Tommi Vatanen

The Dynamics of the Human Infant Gut Microbiome in Development and in Progression toward Type 1 Diabetes

Colonization of the fetal and infant gut microbiome results in dynamic changes in diversity, which can impact disease susceptibility. To examine the relationship between human gut microbiome dynamics throughout infancy and type 1 diabetes (T1D), we examined a cohort of 33 infants genetically predisposed to T1D. Modeling trajectories of microbial abundances through infancy revealed a subset of microbial relationships shared across most subjects. Although strain composition of a given species was highly variable between individuals, it was stable within individuals throughout infancy. Metabolic composition and metabolic pathway abundance remained constant across time. A marked drop in alpha-diversity was observed in T1D progressors in the time window between seroconversion and T1D diagnosis, accompanied by spikes in inflammation-favoring organisms, gene functions, and serum and stool metabolites. This work identifies trends in the development of the human infant gut microbiome along with specific alterations that precede T1D onset and distinguish T1D progressors from nonprogressors.

Population-based metagenomics analysis reveals markers for gut microbiome composition and diversity.

“Normal” for the gut microbiota For the benefit of future clinical studies, it is critical to establish what constitutes a “normal” gut microbiome, if it exists at all. Through fecal samples and questionnaires, Falony et al. and Zhernakova et al. targeted general populations in Belgium and the Netherlands, respectively. Gut microbiota composition correlated with a range of factors including diet, use of medication, red blood cell counts, fecal chromogranin A, and stool consistency. The data give some hints for possible biomarkers of normal gut communities. Science, this issue pp. 560 and 565 Two large-scale studies in Western Europe establish environment-diet-microbe-host interactions. Deep sequencing of the gut microbiomes of 1135 participants from a Dutch population-based cohort shows relations between the microbiome and 126 exogenous and intrinsic host factors, including 31 intrinsic factors, 12 diseases, 19 drug groups, 4 smoking categories, and 60 dietary factors. These factors collectively explain 18.7% of the variation seen in the interindividual distance of microbial composition. We could associate 110 factors to 125 species and observed that fecal chromogranin A (CgA), a protein secreted by enteroendocrine cells, was exclusively associated with 61 microbial species whose abundance collectively accounted for 53% of microbial composition. Low CgA concentrations were seen in individuals with a more diverse microbiome. These results are an important step toward a better understanding of environment-diet-microbe-host interactions.

Variation in Microbiome LPS Immunogenicity Contributes to Autoimmunity in Humans

According to the hygiene hypothesis, the increasing incidence of autoimmune diseases in western countries may be explained by changes in early microbial exposure, leading to altered immune maturation. We followed gut microbiome development from birth until age three in 222 infants in Northern Europe, where early-onset autoimmune diseases are common in Finland and Estonia but are less prevalent in Russia. We found that Bacteroides species are lowly abundant in Russians but dominate in Finnish and Estonian infants. Therefore, their lipopolysaccharide (LPS) exposures arose primarily from Bacteroides rather than from Escherichia coli, which is a potent innate immune activator. We show that Bacteroides LPS is structurally distinct from E.xa0coli LPS and inhibits innate immune signaling and endotoxin tolerance; furthermore, unlike LPS from E.xa0coli, B.xa0dorei LPS does not decrease incidence of autoimmune diabetes in non-obese diabetic mice. Early colonization by immunologically silencing microbiota may thus preclude aspects of immune education.

Natural history of the infant gut microbiome and impact of antibiotic treatment on bacterial strain diversity and stability

A longitudinal strain-level analysis of the infant gut microbiome after repeated antibiotic treatments reveals decreased diversity and stability, as well as transient increases in antibiotic resistance genes. Elucidating the effects of drugs on bugs Despite widespread use of antibiotics in children, the effects of antibiotic exposure on the developing infant gut microbiome have remained underexplored. Here, Yassour et al. present a longitudinal study capturing how the gut microbiome responds to and recovers from antibiotic perturbations. Antibiotic-treated children had less stable and less diverse bacterial communities. Antibiotic resistance genes within the guts of these children peaked after antibiotic treatment but generally returned rapidly to baseline. Delivery mode (vaginal versus cesarean) also had strong long-term effects on microbial diversity. These data give insights into the consequences of early life factors such as birth mode and antibiotic treatment on the infant gut microbiome. The gut microbial community is dynamic during the first 3 years of life, before stabilizing to an adult-like state. However, little is known about the impact of environmental factors on the developing human gut microbiome. We report a longitudinal study of the gut microbiome based on DNA sequence analysis of monthly stool samples and clinical information from 39 children, about half of whom received multiple courses of antibiotics during the first 3 years of life. Whereas the gut microbiome of most children born by vaginal delivery was dominated by Bacteroides species, the four children born by cesarean section and about 20% of vaginally born children lacked Bacteroides in the first 6 to 18 months of life. Longitudinal sampling, coupled with whole-genome shotgun sequencing, allowed detection of strain-level variation as well as the abundance of antibiotic resistance genes. The microbiota of antibiotic-treated children was less diverse in terms of both bacterial species and strains, with some species often dominated by single strains. In addition, we observed short-term composition changes between consecutive samples from children treated with antibiotics. Antibiotic resistance genes carried on microbial chromosomes showed a peak in abundance after antibiotic treatment followed by a sharp decline, whereas some genes carried on mobile elements persisted longer after antibiotic therapy ended. Our results highlight the value of high-density longitudinal sampling studies with high-resolution strain profiling for studying the establishment and response to perturbation of the infant gut microbiome.

The effect of host genetics on the gut microbiome

The gut microbiome is affected by multiple factors, including genetics. In this study, we assessed the influence of host genetics on microbial species, pathways and gene ontology categories, on the basis of metagenomic sequencing in 1,514 subjects. In a genome-wide analysis, we identified associations of 9 loci with microbial taxonomies and 33 loci with microbial pathways and gene ontology terms at P < 5 × 10−8. Additionally, in a targeted analysis of regions involved in complex diseases, innate and adaptive immunity, or food preferences, 32 loci were identified at the suggestive level of P < 5 × 10−6. Most of our reported associations are new, including genome-wide significance for the C-type lectin molecules CLEC4F–CD207 at 2p13.3 and CLEC4A–FAM90A1 at 12p13. We also identified association of a functional LCT SNP with the Bifidobacterium genus (P = 3.45 × 10−8) and provide evidence of a gene–diet interaction in the regulation of Bifidobacterium abundance. Our results demonstrate the importance of understanding host–microbe interactions to gain better insight into human health.

Increased Intestinal Microbial Diversity Following Fecal Microbiota Transplant for Active Crohn's Disease

Background:The microbiota in the lumen of patients with Crohns disease (CD) is characterized by reduced diversity, particularly Firmicutes and Bacteroidetes. It is unknown whether the introduction of the intestinal microbiota from healthy individuals could correct this dysbiosis and reverse mucosal inflammation. We investigated the response to fecal microbial transplantation (FMT) from healthy individuals to subjects with active CD. Methods:We performed a prospective open-label study (uncontrolled) of FMT from healthy donors to subjects with active CD. A single FMT was performed by colonoscopy. Recipients microbial diversity, mucosal T-cell phenotypes, and clinical and inflammatory parameters were measured over 12 weeks, and safety over 26 weeks. Results:Nineteen subjects were treated with FMT and completed the study follow-up. Fifty-eight percent (11/19) demonstrated a clinical response (Harvey–Bradshaw Index decrease >3) following FMT. Fifteen subjects had sufficient pre/postfecal samples for analysis. A significant increase in microbial diversity occurred after FMT (P = 0.02). This was greater in clinical responders than nonresponders. Patients who experienced a clinical response demonstrated a significant shift in fecal microbial composition toward their donors profile as assessed by the Bray–Curtis index at 4 weeks (P = 0.003). An increase in regulatory T cells (CD4+CD25+CD127lo) was also noted in recipients lamina propria following FMT. No serious adverse events were noted over the 26-week study period. Conclusions:In this open-label study, FMT led to an expansion in microbial bacterial diversity in patients with active CD. FMT was overall safe, although the clinical response was variable. Determining donor microbial factors that influence clinical response is needed before randomized clinical trials of FMT in CD.

Dysbiosis, inflammation, and response to treatment: a longitudinal study of pediatric subjects with newly diagnosed inflammatory bowel disease

BackgroundGut microbiome dysbiosis has been demonstrated in subjects with newly diagnosed and chronic inflammatory bowel disease (IBD). In this study we sought to explore longitudinal changes in dysbiosis and ascertain associations between dysbiosis and markers of disease activity and treatment outcome.MethodsWe performed a prospective cohort study of 19 treatment-naïve pediatric IBD subjects and 10 healthy controls, measuring fecal calprotectin and assessing the gut microbiome via repeated stool samples. Associations between clinical characteristics and the microbiome were tested using generalized estimating equations. Random forest classification was used to predict ultimate treatment response (presence of mucosal healing at follow-up colonoscopy) or non-response using patients’ pretreatment samples.ResultsPatients with Crohn’s disease had increased markers of inflammation and dysbiosis compared to controls. Patients with ulcerative colitis had even higher inflammation and dysbiosis compared to those with Crohn’s disease. For all cases, the gut microbial dysbiosis index associated significantly with clinical and biological measures of disease severity, but did not associate with treatment response. We found differences in specific gut microbiome genera between cases/controls and responders/non-responders including Akkermansia, Coprococcus, Fusobacterium, Veillonella, Faecalibacterium, and Adlercreutzia. Using pretreatment microbiome data in a weighted random forest classifier, we were able to obtain 76.5xa0% accuracy for prediction of responder status.ConclusionsPatient dysbiosis improved over time but persisted even among those who responded to treatment and achieved mucosal healing. Although dysbiosis index was not significantly different between responders and non-responders, we found specific genus-level differences. We found that pretreatment microbiome signatures are a promising avenue for prediction of remission and response to treatment.

The influence of a short-term gluten-free diet on the human gut microbiome

BackgroundA gluten-free diet (GFD) is the most commonly adopted special diet worldwide. It is an effective treatment for coeliac disease and is also often followed by individuals to alleviate gastrointestinal complaints. It is known there is an important link between diet and the gut microbiome, but it is largely unknown how a switch to a GFD affects the human gut microbiome.MethodsWe studied changes in the gut microbiomes of 21 healthy volunteers who followed a GFD for four weeks. We collected nine stool samples from each participant: one at baseline, four during the GFD period, and four when they returned to their habitual diet (HD), making a total of 189 samples. We determined microbiome profiles using 16S rRNA sequencing and then processed the samples for taxonomic and imputed functional composition. Additionally, in all 189 samples, six gut health-related biomarkers were measured.ResultsInter-individual variation in the gut microbiota remained stable during this short-term GFD intervention. A number of taxon-specific differences were seen during the GFD: the most striking shift was seen for the family Veillonellaceae (class Clostridia), which was significantly reduced during the intervention (pu2009=u20092.81u2009×u200910−05). Seven other taxa also showed significant changes; the majority of them are known to play a role in starch metabolism. We saw stronger differences in pathway activities: 21 predicted pathway activity scores showed significant association to the change in diet. We observed strong relations between the predicted activity of pathways and biomarker measurements.ConclusionsA GFD changes the gut microbiome composition and alters the activity of microbial pathways.

Self-organization and missing values in SOM and GTM

In this paper, we study fundamental properties of the Self-Organizing Map (SOM) and the Generative Topographic Mapping (GTM), ramifications of the initialization of the algorithms and properties of the algorithms in the presence of missing data. We show that the commonly used principal component analysis (PCA) initialization of the GTM does not guarantee good learning results with high-dimensional data. Initializing the GTM with the SOM is shown to yield improvements in self-organization with three high-dimensional data sets: commonly used MNIST and ISOLET data sets and epigenomic ENCODE data set. We also propose a revision of handling missing data to the batch SOM algorithm called the Imputation SOM and show that the new algorithm is more robust in the presence of missing data. We benchmark the performance of the topographic mappings in the missing value imputation task and conclude that there are better methods for this particular task. Finally, we announce a revised version of the SOM Toolbox for Matlab with added GTM functionality.

Intestinal virome changes precede autoimmunity in type I diabetes-susceptible children

Significance Type 1 diabetes (T1D) is a major autoimmune disease with increasing incidence in recent years. In this study, we found that the intestinal viromes of cases were less diverse than those of controls. We identified eukaryotic viruses and bacteriophage contigs that are associated with the presence or absence of autoimmunity. These viruses provide targets for future mechanistic studies to differentiate causal and incidental associations between the virome and protection against the development of T1D. Viruses have long been considered potential triggers of autoimmune diseases. Here we defined the intestinal virome from birth to the development of autoimmunity in children at risk for type 1 diabetes (T1D). A total of 220 virus-enriched preparations from serially collected fecal samples from 11 children (cases) who developed serum autoantibodies associated with T1D (of whom five developed clinical T1D) were compared with samples from controls. Intestinal viromes of case subjects were less diverse than those of controls. Among eukaryotic viruses, we identified significant enrichment of Circoviridae-related sequences in samples from controls in comparison with cases. Enterovirus, kobuvirus, parechovirus, parvovirus, and rotavirus sequences were frequently detected but were not associated with autoimmunity. For bacteriophages, we found higher Shannon diversity and richness in controls compared with cases and observed that changes in the intestinal virome over time differed between cases and controls. Using Random Forests analysis, we identified disease-associated viral bacteriophage contigs after subtraction of age-associated contigs. These disease-associated contigs were statistically linked to specific components of the bacterial microbiome. Thus, changes in the intestinal virome preceded autoimmunity in this cohort. Specific components of the virome were both directly and inversely associated with the development of human autoimmune disease.