Subspecies in the global human gut microbiome

Genome-resolved metagenomics: a game changer for microbiome medicine

Recent substantial evidence implicating commensal bacteria in human diseases has given rise to a new domain in biomedical research: microbiome medicine. This emerging field aims to understand and leverage the human microbiota and derivative molecules for disease prevention and treatment. Despite the complex and hierarchical organization of this ecosystem, most research over the years has relied on 16S amplicon sequencing, a legacy of bacterial phylogeny and taxonomy. Although advanced sequencing technologies have enabled cost-effective analysis of entire microbiota, translating the relatively short nucleotide information into the functional and taxonomic organization of the microbiome has posed challenges until recently. In the last decade, genome-resolved metagenomics, which aims to reconstruct microbial genomes directly from whole-metagenome sequencing data, has made significant strides and continues to unveil the mysteries of various human-associated microbial communities. There has been a rapid increase in the volume of whole metagenome sequencing data and in the compilation of novel metagenome-assembled genomes and protein sequences in public depositories. This review provides an overview of the capabilities and methods of genome-resolved metagenomics for studying the human microbiome, with a focus on investigating the prokaryotic microbiota of the human gut. Just as decoding the human genome and its variations marked the beginning of the genomic medicine era, unraveling the genomes of commensal microbes and their sequence variations is ushering us into the era of microbiome medicine. Genome-resolved metagenomics stands as a pivotal tool in this transition and can accelerate our journey toward achieving these scientific and medical milestones.

A commensal-derived sugar protects against metabolic disease

Obesity is a worsening global epidemic that is regulated by the microbiota through unknown bacterial factors. We discovered a human-derived commensal bacterium, Clostridium immunis , that protects against metabolic disease by secreting a phosphocholine-modified exopolysaccharide. Genetic interruption of the phosphocholine biosynthesis locus ( licABC ) results in a functionally inactive exopolysaccharide, which demonstrates the critical requirement for this phosphocholine moiety. This C. immunis exopolysaccharide acts via group 3 innate lymphoid cells and modulating IL-22 levels, which results in a reduction in serum triglycerides, body weight, and visceral adiposity. Importantly, phosphocholine biosynthesis genes are less abundant in humans with obesity or hypertriglyceridemia, findings that suggest the role of bacterial phosphocholine is conserved across mice and humans. These results define a bacterial molecule-and its key structural motif-that regulates host metabolism. More broadly, they highlight how small molecules, such as phosphocholine, may help fine-tune microbiome- immune-metabolism interactions.

Evaluation of normalization methods for predicting quantitative phenotypes in metagenomic data analysis

Genotype-to-phenotype mapping is an essential problem in the current genomic era. While qualitative case-control predictions have received significant attention, less emphasis has been placed on predicting quantitative phenotypes. This emerging field holds great promise in revealing intricate connections between microbial communities and host health. However, the presence of heterogeneity in microbiome datasets poses a substantial challenge to the accuracy of predictions and undermines the reproducibility of models. To tackle this challenge, we investigated 22 normalization methods that aimed at removing heterogeneity across multiple datasets, conducted a comprehensive review of them, and evaluated their effectiveness in predicting quantitative phenotypes in three simulation scenarios and 31 real datasets. The results indicate that none of these methods demonstrate significant superiority in predicting quantitative phenotypes or attain a noteworthy reduction in Root Mean Squared Error (RMSE) of the predictions. Given the frequent occurrence of batch effects and the satisfactory performance of batch correction methods in predicting datasets affected by these effects, we strongly recommend utilizing batch correction methods as the initial step in predicting quantitative phenotypes. In summary, the performance of normalization methods in predicting metagenomic data remains a dynamic and ongoing research area. Our study contributes to this field by undertaking a comprehensive evaluation of diverse methods and offering valuable insights into their effectiveness in predicting quantitative phenotypes.

The causality between gut microbiota and non-Hodgkin lymphoma: a two-sample bidirectional Mendelian randomization study

Background

Studies have indicated an association between gut microbiota (GM) and non-Hodgkin lymphoma (NHL). However, the causality between GM and NHL remains unclear. This study aims to investigate the causality between GM and NHL using Mendelian randomization (MR).

Methods

Data on GM is sourced from the MiBioGen consortium, while data on NHL and its subtypes is sourced from the FinnGen consortium R10 version. Inverse variance weighted (IVW) was employed for the primary MR analysis method, with methods such as Bayesian weighted Mendelian randomisation (BWMR) as an adjunct. Sensitivity analyses were conducted using Cochran's Q test, MR-Egger regression, MR-PRESSO, and the "Leave-one-out" method.

Results

The MR results showed that there is a causality between 27 GMs and NHL. Among them, 20 were negatively associated (OR < 1), and 7 were positively associated (OR > 1) with the corresponding diseases. All 27 MR results passed sensitivity tests, and there was no reverse causal association.

Conclusion

By demonstrating a causal link between GM and NHL, this research offers novel ideas to prevent, monitor, and cure NHL later.

Genome plasticity shapes the ecology and evolution of Phocaeicola dorei and Phocaeicola vulgatus

Phocaeicola dorei and Phocaeicola vulgatus are very common and abundant members of the human gut microbiome and play an important role in the infant gut microbiome. These species are closely related and often confused for one another; yet, their genome comparison, interspecific diversity, and evolutionary relationships have not been studied in detail so far. Here, we perform phylogenetic analysis and comparative genomic analyses of these two Phocaeicola species. We report that P. dorei has a larger genome yet a smaller pan-genome than P. vulgatus. We found that this is likely because P. vulgatus is more plastic than P. dorei, with a larger repertoire of genetic mobile elements and fewer anti-phage defense systems. We also found that P. dorei directly descends from a clade of P. vulgatus¸ and experienced genome expansion through genetic drift and horizontal gene transfer. Overall, P. dorei and P. vulgatus have very different functional and carbohydrate utilisation profiles, hinting at different ecological strategies, yet they present similar antimicrobial resistance profiles.

The gut microbiome of Baka forager-horticulturalists from Cameroon is optimized for wild plant foods

The human gut microbiome is losing biodiversity, due to the "microbiome modernization process" that occurs with urbanization. To keep track of it, here we applied shotgun metagenomics to the gut microbiome of the Baka, a group of forager-horticulturalists from Cameroon, who combine hunting and gathering with growing a few crops and working for neighboring Bantu-speaking farmers. We analyzed the gut microbiome of individuals with different access to and use of wild plant and processed foods, to explore the variation of their gut microbiome along the cline from hunter-gatherer to agricultural subsistence patterns. We found that 26 species-level genome bins from our cohort were pivotal for the degradation of the wild plant food substrates. These microbes include Old Friend species and are encoded for genes that are no longer present in industrialized gut microbiome. Our results highlight the potential relevance of these genes to human biology and health, in relation to lifestyle.

Discovering and exploring the hidden diversity of human gut viruses using highly enriched virome samples

Viruses are an abundant and crucial component of the human microbiome, but accurately discovering them via metagenomics is still challenging. Currently, the available viral reference genomes poorly represent the diversity in microbiome samples, and expanding such a set of viral references is difficult. As a result, many viruses are still undetectable through metagenomics even when considering the power of de novo metagenomic assembly and binning, as viruses lack universal markers. Here, we describe a novel approach to catalog new viral members of the human gut microbiome and show how the resulting resource improves metagenomic analyses. We retrieved >3,000 viral-like particles (VLP) enriched metagenomic samples (viromes), evaluated the efficiency of the enrichment in each sample to leverage the viromes of highest purity, and applied multiple analysis steps involving assembly and comparison with hundreds of thousands of metagenome-assembled genomes to discover new viral genomes. We reported over 162,000 viral sequences passing quality control from thousands of gut metagenomes and viromes. The great majority of the retrieved viral sequences (~94.4%) were of unknown origin, most had a CRISPR spacer matching host bacteria, and four of them could be detected in >50% of a set of 18,756 gut metagenomes we surveyed. We included the obtained collection of sequences in a new MetaPhlAn 4.1 release, which can quantify reads within a metagenome matching the known and newly uncovered viral diversity. Additionally, we released the viral database for further virome and metagenomic studies of the human microbiome.

Dynamics of bacterial recombination in the human gut microbiome

Horizontal gene transfer (HGT) is a ubiquitous force in microbial evolution. Previous work has shown that the human gut is a hotspot for gene transfer between species, but the more subtle exchange of variation within species-also known as recombination-remains poorly characterized in this ecosystem. Here, we show that the genetic structure of the human gut microbiome provides an opportunity to measure recent recombination events from sequenced fecal samples, enabling quantitative comparisons across diverse commensal species that inhabit a common environment. By analyzing recent recombination events in the core genomes of 29 human gut bacteria, we observed widespread heterogeneities in the rates and lengths of transferred fragments, which are difficult to explain by existing models of ecological isolation or homology-dependent recombination rates. We also show that natural selection helps facilitate the spread of genetic variants across strain backgrounds, both within individual hosts and across the broader population. These results shed light on the dynamics of in situ recombination, which can strongly constrain the adaptability of gut microbial communities.

An evolution-based framework for describing human gut bacteria

The human gut microbiome contains many bacterial strains of the same species ('strain-level variants'). Describing strains in a biologically meaningful way rather than purely taxonomically is an important goal but challenging due to the genetic complexity of strain-level variation. Here, we measured patterns of co-evolution across >7,000 strains spanning the bacterial tree-of-life. Using these patterns as a prior for studying hundreds of gut commensal strains that we isolated, sequenced, and metabolically profiled revealed widespread structure beneath the phylogenetic level of species. Defining strains by their co-evolutionary signatures enabled predicting their metabolic phenotypes and engineering consortia from strain genome content alone. Our findings demonstrate a biologically relevant organization to strain-level variation and motivate a new schema for describing bacterial strains based on their evolutionary history.

Strain-level diversity of symbiont communities between individuals and populations of a bioluminescent fish

The bioluminescent symbiosis involving the urchin cardinalfish, Siphamia tubifer, and Photobacterium mandapamensis, a luminous member of the Vibrionaceae, is highly specific compared to other bioluminescent fish-bacteria associations. Despite this high degree of specificity, patterns of genetic diversity have been observed for the symbionts from hosts sampled over relatively small spatial scales. We characterized and compared sub-species, strain-level symbiont diversity within and between S. tubifer hosts sampled from the Philippines and Japan using PCR fingerprinting. We then carried out whole genome sequencing of the unique symbiont genotypes identified to characterize the genetic diversity of the symbiont community and the symbiont pangenome. We determined that an individual light organ contains six symbiont genotypes on average, but varied between 1-13. Additionally, we found that there were few genotypes shared between hosts from the same location. A phylogenetic analysis of the unique symbiont strains indicated location-specific clades, suggesting some genetic differentiation in the symbionts between host populations. We also identified symbiont genes that were variable between strains, including luxF, a member of the lux operon, which is responsible for light production. We quantified the light emission and growth rate of two strains missing luxF along with the other strains isolated from the same light organs and determined that strains lacking luxF were dimmer but grew faster than most of the other strains, suggesting a potential metabolic trade-off. This study highlights the importance of strain-level diversity in microbial associations and provides new insight into the underlying genetic architecture of intraspecific symbiont communities within a host.

Inference of the demographic histories and selective effects of human gut commensal microbiota over the course of human history

Despite the importance of gut commensal microbiota to human health, there is little knowledge about their evolutionary histories, including their population demographic histories and their distributions of fitness effects (DFE) of new mutations. Here, we infer the demographic histories and DFEs of 27 of the most highly prevalent and abundant commensal gut microbial species in North Americans over timescales exceeding human generations using a collection of lineages inferred from a panel of healthy hosts. We find overall reductions in genetic variation among commensal gut microbes sampled from a Western population relative to an African rural population. Additionally, some species in North American microbiomes display contractions in population size and others expansions, potentially occurring at several key historical moments in human history. DFEs across species vary from highly to mildly deleterious, with accessory genes experiencing more drift compared to core genes. Within genera, DFEs tend to be more congruent, reflective of underlying phylogenetic relationships. Taken together, these findings suggest that human commensal gut microbes have distinct evolutionary histories, possibly reflecting the unique roles of individual members of the microbiome.

High-resolution strain-level microbiome composition analysis from short reads

BACKGROUND

Bacterial strains under the same species can exhibit different biological properties, making strain-level composition analysis an important step in understanding the dynamics of microbial communities. Metagenomic sequencing has become the major means for probing the microbial composition in host-associated or environmental samples. Although there are a plethora of composition analysis tools, they are not optimized to address the challenges in strain-level analysis: highly similar strain genomes and the presence of multiple strains under one species in a sample. Thus, this work aims to provide a high-resolution and more accurate strain-level analysis tool for short reads.

RESULTS

In this work, we present a new strain-level composition analysis tool named StrainScan that employs a novel tree-based k-mers indexing structure to strike a balance between the strain identification accuracy and the computational complexity. We tested StrainScan extensively on a large number of simulated and real sequencing data and benchmarked StrainScan with popular strain-level analysis tools including Krakenuniq, StrainSeeker, Pathoscope2, Sigma, StrainGE, and StrainEst. The results show that StrainScan has higher accuracy and resolution than the state-of-the-art tools on strain-level composition analysis. It improves the F1 score by 20% in identifying multiple strains at the strain level.

CONCLUSIONS

By using a novel k-mer indexing structure, StrainScan is able to provide strain-level analysis with higher resolution than existing tools, enabling it to return more informative strain composition analysis in one sample or across multiple samples. StrainScan takes short reads and a set of reference strains as input and its source codes are freely available at https://github.com/liaoherui/StrainScan . Video Abstract.

Global within-species phylogenetics of sewage microbes suggest that local adaptation shapes geographical bacterial clustering

Most investigations of geographical within-species differences are limited to focusing on a single species. Here, we investigate global differences for multiple bacterial species using a dataset of 757 metagenomics sewage samples from 101 countries worldwide. The within-species variations were determined by performing genome reconstructions, and the analyses were expanded by gene focused approaches. Applying these methods, we recovered 3353 near complete (NC) metagenome assembled genomes (MAGs) encompassing 1439 different MAG species and found that within-species genomic variation was in 36% of the investigated species (12/33) coherent with regional separation. Additionally, we found that variation of organelle genes correlated less with geography compared to metabolic and membrane genes, suggesting that the global differences of these species are caused by regional environmental selection rather than dissemination limitations. From the combination of the large and globally distributed dataset and in-depth analysis, we present a wide investigation of global within-species phylogeny of sewage bacteria. The global differences found here emphasize the need for worldwide data sets when making global conclusions.

Ultra-deep sequencing of Hadza hunter-gatherers recovers vanishing gut microbes

The gut microbiome modulates immune and metabolic health. Human microbiome data are biased toward industrialized populations, limiting our understanding of non-industrialized microbiomes. Here, we performed ultra-deep metagenomic sequencing on 351 fecal samples from the Hadza hunter-gatherers of Tanzania and comparative populations in Nepal and California. We recovered 91,662 genomes of bacteria, archaea, bacteriophages, and eukaryotes, 44% of which are absent from existing unified datasets. We identified 124 gut-resident species vanishing in industrialized populations and highlighted distinct aspects of the Hadza gut microbiome related to in situ replication rates, signatures of selection, and strain sharing. Industrialized gut microbes were found to be enriched in genes associated with oxidative stress, possibly a result of microbiome adaptation to inflammatory processes. This unparalleled view of the Hadza gut microbiome provides a valuable resource, expands our understanding of microbes capable of colonizing the human gut, and clarifies the extensive perturbation induced by the industrialized lifestyle.

Culturing of a complex gut microbial community in mucin-hydrogel carriers reveals strain- and gene-associated spatial organization

Microbial community function depends on both taxonomic composition and spatial organization. While composition of the human gut microbiome has been deeply characterized, less is known about the organization of microbes between regions such as lumen and mucosa and the microbial genes regulating this organization. Using a defined 117 strain community for which we generate high-quality genome assemblies, we model mucosa/lumen organization with in vitro cultures incorporating mucin hydrogel carriers as surfaces for bacterial attachment. Metagenomic tracking of carrier cultures reveals increased diversity and strain-specific spatial organization, with distinct strains enriched on carriers versus liquid supernatant, mirroring mucosa/lumen enrichment in vivo. A comprehensive search for microbial genes associated with this spatial organization identifies candidates with known adhesion-related functions, as well as novel links. These findings demonstrate that carrier cultures of defined communities effectively recapitulate fundamental aspects of gut spatial organization, enabling identification of key microbial strains and genes.

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.

Role of the Gut Microbiota in the Increased Infant Body Mass Index Induced by Gestational Diabetes Mellitus

The connection between gestational diabetes mellitus (GDM) and the offspring's development, such as obesity, is well established. Emerging evidence indicates that the microbiota of the neonate's meconium is associated with maternal GDM status. To explore whether the association between GDM and infant body mass index (BMI) in early childhood is affected by the meconium microbiota, we recruited 120 mothers (60 healthy women and 60 with GDM) and their newborns from the Women's Hospital of Nanjing Medical University. Meconium of 120 neonates was collected within a few hours after birth and sequenced using 16S rRNA sequencing analysis. Children's BMI was measured at 12 months of age. The results revealed that infants born to mothers with GDM had increased BMI Z-scores at 12 months old and that the β-diversity of their meconium microbiota was reduced. Several genera were observed to be significantly different between the GDM and control groups. The genus Burkholderia-Caballeronia-Paraburkholderia and an untitled genus in the family Enterobacteriaceae enriched in neonates born to healthy mothers were found to be negatively associated with infant BMI by using regression analysis. A coabundance group depleted in the GDM group was correlated negatively with 12-month BMI and mediated 21.65% of the association between GDM and infant BMI by mediation analyses. This study provided evidence for the associations among maternal GDM, the meconium microbiota, and infant BMI. Maternal GDM was demonstrated to affect infant BMI, mediated by the gut microbiome. Gut microbiome interventions might represent a novel technique to decrease the risk of GDM-induced childhood obesity. IMPORTANCE Using 16S rRNA sequencing analysis, regression analysis and mediation analysis were used to explore whether maternal gestational diabetes mellitus (GDM) changed the function and composition of the meconium microbiota and whether this explained the GDM-induced alterations of infant body mass index (BMI). This study showed that gut microbiome dysbiosis induced by maternal GDM might play an important role in the increased infant BMI during the first 12 months of life. Therefore, gut microbiome interventions might represent a novel technique to decrease the risk of GDM-induced childhood obesity.

Codiversification of gut microbiota with humans

The gut microbiomes of human populations worldwide have many core microbial species in common. However, within a species, some strains can show remarkable population specificity. The question is whether such specificity arises from a shared evolutionary history (codiversification) between humans and their microbes. To test for codiversification of host and microbiota, we analyzed paired gut metagenomes and human genomes for 1225 individuals in Europe, Asia, and Africa, including mothers and their children. Between and within countries, a parallel evolutionary history was evident for humans and their gut microbes. Moreover, species displaying the strongest codiversification independently evolved traits characteristic of host dependency, including reduced genomes and oxygen and temperature sensitivity. These findings all point to the importance of understanding the potential role of population-specific microbial strains in microbiome-mediated disease phenotypes.

Gut Bacteria and Neurotransmitters

Gut bacteria play an important role in the digestion of food, immune activation, and regulation of entero-endocrine signaling pathways, but also communicate with the central nervous system (CNS) through the production of specific metabolic compounds, e.g., bile acids, short-chain fatty acids (SCFAs), glutamate (Glu), γ-aminobutyric acid (GABA), dopamine (DA), norepinephrine (NE), serotonin (5-HT) and histamine. Afferent vagus nerve (VN) fibers that transport signals from the gastro-intestinal tract (GIT) and gut microbiota to the brain are also linked to receptors in the esophagus, liver, and pancreas. In response to these stimuli, the brain sends signals back to entero-epithelial cells via efferent VN fibers. Fibers of the VN are not in direct contact with the gut wall or intestinal microbiota. Instead, signals reach the gut microbiota via 100 to 500 million neurons from the enteric nervous system (ENS) in the submucosa and myenteric plexus of the gut wall. The modulation, development, and renewal of ENS neurons are controlled by gut microbiota, especially those with the ability to produce and metabolize hormones. Signals generated by the hypothalamus reach the pituitary and adrenal glands and communicate with entero-epithelial cells via the hypothalamic pituitary adrenal axis (HPA). SCFAs produced by gut bacteria adhere to free fatty acid receptors (FFARs) on the surface of intestinal epithelial cells (IECs) and interact with neurons or enter the circulatory system. Gut bacteria alter the synthesis and degradation of neurotransmitters. This review focuses on the effect that gut bacteria have on the production of neurotransmitters and vice versa.

StrainPanDA: Linked reconstruction of strain composition and gene content profiles via pangenome-based decomposition of metagenomic data

Microbial strains of variable functional capacities coexist in microbiomes. Current bioinformatics methods of strain analysis cannot provide the direct linkage between strain composition and their gene contents from metagenomic data. Here we present Strain-level Pangenome Decomposition Analysis (StrainPanDA), a novel method that uses the pangenome coverage profile of multiple metagenomic samples to simultaneously reconstruct the composition and gene content variation of coexisting strains in microbial communities. We systematically validate the accuracy and robustness of StrainPanDA using synthetic data sets. To demonstrate the power of gene-centric strain profiling, we then apply StrainPanDA to analyze the gut microbiome samples of infants, as well as patients treated with fecal microbiota transplantation. We show that the linked reconstruction of strain composition and gene content profiles is critical for understanding the relationship between microbial adaptation and strain-specific functions (e.g., nutrient utilization and pathogenicity). Finally, StrainPanDA has minimal requirements for computing resources and can be scaled to process multiple species in a community in parallel. In short, StrainPanDA can be applied to metagenomic data sets to detect the association between molecular functions and microbial/host phenotypes to formulate testable hypotheses and gain novel biological insights at the strain or subspecies level.

Gut microbiota and meat quality

Sustainable meat production is important to providing safe and quality protein sources for humans worldwide. Intensive artificial selection and high energy input into the diet of many commercial animals for the last decade has significantly increased the daily gain of body weight and shortened the raising period, but unexpectedly decreased the meat quality. The gastrointestinal tract of animals harbors a diverse and complex microbial community that plays a vital role in the digestion and absorption of nutrients, immune system development, pathogen exclusion, and meat quality. Fatty acid composition and oxidative stress in adipose and muscle tissue influences meat quality in livestock and poultry. Recent studies showed that nutraceuticals are receiving increased attention, which could alter the intestinal microbiota and regulate the fat deposition and immunity of hosts to improve their meat quality. Understanding the microbiota composition, the functions of key bacteria, and the host-microbiota interaction is crucial for the development of knowledge-based strategies to improve both animal meat quality and host health. This paper reviews the microorganisms that affect the meat quality of livestock and poultry. A greater understanding of microbial changes that accompany beneficial dietary changes will lead to novel strategies to improve livestock and poultry meat product quality.

A faecal microbiota signature with high specificity for pancreatic cancer

BACKGROUND

Recent evidence suggests a role for the microbiome in pancreatic ductal adenocarcinoma (PDAC) aetiology and progression.

OBJECTIVE

To explore the faecal and salivary microbiota as potential diagnostic biomarkers.

METHODS

We applied shotgun metagenomic and 16S rRNA amplicon sequencing to samples from a Spanish case-control study (n=136), including 57 cases, 50 controls, and 29 patients with chronic pancreatitis in the discovery phase, and from a German case-control study (n=76), in the validation phase.

RESULTS

Faecal metagenomic classifiers performed much better than saliva-based classifiers and identified patients with PDAC with an accuracy of up to 0.84 area under the receiver operating characteristic curve (AUROC) based on a set of 27 microbial species, with consistent accuracy across early and late disease stages. Performance further improved to up to 0.94 AUROC when we combined our microbiome-based predictions with serum levels of carbohydrate antigen (CA) 19-9, the only current non-invasive, Food and Drug Administration approved, low specificity PDAC diagnostic biomarker. Furthermore, a microbiota-based classification model confined to PDAC-enriched species was highly disease-specific when validated against 25 publicly available metagenomic study populations for various health conditions (n=5792). Both microbiome-based models had a high prediction accuracy on a German validation population (n=76). Several faecal PDAC marker species were detectable in pancreatic tumour and non-tumour tissue using 16S rRNA sequencing and fluorescence in situ hybridisation.

CONCLUSION

Taken together, our results indicate that non-invasive, robust and specific faecal microbiota-based screening for the early detection of PDAC is feasible.

Scalable Microbial Strain Inference in Metagenomic Data Using StrainFacts

While genome databases are nearing a complete catalog of species commonly inhabiting the human gut, their representation of intraspecific diversity is lacking for all but the most abundant and frequently studied taxa. Statistical deconvolution of allele frequencies from shotgun metagenomic data into strain genotypes and relative abundances is a promising approach, but existing methods are limited by computational scalability. Here we introduce StrainFacts, a method for strain deconvolution that enables inference across tens of thousands of metagenomes. We harness a “fuzzy” genotype approximation that makes the underlying graphical model fully differentiable, unlike existing methods. This allows parameter estimates to be optimized with gradient-based methods, speeding up model fitting by two orders of magnitude. A GPU implementation provides additional scalability. Extensive simulations show that StrainFacts can perform strain inference on thousands of metagenomes and has comparable accuracy to more computationally intensive tools. We further validate our strain inferences using single-cell genomic sequencing from a human stool sample. Applying StrainFacts to a collection of more than 10,000 publicly available human stool metagenomes, we quantify patterns of strain diversity, biogeography, and linkage-disequilibrium that agree with and expand on what is known based on existing reference genomes. StrainFacts paves the way for large-scale biogeography and population genetic studies of microbiomes using metagenomic data.

Panoramic Insights into Microevolution and Macroevolution of A Prevotella copri-containing Lineage in Primate Guts

Prevotella copri and its related taxa are widely detected in mammalian gut microbiomes and have been linked with an enterotype in humans. However, their microevolution and macroevolution among hosts are poorly characterized. In this study, extensively collected marker genes and genomes were analyzed to trace their evolutionary history, host specificity, and biogeographic distribution. Investigations based on marker genes and genomes suggest that a P. copri-containing lineage (PCL) harbors diverse species in higher primates. Firstly, P. copri in the human gut consisted of multiple groups exhibiting high genomic divergence and conspicuous but non-strict biogeographic patterns. Most African strains with high genomic divergence from other strains were phylogenetically located at the root of the species, indicating the co-evolutionary history of P. copri and Homo sapiens. Secondly, although long-term co-evolution between PCL and higher primates was revealed, sporadic signals of co-speciation and extensive host jumping of PCL members were suggested among higher primates. Metagenomic and phylogenetic analyses indicated that P. copri and other PCL species found in domesticated mammals had been recently transmitted from humans. Thirdly, strong evidence was found on the extensively horizontal transfer of genes (e.g., genes encoding carbohydrate-active enzymes) among sympatric P. copri groups and PCL species in the same primate host. Our study provides panoramic insights into the combined effects of vertical and horizontal transmission, as well as potential niche adaptation, on the microevolutionary and macroevolutionary history for an enterotype-representative lineage.

Ultra-deep Sequencing of Hadza Hunter-Gatherers Recovers Vanishing Microbes.. [PMID: 36238714 PMCID: PMC9558438 DOI: 10.1101/2022.03.30.486478]

The gut microbiome is a key modulator of immune and metabolic health. Human microbiome data is biased towards industrialized populations, providing limited understanding of the distinct and diverse non-industrialized microbiomes. Here, we performed ultra-deep metagenomic sequencing and strain cultivation on 351 fecal samples from the Hadza, hunter-gatherers in Tanzania, and comparative populations in Nepal and California. We recover 94,971 total genomes of bacteria, archaea, bacteriophages, and eukaryotes, 43% of which are absent from existing unified datasets. Analysis of in situ growth rates, genetic pN/pS signatures, high-resolution strain tracking, and 124 gut-resident species vanishing in industrialized populations reveals differentiating dynamics of the Hadza gut microbiome. Industrialized gut microbes are enriched in genes associated with oxidative stress, possibly a result of microbiome adaptation to inflammatory processes. This unparalleled view of the Hadza gut microbiome provides a valuable resource that expands our understanding of microbes capable of colonizing the human gut and clarifies the extensive perturbation brought on by the industrialized lifestyle.

Cerebral Intraparenchymal Hemorrhage Changes Patients’ Gut Bacteria Composition and Function

Gut bacteria consists of 150 times more genes than humans that are vital for health. Several studies revealed that gut bacteria are associated with disease status and influence human behavior and mentality. Whether human brain injury alters the gut bacteria is yet unclear, we tested 20 fecal samples from patients with cerebral intraparenchymal hemorrhage and corresponding healthy controls through metagenomic shotgun sequencing. The composition of patients’ gut bacteria changed significantly at the phylum level; Verrucomicrobiota was the specific phylum colonized in the patients’ gut. The functional alteration was observed in the patients’ gut bacteria, including high metabolic activity for nutrients or neuroactive compounds, strong antibiotic resistance, and less virulence factor diversity. The changes in the transcription and metabolism of differential species were more evident than those of the non-differential species between groups, which is the primary factor contributing to the functional alteration of patients with cerebral intraparenchymal hemorrhage.

Comprehensive mouse microbiota genome catalog reveals major difference to its human counterpart

Mouse is the most used model for studying the impact of microbiota on its host, but the repertoire of species from the mouse gut microbiome remains largely unknown. Accordingly, the similarity between human and mouse microbiomes at a low taxonomic level is not clear. We construct a comprehensive mouse microbiota genome (CMMG) catalog by assembling all currently available mouse gut metagenomes and combining them with published reference and metagenome-assembled genomes. The 41’798 genomes cluster into 1’573 species, of which 78.1% are uncultured, and we discovered 226 new genera, seven new families, and one new order. CMMG enables an unprecedented coverage of the mouse gut microbiome exceeding 86%, increases the mapping rate over four-fold, and allows functional microbiota analyses of human and mouse linking them to the driver species. Comparing CMMG to microbiota from the unified human gastrointestinal genomes shows an overlap of 62% at the genus but only 10% at the species level, demonstrating that human and mouse gut microbiota are largely distinct. CMMG contains the most comprehensive collection of consistently functionally annotated species of the mouse and human microbiome to date, setting the ground for analysis of new and reanalysis of existing datasets at an unprecedented depth.

The microbiome plays an indispensable role in our health. Metagenomics enables valuable insights into the composition and functional potential of microbial populations. The analysis of metagenomic data is complex and depends on the availability of reference genomes. The mouse is the most used model for studying the impact of microbiota on its host. However, the microbial species living in the mouse gut remain poorly characterized. We created a comprehensive catalog of all bacterial species commonly living in the gut of laboratory mice by analyzing all publicly available metagenomes from the mouse gut. We collected almost 42 thousand bacterial genomes from 1’573 species, of which 78.1% are uncultured. Our catalog effectively answers the need for a genome reference for this microbiome and allows efficient analysis of mouse gut metagenomes down to the species level. We discovered that mice and humans harbor a largely distinct set of species in their gastrointestinal tracts, a hereto unfeasible analysis.

The gut microbiome and antibiotic resistome of chronic diarrhea rhesus macaques (Macaca mulatta) and its similarity to the human gut microbiome

BACKGROUND

Chronic diarrhea is a common disease causing morbidity and mortality of captive rhesus macaques (RMs, Macaca mulatta). Chronic diarrhea in RMs is typically characterized by long-term diarrhea and a weak response to antibiotic treatment. Diarrhea is also a common disease in humans and can cause death. However, the etiology of about half of diarrheal cases of humans is still unclear. Therefore, we performed shotgun metagenomic sequencing to characterize the differences in the gut microbiome and resistome of chronic diarrhea RMs and asymptomatic individuals.

RESULTS

Our results showed Lactobacillus spp. (mainly L. johnsonii, L. reuteri and L. amylovorus) were significantly depleted in chronic diarrhea RM guts compared to asymptomatic individuals (5.2 vs 42.4%). Functional annotation of genes suggested these Lactobacillus spp. carried genes involved in the adhesion of intestinal epithelial cells and production of bacteriocin. Chronic diarrhea RM guts also had a significantly greater abundance of many other gut bacteria, including mucin-degrading bacteria and opportunistic pathogens. The metabolic pathways of chronic diarrhea RM gut microbiome were enriched in aerobactin biosynthesis, while the metabolic pathways of asymptomatic RM gut microbiome were enriched in the production of short-chain fatty acids (SCFAs). Chronic diarrhea RM guts had a significantly greater abundance of antibiotic resistance genes (ARGs), such as ermF, aph(3')-IIIa, ermB, and floR. The strains isolated from feces and tissue fluid of chronic diarrhea RMs had higher resistance rates to the majority of tested antibiotics, but not cephamycin and carbapenem antibiotics. Gut microbial composition comparisons showed that several captive nonhuman primate (NHP) guts were more similar to the guts of humans with a non-westernized diet than humans with a westernized diet. Chronic diarrhea RM gut microbiome was strikingly similar to rural-living humans with diarrhea and humans with a non-westernized diet than asymptomatic RMs.

CONCLUSIONS

Our results suggested chronic diarrhea significantly altered the composition and metabolic pathways of the RM gut microbiome. The frequent use of antibiotics caused antibiotic resistance in chronic diarrhea RM gut microbiome with serious consequences for individual treatment and survival. The findings of this study will help us to improve the effective prevention and treatment of diarrhea in RMs. Video Abstract.

Maternal consumption of artificially sweetened beverages during pregnancy is associated with infant gut microbiota and metabolic modifications and increased infant body mass index

Artificial sweetener consumption by pregnant women has been associated with an increased risk of infant obesity, but the underlying mechanisms are unknown. We aimed to determine if maternal consumption of artificially sweetened beverages (ASB) during pregnancy is associated with modifications of infant gut bacterial community composition and function during the first year of life, and whether these alterations are linked with infant body mass index (BMI) at one year of age. We studied 100 infants from the prospective Canadian CHILD Cohort Study, selected based on maternal ASB consumption during pregnancy (50 non-consumers and 50 daily consumers). BMI was higher among ASB-exposed infants. Infant stool (16S rRNA gene sequencing) and urine (untargeted metabolomics) were acquired in early (3-4 months) and late (12 months) infancy. We identified four microbiome clusters, of which two recapitulated the maturation trajectory of the infant gut bacterial communities from immature (Cluster 1) to mature (Cluster 4) and two deviated from this trajectory (Clusters 2 and 3). Maternal ASB consumption did not differ between clusters, but was associated with community-level shifts in infant gut bacterial taxonomy structure and depletion of several Bacteroides sp. in Cluster 2. In the complete dataset, urine succinate and spermidine levels at 3 months were higher in ASB-exposed infants, and urine succinate was positively associated with BMI at one-year-old. Overall, gestational exposure to ASB was associated with gut microbiota structure in infants from Cluster 2, and gut microbiota structure was associated with infant BMI. Gestational exposure to ASB was positively associated with infant urine succinate and spermidine. Succinate was found to mediate 29% of the effect of ASB exposure on BMI at one-year-old, revealing a potential role of this metabolite in increased infant weight linked to gestational ASB consumption. As we face an unprecedented rise in childhood obesity, future studies should evaluate the causal relationships between maternal ASB consumption (a modifiable exposure), gut microbiota and metabolites, infant metabolism, and body composition.

Towards a metagenomics machine learning interpretable model for understanding the transition from adenoma to colorectal cancer

Gut microbiome is gaining interest because of its links with several diseases, including colorectal cancer (CRC), as well as the possibility of being used to obtain non-intrusive predictive disease biomarkers. Here we performed a meta-analysis of 1042 fecal metagenomic samples from seven publicly available studies. We used an interpretable machine learning approach based on functional profiles, instead of the conventional taxonomic profiles, to produce a highly accurate predictor of CRC with better precision than those of previous proposals. Moreover, this approach is also able to discriminate samples with adenoma, which makes this approach very promising for CRC prevention by detecting early stages in which intervention is easier and more effective. In addition, interpretable machine learning methods allow extracting features relevant for the classification, which reveals basic molecular mechanisms accounting for the changes undergone by the microbiome functional landscape in the transition from healthy gut to adenoma and CRC conditions. Functional profiles have demonstrated superior accuracy in predicting CRC and adenoma conditions than taxonomic profiles and additionally, in a context of explainable machine learning, provide useful hints on the molecular mechanisms operating in the microbiota behind these conditions.

Comparative Population Genetics in the Human Gut Microbiome

Genetic variation in the human gut microbiome is responsible for conferring a number of crucial phenotypes like the ability to digest food and metabolize drugs. Yet, our understanding of how this variation arises and is maintained remains relatively poor. Thus, the microbiome remains a largely untapped resource, as the large number of coexisting species in the microbiome presents a unique opportunity to compare and contrast evolutionary processes across species to identify universal trends and deviations. Here we outline features of the human gut microbiome that, while not unique in isolation, as an assemblage make it a system with unparalleled potential for comparative population genomics studies. We consciously take a broad view of comparative population genetics, emphasizing how sampling a large number of species allows researchers to identify universal evolutionary dynamics in addition to new genes, which can then be leveraged to identify exceptional species that deviate from general patterns. To highlight the potential power of comparative population genetics in the microbiome, we reanalyze patterns of purifying selection across ∼40 prevalent species in the human gut microbiome to identify intriguing trends which highlight functional categories in the microbiome that may be under more or less constraint.

Variation and transmission of the human gut microbiota across multiple familial generations

Although the composition and functional potential of the human gut microbiota evolve over the lifespan, kinship has been identified as a key covariate of microbial community diversification. However, to date, sharing of microbiota features within families has mostly been assessed between parents and their direct offspring. Here we investigate the potential transmission and persistence of familial microbiome patterns and microbial genotypes in a family cohort (n = 102) spanning 3 to 5 generations over the same female bloodline. We observe microbiome community composition associated with kinship, with seven low abundant genera displaying familial distribution patterns. While kinship and current cohabitation emerge as closely entangled variables, our explorative analyses of microbial genotype distribution and transmission estimates point at the latter as a key covariate of strain dissemination. Highest potential transmission rates are estimated between sisters and mother-daughter pairs, decreasing with increasing daughter's age and being higher among cohabiting pairs than those living apart. Although rare, we detect potential transmission events spanning three and four generations, primarily involving species of the genera Alistipes and Bacteroides. Overall, while our analyses confirm the existence of family-bound microbiome community profiles, transmission or co-acquisition of bacterial strains appears to be strongly linked to cohabitation.

Honey bee genetics shape the strain-level structure of gut microbiota in social transmission

BACKGROUND

Honey bee gut microbiota transmitted via social interactions are beneficial to the host health. Although the microbial community is relatively stable, individual variations and high strain-level diversity have been detected across honey bees. Although the bee gut microbiota structure is influenced by environmental factors, the heritability of the gut members and the contribution of the host genetics remains elusive. Considering bees within a colony are not readily genetically identical due to the polyandry of the queen, we hypothesize that the microbiota structure can be shaped by host genetics.

RESULTS

We used shotgun metagenomics to simultaneously profile the microbiota and host genotypes of bees from hives of four different subspecies. Gut composition is more distant between genetically different bees at both phylotype- and "sequence-discrete population" levels. We then performed a successive passaging experiment within colonies of hybrid bees generated by artificial insemination, which revealed that the microbial composition dramatically shifts across batches of bees during the social transmission. Specifically, different strains from the phylotype of Snodgrassella alvi are preferentially selected by genetically varied hosts, and strains from different hosts show a remarkably biased distribution of single-nucleotide polymorphism in the Type IV pili loci. Genome-wide association analysis identified that the relative abundance of a cluster of Bifidobacterium strains is associated with the host glutamate receptor gene specifically expressed in the bee brain. Finally, mono-colonization of Bifidobacterium with a specific polysaccharide utilization locus impacts the alternative splicing of the gluR-B gene, which is associated with an increased GABA level in the brain.

CONCLUSIONS

Our results indicated that host genetics influence the bee gut composition and suggest a gut-brain connection implicated in the gut bacterial strain preference. Honey bees have been used extensively as a model organism for social behaviors, genetics, and the gut microbiome. Further identification of host genetic function as a shaping force of microbial structure will advance our understanding of the host-microbe interactions. Video abstract.

metaSNV v2: detection of SNVs and subspecies in prokaryotic metagenomes

SUMMARY

Taxonomic analysis of microbial communities is well supported at the level of species and strains. However, species can contain significant phenotypic diversity and strains are rarely widely shared across global populations. Stratifying the diversity between species and strains can identify 'subspecies', which are a useful intermediary. High-throughput identification and profiling of subspecies is not yet supported in the microbiome field. Here, we use an operational definition of subspecies based on single nucleotide variant (SNV) patterns within species to identify and profile subspecies in metagenomes, along with their distinctive SNVs and genes. We incorporate this method into metaSNV v2, which extends existing SNV-calling software to support further SNV interpretation for population genetics. These new features support microbiome analyses to link SNV profiles with host phenotype or environment and niche-specificity. We demonstrate subspecies identification in marine and fecal metagenomes. In the latter, we analyze 70 species in 7524 adult and infant subjects, supporting a common subspecies population structure in the human gut microbiome and illustrating some limits in subspecies calling.

AVAILABILITY AND IMPLEMENTATION

Source code, documentation, tutorials and test data are available at https://github.com/metasnv-tool/metaSNV and https://metasnv.embl.de.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Identification and Antibiotic Profiling of Wohlfahrtiimonas chitiniclastica, an Underestimated Human Pathogen

In the past 12 years, several case reports have clearly demonstrated that Wohlfahrtiimonas chitiniclastica is capable of causing sepsis and bacteremia in humans. However, since most clinicians are not familiar with this species, little is known about its pathogenicity and treatment options while it is as rare but underestimated human pathogen. Therefore, a larger strain collection is required so that methods can be identified that are most suitable to obtain rapid and reliable identification. Moreover, the antimicrobial resistance profile needs to be elucidated in order to explore possible treatment options. Over a period of 6 years, we therefore have collected a total of 14 W. chitiniclastica isolates in routine diagnostics, which now served as the basis for a comprehensive characterization with respect to identification and antibiotic profiling. We compared the accuracy and convenience of several identification techniques in which MALDI-TOF MS and sequencing of the 16S rRNA gene have proven to be suitable for identification of W. chitiniclastica. In addition, whole genome sequencing (WGS)-based digital DNA-DNA hybridization (dDDH) was used as a reference method for strain identification, and surprised with the detection of a novel W. chitiniclastica subspecies. A combination of in silico and in vitro analyses revealed a first insight into the antimicrobial resistance profile and the molecular basis of antimicrobial resistance. Based on our findings, trimethoprim/sulfamethoxazole, levofloxacin, and cephalosporins (e.g., ceftazidime) may be the best antibiotics to use in order to treat infections caused by W. chitiniclastica, while resistance to fosfomycin, amikacin and tobramycin is observed.

Genomics and Inflammation in Cardiovascular Disease

Chronic cardiovascular diseases are associated with inflammatory responses within the blood vessels and end organs. The origin of this inflammation has not been certain, and neither is its relationship to disease clear. There is a need to determine whether this association is causal or coincidental to the processes leading to cardiovascular disease. These processes are themselves complex: many cardiovascular diseases arise in conjunction with the presence of sustained elevation of blood pressure. Inflammatory processes have been linked to hypertension, and causality has been suggested. Evidence of causality poses the difficult challenge of linking the integrated and multifaceted biology of blood pressure regulation with vascular function and complex elements of immune system function. These include both, innate and adaptive immunity, as well as interactions between the host immune system and the omnipresent microorganisms that are encountered in the environment and that colonize and exist in commensal relationship with the host. Progress has been made in this task and has drawn on experimental approaches in animals, much of which have focused on hypertension occurring with prolonged infusion of angiotensin II. These laboratory studies are complemented by studies that seek to inform disease mechanism by examining the genomic basis of heritable disease susceptibility in human populations. In this realm too, evidence has emerged that implicates genetic variation affecting immunity in disease pathogenesis. In this article, we survey the genetic and genomic evidence linking high blood pressure and its end-organ injuries to immune system function and examine evidence that genomic factors can influence disease risk. © 2021 American Physiological Society. Compr Physiol 11:1-22, 2021.

Effects of laboratory domestication on the rodent gut microbiome

The domestication of the laboratory mouse has influenced the composition of its native gut microbiome, which is now known to differ from that of its wild ancestor. However, limited exploration of the rodent gut microbiome beyond the model species Mus musculus has made it difficult to interpret microbiome variation in a broader phylogenetic context. Here, we analyse 120 de novo and 469 public metagenomically-sequenced faecal and caecal samples from 16 rodent hosts representing wild, laboratory and captive lifestyles. Distinct gut bacterial communities were observed between rodent host genera, with broadly distributed species originating from the as-yet-uncultured bacterial genera UBA9475 and UBA2821 in the families Oscillospiraceae and Lachnospiraceae, respectively. In laboratory mice, Helicobacteraceae were generally depleted relative to wild mice and specific Muribaculaceae populations were enriched in different laboratory facilities, suggesting facility-specific outgrowths of this historically dominant rodent gut family. Several bacterial families of clinical interest, including Akkermansiaceae, Streptococcaceae and Enterobacteriaceae, were inferred to have gained over half of their representative species in mice within the laboratory environment, being undetected in most wild rodents and suggesting an association between laboratory domestication and pathobiont emergence.

Comparison of Gut Microbiota of 96 Healthy Dogs by Individual Traits: Breed, Age, and Body Condition Score

Simple Summary

The gut microbial ecosystem is affected by various factors such as lifestyle, environment, and disease. Although gut microbiota is closely related to host health, an understanding of the gut microbiota of dogs is still lacking. Therefore, we investigated gut microbial composition in healthy dogs and divided them into groups according to their breed, age, or body condition score. From our results, age is the most crucial factor driving the gut microbial community of dogs compared to breed and body condition score (especially Fusobacterium perfoetens, which was much more abundant in the older group). We have revealed that even in healthy dogs without any diseases, there are differences in gut microbiota depending on individual traits. These results can be used as a basis for improving the quality of life by managing dogs’ gut microbiota.

Abstract

Since dogs are part of many peoples’ lives, research and industry related to their health and longevity are becoming a rising topic. Although gut microbiota (GM) is a key contributor to host health, limited information is available for canines. Therefore, this study characterized GM according to individual signatures (e.g., breed, age, and body condition score—BCS) of dogs living in the same environment. Fresh fecal samples from 96 healthy dogs were analyzed by sequencing the V3-V4 region of the 16S rRNA gene. The major microbial phyla were Firmicutes, Bacteroidetes, Fusobacteria, Proteobacteria, and Actinobacteria. In the comparison by breeds, relative abundance of Fusobacterium was significantly differed. Interestingly, Fusobacterium perfoetens abundance was positively correlated with age (p = 0.018), being significantly more enriched in the 6–10-year-old group (14.3%) than in the 0.5–1-year-old group (7.2%). Moreover, despite the healthy appearance of dogs in all age (0.5–10 years) and BCS (3–6) groups, the gut microbial environment may be disadvantageous in older dogs or in dogs with an abnormal BCS. These findings broaden our understanding of gut microbial ecology according to individual characteristics of dogs and may be used as a reference for providing customized-care to companion animals.

Virus-associated organosulfur metabolism in human and environmental systems

Viruses influence the fate of nutrients and human health by killing microorganisms and altering metabolic processes. Organosulfur metabolism and biologically derived hydrogen sulfide play dynamic roles in manifestation of diseases, infrastructure degradation, and essential biological processes. Although microbial organosulfur metabolism is well studied, the role of viruses in organosulfur metabolism is unknown. Here, we report the discovery of 39 gene families involved in organosulfur metabolism encoded by 3,749 viruses from diverse ecosystems, including human microbiomes. The viruses infect organisms from all three domains of life. Six gene families encode for enzymes that degrade organosulfur compounds into sulfide, whereas others manipulate organosulfur compounds and may influence sulfide production. We show that viral metabolic genes encode key enzymatic domains, are translated into protein, and are maintained after recombination, and sulfide provides a fitness advantage to viruses. Our results reveal viruses as drivers of organosulfur metabolism with important implications for human and environmental health.

Genomic diversity and ecology of human-associated Akkermansia species in the gut microbiome revealed by extensive metagenomic assembly

BACKGROUND

Akkermansia muciniphila is a human gut microbe with a key role in the physiology of the intestinal mucus layer and reported associations with decreased body mass and increased gut barrier function and health. Despite its biomedical relevance, the genomic diversity of A. muciniphila remains understudied and that of closely related species, except for A. glycaniphila, unexplored.

RESULTS

We present a large-scale population genomics analysis of the Akkermansia genus using 188 isolate genomes and 2226 genomes assembled from 18,600 metagenomes from humans and other animals. While we do not detect A. glycaniphila, the Akkermansia strains in the human gut can be grouped into five distinct candidate species, including A. muciniphila, that show remarkable whole-genome divergence despite surprisingly similar 16S rRNA gene sequences. These candidate species are likely human-specific, as they are detected in mice and non-human primates almost exclusively when kept in captivity. In humans, Akkermansia candidate species display ecological co-exclusion, diversified functional capabilities, and distinct patterns of associations with host body mass. Analysis of CRISPR-Cas loci reveals new variants and spacers targeting newly discovered putative bacteriophages. Remarkably, we observe an increased relative abundance of Akkermansia when cognate predicted bacteriophages are present, suggesting ecological interactions. A. muciniphila further exhibits subspecies-level genetic stratification with associated functional differences such as a putative exo/lipopolysaccharide operon.

CONCLUSIONS

We uncover a large phylogenetic and functional diversity of the Akkermansia genus in humans. This variability should be considered in the ongoing experimental and metagenomic efforts to characterize the health-associated properties of A. muciniphila and related bacteria.

Dispersal strategies shape persistence and evolution of human gut bacteria

Human gut bacterial strains can co-exist with their hosts for decades, but little is known about how these microbes persist and disperse, and evolve thereby. Here, we examined these processes in 5,278 adult and infant fecal metagenomes, longitudinally sampled in individuals and families. Our analyses revealed that a subset of gut species is extremely persistent in individuals, families, and geographic regions, represented often by locally successful strains of the phylum Bacteroidota. These “tenacious” bacteria show high levels of genetic adaptation to the human host but a high probability of loss upon antibiotic interventions. By contrast, heredipersistent bacteria, notably Firmicutes, often rely on dispersal strategies with weak phylogeographic patterns but strong family transmissions, likely related to sporulation. These analyses describe how different dispersal strategies can lead to the long-term persistence of human gut microbes with implications for gut flora modulations.

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Bacterial strains may persist within family members through transfer

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Bacteria adapt dispersal strategies: heredipersistent, spatiopersistent, and tenacious

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Dispersal strategies correlate with genetic bottlenecks and effective population size

Microbial driven genetic variation in holobionts

Genetic variation in holobionts, (host and microbiome), occurring by changes in both host and microbiome genomes, can be observed from two perspectives: observable variations and the processes that bring about the variation. The observable includes the enormous genetic diversity of prokaryotes, which gave rise to eukaryotic organisms. Holobionts then evolved a rich microbiome with a stable core containing essential genes, less so common taxa, and a more diverse non-core enabling considerable genetic variation. The result being that, the human gut microbiome, for example, contains 1,000 times more unique genes than are present in the human genome. Microbial driven genetic variation processes in holobionts include: (1) Acquisition of novel microbes from the environment, which bring in multiple genes in one step, (2) amplification/reduction of certain microbes in the microbiome, that contribute to holobiont` s adaptation to changing conditions, (3) horizontal gene transfer between microbes and between microbes and host, (4) mutation, which plays an important role in optimizing interactions between different microbiota and between microbiota and host. We suggest that invertebrates and plants, where microbes can live intracellularly, have a greater chance of genetic exchange between microbiota and host, thus a greater chance of vertical transmission and a greater effect of microbiome on evolution of host than vertebrates. However, even in vertebrates the microbiome can aid in environmental fluctuations by amplification/reduction and by acquisition of novel microorganisms.

Diet and gut microbiome interactions of relevance for symptoms in irritable bowel syndrome

BACKGROUND

While several studies have documented associations between dietary habits and microbiota composition and function in healthy individuals, no study explored these associations in patients with irritable bowel syndrome (IBS), and especially with symptoms.

METHODS

Here, we used a novel approach that combined data from a 4-day food diary, integrated into a food tree, together with gut microbiota (shotgun metagenomic) for individuals with IBS (N = 149) and healthy controls (N = 52). Paired microbiota and food-based trees allowed us to detect new associations between subspecies and diet. Combining co-inertia analysis and linear regression models, exhaled gas levels and symptom severity could be predicted from metagenomic and dietary data.

RESULTS

We showed that individuals with severe IBS are characterized by a higher intake of poorer-quality food items during their main meals. Our analysis suggested that covariations between gut microbiota at subspecies level and diet could be explained with IBS symptom severity, exhaled gas, glycan metabolism, and meat/plant ratio. We provided evidence that IBS severity is associated with altered gut microbiota hydrogen function in correlation with microbiota enzymes involved in animal carbohydrate metabolism.

CONCLUSIONS

Our study provides an unprecedented resolution of diet-microbiota-symptom interactions and ultimately guides new interventional studies that aim to identify gut microbiome-based nutritional recommendations for the management of gastrointestinal symptoms.

TRIAL REGISTRATION

This trial was registered on the ClinicalTrials.gov, with the registration number NCT01252550 , on 3rd December 2010. Video abstract.

Recent advances in culture-based gut microbiome research

Gut microbes affect the physiology of their hosts. Studying their diversity and functions is thus of utmost importance as it will open new avenues towards the discovery of new biomolecules and the treatment of diseases. Gut microbiome research is currently boosted by the unification of metagenomics, which has dominated the field in the last two decades, and cultivation, which is experiencing a renaissance. Each of these approaches has advantages and drawbacks that can be overcome if used synergistically. In this brief article, we summarize recent literature and own studies on the cultivation of gut microbes, provide a succinct status quo of cultured fractions and collections of isolates, and give short opinions on challenges and next steps to take.

From Binary Model Systems to the Human Microbiome: Factors That Drive Strain Specificity in Host-Symbiont Associations

Microbial symbionts are ubiquitous and can have significant impact on hosts. These impacts can vary in the sign (positive or negative) and degree depending on the identity of the interacting partners. Studies on host-symbiont associations indicate that subspecies (strain) genetic variation can influence interaction outcomes, making it necessary to go beyond species-level distinction to understand host-symbiont dynamics. In this review, we discuss examples of strain specificity found in host-symbiont associations, from binary model systems to the human microbiome. Although host and bacterial factors identified as mediators for specificity could be distinct at the molecular level, they generally fall into two broad functional categories: (1) those that contribute a required activity in support of the association and (2) those involved in antagonistic interactions with organisms outside of the association. We argue here based on current literature that factors from these two categories can work in concert to drive strain specificity and that this strain specificity must be considered to fully understand the molecular and ecological dynamics of host-symbiont associations, including the human microbiome.

Microbiome connections with host metabolism and habitual diet from 1,098 deeply phenotyped individuals

The gut microbiome is shaped by diet and influences host metabolism; however, these links are complex and can be unique to each individual. We performed deep metagenomic sequencing of 1,203 gut microbiomes from 1,098 individuals enrolled in the Personalised Responses to Dietary Composition Trial (PREDICT 1) study, whose detailed long-term diet information, as well as hundreds of fasting and same-meal postprandial cardiometabolic blood marker measurements were available. We found many significant associations between microbes and specific nutrients, foods, food groups and general dietary indices, which were driven especially by the presence and diversity of healthy and plant-based foods. Microbial biomarkers of obesity were reproducible across external publicly available cohorts and in agreement with circulating blood metabolites that are indicators of cardiovascular disease risk. While some microbes, such as Prevotella copri and Blastocystis spp., were indicators of favorable postprandial glucose metabolism, overall microbiome composition was predictive for a large panel of cardiometabolic blood markers including fasting and postprandial glycemic, lipemic and inflammatory indices. The panel of intestinal species associated with healthy dietary habits overlapped with those associated with favorable cardiometabolic and postprandial markers, indicating that our large-scale resource can potentially stratify the gut microbiome into generalizable health levels in individuals without clinically manifest disease.

Radiotherapy and the gut microbiome: facts and fiction

An ever-growing body of evidence has linked the gut microbiome with both the effectiveness and the toxicity of cancer therapies. Radiotherapy is an effective way to treat tumors, although large variations exist among patients in tumor radio-responsiveness and in the incidence and severity of radiotherapy-induced side effects. Relatively little is known about whether and how the microbiome regulates the response to radiotherapy. Gut microbiota may be an important player in modulating “hot” versus “cold” tumor microenvironment, ultimately affecting treatment efficacy. The interaction of the gut microbiome and radiotherapy is a bidirectional function, in that radiotherapy can disrupt the microbiome and those disruptions can influence the effectiveness of the anticancer treatments. Limited data have shown that interactions between the radiation and the microbiome can have positive effects on oncotherapy. On the other hand, exposure to ionizing radiation leads to changes in the gut microbiome that contribute to radiation enteropathy. The gut microbiome can influence radiation-induced gastrointestinal mucositis through two mechanisms including translocation and dysbiosis. We propose that the gut microbiome can be modified to maximize the response to treatment and minimize adverse effects through the use of personalized probiotics, prebiotics, or fecal microbial transplantation. 16S rRNA sequencing is the most commonly used approach to investigate distribution and diversity of gut microbiome between individuals though it only identifies bacteria level other than strain level. The functional gut microbiome can be studied using methods involving metagenomics, metatranscriptomics, metaproteomics, as well as metabolomics. Multiple ‘-omic’ approaches can be applied simultaneously to the same sample to obtain integrated results. That said, challenges and remaining unknowns in the future that persist at this time include the mechanisms by which the gut microbiome affects radiosensitivity, interactions between the gut microbiome and combination treatments, the role of the gut microbiome with regard to predictive and prognostic biomarkers, the need for multi “-omic” approach for in-depth exploration of functional changes and their effects on host-microbiome interactions, and interactions between gut microbiome, microbial metabolites and immune microenvironment.

Metapangenomics of the oral microbiome provides insights into habitat adaptation and cultivar diversity

BACKGROUND

The increasing availability of microbial genomes and environmental shotgun metagenomes provides unprecedented access to the genomic differences within related bacteria. The human oral microbiome with its diverse habitats and abundant, relatively well-characterized microbial inhabitants presents an opportunity to investigate bacterial population structures at an ecosystem scale.

RESULTS

Here, we employ a metapangenomic approach that combines public genomes with Human Microbiome Project (HMP) metagenomes to study the diversity of microbial residents of three oral habitats: tongue dorsum, buccal mucosa, and supragingival plaque. For two exemplar taxa, Haemophilus parainfluenzae and the genus Rothia, metapangenomes reveal distinct genomic groups based on shared genome content. H. parainfluenzae genomes separate into three distinct subgroups with differential abundance between oral habitats. Functional enrichment analyses identify an operon encoding oxaloacetate decarboxylase as diagnostic for the tongue-abundant subgroup. For the genus Rothia, grouping by shared genome content recapitulates species-level taxonomy and habitat preferences. However, while most R. mucilaginosa are restricted to the tongue as expected, two genomes represent a cryptic population of R. mucilaginosa in many buccal mucosa samples. For both H. parainfluenzae and the genus Rothia, we identify not only limitations in the ability of cultivated organisms to represent populations in their native environment, but also specifically which cultivar gene sequences are absent or ubiquitous.

CONCLUSIONS

Our findings provide insights into population structure and biogeography in the mouth and form specific hypotheses about habitat adaptation. These results illustrate the power of combining metagenomes and pangenomes to investigate the ecology and evolution of bacteria across analytical scales.

A collection of bacterial isolates from the pig intestine reveals functional and taxonomic diversity

Our knowledge about the gut microbiota of pigs is still scarce, despite the importance of these animals for biomedical research and agriculture. Here, we present a collection of cultured bacteria from the pig gut, including 110 species across 40 families and nine phyla. We provide taxonomic descriptions for 22 novel species and 16 genera. Meta-analysis of 16S rRNA amplicon sequence data and metagenome-assembled genomes reveal prevalent and pig-specific species within Lactobacillus, Streptococcus, Clostridium, Desulfovibrio, Enterococcus, Fusobacterium, and several new genera described in this study. Potentially interesting functions discovered in these organisms include a fucosyltransferase encoded in the genome of the novel species Clostridium porci, and prevalent gene clusters for biosynthesis of sactipeptide-like peptides. Many strains deconjugate primary bile acids in in vitro assays, and a Clostridium scindens strain produces secondary bile acids via dehydroxylation. In addition, cells of the novel species Bullifex porci are coccoidal or spherical under the culture conditions tested, in contrast with the usual helical shape of other members of the family Spirochaetaceae. The strain collection, called ‘Pig intestinal bacterial collection’ (PiBAC), is publicly available at www.dsmz.de/pibac and opens new avenues for functional studies of the pig gut microbiota.

The authors present a public collection of 117 bacterial isolates from the pig gut, including the description of 38 novel taxa. Interesting functions discovered in these organisms include a new fucosyltransferease and sactipeptide-like molecules encoded by biosynthetic gene clusters.