Assembly, stability, and dynamics of the infant gut microbiome are linked to bacterial strains and functions in mother's milk

The establishment of the gut microbiome in early life is critical for healthy infant development. Although human milk is recommended as the sole source of nutrition for the human infant, little is known about how variation in milk composition, and especially the milk microbiome, shapes the microbial communities in the infant gut. Here, we quantified the similarity between the maternal milk and the infant gut microbiome using 507 metagenomic samples collected from 195 mother-infant pairs at one, three, and six months postpartum. We found that the microbial taxonomic overlap between milk and the infant gut was driven by bifidobacteria, in particular by B. longum. Infant stool samples dominated by B. longum also showed higher temporal stability compared to samples dominated by other species. We identified two instances of strain sharing between maternal milk and the infant gut, one involving a commensal (B. longum) and one a pathobiont (K. pneumoniae). In addition, strain sharing between unrelated infants was higher among infants born at the same hospital compared to infants born in different hospitals, suggesting a potential role of the hospital environment in shaping the infant gut microbiome composition. The infant gut microbiome at one month compared to six months of age was enriched in metabolic pathways associated with de-novo molecule biosynthesis, suggesting that early colonisers might be more versatile and metabolically independent compared to later colonizers. Lastly, we found a significant overlap in antimicrobial resistance genes carriage between the mother's milk and their infant's gut microbiome. Taken together, our results suggest that the human milk microbiome has an important role in the assembly, composition, and stability of the infant gut microbiome.

Multi-omic approaches for host-microbiome data integration

The gut microbiome interacts with the host through complex networks that affect physiology and health outcomes. It is becoming clear that these interactions can be measured across many different omics layers, including the genome, transcriptome, epigenome, metabolome, and proteome, among others. Multi-omic studies of the microbiome can provide insight into the mechanisms underlying host-microbe interactions. As more omics layers are considered, increasingly sophisticated statistical methods are required to integrate them. In this review, we provide an overview of approaches currently used to characterize multi-omic interactions between host and microbiome data. While a large number of studies have generated a deeper understanding of host-microbiome interactions, there is still a need for standardization across approaches. Furthermore, microbiome studies would also benefit from the collection and curation of large, publicly available multi-omics datasets.

Integration of 168,000 samples reveals global patterns of the human gut microbiome

Understanding the factors that shape variation in the human microbiome is a major goal of research in biology. While other genomics fields have used large, pre-compiled compendia to extract systematic insights requiring otherwise impractical sample sizes, there has been no comparable resource for the 16S rRNA sequencing data commonly used to quantify microbiome composition. To help close this gap, we have assembled a set of 168,484 publicly available human gut microbiome samples, processed with a single pipeline and combined into the largest unified microbiome dataset to date. We use this resource, which is freely available at microbiomap.org, to shed light on global variation in the human gut microbiome. We find that Firmicutes, particularly Bacilli and Clostridia, are almost universally present in the human gut. At the same time, the relative abundance of the 65 most common microbial genera differ between at least two world regions. We also show that gut microbiomes in undersampled world regions, such as Central and Southern Asia, differ significantly from the more thoroughly characterized microbiomes of Europe and Northern America. Moreover, humans in these overlooked regions likely harbor hundreds of taxa that have not yet been discovered due to this undersampling, highlighting the need for diversity in microbiome studies. We anticipate that this new compendium can serve the community and enable advanced applied and methodological research.

Human Cytomegalovirus in breast milk is associated with milk composition, the infant gut microbiome, and infant growth

Human cytomegalovirus (CMV) is a highly prevalent herpesvirus that is often transmitted to the neonate via breast milk. Postnatal CMV transmission can have negative health consequences for preterm and immunocompromised infants, but any effects on healthy term infants are thought to be benign. Furthermore, the impact of CMV on the composition of the hundreds of bioactive factors in human milk has not been tested. Here, we utilize a cohort of exclusively breastfeeding full term mother-infant pairs to test for differences in the milk transcriptome and metabolome associated with CMV, and the impact of CMV in breast milk on the infant gut microbiome and infant growth. We find upregulation of the indoleamine 2,3- dioxygenase (IDO) tryptophan-to-kynurenine metabolic pathway in CMV+ milk samples, and that CMV+ milk is associated with decreased Bifidobacterium in the infant gut. Our data indicate a complex relationship between milk CMV, milk kynurenine, and infant growth; with kynurenine positively correlated, and CMV viral load negatively correlated, with infant weight-for-length at 1 month of age. These results suggest CMV transmission, CMV-related changes in milk composition, or both may be modulators of full term infant development.

Microbes with higher metabolic independence are enriched in human gut microbiomes under stress

A wide variety of human diseases are associated with loss of microbial diversity in the human gut, inspiring a great interest in the diagnostic or therapeutic potential of the microbiota. However, the ecological forces that drive diversity reduction in disease states remain unclear, rendering it difficult to ascertain the role of the microbiota in disease emergence or severity. One hypothesis to explain this phenomenon is that microbial diversity is diminished as disease states select for microbial populations that are more fit to survive environmental stress caused by inflammation or other host factors. Here, we tested this hypothesis on a large scale, by developing a software framework to quantify the enrichment of microbial metabolisms in complex metagenomes as a function of microbial diversity. We applied this framework to over 400 gut metagenomes from individuals who are healthy or diagnosed with inflammatory bowel disease (IBD). We found that high metabolic independence (HMI) is a distinguishing characteristic of microbial communities associated with individuals diagnosed with IBD. A classifier we trained using the normalized copy numbers of 33 HMI-associated metabolic modules not only distinguished states of health versus IBD, but also tracked the recovery of the gut microbiome following antibiotic treatment, suggesting that HMI is a hallmark of microbial communities in stressed gut environments.

Universal gut microbial relationships in the gut microbiome of wild baboons

Ecological relationships between bacteria mediate the services that gut microbiomes provide to their hosts. Knowing the overall direction and strength of these relationships is essential to learn how ecology scales up to affect microbiome assembly, dynamics, and host health. However, whether bacterial relationships are generalizable across hosts or personalized to individual hosts is debated. Here, we apply a robust, multinomial logistic-normal modeling framework to extensive time series data (5534 samples from 56 baboon hosts over 13 years) to infer thousands of correlations in bacterial abundance in individual baboons and test the degree to which bacterial abundance correlations are 'universal'. We also compare these patterns to two human data sets. We find that, most bacterial correlations are weak, negative, and universal across hosts, such that shared correlation patterns dominate over host-specific correlations by almost twofold. Further, taxon pairs that had inconsistent correlation signs (either positive or negative) in different hosts always had weak correlations within hosts. From the host perspective, host pairs with the most similar bacterial correlation patterns also had similar microbiome taxonomic compositions and tended to be genetic relatives. Compared to humans, universality in baboons was similar to that in human infants, and stronger than one data set from human adults. Bacterial families that showed universal correlations in human infants were often universal in baboons. Together, our work contributes new tools for analyzing the universality of bacterial associations across hosts, with implications for microbiome personalization, community assembly, and stability, and for designing microbiome interventions to improve host health.

Human milk variation is shaped by maternal genetics and impacts the infant gut microbiome

Human milk is a complex mix of nutritional and bioactive components that provide complete nutrition for the infant. However, we lack a systematic knowledge of the factors shaping milk composition and how milk variation influences infant health. Here, we used multi-omic profiling to characterize interactions between maternal genetics, milk gene expression, milk composition, and the infant fecal microbiome in 242 exclusively breastfeeding mother-infant pairs. We identified 487 genetic loci associated with milk gene expression unique to the lactating mammary gland, including loci that impacted breast cancer risk and human milk oligosaccharide concentration. Integrative analyses uncovered connections between milk gene expression and infant gut microbiome, including an association between the expression of inflammation-related genes with IL-6 concentration in milk and the abundance of Bifidobacteria in the infant gut. Our results show how an improved understanding of the genetics and genomics of human milk connects lactation biology with maternal and infant health.

How longitudinal data can contribute to our understanding of host genetic effects on the gut microbiome

A key component of microbiome research is understanding the role of host genetic influence on gut microbial composition. However, it can be difficult to link host genetics with gut microbial composition because host genetic similarity and environmental similarity are often correlated. Longitudinal microbiome data can supplement our understanding of the relative role of genetic processes in the microbiome. These data can reveal environmentally contingent host genetic effects, both in terms of controlling for environmental differences and in comparing how genetic effects differ by environment. Here, we explore four research areas where longitudinal data could lend new insights into host genetic effects on the microbiome: microbial heritability, microbial plasticity, microbial stability, and host and microbiome population genetics. We conclude with a discussion of methodological considerations for future studies.

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.

Identification of shared and disease-specific host gene-microbiome associations across human diseases using multi-omic integration

While gut microbiome and host gene regulation independently contribute to gastrointestinal disorders, it is unclear how the two may interact to influence host pathophysiology. Here we developed a machine learning-based framework to jointly analyse paired host transcriptomic (n = 208) and gut microbiome (n = 208) profiles from colonic mucosal samples of patients with colorectal cancer, inflammatory bowel disease and irritable bowel syndrome. We identified associations between gut microbes and host genes that depict shared as well as disease-specific patterns. We found that a common set of host genes and pathways implicated in gastrointestinal inflammation, gut barrier protection and energy metabolism are associated with disease-specific gut microbes. Additionally, we also found that mucosal gut microbes that have been implicated in all three diseases, such as Streptococcus, are associated with different host pathways in each disease, suggesting that similar microbes can affect host pathophysiology in a disease-specific manner through regulation of different host genes. Our framework can be applied to other diseases for the identification of host gene-microbiome associations that may influence disease outcomes.

Public human microbiome data are dominated by highly developed countries

The importance of sampling from globally representative populations has been well established in human genomics. In human microbiome research, however, we lack a full understanding of the global distribution of sampling in research studies. This information is crucial to better understand global patterns of microbiome-associated diseases and to extend the health benefits of this research to all populations. Here, we analyze the country of origin of all 444,829 human microbiome samples that are available from the world’s 3 largest genomic data repositories, including the Sequence Read Archive (SRA). The samples are from 2,592 studies of 19 body sites, including 220,017 samples of the gut microbiome. We show that more than 71% of samples with a known origin come from Europe, the United States, and Canada, including 46.8% from the US alone, despite the country representing only 4.3% of the global population. We also find that central and southern Asia is the most underrepresented region: Countries such as India, Pakistan, and Bangladesh account for more than a quarter of the world population but make up only 1.8% of human microbiome samples. These results demonstrate a critical need to ensure more global representation of participants in microbiome studies.

The importance of sampling from globally representative populations has been well established in human genomics, but what about the microbiome? This study shows that metadata from almost half a million samples reveals worldwide human microbiome research is skewed heavily in favor of Europe and North America and excludes large but less developed nations in Asia and Africa.

Interspecies variation in hominid gut microbiota controls host gene regulation

The gut microbiome exhibits extreme compositional variation between hominid hosts. However, it is unclear how this variation impacts host physiology across species and whether this effect can be mediated through microbial regulation of host gene expression in interacting epithelial cells. Here, we characterize the transcriptional response of human colonic epithelial cells in vitro to live microbial communities extracted from humans, chimpanzees, gorillas, and orangutans. We find that most host genes exhibit a conserved response, whereby they respond similarly to the four hominid microbiomes. However, hundreds of host genes exhibit a divergent response, whereby they respond only to microbiomes from specific host species. Such genes are associated with intestinal diseases in humans, including inflammatory bowel disease and Crohn’s disease. Last, we find that inflammation-associated microbial species regulate the expression of host genes previously associated with inflammatory bowel disease, suggesting health-related consequences for species-specific host-microbiome interactions across hominids.

Muehlbauer et al. investigate how variation between different hominid microbiomes drives host gene expression in colonic epithelial cell cultures. They find that host genes that respond only to microbiomes from a specific hominid species are linked to gastrointestinal diseases, suggesting implications for understanding how the microbiome can impact human health.

Multi-Omics Analyses Show Disease, Diet, and Transcriptome Interactions With the Virome

BACKGROUND & AIMS

The gut virome includes eukaryotic viruses and bacteriophages that can shape the gut bacterial community and elicit host responses. The virome can be implicated in diseases, such as irritable bowel syndrome (IBS), where gut bacteria play an important role in pathogenesis. We provide a comprehensive and longitudinal characterization of the virome, including DNA and RNA viruses and paired multi-omics data in a cohort of healthy subjects and patients with IBS.

METHODS

We selected 2 consecutive stool samples per subject from a longitudinal study cohort and performed metagenomic sequencing on DNA and RNA viruses after enriching for viral-like particles. Viral sequence abundance was evaluated over time, as well as in the context of diet, bacterial composition and function, metabolite levels, colonic gene expression, host genetics, and IBS subsets.

RESULTS

We found that the gut virome was temporally stable and correlated with the colonic transcriptome. We identified IBS-subset-specific changes in phage populations; Microviridae, Myoviridae, and Podoviridae species were elevated in diarrhea-predominant IBS, and other Microviridae and Myoviridae species were elevated in constipation-predominant IBS compared to healthy controls. We identified correlations between subsets of the virome and bacterial composition (unclassifiable "dark matter" and phages) and diet (eukaryotic viruses).

CONCLUSIONS

We found that the gut virome is stable over time but varies among subsets of patients with IBS. It can be affected by diet and potentially influences host function via interactions with gut bacteria and/or altering host gene expression.

The gut microbiome in konzo

Konzo, a distinct upper motor neuron disease associated with a cyanogenic diet and chronic malnutrition, predominately affects children and women of childbearing age in sub-Saharan Africa. While the exact biological mechanisms that cause this disease have largely remained elusive, host-genetics and environmental components such as the gut microbiome have been implicated. Using a large study population of 180 individuals from the Democratic Republic of the Congo, where konzo is most frequent, we investigate how the structure of the gut microbiome varied across geographical contexts, as well as provide the first insight into the gut flora of children affected with this debilitating disease using shotgun metagenomic sequencing. Our findings indicate that the gut microbiome structure is highly variable depending on region of sampling, but most interestingly, we identify unique enrichments of bacterial species and functional pathways that potentially modulate the susceptibility of konzo in prone regions of the Congo.

Gut microbiome heritability is nearly universal but environmentally contingent

Relatives have more similar gut microbiomes than nonrelatives, but the degree to which this similarity results from shared genotypes versus shared environments has been controversial. Here, we leveraged 16,234 gut microbiome profiles, collected over 14 years from 585 wild baboons, to reveal that host genetic effects on the gut microbiome are nearly universal. Controlling for diet, age, and socioecological variation, 97% of microbiome phenotypes were significantly heritable, including several reported as heritable in humans. Heritability was typically low (mean = 0.068) but was systematically greater in the dry season, with low diet diversity, and in older hosts. We show that longitudinal profiles and large sample sizes are crucial to quantifying microbiome heritability, and indicate scope for selection on microbiome characteristics as a host phenotype.

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.

Microbial control of host gene regulation and the evolution of host-microbiome interactions in primates

Recent comparative studies have found evidence consistent with the action of natural selection on gene regulation across primate species. Other recent work has shown that the microbiome can regulate host gene expression in a wide range of relevant tissues, leading to downstream effects on immunity, metabolism and other biological systems in the host. In primates, even closely related host species can have large differences in microbiome composition. One potential consequence of these differences is that host species-specific microbial traits could lead to differences in gene expression that influence primate physiology and adaptation to local environments. Here, we will discuss and integrate recent findings from primate comparative genomics and microbiome research, and explore the notion that the microbiome can influence host evolutionary dynamics by affecting gene regulation across primate host species. This article is part of the theme issue 'The role of the microbiome in host evolution'.

Longitudinal Multi-omics Reveals Subset-Specific Mechanisms Underlying Irritable Bowel Syndrome

The gut microbiome has been implicated in multiple human chronic gastrointestinal (GI) disorders. Determining its mechanistic role in disease has been difficult due to apparent disconnects between animal and human studies and lack of an integrated multi-omics view of disease-specific physiological changes. We integrated longitudinal multi-omics data from the gut microbiome, metabolome, host epigenome, and transcriptome in the context of irritable bowel syndrome (IBS) host physiology. We identified IBS subtype-specific and symptom-related variation in microbial composition and function. A subset of identified changes in microbial metabolites correspond to host physiological mechanisms that are relevant to IBS. By integrating multiple data layers, we identified purine metabolism as a novel host-microbial metabolic pathway in IBS with translational potential. Our study highlights the importance of longitudinal sampling and integrating complementary multi-omics data to identify functional mechanisms that can serve as therapeutic targets in a comprehensive treatment strategy for chronic GI diseases. VIDEO ABSTRACT.

International authorship and collaboration across bioRxiv preprints

Preprints are becoming well established in the life sciences, but relatively little is known about the demographics of the researchers who post preprints and those who do not, or about the collaborations between preprint authors. Here, based on an analysis of 67,885 preprints posted on bioRxiv, we find that some countries, notably the United States and the United Kingdom, are overrepresented on bioRxiv relative to their overall scientific output, while other countries (including China, Russia, and Turkey) show lower levels of bioRxiv adoption. We also describe a set of 'contributor countries' (including Uganda, Croatia and Thailand): researchers from these countries appear almost exclusively as non-senior authors on international collaborations. Lastly, we find multiple journals that publish a disproportionate number of preprints from some countries, a dynamic that almost always benefits manuscripts from the US.

Genes, geology and germs: gut microbiota across a primate hybrid zone are explained by site soil properties, not host species

Gut microbiota in geographically isolated host populations are often distinct. These differences have been attributed to between-population differences in host behaviours, environments, genetics and geographical distance. However, which factors are most important remains unknown. Here, we fill this gap for baboons by leveraging information on 13 environmental variables from 14 baboon populations spanning a natural hybrid zone. Sampling across a hybrid zone allowed us to additionally test whether phylosymbiosis (codiversification between hosts and their microbiota) is detectable in admixed, closely related primates. We found little evidence of genetic effects: none of host genetic ancestry, host genetic relatedness nor genetic distance between host populations were strong predictors of baboon gut microbiota. Instead, gut microbiota were best explained by the baboons' environments, especially the soil's geologic history and exchangeable sodium. Indeed, soil effects were 15 times stronger than those of host-population F_ST, perhaps because soil predicts which foods are present, or because baboons are terrestrial and consume soil microbes incidentally with their food. Our results support an emerging picture in which environmental variation is the dominant predictor of host-associated microbiomes. We are the first to show that such effects overshadow host species identity among members of the same primate genus.

Interactions between the gut microbiome and host gene regulation in cystic fibrosis

BACKGROUND

Cystic fibrosis is the most common autosomal recessive genetic disease in Caucasians. It is caused by mutations in the CFTR gene, leading to poor hydration of mucus and impairment of the respiratory, digestive, and reproductive organ functions. Advancements in medical care have led to markedly increased longevity of patients with cystic fibrosis, but new complications have emerged, such as early onset of colorectal cancer. Although the pathogenesis of colorectal cancer in cystic fibrosis remains unclear, altered host-microbe interactions might play a critical role. To investigate this, we characterized changes in the microbiome and host gene expression in the colonic mucosa of cystic fibrosis patients relative to healthy controls, and identified host gene-microbiome interactions in the colon of cystic fibrosis patients.

METHODS

We performed RNA-seq on colonic mucosa samples from cystic fibrosis patients and healthy controls to determine differentially expressed host genes. We also performed 16S rRNA sequencing to characterize the colonic mucosal microbiome and identify gut microbes that are differentially abundant between patients and healthy controls. Lastly, we modeled associations between relative abundances of specific bacterial taxa in the gut mucosa and host gene expression.

RESULTS

We find that 1543 genes, including CFTR, show differential expression in the colon of cystic fibrosis patients compared to healthy controls. These genes are enriched with functions related to gastrointestinal and colorectal cancer, such as metastasis of colorectal cancer, tumor suppression, p53, and mTOR signaling pathways. In addition, patients with cystic fibrosis show decreased gut microbial diversity, decreased abundance of butyrate producing bacteria, such as Ruminococcaceae and Butyricimonas, and increased abundance of other taxa, such as Actinobacteria and Clostridium. An integrative analysis identified colorectal cancer-related genes, including LCN2 and DUOX2, for which gene expression is correlated with the abundance of colorectal cancer-associated bacteria, such as Ruminococcaceae and Veillonella.

CONCLUSIONS

In addition to characterizing host gene expression and mucosal microbiome in cystic fibrosis patients, our study explored the potential role of host-microbe interactions in the etiology of colorectal cancer in cystic fibrosis. Our results provide biomarkers that may potentially serve as targets for stratifying risk of colorectal cancer in patients with cystic fibrosis.

Population dynamics of the human gut microbiome: change is the only constant

Characterization of the temporal dynamics of the human gut microbiome is crucial for understanding its role in modulating host health. Two recent studies explored the genetic diversity of gut microbes and unraveled extensive longitudinal dynamics within the host that is driven by natural selection.

Plasticity in the Human Gut Microbiome Defies Evolutionary Constraints

The gut microbiome of primates, including humans, is reported to closely follow host evolutionary history, with gut microbiome composition being specific to the genetic background of its primate host. However, the comparative models used to date have mainly included a limited set of closely related primates. To further understand the forces that shape the primate gut microbiome, with reference to human populations, we expanded the comparative analysis of variation among gut microbiome compositions and their primate hosts, including 9 different primate species and 4 human groups characterized by a diverse set of subsistence patterns (n = 448 samples). The results show that the taxonomic composition of the human gut microbiome, at the genus level, exhibits increased compositional plasticity. Specifically, we show unexpected similarities between African Old World monkeys that rely on eclectic foraging and human populations engaging in nonindustrial subsistence patterns; these similarities transcend host phylogenetic constraints. Thus, instead of following evolutionary trends that would make their microbiomes more similar to that of conspecifics or more phylogenetically similar apes, gut microbiome composition in humans from nonindustrial populations resembles that of generalist cercopithecine monkeys. We also document that wild cercopithecine monkeys with eclectic diets and humans following nonindustrial subsistence patterns harbor high gut microbiome diversity that is not only higher than that seen in humans engaging in industrialized lifestyles but also higher compared to wild primates that typically consume fiber-rich diets.IMPORTANCE The results of this study indicate a discordance between gut microbiome composition and evolutionary history in primates, calling into question previous notions about host genetic control of the primate gut microbiome. Microbiome similarities between humans consuming nonindustrialized diets and monkeys characterized by subsisting on eclectic, omnivorous diets also raise questions about the ecological and nutritional drivers shaping the human gut microbiome. Moreover, a more detailed understanding of the factors associated with gut microbiome plasticity in primates offers a framework to understand why humans following industrialized lifestyles have deviated from states thought to reflect human evolutionary history. The results also provide perspectives for developing therapeutic dietary manipulations that can reset configurations of the gut microbiome to potentially improve human health.

Mapping gastrointestinal gene expression patterns in wild primates and humans via fecal RNA-seq

Background

Limited accessibility to intestinal epithelial tissue in wild animals and humans makes it challenging to study patterns of intestinal gene regulation, and hence to monitor physiological status and health in field conditions. To explore solutions to this limitation, we have used a noninvasive approach via fecal RNA-seq, for the quantification of gene expression markers in gastrointestinal cells of free-range primates and a forager human population. Thus, a combination of poly(A) mRNA enrichment and rRNA depletion methods was used in tandem with RNA-seq to quantify and compare gastrointestinal gene expression patterns in fecal samples of wild Gorilla gorilla gorilla (n = 9) and BaAka hunter-gatherers (n = 10) from The Dzanga Sangha Protected Areas, Central African Republic.

Results

Although only a small fraction (< 4.9%) of intestinal mRNA signals was recovered, the data was sufficient to detect significant functional differences between gorillas and humans, at the gene and pathway levels. These intestinal gene expression differences were specifically associated with metabolic and immune functions. Additionally, non-host RNA-seq reads were used to gain preliminary insights on the subjects’ dietary habits, intestinal microbiomes, and infection prevalence, via identification of fungi, nematode, arthropod and plant RNA.

Conclusions

Overall, the results suggest that fecal RNA-seq, targeting gastrointestinal epithelial cells can be used to evaluate primate intestinal physiology and gut gene regulation, in samples obtained in challenging conditions in situ. The approach used herein may be useful to obtain information on primate intestinal health, while revealing preliminary insights into foraging ecology, microbiome, and diet.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5813-z) contains supplementary material, which is available to authorized users.

Challenges and recommendations to improve the installability and archival stability of omics computational tools

Developing new software tools for analysis of large-scale biological data is a key component of advancing modern biomedical research. Scientific reproduction of published findings requires running computational tools on data generated by such studies, yet little attention is presently allocated to the installability and archival stability of computational software tools. Scientific journals require data and code sharing, but none currently require authors to guarantee the continuing functionality of newly published tools. We have estimated the archival stability of computational biology software tools by performing an empirical analysis of the internet presence for 36,702 omics software resources published from 2005 to 2017. We found that almost 28% of all resources are currently not accessible through uniform resource locators (URLs) published in the paper they first appeared in. Among the 98 software tools selected for our installability test, 51% were deemed "easy to install," and 28% of the tools failed to be installed at all because of problems in the implementation. Moreover, for papers introducing new software, we found that the number of citations significantly increased when authors provided an easy installation process. We propose for incorporation into journal policy several practical solutions for increasing the widespread installability and archival stability of published bioinformatics software.

Changes in the Gut Microbiome Contribute to Changes in Tissue Gene Expression in Rats Fed Prebiotic Dietary Fibers (P15-022-19)

Objectives

We investigated the intersection between the gut microbiome and gene expression of colon and liver tissues in rats, using prebiotic dietary fibers to modulate the gut microbiome and elicit health benefits to the host.

Methods

Male Wistar rats were fed normal fat (NF) or high fat (HF, 51% fat by kcal) diets containing various fibers (6% fiber + 3% cellulose, by weight); including cellulose (NFC and HFC, non-fermentable), polylactose (HFPL, a novel prebiotic), and polydextrose (HFPD, an established prebiotic). After 10 weeks, tissues were harvested. Transcriptome analysis was performed by RNA sequencing of colon and liver tissues, and cecal contents were utilized for 16S microbiome sequencing. Analyses were conducted in R using DESeq2, DADA2, and phyloseq.

Results

Analysis of the gut microbiome revealed an increased abundance of probiotic genera, Bifidobacterium and Lactobacillus, in HFPL fed animals when compared to all other groups. These species are galactose fermenters which synthesize short chain fatty acids (SCFAs). This increased taxonomical abundance correlated with an increased FFar3 (SCFA receptor) expression in the colon. This suggests increased FFar3 signaling, leading to increased energy expenditure and GLP-1 and PYY secretion. Additionally, HFPL and HFPD groups had a decreased Firmicutes: Bacteroidetes ratio, which is associated with reduced adiposity due to the Bacteroidetes phylum being poor carbohydrate metabolizers, resulting in reduced energy uptake, yet increased SCFA synthesis.

Bacteriodetes are also able to survive in SCFA and bile acid rich environments and are involved in the recycling of bile acids which negatively regulates cholesterol synthesis. This corresponds to reduced liver cholesterol and cholesterol synthesis pathway expression in the HFPL group. Further, liver gene expression revealed reduced lipid synthesis and increased lipid oxidation pathway gene expression in the HFPL group, corresponding to the reduction in fatty liver found in this group.

Conclusions

Prebiotic dietary fibers elicit changes in the gut microbiome and gene expression in liver and colon. Changes in gene expression correlated with the abundance of beneficial gut bacteria, providing a connection between the gut microbiome and health benefits to the host.

Funding Sources

Midwest Dairy Association.

Supporting Tables, Images and/or Graphs

Rxivist.org: Sorting biology preprints using social media and readership metrics

Preprints have arrived. In increasing numbers, researchers across the life sciences are embracing the once-niche practice, shaking off decades of reluctance and posting hundreds of papers per week to preprint servers, sharing their findings with the community before embarking on the weary march through peer review. However, there are limited methods for individuals sifting through this avalanche of research to identify the preprints that are most relevant to their interests. Here, we describe Rxivist.org, a website that indexes all preprints posted to bioRxiv.org, the largest preprint server in the life sciences, and allows users to filter and sort papers based on download metrics and Twitter activity over a variety of categories and time periods. In this work, we hope to make it easier for readers to find relevant research on bioRxiv and to improve the visibility of preprints currently being read and discussed online.

This Community Page article describes Rxivist.org, a new website that indexes all preprints posted to bioRxiv.org and allows users to filter and sort papers based on download metrics and Twitter activity over a variety of categories and time periods.

Tracking the popularity and outcomes of all bioRxiv preprints

The growth of preprints in the life sciences has been reported widely and is driving policy changes for journals and funders, but little quantitative information has been published about preprint usage. Here, we report how we collected and analyzed data on all 37,648 preprints uploaded to bioRxiv.org, the largest biology-focused preprint server, in its first five years. The rate of preprint uploads to bioRxiv continues to grow (exceeding 2,100 in October 2018), as does the number of downloads (1.1 million in October 2018). We also find that two-thirds of preprints posted before 2017 were later published in peer-reviewed journals, and find a relationship between the number of downloads a preprint has received and the impact factor of the journal in which it is published. We also describe Rxivist.org, a web application that provides multiple ways to interact with preprint metadata.

Improving the usability and archival stability of bioinformatics software

Implementation of bioinformatics software involves numerous unique challenges; a rigorous standardized approach is needed to examine software tools prior to their publication.

Integrating tumor genomics into studies of the microbiome in colorectal cancer

Although the gut microbiome has been linked to colorectal cancer (CRC) development, associations of microbial taxa with CRC status are often inconsistent across studies. We have recently shown that tumor genomics, a factor that is rarely incorporated in analyses of the CRC microbiome, has a strong effect on the composition of the microbiota. Here, we discuss these results in the wider context of studies characterizing interaction between host genetics and the microbiome, and describe the implications of our findings for understanding the role of the microbiome in CRC.

Gut microbiota diversity across ethnicities in the United States

Composed of hundreds of microbial species, the composition of the human gut microbiota can vary with chronic diseases underlying health disparities that disproportionally affect ethnic minorities. However, the influence of ethnicity on the gut microbiota remains largely unexplored and lacks reproducible generalizations across studies. By distilling associations between ethnicity and differences in two US-based 16S gut microbiota data sets including 1,673 individuals, we report 12 microbial genera and families that reproducibly vary by ethnicity. Interestingly, a majority of these microbial taxa, including the most heritable bacterial family, Christensenellaceae, overlap with genetically associated taxa and form co-occurring clusters linked by similar fermentative and methanogenic metabolic processes. These results demonstrate recurrent associations between specific taxa in the gut microbiota and ethnicity, providing hypotheses for examining specific members of the gut microbiota as mediators of health disparities.

HOMINID: a framework for identifying associations between host genetic variation and microbiome composition

Recent studies have uncovered a strong effect of host genetic variation on the composition of host-associated microbiota. Here, we present HOMINID, a computational approach based on Lasso linear regression, that given host genetic variation and microbiome taxonomic composition data, identifies host single nucleotide polymorphisms (SNPs) that are correlated with microbial taxa abundances. Using simulated data, we show that HOMINID has accuracy in identifying associated SNPs and performs better compared with existing methods. We also show that HOMINID can accurately identify the microbial taxa that are correlated with associated SNPs. Lastly, by using HOMINID on real data of human genetic variation and microbiome composition, we identified 13 human SNPs in which genetic variation is correlated with microbiome taxonomic composition across body sites. In conclusion, HOMINID is a powerful method to detect host genetic variants linked to microbiome composition and can facilitate discovery of mechanisms controlling host-microbiome interactions.

Distinct microbes, metabolites, and ecologies define the microbiome in deficient and proficient mismatch repair colorectal cancers

Background

Links between colorectal cancer (CRC) and the gut microbiome have been established, but the specific microbial species and their role in carcinogenesis remain an active area of inquiry. Our understanding would be enhanced by better accounting for tumor subtype, microbial community interactions, metabolism, and ecology.

Methods

We collected paired colon tumor and normal-adjacent tissue and mucosa samples from 83 individuals who underwent partial or total colectomies for CRC. Mismatch repair (MMR) status was determined in each tumor sample and classified as either deficient MMR (dMMR) or proficient MMR (pMMR) tumor subtypes. Samples underwent 16S rRNA gene sequencing and a subset of samples from 50 individuals were submitted for targeted metabolomic analysis to quantify amino acids and short-chain fatty acids. A PERMANOVA was used to identify the biological variables that explained variance within the microbial communities. dMMR and pMMR microbial communities were then analyzed separately using a generalized linear mixed effects model that accounted for MMR status, sample location, intra-subject variability, and read depth. Genome-scale metabolic models were then used to generate microbial interaction networks for dMMR and pMMR microbial communities. We assessed global network properties as well as the metabolic influence of each microbe within the dMMR and pMMR networks.

Results

We demonstrate distinct roles for microbes in dMMR and pMMR CRC. Bacteroides fragilis and sulfidogenic Fusobacterium nucleatum were significantly enriched in dMMR CRC, but not pMMR CRC. These findings were further supported by metabolic modeling and metabolomics indicating suppression of B. fragilis in pMMR CRC and increased production of amino acid proxies for hydrogen sulfide in dMMR CRC.

Conclusions

Integrating tumor biology and microbial ecology highlighted distinct microbial, metabolic, and ecological properties unique to dMMR and pMMR CRC. This approach could critically improve our ability to define, predict, prevent, and treat colorectal cancers.

Electronic supplementary material

The online version of this article (10.1186/s13073-018-0586-6) contains supplementary material, which is available to authorized users.

Colorectal cancer mutational profiles correlate with defined microbial communities in the tumor microenvironment

Variation in the gut microbiome has been linked to colorectal cancer (CRC), as well as to host genetic variation. However, we do not know whether, in addition to baseline host genetics, somatic mutational profiles in CRC tumors interact with the surrounding tumor microbiome, and if so, whether these changes can be used to understand microbe-host interactions with potential functional biological relevance. Here, we characterized the association between CRC microbial communities and tumor mutations using microbiome profiling and whole-exome sequencing in 44 pairs of tumors and matched normal tissues. We found statistically significant associations between loss-of-function mutations in tumor genes and shifts in the abundances of specific sets of bacterial taxa, suggestive of potential functional interaction. This correlation allows us to statistically predict interactions between loss-of-function tumor mutations in cancer-related genes and pathways, including MAPK and Wnt signaling, solely based on the composition of the microbiome. In conclusion, our study shows that CRC microbiomes are correlated with tumor mutational profiles, pointing towards possible mechanisms of molecular interaction.

The gut microbiome of nonhuman primates: Lessons in ecology and evolution

The mammalian gastrointestinal (GI) tract is home to trillions of bacteria that play a substantial role in host metabolism and immunity. While progress has been made in understanding the role that microbial communities play in human health and disease, much less attention has been given to host-associated microbiomes in nonhuman primates (NHPs). Here we review past and current research exploring the gut microbiome of NHPs. First, we summarize methods for characterization of the NHP gut microbiome. Then we discuss variation in gut microbiome composition and function across different NHP taxa. Finally, we highlight how studying the gut microbiome offers new insights into primate nutrition, physiology, and immune system function, as well as enhances our understanding of primate ecology and evolution. Microbiome approaches are useful tools for studying relevant issues in primate ecology. Further study of the gut microbiome of NHPs will offer new insight into primate ecology and evolution as well as human health.

Archaic Hominin Introgression in Africa Contributes to Functional Salivary MUC7 Genetic Variation

One of the most abundant proteins in human saliva, mucin-7, is encoded by the MUC7 gene, which harbors copy number variable subexonic repeats (PTS-repeats) that affect the size and glycosylation potential of this protein. We recently documented the adaptive evolution of MUC7 subexonic copy number variation among primates. Yet, the evolution of MUC7 genetic variation in humans remained unexplored. Here, we found that PTS-repeat copy number variation has evolved recurrently in the human lineage, thereby generating multiple haplotypic backgrounds carrying five or six PTS-repeat copy number alleles. Contrary to previous studies, we found no associations between the copy number of PTS-repeats and protection against asthma. Instead, we revealed a significant association of MUC7 haplotypic variation with the composition of the oral microbiome. Furthermore, based on in-depth simulations, we conclude that a divergent MUC7 haplotype likely originated in an unknown African hominin population and introgressed into ancestors of modern Africans.

Atopic Dermatitis Susceptibility Variants in Filaggrin Hitchhike Hornerin Selective Sweep

Human skin has evolved rapidly, leaving evolutionary signatures in the genome. The filaggrin (FLG) gene is widely studied for its skin-barrier function in humans. The extensive genetic variation in this gene, especially common loss-of-function (LoF) mutations, has been established as primary risk factors for atopic dermatitis. To investigate the evolution of this gene, we analyzed 2,504 human genomes and genotyped the copy number variation of filaggrin repeats within FLG in 126 individuals from diverse ancestral backgrounds. We were unable to replicate a recent study claiming that LoF of FLG is adaptive in northern latitudes with lower ultraviolet light exposure. Instead, we present multiple lines of evidence suggesting that FLG genetic variation, including LoF variants, have little or no effect on fitness in modern humans. Haplotype-level scrutinization of the locus revealed signatures of a recent selective sweep in Asia, which increased the allele frequency of a haplotype group (Huxian haplogroup) in Asian populations. Functionally, we found that the Huxian haplogroup carries dozens of functional variants in FLG and hornerin (HRNR) genes, including those that are associated with atopic dermatitis susceptibility, HRNR expression levels and microbiome diversity on the skin. Our results suggest that the target of the adaptive sweep is HRNR gene function, and the functional FLG variants that involve susceptibility to atopic dermatitis, seem to hitchhike the selective sweep on HRNR. Our study presents a novel case of a locus that harbors clinically relevant common genetic variation with complex evolutionary trajectories.

Recent evolution of the salivary mucin MUC7

Genomic structural variants constitute the majority of variable base pairs in primate genomes and affect gene function in multiple ways. While whole gene duplications and deletions are relatively well-studied, the biology of subexonic (i.e., within coding exon sequences), copy number variation remains elusive. The salivary MUC7 gene provides an opportunity for studying such variation, as it harbors copy number variable subexonic repeat sequences that encode for densely O-glycosylated domains (PTS-repeats) with microbe-binding properties. To understand the evolution of this gene, we analyzed mammalian and primate genomes within a comparative framework. Our analyses revealed that (i) MUC7 has emerged in the placental mammal ancestor and rapidly gained multiple sites for O-glycosylation; (ii) MUC7 has retained its extracellular activity in saliva in placental mammals; (iii) the anti-fungal domain of the protein was remodified under positive selection in the primate lineage; and (iv) MUC7 PTS-repeats have evolved recurrently and under adaptive constraints. Our results establish MUC7 as a major player in salivary adaptation, likely as a response to diverse pathogenic exposure in primates. On a broader scale, our study highlights variable subexonic repeats as a primary source for modular evolutionary innovation that lead to rapid functional adaptation.

Common methods for fecal sample storage in field studies yield consistent signatures of individual identity in microbiome sequencing data

Field studies of wild vertebrates are frequently associated with extensive collections of banked fecal samples—unique resources for understanding ecological, behavioral, and phylogenetic effects on the gut microbiome. However, we do not understand whether sample storage methods confound the ability to investigate interindividual variation in gut microbiome profiles. Here, we extend previous work on storage methods for gut microbiome samples by comparing immediate freezing, the gold standard of preservation, to three methods commonly used in vertebrate field studies: lyophilization, storage in ethanol, and storage in RNAlater. We found that the signature of individual identity consistently outweighed storage effects: alpha diversity and beta diversity measures were significantly correlated across methods, and while samples often clustered by donor, they never clustered by storage method. Provided that all analyzed samples are stored the same way, banked fecal samples therefore appear highly suitable for investigating variation in gut microbiota. Our results open the door to a much-expanded perspective on variation in the gut microbiome across species and ecological contexts.

Gut Microbiome of Coexisting BaAka Pygmies and Bantu Reflects Gradients of Traditional Subsistence Patterns

To understand how the gut microbiome is impacted by human adaptation to varying environments, we explored gut bacterial communities in the BaAka rainforest hunter-gatherers and their agriculturalist Bantu neighbors in the Central African Republic. Although the microbiome of both groups is compositionally similar, hunter-gatherers harbor increased abundance of Prevotellaceae, Treponema, and Clostridiaceae, while the Bantu gut microbiome is dominated by Firmicutes. Comparisons with US Americans reveal microbiome differences between Africans and westerners but show western-like features in the Bantu, including an increased abundance of predictive carbohydrate and xenobiotic metabolic pathways. In contrast, the hunter-gatherer gut shows increased abundance of predicted virulence, amino acid, and vitamin metabolism functions, as well as dominance of lipid and amino-acid-derived metabolites, as determined through metabolomics. Our results demonstrate gradients of traditional subsistence patterns in two neighboring African groups and highlight the adaptability of the microbiome in response to host ecology.

Temporal variation selects for diet-microbe co-metabolic traits in the gut of Gorilla spp

Although the critical role that our gastrointestinal microbes play in host physiology is now well established, we know little about the factors that influenced the evolution of primate gut microbiomes. To further understand current gut microbiome configurations and diet-microbe co-metabolic fingerprints in primates, from an evolutionary perspective, we characterized fecal bacterial communities and metabolomic profiles in 228 fecal samples of lowland and mountain gorillas (G. g. gorilla and G. b. beringei, respectively), our closest evolutionary relatives after chimpanzees. Our results demonstrate that the gut microbiomes and metabolomes of these two species exhibit significantly different patterns. This is supported by increased abundance of metabolites and bacterial taxa associated with fiber metabolism in mountain gorillas, and enrichment of markers associated with simple sugar, lipid and sterol turnover in the lowland species. However, longitudinal sampling shows that both species' microbiomes and metabolomes converge when hosts face similar dietary constraints, associated with low fruit availability in their habitats. By showing differences and convergence of diet-microbe co-metabolic fingerprints in two geographically isolated primate species, under specific dietary stimuli, we suggest that dietary constraints triggered during their adaptive radiation were potential factors behind the species-specific microbiome patterns observed in primates today.

Variation in Rural African Gut Microbiota Is Strongly Correlated with Colonization by Entamoeba and Subsistence

The human gut microbiota is impacted by host nutrition and health status and therefore represents a potentially adaptive phenotype influenced by metabolic and immune constraints. Previous studies contrasting rural populations in developing countries to urban industrialized ones have shown that industrialization is strongly correlated with patterns in human gut microbiota; however, we know little about the relative contribution of factors such as climate, diet, medicine, hygiene practices, host genetics, and parasitism. Here, we focus on fine-scale comparisons of African rural populations in order to (i) contrast the gut microbiota of populations inhabiting similar environments but having different traditional subsistence modes and either shared or distinct genetic ancestry, and (ii) examine the relationship between gut parasites and bacterial communities. Characterizing the fecal microbiota of Pygmy hunter-gatherers as well as Bantu individuals from both farming and fishing populations in Southwest Cameroon, we found that the gut parasite Entamoeba is significantly correlated with microbiome composition and diversity. We show that across populations, colonization by this protozoa can be predicted with 79% accuracy based on the composition of an individual's gut microbiota, and that several of the taxa most important for distinguishing Entamoeba absence or presence are signature taxa for autoimmune disorders. We also found gut communities to vary significantly with subsistence mode, notably with some taxa previously shown to be enriched in other hunter-gatherers groups (in Tanzania and Peru) also discriminating hunter-gatherers from neighboring farming or fishing populations in Cameroon.

Host genetic variation impacts microbiome composition across human body sites

BACKGROUND

The composition of bacteria in and on the human body varies widely across human individuals, and has been associated with multiple health conditions. While microbial communities are influenced by environmental factors, some degree of genetic influence of the host on the microbiome is also expected. This study is part of an expanding effort to comprehensively profile the interactions between human genetic variation and the composition of this microbial ecosystem on a genome- and microbiome-wide scale.

RESULTS

Here, we jointly analyze the composition of the human microbiome and host genetic variation. By mining the shotgun metagenomic data from the Human Microbiome Project for host DNA reads, we gathered information on host genetic variation for 93 individuals for whom bacterial abundance data are also available. Using this dataset, we identify significant associations between host genetic variation and microbiome composition in 10 of the 15 body sites tested. These associations are driven by host genetic variation in immunity-related pathways, and are especially enriched in host genes that have been previously associated with microbiome-related complex diseases, such as inflammatory bowel disease and obesity-related disorders. Lastly, we show that host genomic regions associated with the microbiome have high levels of genetic differentiation among human populations, possibly indicating host genomic adaptation to environment-specific microbiomes.

CONCLUSIONS

Our results highlight the role of host genetic variation in shaping the composition of the human microbiome, and provide a starting point toward understanding the complex interaction between human genetics and the microbiome in the context of human evolution and disease.

Virulence genes are a signature of the microbiome in the colorectal tumor microenvironment

Background

The human gut microbiome is associated with the development of colon cancer, and recent studies have found changes in the microbiome in cancer patients compared to healthy controls. Studying the microbial communities in the tumor microenvironment may shed light on the role of host–bacteria interactions in colorectal cancer. Here, we highlight the major shifts in the colorectal tumor microbiome relative to that of matched normal colon tissue from the same individual, allowing us to survey the microbial communities in the tumor microenvironment and providing intrinsic control for environmental and host genetic effects on the microbiome.

Methods

We sequenced the microbiome in 44 primary tumor and 44 patient-matched normal colon tissue samples to determine differentially abundant microbial taxa These data were also used to functionally characterize the microbiome of the cancer and normal sample pairs and identify functional pathways enriched in the tumor-associated microbiota.

Results

We find that tumors harbor distinct microbial communities compared to nearby healthy tissue. Our results show increased microbial diversity in the tumor microenvironment, with changes in the abundances of commensal and pathogenic bacterial taxa, including Fusobacterium and Providencia. While Fusobacterium has previously been implicated in colorectal cancer, Providencia is a novel tumor-associated agent which has not been identified in previous studies. Additionally, we identified a clear, significant enrichment of predicted virulence-associated genes in the colorectal cancer microenvironment, likely dependent upon the genomes of Fusobacterium and Providencia.

Conclusions

This work identifies bacterial taxa significantly correlated with colorectal cancer, including a novel finding of an elevated abundance of Providencia in the tumor microenvironment. We also describe the predicted metabolic pathways and enzymes differentially present in the tumor-associated microbiome, and show an enrichment of virulence-associated bacterial genes in the tumor microenvironment. This predicted virulence enrichment supports the hypothesis that the microbiome plays an active role in colorectal cancer development and/or progression. Our results provide a starting point for future prognostic and therapeutic research with the potential to improve patient outcomes.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-015-0177-8) contains supplementary material, which is available to authorized users.

Population genomic analysis of 962 whole genome sequences of humans reveals natural selection in non-coding regions

Whole genome analysis in large samples from a single population is needed to provide adequate power to assess relative strengths of natural selection across different functional components of the genome. In this study, we analyzed next-generation sequencing data from 962 European Americans, and found that as expected approximately 60% of the top 1% of positive selection signals lie in intergenic regions, 33% in intronic regions, and slightly over 1% in coding regions. Several detailed functional annotation categories in intergenic regions showed statistically significant enrichment in positively selected loci when compared to the null distribution of the genomic span of ENCODE categories. There was a significant enrichment of purifying selection signals detected in enhancers, transcription factor binding sites, microRNAs and target sites, but not on lincRNA or piRNAs, suggesting different evolutionary constraints for these domains. Loci in “repressed or low activity regions” and loci near or overlapping the transcription start site were the most significantly over-represented annotations among the top 1% of signals for positive selection.

Human genetics shape the gut microbiome

Host genetics and the gut microbiome can both influence metabolic phenotypes. However, whether host genetic variation shapes the gut microbiome and interacts with it to affect host phenotype is unclear. Here, we compared microbiotas across >1,000 fecal samples obtained from the TwinsUK population, including 416 twin pairs. We identified many microbial taxa whose abundances were influenced by host genetics. The most heritable taxon, the family Christensenellaceae, formed a co-occurrence network with other heritable Bacteria and with methanogenic Archaea. Furthermore, Christensenellaceae and its partners were enriched in individuals with low body mass index (BMI). An obese-associated microbiome was amended with Christensenella minuta, a cultured member of the Christensenellaceae, and transplanted to germ-free mice. C. minuta amendment reduced weight gain and altered the microbiome of recipient mice. Our findings indicate that host genetics influence the composition of the human gut microbiome and can do so in ways that impact host metabolism.

Social networks predict gut microbiome composition in wild baboons

Social relationships have profound effects on health in humans and other primates, but the mechanisms that explain this relationship are not well understood. Using shotgun metagenomic data from wild baboons, we found that social group membership and social network relationships predicted both the taxonomic structure of the gut microbiome and the structure of genes encoded by gut microbial species. Rates of interaction directly explained variation in the gut microbiome, even after controlling for diet, kinship, and shared environments. They therefore strongly implicate direct physical contact among social partners in the transmission of gut microbial species. We identified 51 socially structured taxa, which were significantly enriched for anaerobic and non-spore-forming lifestyles. Our results argue that social interactions are an important determinant of gut microbiome composition in natural animal populations-a relationship with important ramifications for understanding how social relationships influence health, as well as the evolution of group living.