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Additional file 1: Supplementary Figures S1-S15.

Additional file 1. Supplementary Figures.

Additional file 10. Review history.

Figure S3. Presence (blue)/absence (yellow) heatmap displaying only the gene families found to be significantly over- (or under-)represented in genomes deriving from one of the four sampling sites. (PPTX 1073Â kb)

Figure S4. Anviâ O plots displaying the clustering patterns of assembled contigs along with their coverage by each metagenome. Leftmost graph shows the contigs clustered only by sequence composition (i.e., tetrameric signature); rightmost graph clusters the contigs only by their differential coverage; middle graph, combination of differential coverage and tetrameric composition. (PPTX 829Â kb)

Figure S1a. Rank abundance plots of the families detected using MetaPhlAn2 in the four metagenomes. y-axis, abundances (expressed as percentage of the reads mapping on taxonomically informative marker genes); x-axis, families detected. (PPTX 471Â kb)

Figure S2. Venn diagram showing the distribution of functions in the four metagenomes. Each ellipse corresponds to the metagenome of a site; the overlapping areas represents the functions that are either shared among- or unique to- each site. Unique functions are explicitly annotated. (PPTX 988Â kb)

Figure S1. Scatterplot contrasting for each sample the number of successfully profiled species against the metagenome size (in million reads). Each dot corresponds to a sample in the MetaSUB dataset. The number of detected species was calculated with MetaPhlAn2 by requiring a species to have a relative abundance higher than 0.5% within the sample. (PDF 113Â kb)

Metagenomic assembly enables new organism discovery from microbial communities, but it can only capture few abundant organisms from most metagenomes. Here we present MetaPhlAn 4, which integrates information from metagenome assemblies and microbial isolate genomes for more comprehensive metagenomic taxonomic profiling. From a curated collection of 1.01 M prokaryotic reference and metagenome-assembled genomes, we define unique marker genes for 26,970 species-level genome bins, 4,992 of them taxonomically unidentified at the species level. MetaPhlAn 4 explains ~20% more reads in most international human gut microbiomes and >40% in less-characterized environments such as the rumen microbiome and proves more accurate than available alternatives on synthetic evaluations while also reliably quantifying organisms with no cultured isolates. Application of the method to >24,500 metagenomes highlights previously undetected species to be strong biomarkers for host conditions and lifestyles in human and mouse microbiomes and shows that even previously uncharacterized species can be genetically profiled at the resolution of single microbial strains.

Background Water springs provide important ecosystem services including drinking water supply, recreation, and balneotherapy, but their microbial communities remain largely unknown. In this study, we characterized the spring water microbiome of Comano Terme (Italy) at four sampling points of the thermal spa, including natural (spring and well) and human-built (storage tank, bathtubs) environments. We integrated large-scale culturing and metagenomic approaches, with the aim of comprehensively determining the spring water taxonomic composition and functional potential. Results The groundwater feeding the spring hosted the most atypical microbiome, including many taxa known to be recalcitrant to cultivation. The core microbiome included the orders Sphingomonadales, Rhizobiales, and Caulobacterales, and the families Bradyrhizobiaceae and Moraxellaceae. A comparative genomic analysis of 72 isolates and 30 metagenome-assembled genomes (MAGs) revealed that most isolates and MAGs belonged to new species or higher taxonomic ranks widely distributed in the microbial tree of life. Average nucleotide identity (ANI) values calculated for each isolated or assembled genome showed that 10 genomes belonged to known bacterial species (> 95% ANI), 36 genomes (including 1 MAG) had ANI values ranging 85–92.5% and could be assigned as undescribed species belonging to known genera, while the remaining 55 genomes had lower ANI values (

The body-wide human microbiome plays a role in health, but its full diversity remains uncharacterized, particularly outside of the gut and in international populations. We leveraged 9,428 metagenomes to reconstruct 154,723 microbial genomes (45% of high quality) spanning body sites, ages, countries, and lifestyles. We recapitulated 4,930 species-level genome bins (SGBs), 77% without genomes in public repositories (unknown SGBs [uSGBs]). uSGBs are prevalent (in 93% of well-assembled samples), expand underrepresented phyla, and are enriched in non-Westernized populations (40% of the total SGBs). We annotated 2.85 M genes in SGBs, many associated with conditions including infant development (94,000) or Westernization (106,000). SGBs and uSGBs permit deeper microbiome analyses and increase the average mappability of metagenomic reads from 67.76% to 87.51% in the gut (median 94.26%) and 65.14% to 82.34% in the mouth. We thus identify thousands of microbial genomes from yet-to-be-named species, expand the pangenomes of human-associated microbes, and allow better exploitation of metagenomic technologies.The human microbiome harbors many unidentified species. By large-scale metagenomic assembly of samples from diverse populations, we uncovered >150,000 microbial genomes that are recapitulated in 4,930 species. Many species (77%) were never described before, increase the mappability of metagenomes, and expand our understanding of global body-wide human microbiomes., This work was supported by EU-H2020 (DiMeTrack-707345) to E.P.; by NIH NHGRI (R01HG005220), NIDDK (R24DK110499), NIDDK (U54DE023798), CMIT (6935956) to C.H.; and by ERC (MetaPG-716575), MIUR (RBFR13EWWI), EU-FP7 (PCIG13-GA-2013-618833), CARITRO (2013.0239), and LEO Pharma Foundation to N.S. Madagascar data and sample collection was supported by the Rockefeller Foundation to C.D.G.

Several studies have investigated links between the gut microbiome and colorectal cancer (CRC), but questions remain about the replicability of biomarkers across cohorts and populations. We performed a meta-analysis of five publicly available datasets and two new cohorts and validated the findings on two additional cohorts, considering in total 969 fecal metagenomes. Unlike microbiome shifts associated with gastrointestinal syndromes, the gut microbiome in CRC showed reproducibly higher richness than controls (P

Summary Prevotella copri is a common human gut microbe that has been both positively and negatively associated with host health. In a cross-continent meta-analysis exploiting >6,500 metagenomes, we obtained >1,000 genomes and explored the genetic and population structure of P. copri. P. copri encompasses four distinct clades (>10% inter-clade genetic divergence) that we propose constitute the P. copri complex, and all clades were confirmed by isolate sequencing. These clades are nearly ubiquitous and co-present in non-Westernized populations. Genomic analysis showed substantial functional diversity in the complex with notable differences in carbohydrate metabolism, suggesting that multi-generational dietary modifications may be driving reduced prevalence in Westernized populations. Analysis of ancient metagenomes highlighted patterns of P. copri presence consistent with modern non-Westernized populations and a clade delineation time pre-dating human migratory waves out of Africa. These findings reveal that P. copri exhibits a high diversity that is underrepresented in Western-lifestyle populations., Graphical Abstract, Highlights • P. copri is not a monotypic species but composed of four distinct clades • The P. copri complex is more prevalent in populations with non-Westernized lifestyles • P. copri clades are frequently co-present within non-Westernized individuals • Ancient stool samples suggest Westernization leads to P. copri underrepresentation, Tett et al. find that the intestinal microbe Prevotella copri encompasses four distinct clades constituting the P. copri complex. The complex is prevalent in non-Westernized populations where co-presence of all clades is commonly observed within individuals. Analysis of ancient stool samples supports Westernization as contributing to reduced P. copri prevalence.

Summary The role of intestinal Prevotella species in human health is controversial, with both positive and negative associations. Strain-level diversity may contribute to discrepancies in genus and species associations with health and disease. We dissected the gut metagenomes of Italians with varying dietary habits, investigating the presence of distinct Prevotella copri strains. Fiber-rich diets were linked to P. copri types with enhanced potential for carbohydrate catabolism. P. copri strains associated with an omnivore diet had a higher prevalence of the leuB gene—involved in branched-chain amino acid biosynthesis—a risk factor for glucose intolerance and type 2 diabetes. These P. copri pangenomes were compared to existing cohorts, providing evidence of distinct gene repertoires characterizing different P. copri populations, with drug metabolism and complex carbohydrate degradation significantly associated with Western and non-Western individuals, respectively. Strain-level P. copri diversity in gut microbiomes is affected by diet and should be considered when examining host-microbe associations.

Background The microbial communities populating human and natural environments have been extensively characterized with shotgun metagenomics, which provides an in-depth representation of the microbial diversity within a sample. Microbes thriving in urban environments may be crucially important for human health, but have received less attention than those of other environments. Ongoing efforts started to target urban microbiomes at a large scale, but the most recent computational methods to profile these metagenomes have never been applied in this context. It is thus currently unclear whether such methods, that have proven successful at distinguishing even closely related strains in human microbiomes, are also effective in urban settings for tasks such as cultivation-free pathogen detection and microbial surveillance. Here, we aimed at a) testing the currently available metagenomic profiling tools on urban metagenomics; b) characterizing the organisms in urban environment at the resolution of single strain and c) discussing the biological insights that can be inferred from such methods. Results We applied three complementary methods on the 1614 metagenomes of the CAMDA 2017 challenge. With MetaMLST we identified 121 known sequence-types from 15 species of clinical relevance. For instance, we identified several Acinetobacter strains that were close to the nosocomial opportunistic pathogen A. nosocomialis. With StrainPhlAn, a generalized version of the MetaMLST approach, we inferred the phylogenetic structure of Pseudomonas stutzeri strains and suggested that the strain-level heterogeneity in environmental samples is higher than in the human microbiome. Finally, we also probed the functional potential of the different strains with PanPhlAn. We further showed that SNV-based and pangenome-based profiling provide complementary information that can be combined to investigate the evolutionary trajectories of microbes and to identify specific genetic determinants of virulence and antibiotic resistances within closely related strains. Conclusion We show that strain-level methods developed primarily for the analysis of human microbiomes can be effective for city-associated microbiomes. In fact, (opportunistic) pathogens can be tracked and monitored across many hundreds of urban metagenomes. However, while more effort is needed to profile strains of currently uncharacterized species, this work poses the basis for high-resolution analyses of microbiomes sampled in city and mass transportation environments. Reviewers This article was reviewed by Alexandra Bettina Graf, Daniel Huson and Trevor Cickovski. Electronic supplementary material The online version of this article (10.1186/s13062-018-0211-z) contains supplementary material, which is available to authorized users.

Identifying microbial strains and characterizing their functional potential is essential for pathogen discovery, epidemiology and population genomics. We present pangenome-based phylogenomic analysis (PanPhlAn; http://segatalab.cibio.unitn.it/tools/panphlan), a tool that uses metagenomic data to achieve strain-level microbial profiling resolution. PanPhlAn recognized outbreak strains, produced the largest strain-level population genomic study of human-associated bacteria and, in combination with metatranscriptomics, profiled the transcriptional activity of strains in complex communities.