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Animals harbor diverse communities of microbes within their gastrointestinal tracts. Phylogenetic relationship, diet, gut morphology, host physiology, and ecology all influence microbiome composition within and between animal clades. Emerging evidence points to host genetics as also playing a role in determining gut microbial composition within species. Here, we discuss recent advances in the study of microbiome heritability across a variety of animal species . Candidate gene and discovery-based studies in humans, mice, Drosophila, Caenorhabditis elegans, cattle, swine, poultry, and baboons reveal trends in the types of microbes that are heritable and the host genes and pathways involved in shaping the microbiome. Heritable gut microbes within a host species tend to be phylogenetically restricted. Host genetic variation in immune- and growth-related genes drives the abundances of these heritable bacteria within the gut. With only a small slice of the metazoan branch of the tree of life explored to date, this is an area rife with opportunities to shed light into the mechanisms governing host–microbe relationships.

Because of the variety of factors that can affect the decomposition process, it can be difficult to determine the post-mortem interval (PMI). The process is highly dependent on microbial activity, and volatile organic compounds (VOCs) are a by-product of this activity. Given both have been proposed to assist in PMI determination, a deeper understanding of this relationship is needed. The current study investigates the temporal evolution of the microbiome and VOC profile of a decomposing human analog (swine) in a controlled, indoor environment. Microbial communities and VOCs were sampled at six-time points, up to the active decay phase. Sampling locations included the abdominal area, anus, right ear canal, and right nostril. Bacterial communities were found to significantly change during decomposition (p-value < 0.001), and communities evolved differently based on sampling location. The families Moraxellaceae, Planococcaceae, Lactobacillaceae, and Staphylococcaceae drove these community shifts. From random forest analysis, the nostril sampling location was determined to be the best location to predict stage of decomposition. Individual VOCs exhibited large temporal shifts through decomposition stage in contrast to smaller shifts when evaluated based on functional groups. Finally, pairwise linear regression models between abdominal area bacteria and selected VOCs were assessed; Planococcaceae and Tissierellaceae were significantly correlated to indole. Overall, this study provides an exploratory analysis to support the connection between the microbiome, VOCs, and their relationship throughout decomposition.ImportanceThis research provides valuable insight into the complex process of decomposition, which is pertinent to forensic death investigations. The temporal evolution of both the microbiome and volatile organic compounds (VOCs) were characterized as a function of stage of decomposition and evaluated their interdependency upon one another. In turn, this information may assist in determining time since death, and fill a knowledge gap about VOC-bacteria associations during the decay process.

Despite the growing knowledge surrounding host–microbiome interactions, we are just beginning to understand how the gut microbiome influences—and is influenced by—host gene expression. Here, we review recent literature that intersects these two fields, summarizing themes across studies. Work in model organisms, human biopsies, and cell culture demonstrate that the gut microbiome is an important regulator of several host pathways relevant for disease, including immune development and energy metabolism, and vice versa. The gut microbiome remodels host chromatin, causes differential splicing, alters the epigenetic landscape, and directly interrupts host signaling cascades. Emerging techniques like single-cell RNA sequencing and organoid generation have the potential to refine our understanding of the relationship between the gut microbiome and host gene expression in the future. By intersecting microbiome and host gene expression, we gain a window into the physiological processes important for fostering the extensive cross-kingdom interactions and ultimately our health. Electronic supplementary material The online version of this article (10.1007/s00439-020-02237-0) contains supplementary material, which is available to authorized users.

Environmental influences (infections and diet) strongly affect a host’s microbiota. However, host genetics may influence commensal communities, as suggested by the greater similarity between the microbiomes of identical twins compared to nonidentical twins. Variability of human genomes and microbiomes complicates the understanding of polymorphic mechanisms regulating the commensal communities. Whereas animal studies allow genetic modifications, they are sensitive to influences known as “cage” or “legacy” effects. Here, we analyze exgerm-free mice of various genetic backgrounds, including immunodeficient and major histocompatibility complex (MHC) congenic strains, receiving identical input microbiota. The host’s polymorphic mechanisms affect the gut microbiome, and both innate (anti-microbial peptides, complement, pentraxins, and enzymes affecting microbial survival) and adaptive (MHC-dependent and MHC-independent) pathways influence the microbiota. In our experiments, polymorphic mechanisms regulate only a limited number of microbial lineages (independently of their abundance). Our comparative analyses suggest that some microbes may benefit from the specific immune responses that they elicit.

Japanese eel (Anguilla japonica) is an important food source in East Asia whose population has dramatically declined since the 1970s. Despite past analysis with DNA sequencing, microsatellite and isozyme methods, management decisions remain hampered by contradictory findings. For example, it remains unresolved whether Japanese eels are a single panmictic population or whether they harbor significant substructure. Accurate assessment of population genetic substructure, both spatial and temporal, is essential for determining the relevant number of distinct management units appropriate for this species. In the present study, we assayed genetic variation genome-wide using Restriction Site Associated DNA Sequencing (RAD-seq) technology to analyze the population genetic structure of Japanese eels. For analysis of temporal isolation, five “cohort” samples were collected yearly from 2005 to 2009 in the Yangtze River Estuary. For analysis of spatial structure, five “arrival wave” samples were collected in China in 2009, and two arrival wave samples were collected in Japan in 2001. In each cohort of each arrival wave, five individuals were collected for a total of 55 eels sampled. In total, 214,210 loci were identified from these individuals, 106,652 of which satisfied quality checks and were retained for further analysis. There was relatively little population differentiation between arrival waves and cohorts collected either at different locations during the same year (Fst = 0.077) or at the same location collected over subsequent years (Fst = 0.082), and locations displayed no consistent isolation-by-distance.

Contains fulltext : 235695.pdf (Publisher’s version ) (Closed access) Individuals who are minoritized as a result of race, sexual identity, gender, or socioeconomic status experience a higher prevalence of many diseases. Understanding the biological processes that cause and maintain these socially driven health inequities is essential for addressing them. The gut microbiome is strongly shaped by host environments and affects host metabolic, immune, and neuroendocrine functions, making it an important pathway by which differences in experiences caused by social, political, and economic forces could contribute to health inequities. Nevertheless, few studies have directly integrated the gut microbiome into investigations of health inequities. Here, we argue that accounting for host-gut microbe interactions will improve understanding and management of health inequities, and that health policy must begin to consider the microbiome as an important pathway linking environments to population health.

Although thousands of loci have been associated with human phenotypes, the role of gene-environment (GxE) interactions in determining individual risk of human diseases remains unclear. This is partly because of the severe erosion of statistical power resulting from the massive number of statistical tests required to detect such interactions. Here, we focus on improving the power of GxE tests by developing a statistical framework for assessing quantitative trait loci (QTLs) associated with the trait means and/or trait variances. When applying this framework to body mass index (BMI), we find that GxE discovery and replication rates are significantly higher when prioritizing genetic variants associated with the variance of the phenotype (vQTLs) compared to when assessing all genetic variants. Moreover, we find that vQTLs are enriched for associations with other non-BMI phenotypes having strong environmental influences, such as diabetes or ulcerative colitis. We show that GxE effects first identified in quantitative traits such as BMI can be used for GxE discovery in disease phenotypes such as diabetes. A clear conclusion is that strong GxE interactions mediate the genetic contribution to body weight and diabetes risk.

While thousands of loci have been associated with human phenotypes, the role of gene-environment (GxE) interactions in determining individual risk of human diseases remains unclear. This is partly due to the severe erosion of statistical power resulting from the massive number of statistical tests required to detect such interactions. Here, we focus on improving the power of GxE tests by developing a statistical framework for assessing quantitative trait loci (QTLs) associated with the trait means and/or trait variances. When applying this framework to body mass index (BMI), we find that GxE discovery and replication rates are significantly higher when prioritizing genetic variants associated with the variance of the phenotype (vQTLs) compared to assessing all genetic variants. Moreover, we find that vQTLs are enriched for associations with other non-BMI phenotypes having strong environmental influences, such as diabetes or ulcerative colitis. We show that GxE effects first identified in quantitative traits such as BMI can be used for GxE discovery in disease phenotypes such as diabetes. A clear conclusion is that strong GxE interactions mediate the genetic contribution to body weight and diabetes risk.

The trillions of microbes living in the gut—the gut microbiota—play an important role in human biology and disease. While much has been done to explore its diversity, a full understanding of our microbiomes demands an evolutionary perspective. In this review, we compare microbiomes from human populations, placing them in the context of microbes from humanity’s near and distant animal relatives. We discuss potential mechanisms to generate host-specific microbiome configurations and the consequences of disrupting those configurations. Finally, we propose that this broader phylogenetic perspective is useful for understanding the mechanisms underlying human–microbiome interactions.

Despite a marked impact on society in terms of patient suffering and healthcare expenditure, colonic diverticulitis has a relative scarcity of published literature examining its pathophysiology. Based on preliminary studies, akin to other gastrointestinal diseases, alterations of the microbiome appear to be associated with diverticulitis. In fact, these perturbations in the microbiome can be detected when comparing segments of diseased and non-diseased colonic tissues within the same individual. Unfortunately, differentiating cause from effect is not feasible without longitudinal studies. While the use of antibiotics for the treatment of uncomplicated diverticulitis is waning, studies utilizing rifaximin, probiotics, and even fecal microbiota transplantation are growing. At present, treatment recommendations are limited by significant heterogeneity in the study populations as well as confounding bias. Ultimately, while dysbiosis is likely to play a role in diverticulitis, a lack of animal models upon which to perform mechanistic study has limited evidence-based recommendations.

Streptococcus pyogenes causes 700 million human infections annually worldwide, yet, despite a century of intensive effort, there is no licensed vaccine against this bacterium. Although a number of large-scale genomic studies of bacterial pathogens have been published, the relationships among the genome, transcriptome, and virulence in large bacterial populations remain poorly understood. We sequenced the genomes of 2,101 emm28 S. pyogenes invasive strains, from which we selected 492 phylogenetically diverse strains for transcriptome analysis and 50 strains for virulence assessment. Data integration provided a novel understanding of the virulence mechanisms of this model organism. Genome-wide association study, expression quantitative trait loci analysis, machine learning, and isogenic mutant strains identified and confirmed a one-nucleotide indel in an intergenic region that significantly alters global transcript profiles and ultimately virulence. The integrative strategy that we used is generally applicable to any microbe and may lead to new therapeutics for many human pathogens. This study presents the genomes of 2,101 emm28 Streptococcus pyogenes invasive strains, of which 492 were transcriptionally profiled, and 50 were assessed for virulence. GWAS, eQTL analysis, and study of isogenic mutant strains identified an intergenic region that alters global transcript profiles and bacterial virulence.

Recent studies in human populations and mouse models reveal notable congruences in gut microbial taxa whose abundances are partly regulated by host genotype. Host genes associating with these taxa are related to diet sensing, metabolism, and immunity. These broad patterns are further validated in similar studies of nonmammalian microbiomes. The next generation of genome-wide association studies will expand the size of the data sets and refine the microbial phenotypes to fully capture these intriguing signatures of host-microbiome coevolution.

The mix of bacteria that coat our teeth impact oral health, but it remains unclear what factors govern their composition. In this issue of Cell Host & Microbe, Gomez et al. (2017) examine the relationship between host genetics and the oral microbiome in the context of health and disease.

Summary Studies in mice and humans have revealed intriguing associations between host genetics and the microbiome. Here we report a 16S rRNA-based analysis of the gut microbiome in 1,126 twin pairs, a subset of which was previously reported. Tripling the sample narrowed the confidence intervals around heritability estimates and uncovered additional heritable taxa, some of which are validated in other studies. Repeat sampling of subjects showed heritable taxa to be temporally stable. A candidate gene approach uncovered associations between heritable taxa and genes related to diet, metabolism, and olfaction. We replicate an association between Bifidobacterium and the lactase (LCT) gene locus and identify an association between the host gene ALDH1L1 and the bacteria SHA-98, suggesting a link between formate production and blood pressure. Additional genes detected are involved in barrier defense and self/non-self recognition. Our results indicate that diet-sensing, metabolism, and immune defense are important drivers of human-microbiome co-evolution.

The composition of the gut microbiome in industrialized populations differs from those living traditional lifestyles. However, it has been difficult to separate the contributions of human genetic and geographic factors from lifestyle/modernization. Here, we characterize the stool bacterial composition of four Himalayan populations to investigate how the gut community changes in response to shifts in human lifestyles. These groups led seminomadic hunting-gathering lifestyles until transitioning to varying dependence upon farming. The Tharu began farming 250-300 years ago, the Raute and Raji transitioned 30-40 years ago, and the Chepang retain many aspects of a foraging lifestyle. We assess the contributions of dietary and environmental factors on their gut microbiota and find that the gut microbiome composition is significantly associated with lifestyle. The Chepang foragers harbor elevated abundance of taxa associated with foragers around the world. Conversely, the gut microbiomes of populations that have transitioned to farming are more similar to those of Americans, with agricultural dependence and several associated lifestyle and environmental factors correlating with the extent of microbiome divergence from the foraging population. For example, our results show that drinking water source and solid cooking fuel are significantly associated with the gut microbiome. Despite the pronounced differences in gut bacterial composition across populations, we found little differences in alpha diversity across populations. These findings in genetically similar populations living in the same geographical region establish the key role of lifestyle in determining human gut microbiome composition and point to the next challenging steps of isolating dietary effects from other factors that change during modernization.

The composition of the gut microbiome in industrialized populations differs from those living traditional lifestyles. However, it has been difficult to separate the contributions of human genetic and geographic factors from lifestyle. Whether shifts away from the foraging lifestyle that characterize much of humanity’s past influence the gut microbiome, and to what degree, remains unclear. Here, we characterize the stool bacterial composition of four Himalayan populations to investigate how the gut community changes in response to shifts in traditional human lifestyles. These groups led seminomadic hunting–gathering lifestyles until transitioning to varying levels of agricultural dependence upon farming. The Tharu began farming 250–300 years ago, the Raute and Raji transitioned 30–40 years ago, and the Chepang retain many aspects of a foraging lifestyle. We assess the contributions of dietary and environmental factors on their gut-associated microbes and find that differences in the lifestyles of Himalayan foragers and farmers are strongly correlated with microbial community variation. Furthermore, the gut microbiomes of all four traditional Himalayan populations are distinct from that of the Americans, indicating that industrialization may further exacerbate differences in the gut community. The Chepang foragers harbor an elevated abundance of taxa associated with foragers around the world. Conversely, the gut microbiomes of the populations that have transitioned to farming are more similar to those of Americans, with agricultural dependence and several associated lifestyle and environmental factors correlating with the extent of microbiome divergence from the foraging population. The gut microbiomes of Raute and Raji reveal an intermediate state between the Chepang and Tharu, indicating that divergence from a stereotypical foraging microbiome can occur within a single generation. Our results also show that environmental factors such as drinking water source and solid cooking fuel are significantly associated with the gut microbiome. Despite the pronounced differences in gut bacterial composition across populations, we found little differences in alpha diversity across lifestyles. These findings in genetically similar populations living in the same geographical region establish the key role of lifestyle in determining human gut microbiome composition and point to the next challenging steps of determining how large-scale gut microbiome reconfiguration impacts human biology., Author summary Although much of humanity’s history has been spent foraging in the forests, the advent of agriculture approximately 10,000 years ago and industrialization approximately 250 years ago mark major shifts in human lifestyle. Several studies have investigated the effect of industrialization on the human gut microbiome—a collection of microbes that inhabit the human gut. However, little is known about whether the gut microbiome changed as humans shifted away from foraging. To investigate how the gut community changes in response to shifts in traditional human lifestyles, we characterized the gut microbial community from four Himalayan populations representing diverse subsistence strategies. We show that the divergence of the gut microbiome from the foraging population is strongly correlated with agricultural dependence in these populations. Many of the taxa that differ across lifestyles are known to be influenced by diet, but we also demonstrate that environmental factors, such as sources of drinking water, are strongly associated with the human gut microbiome. Our findings show that both diet and environment play key roles in shaping the human gut microbiome.

The body's microbiome, composed of microbial cells that number in the trillions, is involved in human health and disease in ways that are just starting to emerge. The microbiome is assembled at birth, develops with its host, and is greatly influenced by environmental factors such as diet and other exposures. Recently, a role for human genetic variation has emerged as also influential in accounting for interpersonal differences in microbiomes. Thus, human genes may influence health directly or by promoting a beneficial microbiome. Studies of the heritability of gut microbiotas reveal a subset of microbes whose abundances are partly genetically determined by the host. However, the use of genome-wide association studies (GWASs) to identify human genetic variants associated with microbiome phenotypes has proven challenging. Studies to date are small by GWAS standards, and cross-study comparisons are hampered by differences in analytical approaches. Nevertheless, associations between microbes or microbial genes and human genes have emerged that are consistent between human populations. Most notably, higher levels of beneficial gut bacteria called Bifidobacteria are associated with the human lactase nonpersister genotype, which typically confers lactose intolerance, in several different human populations. It is time for the microbiome to be incorporated into studies that quantify interactions among genotype, environment, and the microbiome in order to predict human disease susceptibility.

Background Variation in the human fecal microbiota has previously been associated with body mass index (BMI). Although obesity is a global health burden, the accumulation of abdominal visceral fat is the specific cardio-metabolic disease risk factor. Here, we explore links between the fecal microbiota and abdominal adiposity using body composition as measured by dual-energy X-ray absorptiometry in a large sample of twins from the TwinsUK cohort, comparing fecal 16S rRNA diversity profiles with six adiposity measures. Results We profile six adiposity measures in 3666 twins and estimate their heritability, finding novel evidence for strong genetic effects underlying visceral fat and android/gynoid ratio. We confirm the association of lower diversity of the fecal microbiome with obesity and adiposity measures, and then compare the association between fecal microbial composition and the adiposity phenotypes in a discovery subsample of twins. We identify associations between the relative abundances of fecal microbial operational taxonomic units (OTUs) and abdominal adiposity measures. Most of these results involve visceral fat associations, with the strongest associations between visceral fat and Oscillospira members. Using BMI as a surrogate phenotype, we pursue replication in independent samples from three population-based cohorts including American Gut, Flemish Gut Flora Project and the extended TwinsUK cohort. Meta-analyses across the replication samples indicate that 8 OTUs replicate at a stringent threshold across all cohorts, while 49 OTUs achieve nominal significance in at least one replication sample. Heritability analysis of the adiposity-associated microbial OTUs prompted us to assess host genetic-microbe interactions at obesity-associated human candidate loci. We observe significant associations of adiposity-OTU abundances with host genetic variants in the FHIT, TDRG1 and ELAVL4 genes, suggesting a potential role for host genes to mediate the link between the fecal microbiome and obesity. Conclusions Our results provide novel insights into the role of the fecal microbiota in cardio-metabolic disease with clear potential for prevention and novel therapies. Electronic supplementary material The online version of this article (doi:10.1186/s13059-016-1052-7) contains supplementary material, which is available to authorized users.

A major goal of microbiome research is to identify the factors that determine bacterial composition within and upon a host. Environmental factors are thought to play a large role, such as diet in determining gut microbiome composition and moisture in determining skin microbiome composition. The role of host genetics, however, has been a source of debate in the literature. Recently, we examined the association of host genetics with human gut microbiome composition in the Hutterites, a population that lives and eats communally. We identified heritable bacterial taxa and host genetic loci associated with their abundances. In this addendum, I put these results into a broader context along with other recent studies of microbiome heritability, and synthesize common themes that appear across organisms and tissues, such as the relatively small extent genetics plays compared to environment and the role of host genetic variation in immune response and barrier integrity.

Background Changes in gene regulation have long been thought to play an important role in evolution and speciation, especially in primates. Over the past decade, comparative genomic studies have revealed extensive inter-species differences in gene expression levels, yet we know much less about the extent to which regulatory mechanisms differ between species. Results To begin addressing this gap, we perform a comparative epigenetic study in primate lymphoblastoid cell lines, to query the contribution of RNA polymerase II and four histone modifications, H3K4me1, H3K4me3, H3K27ac, and H3K27me3, to inter-species variation in gene expression levels. We find that inter-species differences in mark enrichment near transcription start sites are significantly more often associated with inter-species differences in the corresponding gene expression level than expected by chance alone. Interestingly, we also find that first-order interactions among the five marks, as well as chromatin states, do not markedly contribute to the degree of association between the marks and inter-species variation in gene expression levels, suggesting that the marginal effects of the five marks dominate this contribution. Conclusions Our observations suggest that epigenetic modifications are substantially associated with changes in gene expression levels among primates and may represent important molecular mechanisms in primate evolution. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0547-3) contains supplementary material, which is available to authorized users.

The composition of the human gut microbiome is influenced by many environmental factors. Diet is thought to be one of the most important determinants, though we have limited understanding of the extent to which dietary fluctuations alter variation in the gut microbiome between individuals. In this study, we examined variation in gut microbiome composition between winter and summer over the course of one year in 60 members of a founder population, the Hutterites. Because of their communal lifestyle, Hutterite diets are similar across individuals and remarkably stable throughout the year, with the exception that fresh produce is primarily served during the summer and autumn months. Our data indicate that despite overall gut microbiome stability within individuals over time, there are consistent and significant population-wide shifts in microbiome composition across seasons. We found seasonal differences in both (i) the abundance of particular taxa (false discovery rate

Massively parallel high throughput sequencing technologies allow us to interrogate the microbial composition of biological samples at unprecedented resolution. The typical approach is to perform high-throughout sequencing of 16S rRNA genes, which are then taxonomically classified based on similarity to known sequences in existing databases. Current technologies cause a predicament though, because although they enable deep coverage of samples, they are limited in the length of sequence they can produce. As a result, high-throughout studies of microbial communities often do not sequence the entire 16S rRNA gene. The challenge is to obtain reliable representation of bacterial communities through taxonomic classification of short 16S rRNA gene sequences. In this study we explored properties of different study designs and developed specific recommendations for effective use of short-read sequencing technologies for the purpose of interrogating bacterial communities, with a focus on classification using naive Bayesian classifiers. To assess precision and coverage of each design, we used a collection of ∼8,500 manually curated 16S rRNA gene sequences from cultured bacteria and a set of over one million bacterial 16S rRNA gene sequences retrieved from environmental samples, respectively. We also tested different configurations of taxonomic classification approaches using short read sequencing data, and provide recommendations for optimal choice of the relevant parameters. We conclude that with a judicious selection of the sequenced region and the corresponding choice of a suitable training set for taxonomic classification, it is possible to explore bacterial communities at great depth using current technologies, with only a minimal loss of taxonomic resolution.

Many scientists write code as part of their research. Just as experiments are logged in laboratory notebooks, it is important to document the code you use for analysis. However, a few key problems can arise when iteratively developing code that make it difficult to document and track which code version was used to create each result. First, you often need to experiment with new ideas, such as adding new features to a script or increasing the speed of a slow step, but you do not want to risk breaking the currently working code. One often-utilized solution is to make a copy of the script before making new edits. However, this can quickly become a problem because it clutters your file system with uninformative filenames, e.g., analysis.sh, analysis_02.sh, analysis_03.sh, etc. It is difficult to remember the differences between the versions of the files and, more importantly, which version you used to produce specific results, especially if you return to the code months later. Second, you will likely share your code with multiple lab mates or collaborators, and they may have suggestions on how to improve it. If you email the code to multiple people, you will have to manually incorporate all the changes each of them sends. Fortunately, software engineers have already developed software to manage these issues: version control. A version control system (VCS) allows you to track the iterative changes you make to your code. Thus, you can experiment with new ideas but always have the option to revert to a specific past version of the code you used to generate particular results. Furthermore, you can record messages as you save each successive version so that you (or anyone else) reviewing the development history of the code is able to understand the rationale for the given edits. It also facilitates collaboration. Using a VCS, your collaborators can make and save changes to the code, and you can automatically incorporate these changes to the main code base. The collaborative aspect is enhanced with the emergence of websites that host version-controlled code. In this quick guide, we introduce you to one VCS, Git (https://git-scm.com), and one online hosting site, GitHub (https://github.com), both of which are currently popular among scientists and programmers in general. More importantly, we hope to convince you that although mastering a given VCS takes time, you can already achieve great benefits by getting started using a few simple commands. Furthermore, not only does using a VCS solve many common problems when writing code, it can also improve the scientific process. By tracking your code development with a VCS and hosting it online, you are performing science that is more transparent, reproducible, and open to collaboration [1,2]. There is no reason this framework needs to be limited only to code; a VCS is well-suited for tracking any plain-text files: manuscripts, electronic lab notebooks, protocols, etc.

The bacterial composition of the human fecal microbiome is influenced by many lifestyle factors, notably diet. It is less clear, however, what role host genetics plays in dictating the composition of bacteria living in the gut. In this study, we examined the association of ~200K host genotypes with the relative abundance of fecal bacterial taxa in a founder population, the Hutterites, during two seasons (n = 91 summer, n = 93 winter, n = 57 individuals collected in both). These individuals live and eat communally, minimizing variation due to environmental exposures, including diet, which could potentially mask small genetic effects. Using a GWAS approach that takes into account the relatedness between subjects, we identified at least 8 bacterial taxa whose abundances were associated with single nucleotide polymorphisms in the host genome in each season (at genome-wide FDR of 20%). For example, we identified an association between a taxon known to affect obesity (genus Akkermansia) and a variant near PLD1, a gene previously associated with body mass index. Moreover, we replicate a previously reported association from a quantitative trait locus (QTL) mapping study of fecal microbiome abundance in mice (genus Lactococcus, rs3747113, P = 3.13 x 10−7). Finally, based on the significance distribution of the associated microbiome QTLs in our study with respect to chromatin accessibility profiles, we identified tissues in which host genetic variation may be acting to influence bacterial abundance in the gut.

T U E S D A Y 890 Decrease in Diversity of Nasal Microbiota during Wheezing Episodes in Preschool Children Gorka Alkorta-Aranburu, PhD, Catherine Igartua, Emily R. Davenport, Katherine Naughton, So Watanabe, MD, PhD, Yoav Gilad, PhD, Robert F. Lemanske, Jr, MD, FAAAAI, David M. Mauger, PhD, Carole Ober, PhD, Daniel J. Jackson, MD, Jayant M. Pinto, MD; The University of Chicago, Showa University, Toyko, Japan, University of Chicago, University of Wisconsin School of Medicine and Public Health, Madison, WI, Penn State University College of Medicine, Hershey, PA, University of Chicago, Chicago, IL, Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, WI, The University of Chicago, Chicago, IL. RATIONALE: Wheezing episodes are responsible for significant morbidity in children and are closely associated with respiratory tract infections (RTIs).We hypothesized that the composition of airway bacteria would be altered during these illnesses. METHODS: Using DNA from nasal lavage samples prospectively collected in the Maintenance and Intermittent Inhaled Corticosteroids in Wheezing Toddlers (MIST) clinical trial, we sequenced the 16S rRNA gene (V4 region) to analyze the bacterial microbiome of 33 children at baseline and during RTI. 160,000 sequence reads per sample were subsampled at random and classified using Mothur (RDP database) in order to generate standard ecologic metrics and identify the abundance of specific bacteria. RESULTS: Among the 18 males and 15 females (mean age 36 months), a majority had allergic sensitization (51.5%) or a parent with asthma (57.6%). Microbial diversity was significantly decreased during RTIs (Shannon Index 1.17 vs. 0.71, P50.018), particularly episodes severe enough to be treated with oral corticosteroids. The relative abundance of the phyla Bacteroidetes and Fusobacteria were lower during RTIs (Bonferroni P 0.01). CONCLUSIONS: Severe RTIs are associated with decreased bacterial diversity in the upper airway, indicating that the composition of nasal microbiota may influence wheezing episodes. Future studies should define the role of specific bacterial populations in these episodes. The nose is an accessible site to assess these relationships.

The degree to which host genetic variation can modulate microbial communities in humans remains an open question. Here we performed a genetic mapping study of the microbiome in two accessible upper airway sites, the nasopharynx and the nasal vestibule, during two seasons in 144 adult members of a founder population of European decent. We estimated the relative abundances (RAs) of genus level bacteria from 16S rRNA gene sequences and examined associations with 148,653 genetic variants (linkage disequilibrium [LD] r2 < 0.5) selected from among all common variants discovered in genome sequences in this population. We identified 37 microbiome quantitative trait loci (mbQTLs) that showed evidence of association with the RAs of 22 genera (q < 0.05), and were enriched for genes in mucosal immunity pathways. The most significant association was between the RA of Dermacoccus (phylum Actinobacteria) and a variant 8kb upstream of TINCR (rs117042385; p = 1.61⨯10−8; q = 0.002), a long non-coding RNA that binds to peptidoglycan recognition protein 3 (PGLYRP3) mRNA, a gene encoding a known antimicrobial protein. A second association was between a missense variant in PGLYRP4 (rs3006458) and the RA of an unclassified genus of family Micrococcaceae (phylum Actinobacteria) (p = 5.10⨯10−7; q = 0.032). Our findings provide evidence of host genetic influences on upper airway microbial composition in humans, and implicate mucosal immunity genes in this relationship.