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. coli LPS and inhibits innate immune signaling and endotoxin tolerance; furthermore, unlike LPS from E. coli, B. dorei 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.

Reconstruction of ancient microbial genomes from the human gut.

Loss of gut microbial diversity1-6 in industrial populations is associated with chronic diseases7, underscoring the importance of studying our ancestral gut microbiome. However, relatively little is known about the composition of pre-industrial gut microbiomes. Here we performed a large-scale de novo assembly of microbial genomes from palaeofaeces. From eight authenticated human palaeofaeces samples (1,000-2,000 years old) with well-preserved DNA from southwestern USA and Mexico, we reconstructed 498 medium- and high-quality microbial genomes. Among the 181 genomes with the strongest evidence of being ancient and of human gut origin, 39% represent previously undescribed species-level genome bins. Tip dating suggests an approximate diversification timeline for the key human symbiont Methanobrevibacter smithii. In comparison to 789 present-day human gut microbiome samples from eight countries, the palaeofaeces samples are more similar to non-industrialized than industrialized human gut microbiomes. Functional profiling of the palaeofaeces samples reveals a markedly lower abundance of antibiotic-resistance and mucin-degrading genes, as well as enrichment of mobile genetic elements relative to industrial gut microbiomes. This study facilitates the discovery and characterization of previously undescribed gut microorganisms from ancient microbiomes and the investigation of the evolutionary history of the human gut microbiota through genome reconstruction from palaeofaeces.

Systematically assessing microbiome-disease associations identifies drivers of inconsistency in metagenomic research.

Evaluating the relationship between the human gut microbiome and disease requires computing reliable statistical associations. Here, using millions of different association modeling strategies, we evaluated the consistency-or robustness-of microbiome-based disease indicators for 6 prevalent and well-studied phenotypes (across 15 public cohorts and 2,343 individuals). We were able to discriminate between analytically robust versus nonrobust results. In many cases, different models yielded contradictory associations for the same taxon-disease pairing, some showing positive correlations and others negative. When querying a subset of 581 microbe-disease associations that have been previously reported in the literature, 1 out of 3 taxa demonstrated substantial inconsistency in association sign. Notably, >90% of published findings for type 1 diabetes (T1D) and type 2 diabetes (T2D) were particularly nonrobust in this regard. We additionally quantified how potential confounders-sequencing depth, glucose levels, cholesterol, and body mass index, for example-influenced associations, analyzing how these variables affect the ostensible correlation between Faecalibacterium prausnitzii abundance and a healthy gut. Overall, we propose our approach as a method to maximize confidence when prioritizing findings that emerge from microbiome association studies.

Leveraging vibration of effects analysis for robust discovery in observational biomedical data science.

Hypothesis generation in observational, biomedical data science often starts with computing an association or identifying the statistical relationship between a dependent and an independent variable. However, the outcome of this process depends fundamentally on modeling strategy, with differing strategies generating what can be called "vibration of effects" (VoE). VoE is defined by variation in associations that often lead to contradictory results. Here, we present a computational tool capable of modeling VoE in biomedical data by fitting millions of different models and comparing their output. We execute a VoE analysis on a series of widely reported associations (e.g., carrot intake associated with eyesight) with an extended additional focus on lifestyle exposures (e.g., physical activity) and components of the Framingham Risk Score for cardiovascular health (e.g., blood pressure). We leveraged our tool for potential confounder identification, investigating what adjusting variables are responsible for conflicting models. We propose modeling VoE as a critical step in navigating discovery in observational data, discerning robust associations, and cataloging adjusting variables that impact model output.

Inflammatory bowel disease as a model for translating the microbiome.

The inflammatory bowel diseases (IBDs) are among the most closely studied chronic inflammatory disorders that involve environmental, host genetic, and commensal microbial factors. This combination of features has made IBD both an appropriate and a high-priority platform for translatable research in host-microbiome interactions. Decades of epidemiology have identified environmental risk factors, although most mechanisms of action remain unexplained. The genetic architecture of IBD has been carefully dissected in multiple large populations, identifying several responsible host epithelial and immune pathways but without yet a complete systems-level explanation. Most recently, the commensal gut microbiota have been found to be both ecologically and functionally perturbed during the disease, but with as-yet-unexplained heterogeneity among IBD subtypes and individual patients. IBD thus represents perhaps the most comprehensive current model for understanding the human microbiome's role in complex inflammatory disease. Here, we review the influences of the microbiota on IBD and its potential for translational medicine.

A systematic machine learning and data type comparison yields metagenomic predictors of infant age, sex, breastfeeding, antibiotic usage, country of origin, and delivery type.

The microbiome is a new frontier for building predictors of human phenotypes. However, machine learning in the microbiome is fraught with issues of reproducibility, driven in large part by the wide range of analytic models and metagenomic data types available. We aimed to build robust metagenomic predictors of host phenotype by comparing prediction performances and biological interpretation across 8 machine learning methods and 4 different types of metagenomic data. Using 1,570 samples from 300 infants, we fit 7,865 models for 6 host phenotypes. We demonstrate the dependence of accuracy on algorithm choice and feature definition in microbiome data and propose a framework for building microbiome-derived indicators of host phenotype. We additionally identify biological features predictive of age, sex, breastfeeding status, historical antibiotic usage, country of origin, and delivery type. Our complete results can be viewed at http://apps.chiragjpgroup.org/ubiome_predictions/.

Exploring host-microbiota interactions in animal models and humans.

The animal and bacterial kingdoms have coevolved and coadapted in response to environmental selective pressures over hundreds of millions of years. The meta'omics revolution in both sequencing and its analytic pipelines is fostering an explosion of interest in how the gut microbiome impacts physiology and propensity to disease. Gut microbiome studies are inherently interdisciplinary, drawing on approaches and technical skill sets from the biomedical sciences, ecology, and computational biology. Central to unraveling the complex biology of environment, genetics, and microbiome interaction in human health and disease is a deeper understanding of the symbiosis between animals and bacteria. Experimental model systems, including mice, fish, insects, and the Hawaiian bobtail squid, continue to provide critical insight into how host-microbiota homeostasis is constructed and maintained. Here we consider how model systems are influencing current understanding of host-microbiota interactions and explore recent human microbiome studies.

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

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.

Aether: leveraging linear programming for optimal cloud computing in genomics.

Motivation: Across biology, we are seeing rapid developments in scale of data production without a corresponding increase in data analysis capabilities. Results: Here, we present Aether (http://aether.kosticlab.org), an intuitive, easy-to-use, cost-effective and scalable framework that uses linear programming to optimally bid on and deploy combinations of underutilized cloud computing resources. Our approach simultaneously minimizes the cost of data analysis and provides an easy transition from users' existing HPC pipelines. Availability and implementation: Data utilized are available at https://pubs.broadinstitute.org/diabimmune and with EBI SRA accession ERP005989. Source code is available at (https://github.com/kosticlab/aether). Examples, documentation and a tutorial are available at http://aether.kosticlab.org. Contact: chirag_patel@hms.harvard.edu or aleksandar.kostic@joslin.harvard.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Fusobacterium nucleatum in colorectal carcinoma tissue and patient prognosis.

OBJECTIVE: Accumulating evidence links the intestinal microbiota and colorectal carcinogenesis. Fusobacterium nucleatum may promote colorectal tumour growth and inhibit T cell-mediated immune responses against colorectal tumours. Thus, we hypothesised that the amount of F. nucleatum in colorectal carcinoma might be associated with worse clinical outcome. DESIGN: We used molecular pathological epidemiology database of 1069 rectal and colon cancer cases in the Nurses' Health Study and the Health Professionals Follow-up Study, and measured F. nucleatum DNA in carcinoma tissue. Cox proportional hazards model was used to compute hazard ratio (HR), controlling for potential confounders, including microsatellite instability (MSI, mismatch repair deficiency), CpG island methylator phenotype (CIMP), KRAS, BRAF, and PIK3CA mutations, and LINE-1 hypomethylation (low-level methylation). RESULTS: Compared with F. nucleatum-negative cases, multivariable HRs (95% CI) for colorectal cancer-specific mortality in F. nucleatum-low cases and F. nucleatum-high cases were 1.25 (0.82 to 1.92) and 1.58 (1.04 to 2.39), respectively, (p for trend=0.020). The amount of F. nucleatum was associated with MSI-high (multivariable odd ratio (OR), 5.22; 95% CI 2.86 to 9.55) independent of CIMP and BRAF mutation status, whereas CIMP and BRAF mutation were associated with F. nucleatum only in univariate analyses (p<0.001) but not in multivariate analysis that adjusted for MSI status. CONCLUSIONS: The amount of F. nucleatum DNA in colorectal cancer tissue is associated with shorter survival, and may potentially serve as a prognostic biomarker. Our data may have implications in developing cancer prevention and treatment strategies through targeting GI microflora by diet, probiotics and antibiotics.

Human genome-wide RNAi screen identifies an essential role for inositol pyrophosphates in Type-I interferon response.

The pattern recognition receptor RIG-I is critical for Type-I interferon production. However, the global regulation of RIG-I signaling is only partially understood. Using a human genome-wide RNAi-screen, we identified 226 novel regulatory proteins of RIG-I mediated interferon-ß production. Furthermore, the screen identified a metabolic pathway that synthesizes the inositol pyrophosphate 1-IP7 as a previously unrecognized positive regulator of interferon production. Detailed genetic and biochemical experiments demonstrated that the kinase activities of IPPK, PPIP5K1 and PPIP5K2 (which convert IP5 to1-IP7) were critical for both interferon induction, and the control of cellular infection by Sendai and influenza A viruses. Conversely, ectopically expressed inositol pyrophosphate-hydrolases DIPPs attenuated interferon transcription. Mechanistic experiments in intact cells revealed that the expression of IPPK, PPIP5K1 and PPIP5K2 was needed for the phosphorylation and activation of IRF3, a transcription factor for interferon. The addition of purified individual inositol pyrophosphates to a cell free reconstituted RIG-I signaling assay further identified 1-IP7 as an essential component required for IRF3 activation. The inositol pyrophosphate may act by ß-phosphoryl transfer, since its action was not recapitulated by a synthetic phosphonoacetate analogue of 1-IP7. This study thus identified several novel regulators of RIG-I, and a new role for inositol pyrophosphates in augmenting innate immune responses to viral infection that may have therapeutic applications.

The microbiome in inflammatory bowel disease: current status and the future ahead.

Studies of the roles of microbial communities in the development of inflammatory bowel disease (IBD) have reached an important milestone. A decade of genome-wide association studies and other genetic analyses have linked IBD with loci that implicate an aberrant immune response to the intestinal microbiota. More recently, profiling studies of the intestinal microbiome have associated the pathogenesis of IBD with characteristic shifts in the composition of the intestinal microbiota, reinforcing the view that IBD results from altered interactions between intestinal microbes and the mucosal immune system. Enhanced technologies can increase our understanding of the interactions between the host and its resident microbiota and their respective roles in IBD from both a large-scale pathway view and at the metabolic level. We review important microbiome studies of patients with IBD and describe what we have learned about the mechanisms of intestinal microbiota dysfunction. We describe the recent progress in microbiome research from exploratory 16S-based studies, reporting associations of specific organisms with a disease, to more recent studies that have taken a more nuanced view, addressing the function of the microbiota by metagenomic and metabolomic methods. Finally, we propose study designs and methodologies for future investigations of the microbiome in patients with inflammatory gut and autoimmune diseases in general.

Genomic analysis identifies association of Fusobacterium with colorectal carcinoma.

The tumor microenvironment of colorectal carcinoma is a complex community of genomically altered cancer cells, nonneoplastic cells, and a diverse collection of microorganisms. Each of these components may contribute to carcinogenesis; however, the role of the microbiota is the least well understood. We have characterized the composition of the microbiota in colorectal carcinoma using whole genome sequences from nine tumor/normal pairs. Fusobacterium sequences were enriched in carcinomas, confirmed by quantitative PCR and 16S rDNA sequence analysis of 95 carcinoma/normal DNA pairs, while the Bacteroidetes and Firmicutes phyla were depleted in tumors. Fusobacteria were also visualized within colorectal tumors using FISH. These findings reveal alterations in the colorectal cancer microbiota; however, the precise role of Fusobacteria in colorectal carcinoma pathogenesis requires further investigation.

Quantifying Shared and Unique Gene Content across 17 Microbial Ecosystems.

Measuring microbial diversity is traditionally based on microbe taxonomy. Here, in contrast, we aimed to quantify heterogeneity in microbial gene content across 14,183 metagenomic samples spanning 17 ecologies, including 6 human associated, 7 nonhuman host associated, and 4 in other nonhuman host environments. In total, we identified 117,629,181 nonredundant genes. The vast majority of genes (66%) occurred in only one sample (i.e., "singletons"). In contrast, we found 1,864 sequences present in every metagenome, but not necessarily every bacterial genome. Additionally, we report data sets of other ecology-associated genes (e.g., abundant in only gut ecosystems) and simultaneously demonstrated that prior microbiome gene catalogs are both incomplete and inaccurately cluster microbial genetic life (e.g., at gene sequence identities that are too restrictive). We provide our results and the sets of environmentally differentiating genes described above at http://www.microbial-genes.bio. IMPORTANCE The amount of shared genetic elements has not been quantified between the human microbiome and other host- and non-host-associated microbiomes. Here, we made a gene catalog of 17 different microbial ecosystems and compared them. We show that most species shared between environment and human gut microbiomes are pathogens and that prior gene catalogs described as "nearly complete" are far from it. Additionally, over two-thirds of all genes only appear in a single sample, and only 1,864 genes (0.001%) are found in all types of metagenomes. These results highlight the large diversity between metagenomes and reveal a new, rare class of genes, those found in every type of metagenome, but not every microbial genome.

DNA characterization reveals potential operon-unit packaging of extracellular vesicle cargo from a gut bacterial symbiont.

Extracellular vesicles (EVs) are lipid bilayer-bound entities secreted by cells across all domains of life, known to contain a range of components, including protein complexes, RNA, and DNA. Recent studies on microbial extracellular vesicles indicate that these virus-sized nanoparticles, 40-90nm in diameter, readily cross the epithelial barrier and reach systemic circulation, can be detected in tissues throughout the body in mice and that 1mL of plasma from healthy humans contains up to one million bacterial EVs. They have been recently recognized for their biologically functional roles, including modulation of bacterial physiology and host-microbe interactions, hence their gain in the microbiome research community's attention. However, the exact understanding of their functionality is still a subject of active research and debate. Here, we employ long-read DNA sequencing on purified extracellular vesicles from a common mammalian gut symbiont, Parabacteroides goldsteinii, to characterize the genomic component within EV cargos. Our findings challenge the notion of DNA packaging into EVs as a stochastic event. Instead, our data demonstrate that the DNA packaging is non-random. Here, we suggest a novel hypothesis of selective EV-DNA packaging, potentially arranged in operon units, hence providing new insights into our understanding of its genetic makeup and its potential role, underlining the importance of our findings in microbial community dynamics.

The human microbiome: A coming of age story.

The human microbiome field is coming of age, but it is still defining itself. I can say the same as an investigator who started his career in the early days of this expanding field. This commentary reflects on my Cell Host & Microbe papers along this journey that captured the field's progress.

Resources to Facilitate Use of the Altered Schaedler Flora (ASF) Mouse Model to Study Microbiome Function.

Animals colonized with a defined microbiota represent useful experimental systems to investigate microbiome function. The altered Schaedler flora (ASF) represents a consortium of eight murine bacterial species that have been used for more than 4 decades where the study of mice with a reduced microbiota is desired. In contrast to germ-free mice, or mice colonized with only one or two species, ASF mice show the normal gut structure and immune system development. To further expand the utility of the ASF, we have developed technical and bioinformatic resources to enable a systems-based analysis of microbiome function using this model. Here, we highlighted four distinct applications of these resources that enable and improve (i) measurements of the abundance of each ASF member by quantitative PCR; (ii) exploration and comparative analysis of ASF genomes and the metabolic pathways they encode that comprise the entire gut microbiome; (iii) global transcriptional profiling to identify genes whose expression responds to environmental changes within the gut; and (iv) discovery of genetic changes resulting from the evolutionary adaptation of the microbiota. These resources were designed to be accessible to a broad community of researchers that, in combination with conventionally-reared mice (i.e., with complex microbiome), should contribute to our understanding of microbiome structure and function. IMPORTANCE Improved experimental systems are needed to advance our understanding of how the gut microbiome influences processes of the mammalian host as well as microbial community structure and function. An approach that is receiving considerable attention is the use of animal models that harbor a stable microbiota of known composition, i.e., defined microbiota, which enables control over an otherwise highly complex and variable feature of mammalian biology. The altered Schaedler flora (ASF) consortium is a well-established defined microbiota model, where mice are stably colonized with 8 distinct murine bacterial species. To take better advantage of the ASF, we established new experimental and bioinformatics resources for researchers to make better use of this model as an experimental system to study microbiome function.

The TPR-containing domain within Est1 homologs exhibits species-specific roles in telomerase interaction and telomere length homeostasis.

BACKGROUND: The first telomerase-associated protein (Est1) was isolated in yeast due to its essential role in telomere maintenance. The human counterparts EST1A, EST1B, and EST1C perform diverse functions in nonsense-mediated mRNA decay (NMD), telomere length homeostasis, and telomere transcription. Although Est1 and EST1A/B interact with the catalytic subunit of yeast and human telomerase (Est2 and TERT, respectively), the molecular determinants of these interactions have not been elaborated fully. RESULTS: To investigate the functional conservation of the EST1 protein family, we performed protein-protein interaction mapping and structure-function analysis. The domain in hEST1A most conserved between species, containing a TPR (tricotetrapeptide repeat), was sufficient for interaction of hEST1A with multiple fragments of hTERT including the N-terminus. Two mutations within the hTERT N-terminus that perturb in vivo function (NAAIRS(92), NAAIRS(122)) did not affect this protein interaction. ScEst1 hybrids containing the TPR of hEST1A, hEST1B, or hEST1C were expressed in yeast strains lacking EST1, yet they failed to complement senescence. Point mutations within and outside the cognate ScEst1 TPR, chosen to disrupt a putative protein interaction surface, resulted in telomere lengthening or shortening without affecting recruitment to telomeres. CONCLUSIONS: These results identify a domain encompassing the TPR of hEST1A as an hTERT interaction module. The TPR of S. cerevisiae Est1 is required for telomerase-mediated telomere length maintenance in a manner that appears separable from telomere recruitment. Discrete residues in or adjacent to the TPR of Est1 also regulate telomere length homeostasis.

Mechanisms of microbial-neuronal interactions in pain and nociception.

Nociceptor sensory neurons innervate barrier tissues that are constantly exposed to microbial stimuli. During infection, pathogenic microorganisms can breach barrier surfaces and produce pain by directly activating nociceptors. Microorganisms that live in symbiotic relationships with their hosts, commensals and mutualists, have also been associated with pain, but the molecular mechanisms of how symbionts act on nociceptor neurons to modulate pain remain largely unknown. In this review, we will discuss the known molecular mechanisms of how microbes directly interact with sensory afferent neurons affecting nociception in the gut, skin and lungs. We will touch on how bacterial, viral and fungal pathogens signal to the host to inflict or suppress pain. We will also discuss recent studies examining how gut symbionts affect pain. Specifically, we will discuss how gut symbionts may interact with sensory afferent neurons either directly, through secretion of metabolites or neurotransmitters, or indirectly,through first signaling to epithelial cells or immune cells, to regulate visceral, neuropathic and inflammatory pain. While this area of research is still in its infancy, more mechanistic studies to examine microbial-sensory neuron crosstalk in nociception may allow us to develop new therapies for the treatment of acute and chronic pain.