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Metagenomics emerged as an important field of research not only in microbial ecology but also for human health and disease, and metagenomic studies are performed on increasingly larger scales. While recent taxonomic classification programs achieve high speed by comparing genomic k -mers, they often lack sensitivity for overcoming evolutionary divergence, so that large fractions of the metagenomic reads remain unclassified. Here we present the novel metagenome classifier Kaiju, which finds maximum (in-)exact matches on the protein-level using the Burrows–Wheeler transform. We show in a genome exclusion benchmark that Kaiju classifies reads with higher sensitivity and similar precision compared with current k -mer-based classifiers, especially in genera that are underrepresented in reference databases. We also demonstrate that Kaiju classifies up to 10 times more reads in real metagenomes. Kaiju can process millions of reads per minute and can run on a standard PC. Source code and web server are available at http://kaiju.binf.ku.dk . Here, Anders Krogh and colleagues describe Kaiju, a metagenome taxonomic classification program that uses maximum (in-)exact matches on the protein-level to account for evolutionary divergence. The authors show that Kaiju performs faster and is more sensitive compared with existing algorithms and can be used on a standard computer.

A wide array of microorganisms, including many novel, phylogenetically deeply rooted taxa, survive and thrive in extreme environments. These unique and reduced-complexity ecosystems offer a tremendous opportunity for studying the structure, function and evolution of natural microbial communities. Marker gene surveys have resolved patterns and ecological drivers of these extremophile assemblages, revealing a vast uncultured microbial diversity and the often predominance of archaea in the most extreme conditions. New omics studies have uncovered linkages between community function and environmental variables, and have enabled discovery and genomic characterization of major new lineages that substantially expand microbial diversity and change the structure of the tree of life. These efforts have significantly advanced our understanding of the diversity, ecology and evolution of microorganisms populating Earth’s extreme environments, and have facilitated the exploration of microbiota and processes in more complex ecosystems.Microbial life can thrive in extreme environments such as terrestrial hot springs and deep sea hydrothermal vents, glaciers and permafrost, hypersaline habitats, acid mine drainage and the subsurface. In this Review, Shu and Huang explore the diversity, functions and evolution of bacteria and archaea inhabiting Earth’s major extreme environments.

The gut microbiota has been linked to cardiovascular diseases. However, the composition and functional capacity of the gut microbiome in relation to cardiovascular diseases have not been systematically examined. Here, we perform a metagenome-wide association study on stools from 218 individuals with atherosclerotic cardiovascular disease (ACVD) and 187 healthy controls. The ACVD gut microbiome deviates from the healthy status by increased abundance of Enterobacteriaceae and Streptococcus spp. and, functionally, in the potential for metabolism or transport of several molecules important for cardiovascular health. Although drug treatment represents a confounding factor, ACVD status, and not current drug use, is the major distinguishing feature in this cohort. We identify common themes by comparison with gut microbiome data associated with other cardiometabolic diseases (obesity and type 2 diabetes), with liver cirrhosis, and rheumatoid arthritis. Our data represent a comprehensive resource for further investigations on the role of the gut microbiome in promoting or preventing ACVD as well as other related diseases. The gut microbiota may play a role in cardiovascular diseases. Here, the authors perform a metagenome-wide association study on stools from individuals with atherosclerotic cardiovascular disease and healthy controls, identifying microbial strains and functions associated with the disease.

Long-read Oxford Nanopore sequencing has democratized microbial genome sequencing and enables the recovery of highly contiguous microbial genomes from isolates or metagenomes. However, to obtain near-finished genomes it has been necessary to include short-read polishing to correct insertions and deletions derived from homopolymer regions. Here, we show that Oxford Nanopore R10.4 can be used to generate near-finished microbial genomes from isolates or metagenomes without short-read or reference polishing. This study demonstrates the feasibility of generating near-finished microbial genomes using only Oxford Nanopore R10.4 data from pure cultures or metagenomes.

Tomato rhizosphere microbiome alterations that contribute to bacterial wilt resistance are detected using metagenomics. Tomato variety Hawaii 7996 is resistant to the soil-borne pathogen Ralstonia solanacearum , whereas the Moneymaker variety is susceptible to the pathogen. To evaluate whether plant-associated microorganisms have a role in disease resistance, we analyzed the rhizosphere microbiomes of both varieties in a mesocosm experiment. Microbiome structures differed between the two cultivars. Transplantation of rhizosphere microbiota from resistant plants suppressed disease symptoms in susceptible plants. Comparative analyses of rhizosphere metagenomes from resistant and susceptible plants enabled the identification and assembly of a flavobacterial genome that was far more abundant in the resistant plant rhizosphere microbiome than in that of the susceptible plant. We cultivated this flavobacterium, named TRM1, and found that it could suppress R. solanacearum -disease development in a susceptible plant in pot experiments. Our findings reveal a role for native microbiota in protecting plants from microbial pathogens, and our approach charts a path toward the development of probiotics to ameliorate plant diseases.

Metagenomic experiments expose the wide range of microscopic organisms in any microbial environment through high-throughput DNA sequencing. The computational analysis of the sequencing data is critical for the accurate and complete characterization of the microbial community. To facilitate efficient and reproducible metagenomic analysis, we introduce a step-by-step protocol for the Kraken suite, an end-to-end pipeline for the classification, quantification and visualization of metagenomic datasets. Our protocol describes the execution of the Kraken programs, via a sequence of easy-to-use scripts, in two scenarios: (1) quantification of the species in a given metagenomics sample; and (2) detection of a pathogenic agent from a clinical sample taken from a human patient. The protocol, which is executed within 1–2 h, is targeted to biologists and clinicians working in microbiome or metagenomics analysis who are familiar with the Unix command-line environment.The authors provide a guide to using the Kraken suite for metagenomics analysis, including classification, quantification and visualization, illustrated by quantification of species in the microbiome and identification of pathogens in a clinical sample.

Recent advances have made it possible to analyze high-throughput marker-gene sequencing data without resorting to the customary construction of molecular operational taxonomic units (OTUs): clusters of sequencing reads that differ by less than a fixed dissimilarity threshold. New methods control errors sufficiently such that amplicon sequence variants (ASVs) can be resolved exactly, down to the level of single-nucleotide differences over the sequenced gene region. The benefits of finer resolution are immediately apparent, and arguments for ASV methods have focused on their improved resolution. Less obvious, but we believe more important, are the broad benefits that derive from the status of ASVs as consistent labels with intrinsic biological meaning identified independently from a reference database. Here we discuss how these features grant ASVs the combined advantages of closed-reference OTUs—including computational costs that scale linearly with study size, simple merging between independently processed data sets, and forward prediction—and of de novo OTUs—including accurate measurement of diversity and applicability to communities lacking deep coverage in reference databases. We argue that the improvements in reusability, reproducibility and comprehensiveness are sufficiently great that ASVs should replace OTUs as the standard unit of marker-gene analysis and reporting.

Sequence comparison tools for metagenome-assembled genomes (MAGs) struggle with high-volume or low-quality data. We present skani ( https://github.com/bluenote-1577/skani ), a method for determining average nucleotide identity (ANI) via sparse approximate alignments. skani outperforms FastANI in accuracy and speed (>20× faster) for fragmented, incomplete MAGs. skani can query genomes against >65,000 prokaryotic genomes in seconds and 6 GB memory. skani unlocks higher-resolution insights for extensive, noisy metagenomic datasets. skani achieves fast calculation of average nucleotide identity (ANI) between metagenome-assembled genomes (MAGs), with improved robustness against incomplete and fragmented MAGs.

Asgard is a recently discovered superphylum of archaea that appears to include the closest archaeal relatives of eukaryotes 1 – 5 . Debate continues as to whether the archaeal ancestor of eukaryotes belongs within the Asgard superphylum or whether this ancestor is a sister group to all other archaea (that is, a two-domain versus a three-domain tree of life) 6 – 8 . Here we present a comparative analysis of 162 complete or nearly complete genomes of Asgard archaea, including 75 metagenome-assembled genomes that—to our knowledge—have not previously been reported. Our results substantially expand the phylogenetic diversity of Asgard and lead us to propose six additional phyla that include a deep branch that we have provisionally named Wukongarchaeota. Our phylogenomic analysis does not resolve unequivocally the evolutionary relationship between eukaryotes and Asgard archaea, but instead—depending on the choice of species and conserved genes used to build the phylogeny—supports either the origin of eukaryotes from within Asgard (as a sister group to the expanded Heimdallarchaeota–Wukongarchaeota branch) or a deeper branch for the eukaryote ancestor within archaea. Our comprehensive protein domain analysis using the 162 Asgard genomes results in a major expansion of the set of eukaryotic signature proteins. The Asgard eukaryotic signature proteins show variable phyletic distributions and domain architectures, which is suggestive of dynamic evolution through horizontal gene transfer, gene loss, gene duplication and domain shuffling. The phylogenomics of the Asgard archaea points to the accumulation of the components of the mobile archaeal ‘eukaryome’ in the archaeal ancestor of eukaryotes (within or outside Asgard) through extensive horizontal gene transfer. Comparative analysis of 162 genomes of Asgard archaea results in six newly proposed phyla, including a deep branch that is provisionally named Wukongarchaeota, and sheds light on the evolutionary history of this clade.

NRC publication: Yes