Gabriel A. Al-Ghalith

Complex host genetics influence the microbiome in inflammatory bowel disease

BackgroundHuman genetics and host-associated microbial communities have been associated independently with a wide range of chronic diseases. One of the strongest associations in each case is inflammatory bowel disease (IBD), but disease risk cannot be explained fully by either factor individually. Recent findings point to interactions between host genetics and microbial exposures as important contributors to disease risk in IBD. These include evidence of the partial heritability of the gut microbiota and the conferral of gut mucosal inflammation by microbiome transplant even when the dysbiosis was initially genetically derived. Although there have been several tests for association of individual genetic loci with bacterial taxa, there has been no direct comparison of complex genome-microbiome associations in large cohorts of patients with an immunity-related disease.MethodsWe obtained 16S ribosomal RNA (rRNA) gene sequences from intestinal biopsies as well as host genotype via Immunochip in three independent cohorts totaling 474 individuals. We tested for correlation between relative abundance of bacterial taxa and number of minor alleles at known IBD risk loci, including fine mapping of multiple risk alleles in the Nucleotide-binding oligomerization domain-containing protein 2 (NOD2) gene exon. We identified host polymorphisms whose associations with bacterial taxa were conserved across two or more cohorts, and we tested related genes for enrichment of host functional pathways.ResultsWe identified and confirmed in two cohorts a significant association between NOD2 risk allele count and increased relative abundance of Enterobacteriaceae, with directionality of the effect conserved in the third cohort. Forty-eight additional IBD-related SNPs have directionality of their associations with bacterial taxa significantly conserved across two or three cohorts, implicating genes enriched for regulation of innate immune response, the JAK-STAT cascade, and other immunity-related pathways.ConclusionsThese results suggest complex interactions between genetically altered host functional pathways and the structure of the microbiome. Our findings demonstrate the ability to uncover novel associations from paired genome-microbiome data, and they suggest a complex link between host genetics and microbial dysbiosis in subjects with IBD across independent cohorts.

Captivity humanizes the primate microbiome

Significance Trillions of bacteria live in the primate gut, contributing to metabolism, immune system development, and pathogen resistance. Perturbations to these bacteria are associated with metabolic and autoimmune human diseases that are prevalent in Westernized societies. Herein, we measured gut microbial communities and diet in multiple primate species living in the wild, in a sanctuary, and in full captivity. We found that captivity and loss of dietary fiber in nonhuman primates are associated with loss of native gut microbiota and convergence toward the modern human microbiome, suggesting that parallel processes may be driving recent loss of core microbial biodiversity in humans. The primate gastrointestinal tract is home to trillions of bacteria, whose composition is associated with numerous metabolic, autoimmune, and infectious human diseases. Although there is increasing evidence that modern and Westernized societies are associated with dramatic loss of natural human gut microbiome diversity, the causes and consequences of such loss are challenging to study. Here we use nonhuman primates (NHPs) as a model system for studying the effects of emigration and lifestyle disruption on the human gut microbiome. Using 16S rRNA gene sequencing in two model NHP species, we show that although different primate species have distinctive signature microbiota in the wild, in captivity they lose their native microbes and become colonized with Prevotella and Bacteroides, the dominant genera in the modern human gut microbiome. We confirm that captive individuals from eight other NHP species in a different zoo show the same pattern of convergence, and that semicaptive primates housed in a sanctuary represent an intermediate microbiome state between wild and captive. Using deep shotgun sequencing, chemical dietary analysis, and chloroplast relative abundance, we show that decreasing dietary fiber and plant content are associated with the captive primate microbiome. Finally, in a meta-analysis including published human data, we show that captivity has a parallel effect on the NHP gut microbiome to that of Westernization in humans. These results demonstrate that captivity and lifestyle disruption cause primates to lose native microbiota and converge along an axis toward the modern human microbiome.

Chemotherapy-driven dysbiosis in the intestinal microbiome

Chemotherapy is commonly used as myeloablative conditioning treatment to prepare patients for haematopoietic stem cell transplantation (HSCT). Chemotherapy leads to several side effects, with gastrointestinal (GI) mucositis being one of the most frequent. Current models of GI mucositis pathophysiology are generally silent on the role of the intestinal microbiome.

Pretreatment gut microbiome predicts chemotherapy-related bloodstream infection.

BackgroundBacteremia, or bloodstream infection (BSI), is a leading cause of death among patients with certain types of cancer. A previous study reported that intestinal domination, defined as occupation of at least 30 % of the microbiota by a single bacterial taxon, is associated with BSI in patients undergoing allo-HSCT. However, the impact of the intestinal microbiome before treatment initiation on the risk of subsequent BSI remains unclear. Our objective was to characterize the fecal microbiome collected before treatment to identify microbes that predict the risk of BSI.MethodsWe sampled 28 patients with non-Hodgkin lymphoma undergoing allogeneic hematopoietic stem cell transplantation (HSCT) prior to administration of chemotherapy and characterized 16S ribosomal RNA genes using high-throughput DNA sequencing. We quantified bacterial taxa and used techniques from machine learning to identify microbial biomarkers that predicted subsequent BSI.ResultsWe found that patients who developed subsequent BSI exhibited decreased overall diversity and decreased abundance of taxa including Barnesiellaceae, Coriobacteriaceae, Faecalibacterium, Christensenella, Dehalobacterium, Desulfovibrio, and Sutterella. Using machine-learning methods, we developed a BSI risk index capable of predicting BSI incidence with a sensitivity of 90 % at a specificity of 90 % based only on the pretreatment fecal microbiome.ConclusionsThese results suggest that the gut microbiota can identify high-risk patients before HSCT and that manipulation of the gut microbiota for prevention of BSI in high-risk patients may be a useful direction for future research. This approach may inspire the development of similar microbiome-based diagnostic and prognostic models in other diseases.

NINJA-OPS: Fast Accurate Marker Gene Alignment Using Concatenated Ribosomes

The explosion of bioinformatics technologies in the form of next generation sequencing (NGS) has facilitated a massive influx of genomics data in the form of short reads. Short read mapping is therefore a fundamental component of next generation sequencing pipelines which routinely match these short reads against reference genomes for contig assembly. However, such techniques have seldom been applied to microbial marker gene sequencing studies, which have mostly relied on novel heuristic approaches. We propose NINJA Is Not Just Another OTU-Picking Solution (NINJA-OPS, or NINJA for short), a fast and highly accurate novel method enabling reference-based marker gene matching (picking Operational Taxonomic Units, or OTUs). NINJA takes advantage of the Burrows-Wheeler (BW) alignment using an artificial reference chromosome composed of concatenated reference sequences, the “concatesome,” as the BW input. Other features include automatic support for paired-end reads with arbitrary insert sizes. NINJA is also free and open source and implements several pre-filtering methods that elicit substantial speedup when coupled with existing tools. We applied NINJA to several published microbiome studies, obtaining accuracy similar to or better than previous reference-based OTU-picking methods while achieving an order of magnitude or more speedup and using a fraction of the memory footprint. NINJA is a complete pipeline that takes a FASTA-formatted input file and outputs a QIIME-formatted taxonomy-annotated BIOM file for an entire MiSeq run of human gut microbiome 16S genes in under 10 minutes on a dual-core laptop.

Systematic review: human gut dysbiosis induced by non‐antibiotic prescription medications

Global prescription drug use has been increasing continuously for decades. The gut microbiome, a key contributor to health status, can be altered by prescription drug use, as antibiotics have been repeatedly described to have both short‐term and long‐standing effects on the intestinal microbiome.

Patterns of seasonality and group membership characterize the gut microbiota in a longitudinal study of wild Verreaux's sifakas (Propithecus verreauxi)

Abstract The intestinal microbiota plays a major role in host development, metabolism, and health. To date, few longitudinal studies have investigated the causes and consequences of microbiota variation in wildlife, although such studies provide a comparative context for interpreting the adaptive significance of findings from studies on humans or captive animals. Here, we investigate the impact of seasonality, diet, group membership, sex, age, and reproductive state on gut microbiota composition in a wild population of group‐living, frugi‐folivorous primates, Verreauxs sifakas (Propithecus verreauxi). We repeatedly sampled 32 individually recognizable animals from eight adjacent groups over the course of two different climatic seasons. We used high‐throughput sequencing of the 16S rRNA gene to determine the microbiota composition of 187 fecal samples. We demonstrate a clear pattern of seasonal variation in the intestinal microbiota, especially affecting the Firmicutes‐Bacteroidetes ratio, which may be driven by seasonal differences in diet. The relative abundances of certain polysaccharide‐fermenting taxa, for example, Lachnospiraceae, were correlated with fruit and fiber consumption. Additionally, group membership influenced microbiota composition independent of season, but further studies are needed to determine whether this pattern is driven by group divergences in diet, social contacts, or genetic factors. In accordance with findings in other wild mammals and primates with seasonally fluctuating food availability, we demonstrate seasonal variation in the microbiota of wild Verreauxs sifakas, which may be driven by food availability. This study adds to mounting evidence that variation in the intestinal microbiota may play an important role in the ability of primates to cope with seasonal variation in food availability.

High-Fat Diet Changes Fungal Microbiomes and Interkingdom Relationships in the Murine Gut

Recent research shows that gut microbes are involved in the development of obesity, a growing health problem in developed countries that is linked to increased risk for cardiovascular disease. However, studies showing links between microbes and metabolism have been limited to the analysis of bacteria and have ignored the potential contribution of fungi in metabolic health. This study provides evidence that ingestion of a high-fat diet is associated with changes to the fungal (and bacterial) microbiome in a mouse model. In addition, we find that interkingdom structural and functional relationships exist between fungi and bacteria within the gut and that these are perturbed by high-fat diet. ABSTRACT Dietary fat intake and shifts in gut bacterial community composition are associated with the development of obesity. To date, characterization of microbiota in lean versus obese subjects has been dominated by studies of gut bacteria. Fungi, recently shown to affect gut inflammation, have received little study for their role in obesity. We sought to determine the effects of high-fat diet on fungal and bacterial community structures in a mouse model using the internal transcribed spacer region 2 (ITS2) of fungal ribosomal DNA (rDNA) and the 16S rRNA genes of bacteria. Mice fed a high-fat diet had significantly different abundances of 19 bacterial and 6 fungal taxa than did mice fed standard chow, with high-fat diet causing similar magnitudes of change in overall fungal and bacterial microbiome structures. We observed strong and complex diet-specific coabundance relationships between intra- and interkingdom microbial pairs and dramatic reductions in the number of coabundance correlations in mice fed a high-fat diet compared to those fed standard chow. Furthermore, predicted microbiome functional modules related to metabolism were significantly less abundant in high-fat-diet-fed than in standard-chow-fed mice. These results suggest a role for fungi and interkingdom interactions in the association between gut microbiomes and obesity. IMPORTANCE Recent research shows that gut microbes are involved in the development of obesity, a growing health problem in developed countries that is linked to increased risk for cardiovascular disease. However, studies showing links between microbes and metabolism have been limited to the analysis of bacteria and have ignored the potential contribution of fungi in metabolic health. This study provides evidence that ingestion of a high-fat diet is associated with changes to the fungal (and bacterial) microbiome in a mouse model. In addition, we find that interkingdom structural and functional relationships exist between fungi and bacteria within the gut and that these are perturbed by high-fat diet.

Moving beyond de novo clustering in fungal community ecology

High throughput sequencing (HTS) has rapidly become the de facto tool for characterizing microbial community structure in a wide variety of habitats (Caporaso et al., 2011; Peay et al., 2016; Truong et al., 2017). Accompanying the expanding use of HTS to quantify microbial diversity is the need to delineate species, the ecological unit traditionally used to compare the richness and composition of communities across treatments, locations or habitats (Magurran, 2005). Due to the challenges in identifying microbial species using morphology or biology alone, designations are typically made by ‘binning’ DNA sequences that meet a similarity threshold into operational taxonomic units (OTUs; Blaxter et al., 2005). Currently, the most widely employed approach for defining fungal OTUs is done according to similarities among sequences within the dataset (Supporting Information Fig. S1). Commonly referred to as de novo clustering (Bik et al., 2012), this approach requires no input database as a reference, which is advantageous when characterizing communities with little a priori knowledge. Despite this benefit, the ecological insights gleaned from de novo clustering can be limited by the challenge of directly comparing OTU identity across different studies (€ Opik et al., 2014), and the coarse phylogenetic resolution of many taxonomic assignments (Halwachs et al., 2017). One alternative to de novo clustering is the closed reference approach, where OTUs are binned according to sequence similarity of those in a reference database. With this approach, both OTU clustering and taxonomic designations occur simultaneously. Although the use of closed reference clustering in fungal ecology has been scarce (Fig. S1), it has become increasingly common in the molecular characterization of arbuscular mycorrhizal (AM) fungal communities as well as in many bacterial ‘microbiome’ studies (€ Opik et al., 2014; Kelly et al., 2016). The relatively low taxonomic and phylogenetic diversity of AM fungal communities (Stajich et al., 2009; Redecker et al., 2013; Davison et al., 2015), combined with a curated database (€ Opik et al., 2010) and increasingly wide usage of the 18S rRNA gene for molecular characterization ( € Opik et al., 2014), may explain why AM fungal community ecologists (relative to other fungal ecologists) have readily embraced closed reference clustering. Notably, the closed reference clustering approach has contributed significant new ecological understanding to patterns of AM community assembly by tracking OTUs (referred to as VT, € Opik et al., 2010) across studies with both contrasting habitat types and a wide variety of spatial scales (Davison et al., 2015; Garc ıa de Le on et al., 2016). A second alternative to de novo clustering is an open reference approach, which first clusters sequences to a reference database, followed by de novo clustering of the remaining unmatched sequences. This hybrid approach can combine the advantages of the two aforementioned clustering approaches (Rideout et al., 2014; He et al., 2015), but its interpretation can be problematic if the OTU definitions between closed reference and de novo approaches differ. Although open reference clustering is the least commonly used in fungal community ecology analyses to date (Fig. S1), it has been employed in studies of both arbuscular mycorrhizal and ectomycorrhizal fungal communities (Dumbrell et al., 2010; Jarvis et al., 2015). The increasingly widespread adoption of reference-based clustering inmanymicrobial analyses raises the question: should fungal ecologists re-consider their default use of de novo clustering? In particular, it seems that reference-based clusteringmay represent an increasingly useful approach to fungal community analyses as databases such as UNITE (K~oljalg et al., 2013) grow in size and a greater diversity of fungal habitats are molecularly characterized. Recent studies have suggested that reference-based clustering can increase OTU stability and taxonomic accuracy relative to de novo clustering (He et al., 2015; Halwachs et al., 2017), although how this clustering approach influences fungal community analyses across diverse habitats is currently unclear. To assess this gap in knowledge, we compared the relative performance of de novo, closed reference, and open reference clustering approaches on a mock community, as well as samples from four ecologically distinct habitats. These habitats varied in the degree to which fungal composition was captured by the UNITE database, providing an opportunity to investigate the importance of a priori habitat characterization on clustering approach performance. Using dead wood, live wood, live leaf and forest soil samples, we quantified fungal species assignments, OTU richness and community composition from ITS1 amplicon libraries sequenced on the IlluminaMiSeq platform.We compared two de novo clustering algorithms (CD-HIT and USEARCH; Li & Godzik, 2006; Edgar, 2010), two closed reference clustering algorithms (BLAST and NINJA-OPS; Altschul et al., 1990; Al-Ghalith et al., 2016), as well as two open reference clustering scenarios (NINJA/USEARCH; BLAST/ CD-HIT) applying a 97% sequence similarity cutoff for OTU clustering aswell as taxonomy assignments (Table S1). For the open reference clustering, sequences were first clustered by a closed reference algorithm (i.e. NINJA or BLAST); the remaining sequences that failed to cluster were then clustered by a de novo clustering approach (i.e. USEARCH or CD-HIT), and the OTU tables were combined (sensu Rideout et al., 2014). The UNITE database (v.7.0) was used for reference-based clustering as well as for designating

Development of the Human Mycobiome over the First Month of Life and across Body Sites

Humans are colonized by diverse fungi (mycobiome), which have received much less study to date than colonizing bacteria. We know very little about the succession of fungal colonization in early life and whether it may relate to long-term health. To better understand fungal colonization and its sources, we studied the skin, oral, and anal mycobiomes of healthy term infants and the vaginal and anal mycobiomes of their mothers. Generally, infants were colonized by few fungal taxa, and fungal alpha diversity did not increase over the first month of life. There was no clear community maturation over the first month of life, regardless of body site. Key body-site-specific taxa, but not overall fungal community structures, were impacted by birth mode. Thus, additional studies to characterize mycobiome acquisition and succession throughout early life are needed to form a foundation for research into the relationship between mycobiome development and human disease. ABSTRACT With the advent of next-generation sequencing and microbial community characterization, we are beginning to understand the key factors that shape early-life microbial colonization and associated health outcomes. Studies characterizing infant microbial colonization have focused mostly on bacteria in the microbiome and have largely neglected fungi (the mycobiome), despite their relevance to mucosal infections in healthy infants. In this pilot study, we characterized the skin, oral, and anal mycobiomes of infants over the first month of life (n = 17) and the anal and vaginal mycobiomes of mothers (n = 16) by internal transcribed spacer 2 (ITS2) amplicon sequencing. We found that infant mycobiomes differed by body site, with the infant mycobiomes at the anal sites being different from those at the skin and oral sites. The relative abundances of body site-specific taxa differed by birth mode, with significantly more Candida albicans fungi present on the skin of vaginally born infants on day 30 and significantly more Candida orthopsilosis fungi present in the oral cavity of caesarean section-born infants throughout the first month of life. We found the mycobiomes within individual infants to be variable over the first month of life, and vaginal birth did not result in infant mycobiomes that were more similar to the mother’s vaginal mycobiome. Therefore, although vertical transmission of specific fungal isolates from mother to infant has been reported, it is likely that other sources (environment, other caregivers) also contribute to early-life mycobiome establishment. Thus, future longitudinal studies of mycobiome and bacterial microbiome codevelopment, with dense sampling from birth to beyond the first month of life, are warranted. IMPORTANCE Humans are colonized by diverse fungi (mycobiome), which have received much less study to date than colonizing bacteria. We know very little about the succession of fungal colonization in early life and whether it may relate to long-term health. To better understand fungal colonization and its sources, we studied the skin, oral, and anal mycobiomes of healthy term infants and the vaginal and anal mycobiomes of their mothers. Generally, infants were colonized by few fungal taxa, and fungal alpha diversity did not increase over the first month of life. There was no clear community maturation over the first month of life, regardless of body site. Key body-site-specific taxa, but not overall fungal community structures, were impacted by birth mode. Thus, additional studies to characterize mycobiome acquisition and succession throughout early life are needed to form a foundation for research into the relationship between mycobiome development and human disease.