Microbiota modulate behavioral and physiological abnormalities associated with neurodevelopmental disorders.

Neurodevelopmental disorders, including autism spectrum disorder (ASD), are defined by core behavioral impairments; however, subsets of individuals display a spectrum of gastrointestinal (GI) abnormalities. We demonstrate GI barrier defects and microbiota alterations in the maternal immune activation (MIA) mouse model that is known to display features of ASD. Oral treatment of MIA offspring with the human commensal Bacteroides fragilis corrects gut permeability, alters microbial composition, and ameliorates defects in communicative, stereotypic, anxiety-like and sensorimotor behaviors. MIA offspring display an altered serum metabolomic profile, and B. fragilis modulates levels of several metabolites. Treating naive mice with a metabolite that is increased by MIA and restored by B. fragilis causes certain behavioral abnormalities, suggesting that gut bacterial effects on the host metabolome impact behavior. Taken together, these findings support a gut-microbiome-brain connection in a mouse model of ASD and identify a potential probiotic therapy for GI and particular behavioral symptoms in human neurodevelopmental disorders.

Impacts of the Human Gut Microbiome on Therapeutics.

The human microbiome contains a vast source of genetic and biochemical variation, and its impacts on therapeutic responses are just beginning to be understood. This expanded understanding is especially important because the human microbiome differs far more among different people than does the human genome, and it is also dramatically easier to change. Here, we describe some of the major factors driving differences in the human microbiome among individuals and populations. We then describe some of the many ways in which gut microbes modify the action of specific chemotherapeutic agents, including nonsteroidal anti-inflammatory drugs and cardiac glycosides, and outline the potential of fecal microbiota transplant as a therapeutic. Intriguingly, microbes also alter how hosts respond to therapeutic agents through various pathways acting at distal sites. Finally, we discuss some of the computational and practical issues surrounding use of the microbiome to stratify individuals for drug response, and we envision a future where the microbiome will be modified to increase everyone's potential to benefit from therapy.

The Microbiome and Human Biology.

Over the past few years, microbiome research has dramatically reshaped our understanding of human biology. New insights range from an enhanced understanding of how microbes mediate digestion and disease processes (e.g., in inflammatory bowel disease) to surprising associations with Parkinson's disease, autism, and depression. In this review, we describe how new generations of sequencing technology, analytical advances coupled to new software capabilities, and the integration of animal model data have led to these new discoveries. We also discuss the prospects for integrating studies of the microbiome, metabolome, and immune system, with the goal of elucidating mechanisms that govern their interactions. This systems-level understanding will change how we think about ourselves as organisms.

Coupling Targeted and Untargeted Mass Spectrometry for Metabolome-Microbiome-Wide Association Studies of Human Fecal Samples.

Increasing appreciation of the gut microbiome's role in health motivates understanding the molecular composition of human feces. To analyze such complex samples, we developed a platform coupling targeted and untargeted metabolomics. The approach is facilitated through split flow from one UPLC, joint timing triggered by contact closure relays, and a script to retrieve the data. It is designed to detect specific metabolites of interest with high sensitivity, allows for correction of targeted information, enables better quantitation thus providing an advanced analytical tool for exploratory studies. Procrustes analysis revealed that untargeted approach provides a better correlation to microbiome data, associating specific metabolites with microbes that produce or process them. With the subset of over one hundred human fecal samples from the American Gut project, the implementation of the described coupled workflow revealed that targeted analysis using combination of single transition per compound with retention time misidentifies 30% of the targeted data and could lead to incorrect interpretations. At the same time, the targeted analysis extends detection limits and dynamic range, depending on the compounds, by orders of magnitude. A software application has been developed as a part of the workflow to allows for quantitative assessments based on calibration curves. Using this approach, we detect expected microbially modified molecules such as secondary bile acids and unexpected microbial molecules including Pseudomonas-associated quinolones and rhamnolipids in feces, setting the stage for metabolome-microbiome-wide association studies (MMWAS).

The Microbiome in Posttraumatic Stress Disorder and Trauma-Exposed Controls: An Exploratory Study.

OBJECTIVE: Inadequate immunoregulation and elevated inflammation may be risk factors for posttraumatic stress disorder (PTSD), and microbial inputs are important determinants of immunoregulation; however, the association between the gut microbiota and PTSD is unknown. This study investigated the gut microbiome in a South African sample of PTSD-affected individuals and trauma-exposed (TE) controls to identify potential differences in microbial diversity or microbial community structure. METHODS: The Clinician-Administered PTSD Scale for DSM-5 was used to diagnose PTSD according to Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria. Microbial DNA was extracted from stool samples obtained from 18 individuals with PTSD and 12 TE control participants. Bacterial 16S ribosomal RNA gene V3/V4 amplicons were generated and sequenced. Microbial community structure, α-diversity, and ß-diversity were analyzed; random forest analysis was used to identify associations between bacterial taxa and PTSD. RESULTS: There were no differences between PTSD and TE control groups in α- or ß-diversity measures (e.g., α-diversity: Shannon index, t = 0.386, p = .70; ß-diversity, on the basis of analysis of similarities: Bray-Curtis test statistic = -0.033, p = .70); however, random forest analysis highlighted three phyla as important to distinguish PTSD status: Actinobacteria, Lentisphaerae, and Verrucomicrobia. Decreased total abundance of these taxa was associated with higher Clinician-Administered PTSD Scale scores (r = -0.387, p = .035). CONCLUSIONS: In this exploratory study, measures of overall microbial diversity were similar among individuals with PTSD and TE controls; however, decreased total abundance of Actinobacteria, Lentisphaerae, and Verrucomicrobia was associated with PTSD status.

Euphorbia plant latex is inhabited by diverse microbial communities.

PREMISE OF THE STUDY: The antimicrobial properties and toxicity of Euphorbia plant latex should make it a hostile environment to microbes. However, when specimens from Euphorbia spp. were propagated in tissue culture, microbial growth was observed routinely, raising the question whether the latex of this diverse plant genus can be a niche for polymicrobial communities. METHODS: Latex from a phylogenetically diverse set of Euphorbia species was collected and genomic microbial DNA extracted. Deep sequencing of bar-coded amplicons from taxonomically informative gene fragments was used to measure bacterial and fungal species richness, evenness, and composition. KEY RESULTS: Euphorbia latex was found to contain unexpectedly complex bacterial (mean: 44.0 species per sample; 9 plants analyzed) and fungal (mean: 20.9 species per sample; 22 plants analyzed) communities using culture-independent methods. Many of the identified taxa are known plant endophytes, but have not been previously found in latex. CONCLUSIONS: Our results suggest that Euphorbia plant latex, a putatively hostile antimicrobial environment, unexpectedly supports diverse bacterial and fungal communities. The ecological roles of these microorganisms and potential interactions with their host plants are unknown and warrant further research.

Initial insights into bacterial succession during human decomposition.

Decomposition is a dynamic ecological process dependent upon many factors such as environment, climate, and bacterial, insect, and vertebrate activity in addition to intrinsic properties inherent to individual cadavers. Although largely attributed to microbial metabolism, very little is known about the bacterial basis of human decomposition. To assess the change in bacterial community structure through time, bacterial samples were collected from several sites across two cadavers placed outdoors to decompose and analyzed through 454 pyrosequencing and analysis of variable regions 3-5 of the bacterial 16S ribosomal RNA (16S rRNA) gene. Each cadaver was characterized by a change in bacterial community structure for all sites sampled as time, and decomposition, progressed. Bacteria community structure is variable at placement and before purge for all body sites. At bloat and purge and until tissues began to dehydrate or were removed, bacteria associated with flies, such as Ignatzschineria and Wohlfahrtimonas, were common. After dehydration and skeletonization, bacteria associated with soil, such as Acinetobacter, were common at most body sites sampled. However, more cadavers sampled through multiple seasons are necessary to assess major trends in bacterial succession.

A microbiota signature associated with experimental food allergy promotes allergic sensitization and anaphylaxis.

BACKGROUND: Commensal microbiota play a critical role in maintaining oral tolerance. The effect of food allergy on the gut microbial ecology remains unknown. OBJECTIVE: We sought to establish the composition of the gut microbiota in experimental food allergy and its role in disease pathogenesis. METHODS: Food allergy-prone mice with a gain-of-function mutation in the IL-4 receptor α chain (Il4raF709) and wild-type (WT) control animals were subjected to oral sensitization with chicken egg ovalbumin (OVA). Enforced tolerance was achieved by using allergen-specific regulatory T (Treg) cells. Community structure analysis of gut microbiota was performed by using a high-density 16S rDNA oligonucleotide microarrays (PhyloChip) and massively parallel pyrosequencing of 16S rDNA amplicons. RESULTS: OVA-sensitized Il4raF709 mice exhibited a specific microbiota signature characterized by coordinate changes in the abundance of taxa of several bacterial families, including the Lachnospiraceae, Lactobacillaceae, Rikenellaceae, and Porphyromonadaceae. This signature was not shared by similarly sensitized WT mice, which did not exhibit an OVA-induced allergic response. Treatment of OVA-sensitized Il4raF709 mice with OVA-specific Treg cells led to a distinct tolerance-associated signature coincident with the suppression of the allergic response. The microbiota of allergen-sensitized Il4raF709 mice differentially promoted OVA-specific IgE responses and anaphylaxis when reconstituted in WT germ-free mice. CONCLUSION: Mice with food allergy exhibit a specific gut microbiota signature capable of transmitting disease susceptibility and subject to reprogramming by enforced tolerance. Disease-associated microbiota may thus play a pathogenic role in food allergy.

BIOME-Preserve: A novel storage and transport medium for preserving anaerobic microbiota samples for culture recovery.

Sequencing-based protocols for studying the human microbiome have unearthed a wealth of information about the relationship between the microbiome and human health. But these microbes cannot be leveraged as therapeutic targets without culture-based studies to phenotype species of interest and to establish culture collections for use in animal models. Traditional sample collection protocols are focused on preserving nucleic acids and metabolites and are largely inappropriate for preserving sensitive anaerobic bacteria for later culture recovery. Here we introduce a novel microbiome preservation kit (BIOME-Preserve) that facilitates recovery of anaerobic bacteria from human stool. Using a combination of culture recovery and shallow whole-genome shotgun sequencing, we characterized the anaerobes cultured from fresh human stool and from human stool held at room temperature in BIOME-Preserve for up to 120 hours. We recovered several species of interest to microbiome researchers, including Bifidobacterium spp., Bacteroides spp., Blautia spp., Eubacterium halii (now Anaerobutyricum hallii), Akkermansia muciniphila, and Faecalibacterium prausnitzii. We also demonstrated that freezing at -80°C did not adversely affect our ability to culture organisms from BIOME-Preserve, suggesting that it is appropriate both as a transport medium and as a medium for longer-term ultra-cold storage. Together, our results suggest BIOME-Preserve is practical for the collection, transport, and culture of anaerobic bacteria from human samples and can help enable researchers to better understand the link between the microbiome and human health and how to leverage that link through novel microbiome-based therapeutics.

Frequency of Tongue Cleaning Impacts the Human Tongue Microbiome Composition and Enterosalivary Circulation of Nitrate.

The oral microbiome has the potential to provide an important symbiotic function in human blood pressure physiology by contributing to the generation of nitric oxide (NO), an essential cardiovascular signaling molecule. NO is produced by the human body via conversion of arginine to NO by endogenous nitric oxide synthase (eNOS) but eNOS activity varies by subject. Oral microbial communities are proposed to supplement host NO production by reducing dietary nitrate to nitrite via bacterial nitrate reductases. Unreduced dietary nitrate is delivered to the oral cavity in saliva, a physiological process termed the enterosalivary circulation of nitrate. Previous studies demonstrated that disruption of enterosalivary circulation via use of oral antiseptics resulted in increases in systolic blood pressure. These previous studies did not include detailed information on the oral health of enrolled subjects. Using 16S rRNA gene sequencing and analysis, we determined whether introduction of chlorhexidine antiseptic mouthwash for 1 week was associated with changes in tongue bacterial communities and resting systolic blood pressure in healthy normotensive individuals with documented oral hygiene behaviors and free of oral disease. Tongue cleaning frequency was a predictor of chlorhexidine-induced changes in systolic blood pressure and tongue microbiome composition. Twice-daily chlorhexidine usage was associated with a significant increase in systolic blood pressure after 1 week of use and recovery from use resulted in an enrichment in nitrate-reducing bacteria on the tongue. Individuals with relatively high levels of bacterial nitrite reductases had lower resting systolic blood pressure. These results further support the concept of a symbiotic oral microbiome contributing to human health via the enterosalivary nitrate-nitrite-NO pathway. These data suggest that management of the tongue microbiome by regular cleaning together with adequate dietary intake of nitrate provide an opportunity for the improvement of resting systolic blood pressure.

Molecular and Microbial Microenvironments in Chronically Diseased Lungs Associated with Cystic Fibrosis.

To visualize the personalized distributions of pathogens and chemical environments, including microbial metabolites, pharmaceuticals, and their metabolic products, within and between human lungs afflicted with cystic fibrosis (CF), we generated three-dimensional (3D) microbiome and metabolome maps of six explanted lungs from three cystic fibrosis patients. These 3D spatial maps revealed that the chemical environments differ between patients and within the lungs of each patient. Although the microbial ecosystems of the patients were defined by the dominant pathogen, their chemical diversity was not. Additionally, the chemical diversity between locales in the lungs of the same individual sometimes exceeded interindividual variation. Thus, the chemistry and microbiome of the explanted lungs appear to be not only personalized but also regiospecific. Previously undescribed analogs of microbial quinolones and antibiotic metabolites were also detected. Furthermore, mapping the chemical and microbial distributions allowed visualization of microbial community interactions, such as increased production of quorum sensing quinolones in locations where Pseudomonas was in contact with Staphylococcus and Granulicatella, consistent with in vitro observations of bacteria isolated from these patients. Visualization of microbe-metabolite associations within a host organ in early-stage CF disease in animal models will help elucidate the complex interplay between the presence of a given microbial structure, antibiotics, metabolism of antibiotics, microbial virulence factors, and host responses.IMPORTANCE Microbial infections are now recognized to be polymicrobial and personalized in nature. Comprehensive analysis and understanding of the factors underlying the polymicrobial and personalized nature of infections remain limited, especially in the context of the host. By visualizing microbiomes and metabolomes of diseased human lungs, we reveal how different the chemical environments are between hosts that are dominated by the same pathogen and how community interactions shape the chemical environment or vice versa. We highlight that three-dimensional organ mapping methods represent hypothesis-building tools that allow us to design mechanistic studies aimed at addressing microbial responses to other microbes, the host, and pharmaceutical drugs.

American Gut: an Open Platform for Citizen Science Microbiome Research.

Although much work has linked the human microbiome to specific phenotypes and lifestyle variables, data from different projects have been challenging to integrate and the extent of microbial and molecular diversity in human stool remains unknown. Using standardized protocols from the Earth Microbiome Project and sample contributions from over 10,000 citizen-scientists, together with an open research network, we compare human microbiome specimens primarily from the United States, United Kingdom, and Australia to one another and to environmental samples. Our results show an unexpected range of beta-diversity in human stool microbiomes compared to environmental samples; demonstrate the utility of procedures for removing the effects of overgrowth during room-temperature shipping for revealing phenotype correlations; uncover new molecules and kinds of molecular communities in the human stool metabolome; and examine emergent associations among the microbiome, metabolome, and the diversity of plants that are consumed (rather than relying on reductive categorical variables such as veganism, which have little or no explanatory power). We also demonstrate the utility of the living data resource and cross-cohort comparison to confirm existing associations between the microbiome and psychiatric illness and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education. IMPORTANCE We show that a citizen science, self-selected cohort shipping samples through the mail at room temperature recaptures many known microbiome results from clinically collected cohorts and reveals new ones. Of particular interest is integrating n = 1 study data with the population data, showing that the extent of microbiome change after events such as surgery can exceed differences between distinct environmental biomes, and the effect of diverse plants in the diet, which we confirm with untargeted metabolomics on hundreds of samples.

The Microbiome and Big Data.

Microbiome datasets have expanded rapidly in recent years. Advances in DNA sequencing, as well as the rise of shotgun metagenomics and metabolomics, are producing datasets that exceed the ability of researchers to analyze them on their personal computers. Here we describe what Big Data is in the context of microbiome research, how this data can be transformed into knowledge about microbes and their functions in their environments, and how the knowledge can be applied to move microbiome research forward. In particular, the development of new high-resolution tools to assess strain-level variability (moving away from OTUs), the advent of cloud computing and centralized analysis resources such as Qiita (for sequences) and GNPS (for mass spectrometry), and better methods for curating and describing "metadata" (contextual information about the sequence or chemical information) are rapidly assisting the use of microbiome data in fields ranging from human health to environmental studies.

Correction for Gonzalez et al., "Migraines Are Correlated with Higher Levels of Nitrate-, Nitrite-, and Nitric Oxide-Reducing Oral Microbes in the American Gut Project Cohort".

[This corrects the article DOI: 10.1128/mSystems.00105-16.].

Microbiome disruption and recovery in the fish Gambusia affinis following exposure to broad-spectrum antibiotic.

Antibiotics are a relatively common disturbance to the normal microbiota of humans and agricultural animals, sometimes resulting in severe side effects such as antibiotic-associated enterocolitis. Gambusia affinis was used as a vertebrate model for effects of a broad-spectrum antibiotic, rifampicin, on the skin and gut mucosal microbiomes. The fish were exposed to the antibiotic in the water column for 1 week, and then monitored during recovery. As observed via culture, viable counts from the skin microbiome dropped strongly yet returned to pretreatment levels by 1.6 days and became >70% resistant. The gut microbiome counts dropped and took longer to recover (2.6 days), and became >90% drug resistant. The resistance persisted at ~20% of skin counts in the absence of antibiotic selection for 2 weeks. A community biochemical analysis measuring the presence/absence of 31 activities observed a 39% change in results after 3 days of antibiotic treatment. The antibiotic lowered the skin and gut microbiome community diversity and altered taxonomic composition, observed by 16S rRNA profiling. A 1-week recovery period did not return diversity or composition to pretreatment levels. The genus Myroides dominated both the microbiomes during the treatment, but was not stable and declined in abundance over time during recovery. Rifampicin selected for members of the family Comamonadaceae in the skin but not the gut microbiome. Consistent with other studies, this tractable animal model shows lasting effects on mucosal microbiomes following antibiotic exposure, including persistence of drug-resistant organisms in the community.

Correcting for Microbial Blooms in Fecal Samples during Room-Temperature Shipping.

The use of sterile swabs is a convenient and common way to collect microbiome samples, and many studies have shown that the effects of room-temperature storage are smaller than physiologically relevant differences between subjects. However, several bacterial taxa, notably members of the class Gammaproteobacteria, grow at room temperature, sometimes confusing microbiome results, particularly when stability is assumed. Although comparative benchmarking has shown that several preservation methods, including the use of 95% ethanol, fecal occult blood test (FOBT) and FTA cards, and Omnigene-GUT kits, reduce changes in taxon abundance during room-temperature storage, these techniques all have drawbacks and cannot be applied retrospectively to samples that have already been collected. Here we performed a meta-analysis using several different microbiome sample storage condition studies, showing consistent trends in which specific bacteria grew (i.e., "bloomed") at room temperature, and introduce a procedure for removing the sequences that most distort analyses. In contrast to similarity-based clustering using operational taxonomic units (OTUs), we use a new technique called "Deblur" to identify the exact sequences corresponding to blooming taxa, greatly reducing false positives and also dramatically decreasing runtime. We show that applying this technique to samples collected for the American Gut Project (AGP), for which participants simply mail samples back without the use of ice packs or other preservatives, yields results consistent with published microbiome studies performed with frozen or otherwise preserved samples. IMPORTANCE In many microbiome studies, the necessity to store samples at room temperature (i.e., remote fieldwork) and the ability to ship samples without hazardous materials that require special handling training, such as ethanol (i.e., citizen science efforts), is paramount. However, although room-temperature storage for a few days has been shown not to obscure physiologically relevant microbiome differences between comparison groups, there are still changes in specific bacterial taxa, notably, in members of the class Gammaproteobacteria, that can make microbiome profiles difficult to interpret. Here we identify the most problematic taxa and show that removing sequences from just a few fast-growing taxa is sufficient to correct microbiome profiles.

Normalization and microbial differential abundance strategies depend upon data characteristics.

BACKGROUND: Data from 16S ribosomal RNA (rRNA) amplicon sequencing present challenges to ecological and statistical interpretation. In particular, library sizes often vary over several ranges of magnitude, and the data contains many zeros. Although we are typically interested in comparing relative abundance of taxa in the ecosystem of two or more groups, we can only measure the taxon relative abundance in specimens obtained from the ecosystems. Because the comparison of taxon relative abundance in the specimen is not equivalent to the comparison of taxon relative abundance in the ecosystems, this presents a special challenge. Second, because the relative abundance of taxa in the specimen (as well as in the ecosystem) sum to 1, these are compositional data. Because the compositional data are constrained by the simplex (sum to 1) and are not unconstrained in the Euclidean space, many standard methods of analysis are not applicable. Here, we evaluate how these challenges impact the performance of existing normalization methods and differential abundance analyses. RESULTS: Effects on normalization: Most normalization methods enable successful clustering of samples according to biological origin when the groups differ substantially in their overall microbial composition. Rarefying more clearly clusters samples according to biological origin than other normalization techniques do for ordination metrics based on presence or absence. Alternate normalization measures are potentially vulnerable to artifacts due to library size. Effects on differential abundance testing: We build on a previous work to evaluate seven proposed statistical methods using rarefied as well as raw data. Our simulation studies suggest that the false discovery rates of many differential abundance-testing methods are not increased by rarefying itself, although of course rarefying results in a loss of sensitivity due to elimination of a portion of available data. For groups with large (~10×) differences in the average library size, rarefying lowers the false discovery rate. DESeq2, without addition of a constant, increased sensitivity on smaller datasets (<20 samples per group) but tends towards a higher false discovery rate with more samples, very uneven (~10×) library sizes, and/or compositional effects. For drawing inferences regarding taxon abundance in the ecosystem, analysis of composition of microbiomes (ANCOM) is not only very sensitive (for >20 samples per group) but also critically the only method tested that has a good control of false discovery rate. CONCLUSIONS: These findings guide which normalization and differential abundance techniques to use based on the data characteristics of a given study.

Deblur Rapidly Resolves Single-Nucleotide Community Sequence Patterns.

High-throughput sequencing of 16S ribosomal RNA gene amplicons has facilitated understanding of complex microbial communities, but the inherent noise in PCR and DNA sequencing limits differentiation of closely related bacteria. Although many scientific questions can be addressed with broad taxonomic profiles, clinical, food safety, and some ecological applications require higher specificity. Here we introduce a novel sub-operational-taxonomic-unit (sOTU) approach, Deblur, that uses error profiles to obtain putative error-free sequences from Illumina MiSeq and HiSeq sequencing platforms. Deblur substantially reduces computational demands relative to similar sOTU methods and does so with similar or better sensitivity and specificity. Using simulations, mock mixtures, and real data sets, we detected closely related bacterial sequences with single nucleotide differences while removing false positives and maintaining stability in detection, suggesting that Deblur is limited only by read length and diversity within the amplicon sequences. Because Deblur operates on a per-sample level, it scales to modern data sets and meta-analyses. To highlight Deblur's ability to integrate data sets, we include an interactive exploration of its application to multiple distinct sequencing rounds of the American Gut Project. Deblur is open source under the Berkeley Software Distribution (BSD) license, easily installable, and downloadable from https://github.com/biocore/deblur. IMPORTANCE Deblur provides a rapid and sensitive means to assess ecological patterns driven by differentiation of closely related taxa. This algorithm provides a solution to the problem of identifying real ecological differences between taxa whose amplicons differ by a single base pair, is applicable in an automated fashion to large-scale sequencing data sets, and can integrate sequencing runs collected over time.