reads that produced an enriched assessment of the real diversity and allowed the discovery of novel genes with biotechnological potential (e.g., endolysin genes).IMPORTANCE We explored the vast genetic diversity of environmental viruses by using a combination of cellular metagenome (as opposed to virome) sequencing using high-fidelity long-read sequences (in this case, PacBio CCS). This approach resulted in the recovery of a representative sample of the viral population, and it performed better (more phage contigs, larger average contig size) than Illumina sequencing applied to the same sample. By this approach, the many biases of assembly are avoided, as the CCS reads recovers (typically around 5 kb) complete genes and even operons, resulting in a better discovery of the viral gene diversity based on viral marker proteins. Thus, biotechnologically promising genes, such as endolysin genes, can be very efficiently searched with this approach. In addition, hybrid assembly produces more complete and longer contigs, which is particularly important for studying little-known viral groups such as the nucleocytoplasmic large DNA viruses (NCLDV).

Short- and long-read metagenomics expand individualized structural variations in gut microbiomes.

In-depth profiling of genetic variations in the gut microbiome is highly desired for understanding its functionality and impacts on host health and disease. Here, by harnessing the long read advantage provided by Oxford Nanopore Technology (ONT), we characterize fine-scale genetic variations of structural variations (SVs) in hundreds of gut microbiomes from healthy humans. ONT long reads dramatically improve the quality of metagenomic assemblies, enable reliable detection of a large, expanded set of structural variation types (notably including large insertions and inversions). We find SVs are highly distinct between individuals and stable within an individual, representing gut microbiome fingerprints that shape strain-level differentiations in function within species, complicating the associations to metabolites and host phenotypes such as blood glucose. In summary, our study strongly emphasizes that incorporating ONT reads into metagenomic analyses expands the detection scope of genetic variations, enables profiling strain-level variations in gut microbiome, and their intricate correlations with metabolome.

Investigating plant disease outbreaks with long-read metagenomics: sensitive detection and highly resolved phylogenetic reconstruction applied to Xylella fastidiosa.

Early disease detection is a prerequisite for enacting effective interventions for disease control. Strains of the bacterial plant pathogen Xylella fastidiosa have recurrently spread to new crops in new countries causing devastating outbreaks. So far, investigation of outbreak strains and highly resolved phylogenetic reconstruction have required whole-genome sequencing of pure bacterial cultures, which are challenging to obtain due to the fastidious nature of X. fastidiosa . Here, we show that culture-independent metagenomic sequencing, using the Oxford Nanopore Technologies MinION long-read sequencer, can sensitively and specifically detect the causative agent of Pierce’s disease of grapevine, X. fastidiosa subspecies fastidiosa . Using a DNA sample from a grapevine in Virginia, USA, it was possible to obtain a metagenome-assembled genome (MAG) of sufficient quality for phylogenetic reconstruction with SNP resolution. The analysis placed the MAG in a clade with isolates from Georgia, USA, suggesting introduction of X. fastidiosa subspecies fastidiosa to Virginia from the south-eastern USA. This proof of concept study, thus, revealed that metagenomic sequencing can replace culture-dependent genome sequencing for reconstructing transmission routes of bacterial plant pathogens.