Extensive Unexplored Human Microbiome Diversity Revealed by Over 150,000 Genomes from Metagenomes Spanning Age, Geography, and Lifestyle.

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 person-to-person transmission landscape of the gut and oral microbiomes.

The human microbiome is an integral component of the human body and a co-determinant of several health conditions1,2. However, the extent to which interpersonal relations shape the individual genetic makeup of the microbiome and its transmission within and across populations remains largely unknown3,4. Here, capitalizing on more than 9,700 human metagenomes and computational strain-level profiling, we detected extensive bacterial strain sharing across individuals (more than 10 million instances) with distinct mother-to-infant, intra-household and intra-population transmission patterns. Mother-to-infant gut microbiome transmission was considerable and stable during infancy (around 50% of the same strains among shared species (strain-sharing rate)) and remained detectable at older ages. By contrast, the transmission of the oral microbiome occurred largely horizontally and was enhanced by the duration of cohabitation. There was substantial strain sharing among cohabiting individuals, with 12% and 32% median strain-sharing rates for the gut and oral microbiomes, and time since cohabitation affected strain sharing more than age or genetics did. Bacterial strain sharing additionally recapitulated host population structures better than species-level profiles did. Finally, distinct taxa appeared as efficient spreaders across transmission modes and were associated with different predicted bacterial phenotypes linked with out-of-host survival capabilities. The extent of microorganism transmission that we describe underscores its relevance in human microbiome studies5, especially those on non-infectious, microbiome-associated diseases.

Host phenotype classification from human microbiome data is mainly driven by the presence of microbial taxa.

Machine learning-based classification approaches are widely used to predict host phenotypes from microbiome data. Classifiers are typically employed by considering operational taxonomic units or relative abundance profiles as input features. Such types of data are intrinsically sparse, which opens the opportunity to make predictions from the presence/absence rather than the relative abundance of microbial taxa. This also poses the question whether it is the presence rather than the abundance of particular taxa to be relevant for discrimination purposes, an aspect that has been so far overlooked in the literature. In this paper, we aim at filling this gap by performing a meta-analysis on 4,128 publicly available metagenomes associated with multiple case-control studies. At species-level taxonomic resolution, we show that it is the presence rather than the relative abundance of specific microbial taxa to be important when building classification models. Such findings are robust to the choice of the classifier and confirmed by statistical tests applied to identifying differentially abundant/present taxa. Results are further confirmed at coarser taxonomic resolutions and validated on 4,026 additional 16S rRNA samples coming from 30 public case-control studies.

Stool microRNA profiles reflect different dietary and gut microbiome patterns in healthy individuals.

OBJECTIVES: MicroRNA (miRNA) profiles have been evaluated in several biospecimens in relation to common diseases for which diet may have a considerable impact. We aimed at characterising how specific diets are associated with the miRNome in stool of vegans, vegetarians and omnivores and how this is reflected in the gut microbial composition, as this is still poorly explored. DESIGN: We performed small RNA and shotgun metagenomic sequencing in faecal samples and dietary recording from 120 healthy volunteers, equally distributed for the different diets and matched for sex and age. RESULTS: We found 49 miRNAs differentially expressed among vegans, vegetarians and omnivores (adj. p <0.05) and confirmed trends of expression levels of such miRNAs in vegans and vegetarians compared with an independent cohort of 45 omnivores. Two miRNAs related to lipid metabolism, miR-636 and miR-4739, were inversely correlated to the non-omnivorous diet duration, independently of subject age. Seventeen miRNAs correlated (|rho|>0.22, adj. p <0.05) with the estimated intake of nutrients, particularly animal proteins, phosphorus and, interestingly, lipids. In omnivores, higher Prevotella and Roseburia and lower Bacteroides abundances than in vegans and vegetarians were observed. Lipid metabolism-related miR-425-3p and miR-638 expression levels were associated with increased abundances of microbial species, such as Roseburia sp. CAG 182 and Akkermansia muciniphila, specific of different diets. An integrated analysis identified 25 miRNAs, 25 taxa and 7 dietary nutrients that clearly discriminated (area under the receiver operating characteristic curve=0.89) the three diets. CONCLUSION: Stool miRNA profiles are associated with specific diets and support the role of lipids as a driver of epigenetic changes and host-microbial molecular interactions in the gut.

Mediterranean diet intervention in overweight and obese subjects lowers plasma cholesterol and causes changes in the gut microbiome and metabolome independently of energy intake.

OBJECTIVES: This study aimed to explore the effects of an isocaloric Mediterranean diet (MD) intervention on metabolic health, gut microbiome and systemic metabolome in subjects with lifestyle risk factors for metabolic disease. DESIGN: Eighty-two healthy overweight and obese subjects with a habitually low intake of fruit and vegetables and a sedentary lifestyle participated in a parallel 8-week randomised controlled trial. Forty-three participants consumed an MD tailored to their habitual energy intakes (MedD), and 39 maintained their regular diets (ConD). Dietary adherence, metabolic parameters, gut microbiome and systemic metabolome were monitored over the study period. RESULTS: Increased MD adherence in the MedD group successfully reprogrammed subjects' intake of fibre and animal proteins. Compliance was confirmed by lowered levels of carnitine in plasma and urine. Significant reductions in plasma cholesterol (primary outcome) and faecal bile acids occurred in the MedD compared with the ConD group. Shotgun metagenomics showed gut microbiome changes that reflected individual MD adherence and increase in gene richness in participants who reduced systemic inflammation over the intervention. The MD intervention led to increased levels of the fibre-degrading Faecalibacterium prausnitzii and of genes for microbial carbohydrate degradation linked to butyrate metabolism. The dietary changes in the MedD group led to increased urinary urolithins, faecal bile acid degradation and insulin sensitivity that co-varied with specific microbial taxa. CONCLUSION: Switching subjects to an MD while maintaining their energy intake reduced their blood cholesterol and caused multiple changes in their microbiome and metabolome that are relevant in future strategies for the improvement of metabolic health.

Microbial strain-level population structure and genetic diversity from metagenomes.

Among the human health conditions linked to microbial communities, phenotypes are often associated with only a subset of strains within causal microbial groups. Although it has been critical for decades in microbial physiology to characterize individual strains, this has been challenging when using culture-independent high-throughput metagenomics. We introduce StrainPhlAn, a novel metagenomic strain identification approach, and apply it to characterize the genetic structure of thousands of strains from more than 125 species in more than 1500 gut metagenomes drawn from populations spanning North and South American, European, Asian, and African countries. The method relies on per-sample dominant sequence variant reconstruction within species-specific marker genes. It identified primarily subject-specific strain variants (<5% inter-subject strain sharing), and we determined that a single strain typically dominated each species and was retained over time (for >70% of species). Microbial population structure was correlated in several distinct ways with the geographic structure of the host population. In some cases, discrete subspecies (e.g., for Eubacterium rectale and Prevotella copri) or continuous microbial genetic variations (e.g., for Faecalibacterium prausnitzii) were associated with geographically distinct human populations, whereas few strains occurred in multiple unrelated cohorts. We further estimated the genetic variability of gut microbes, with Bacteroides species appearing remarkably consistent (0.45% median number of nucleotide variants between strains), whereas P. copri was among the most plastic gut colonizers. We thus characterize here the population genetics of previously inaccessible intestinal microbes, providing a comprehensive strain-level genetic overview of the gut microbial diversity.

Strain-level microbial epidemiology and population genomics from shotgun metagenomics.

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.

Machine Learning Meta-analysis of Large Metagenomic Datasets: Tools and Biological Insights.

Shotgun metagenomic analysis of the human associated microbiome provides a rich set of microbial features for prediction and biomarker discovery in the context of human diseases and health conditions. However, the use of such high-resolution microbial features presents new challenges, and validated computational tools for learning tasks are lacking. Moreover, classification rules have scarcely been validated in independent studies, posing questions about the generality and generalization of disease-predictive models across cohorts. In this paper, we comprehensively assess approaches to metagenomics-based prediction tasks and for quantitative assessment of the strength of potential microbiome-phenotype associations. We develop a computational framework for prediction tasks using quantitative microbiome profiles, including species-level relative abundances and presence of strain-specific markers. A comprehensive meta-analysis, with particular emphasis on generalization across cohorts, was performed in a collection of 2424 publicly available metagenomic samples from eight large-scale studies. Cross-validation revealed good disease-prediction capabilities, which were in general improved by feature selection and use of strain-specific markers instead of species-level taxonomic abundance. In cross-study analysis, models transferred between studies were in some cases less accurate than models tested by within-study cross-validation. Interestingly, the addition of healthy (control) samples from other studies to training sets improved disease prediction capabilities. Some microbial species (most notably Streptococcus anginosus) seem to characterize general dysbiotic states of the microbiome rather than connections with a specific disease. Our results in modelling features of the "healthy" microbiome can be considered a first step toward defining general microbial dysbiosis. The software framework, microbiome profiles, and metadata for thousands of samples are publicly available at http://segatalab.cibio.unitn.it/tools/metaml.

Transcriptomic analysis reveals differential gene expression patterns of Lacticaseibacillus casei ATCC 393 in response to ultrasound stress.

In recent years, there has been a growing interest in modulating the performance of probiotic, mainly Lactic Acid Bacteria (LAB), in the field of probiotic food. Attenuation, induced by sub-lethal stresses, delays the probiotic metabolism, and induces a metabolic shift as survival strategy. In this paper, RNA sequencing was used to uncover the transcriptional regulation in Lacticaseibacillus casei ATCC 393 after ultrasound-induced attenuation. Six (T) and 8 (ST) min of sonication induced a significant differential expression of 742 and 409 genes, respectively. We identified 198 up-regulated and 321 down-regulated genes in T, and similarly 321 up-regulated and 249 down-regulated in ST. These results revealed a strong defensive response at 6 min, followed by adaptation at 8 min. Ultrasound attenuation modified the expression of genes related to a series of crucial biomolecular processes including membrane transport, carbohydrate and purine metabolism, phage-related genes, and translation. Specifically, genes encoding PTS transporters and genes involved in the glycolytic pathway and pyruvate metabolism were up-regulated, indicating an increased need for energy supply, as also suggested by an increase in the transcription of purine biosynthetic genes. Instead, protein translation, a high-energy process, was inhibited with the down-regulation of ribosomal protein biosynthetic genes. Moreover, phage-related genes were down-regulated suggesting a tight transcriptional control on DNA structure. The observed phenomena highlight the cell need of ATP to cope with the multiple ultrasound stresses and the activation of processes to stabilize and preserve the DNA structure. Our work demonstrates that ultrasound has remarkable effects on the tested strain and elucidates the involvement of different pathways in its defensive stress-response and in the modification of its phenotype.

Exposure to environmental pollutants selects for xenobiotic-degrading functions in the human gut microbiome.

Environmental pollutants from different chemical families may reach the gut microbiome, where they can be metabolized and transformed. However, how our gut symbionts respond to the exposure to environmental pollution is still underexplored. In this observational, cohort study, we aim to investigate the influence of environmental pollution on the gut microbiome composition and potential activity by shotgun metagenomics. We select as a case study a population living in a highly polluted area in Campania region (Southern Italy), proposed as an ideal field for exposomic studies and we compare the fecal microbiome of 359 subjects living in areas with high, medium and low environmental pollution. We highlight changes in gut microbiome composition and functionality that were driven by pollution exposure. Subjects from highly polluted areas show higher blood concentrations of dioxin and heavy metals, as well as an increase in microbial genes related to degradation and/or resistance to these molecules. Here we demonstrate the dramatic effect that environmental xenobiotics have on gut microbial communities, shaping their composition and boosting the selection of strains with degrading capacity. The gut microbiome can be considered as a pivotal player in the environment-health interaction that may contribute to detoxifying toxic compounds and should be taken into account when developing risk assessment models. The study was registered at ClinicalTrials.gov with the identifier NCT05976126.

Establishment of a non-Westernized gut microbiota in men who have sex with men is associated with sexual practices.

The human gut microbiota is influenced by various factors, including health status and environmental conditions, yet considerable inter-individual differences remain unexplained. Previous studies identified that the gut microbiota of men who have sex with men (MSM) is distinct from that of non-MSM. Here, we reveal through species-level microbiota analysis using shotgun metagenomics that the gut microbiota of many MSM with Western origin resembles gut microbial communities of non-Westernized populations. Specifically, MSM gut microbiomes are frequently dominated by members of the Prevotellaceae family, including co-colonization of species from the Segatella copri complex and unknown Prevotellaceae members. Questionnaire-based analysis exploring inter-individual differences in MSM links specific sexual practices to microbiota composition. Moreover, machine learning identifies microbial features associated with sexual activities in MSM. Together, this study shows associations of sexual activities with gut microbiome alterations in MSM, which may have a large impact on population-based microbiota studies.

Favorable subgingival plaque microbiome shifts are associated with clinical treatment for peri-implant diseases.

We performed a longitudinal shotgun metagenomic investigation of the plaque microbiome associated with peri-implant diseases in a cohort of 91 subjects with 320 quality-controlled metagenomes. Through recently improved taxonomic profiling methods, we identified the most discriminative species between healthy and diseased subjects at baseline, evaluated their change over time, and provided evidence that clinical treatment had a positive effect on plaque microbiome composition in patients affected by mucositis and peri-implantitis.

Plastics shape the black soldier fly larvae gut microbiome and select for biodegrading functions.

BACKGROUND: In the last few years, considerable attention has been focused on the plastic-degrading capability of insects and their gut microbiota in order to develop novel, effective, and green strategies for plastic waste management. Although many analyses based on 16S rRNA gene sequencing are available, an in-depth analysis of the insect gut microbiome to identify genes with plastic-degrading potential is still lacking. RESULTS: In the present work, we aim to fill this gap using Black Soldier Fly (BSF) as insect model. BSF larvae have proven capability to efficiently bioconvert a wide variety of organic wastes but, surprisingly, have never been considered for plastic degradation. BSF larvae were reared on two widely used plastic polymers and shotgun metagenomics was exploited to evaluate if and how plastic-containing diets affect composition and functions of the gut microbial community. The high-definition picture of the BSF gut microbiome gave access for the first time to the genomes of culturable and unculturable microorganisms in the gut of insects reared on plastics and revealed that (i) plastics significantly shaped bacterial composition at species and strain level, and (ii) functions that trigger the degradation of the polymer chains, i.e., DyP-type peroxidases, multicopper oxidases, and alkane monooxygenases, were highly enriched in the metagenomes upon exposure to plastics, consistently with the evidences obtained by scanning electron microscopy and 1H nuclear magnetic resonance analyses on plastics. CONCLUSIONS: In addition to highlighting that the astonishing plasticity of the microbiota composition of BSF larvae is associated with functional shifts in the insect microbiome, the present work sets the stage for exploiting BSF larvae as "bioincubators" to isolate microbial strains and enzymes for the development of innovative plastic biodegradation strategies. However, most importantly, the larvae constitute a source of enzymes to be evolved and valorized by pioneering synthetic biology approaches. Video Abstract.

Maternal and food microbial sources shape the infant microbiome of a rural Ethiopian population.

The human microbiome seeding starts at birth, when pioneer microbes are acquired mainly from the mother. Mode of delivery, antibiotic prophylaxis, and feeding method have been studied as modulators of mother-to-infant microbiome transmission, but other key influencing factors like modern westernized lifestyles with high hygienization, high-calorie diets, and urban settings, compared with non-westernized lifestyles have not been investigated yet. In this study, we explored the mother-infant sharing of characterized and uncharacterized microbiome members via strain-resolved metagenomics in a cohort of Ethiopian mothers and infants, and we compared them with four other cohorts with different lifestyles. The westernized and non-westernized newborns' microbiomes composition overlapped during the first months of life more than later in life, likely reflecting similar initial breast-milk-based diets. Ethiopian and other non-westernized infants shared a smaller fraction of the microbiome with their mothers than did most westernized populations, despite showing a higher microbiome diversity, and uncharacterized species represented a substantial fraction of those shared in the Ethiopian cohort. Moreover, we identified uncharacterized species belonging to the Selenomonadaceae and Prevotellaceae families specifically present and shared only in the Ethiopian cohort, and we showed that a locally produced fermented food, injera, can contribute to the higher diversity observed in the Ethiopian infants' gut with bacteria that are not part of the human microbiome but are acquired through fermented food consumption. Taken together, these findings highlight the fact that lifestyle can impact the gut microbiome composition not only through differences in diet, drug consumption, and environmental factors but also through its effect on mother-infant strain-sharing patterns.

Distinct Signatures of Tumor-Associated Microbiota and Metabolome in Low-Grade vs. High-Grade Dysplastic Colon Polyps: Inference of Their Role in Tumor Initiation and Progression.

According to the driver-passenger model for colorectal cancer (CRC), the tumor-associated microbiota is a dynamic ecosystem of bacterial species where bacteria with carcinogenic features linked to CRC initiation are defined as "drivers", while opportunistic bacteria colonizing more advanced tumor stages are known as "passengers". We reasoned that also gut microbiota-associated metabolites may be differentially enriched according to tumor stage, and be potential determinants of CRC development. Thus, we characterized the mucosa- and lumen-associated microbiota (MAM and LAM, respectively) and mucosa-associated metabolites in low- vs. high-grade dysplastic colon polyps from 78 patients. We show that MAM, obtained with a new biopsy-preserving approach, and LAM differ in composition and α/ß-diversity. By stratifying patients for polyp histology, we found that bacteria proposed as passengers by previous studies colonized high-grade dysplastic adenomas, whereas driver taxa were enriched in low-grade polyps. Furthermore, we report altered "mucosa-associated metabolite" levels in low- vs. high-grade groups. Integrated microbiota-metabolome analysis suggests the involvement of the gut microbiota in the production and consumption of these metabolites. Altogether, our findings support the involvement of bacterial species and associated metabolites in CRC mucosal homeostasis in a tumor-stage-specific manner. These distinct signatures may be used to distinguish low-grade from high-grade dysplastic polyps.

Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4.

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.

MetaPhlAn 4 profiling of unknown species-level genome bins improves the characterization of diet-associated microbiome changes in mice.

Mouse models are key tools for investigating host-microbiome interactions. However, shotgun metagenomics can only profile a limited fraction of the mouse gut microbiome. Here, we employ a metagenomic profiling method, MetaPhlAn 4, which exploits a large catalog of metagenome-assembled genomes (including 22,718 metagenome-assembled genomes from mice) to improve the profiling of the mouse gut microbiome. We combine 622 samples from eight public datasets and an additional cohort of 97 mouse microbiomes, and we assess the potential of MetaPhlAn 4 to better identify diet-related changes in the host microbiome using a meta-analysis approach. We find multiple, strong, and reproducible diet-related microbial biomarkers, largely increasing those identifiable by other available methods relying only on reference information. The strongest drivers of the diet-induced changes are uncharacterized and previously undetected taxa, confirming the importance of adopting metagenomic methods integrating metagenomic assemblies for comprehensive profiling.

Extension of the Segatella copri complex to 13 species with distinct large extrachromosomal elements and associations with host conditions.

The Segatella copri (formerly Prevotella copri) complex (ScC) comprises taxa that are key members of the human gut microbiome. It was previously described to contain four distinct phylogenetic clades. Combining targeted isolation with large-scale metagenomic analysis, we defined 13 distinct Segatella copri-related species, expanding the ScC complex beyond four clades. Complete genome reconstruction of thirteen strains from seven species unveiled the presence of genetically diverse large circular extrachromosomal elements. These elements are consistently present in most ScC species, contributing to intra- and inter-species diversities. The nine species-level clades present in humans display striking differences in prevalence and intra-species genetic makeup across human populations. Based on a meta-analysis, we found reproducible associations between members of ScC and the male sex and positive correlations with lower visceral fat and favorable markers of cardiometabolic health. Our work uncovers genomic diversity within ScC, facilitating a better characterization of the human microbiome.