Capacity of a Microbial Synbiotic To Rescue the In Vitro Metabolic Activity of the Gut Microbiome following Perturbation with Alcohol or Antibiotics.

The human gut microbiome contributes crucial bioactive metabolites that support human health and is sensitive to perturbations from the ingestion of alcohol and antibiotics. We interrogated the response and recovery of human gut microbes after acute alcohol or broad-spectrum antibiotic administration in a gut model simulating the luminal and mucosal colonic environment with an inoculated human microbiome. Both alcohol and antibiotic treatments reduced the production of major short-chain fatty acids (SCFAs) (acetate, propionate, and butyrate), which are established modulators of human health. Treatment with a microbial synbiotic restored and enhanced gut function. Butyrate and acetate production increased by up to 29.7% and 18.6%, respectively, relative to untreated, dysbiotic samples. In parallel, treatment led to increases in the relative abundances of beneficial commensal organisms not found in the synbiotic (e.g., Faecalibacterium prausnitzii and the urolithin-producing organism Gordonibacter pamelaeae) as well as species present in the synbiotic (e.g., Bifidobacterium infantis), suggesting synergistic interactions between supplemented and native microorganisms. These results lead us to conclude that functional shifts in the microbiome, evaluated by both metabolite production and specific taxonomic compositional changes, are an appropriate metric to assess microbiome "recovery" following a dysbiosis-inducing disruption. Overall, these findings support the execution of randomized clinical studies to determine whether a microbial synbiotic can help restore microbiome function after a disruption. IMPORTANCE The human gut microbiome is sensitive to disruptions by common stressors such as alcohol consumption and antibiotic treatment. In this study, we used an in vitro system modeling the gut microbiome to investigate whether treatment with a microbial synbiotic can help restore microbiome function after stress. We find that a complex gut community treated with alcohol or antibiotics showed reduced levels of production of short-chain fatty acids, which are critical beneficial molecules produced by a healthy gut microbiota. Treatment of stressed communities with a microbial synbiotic resulted in the recovery of SCFA production as well as an increase in the abundance of beneficial commensal organisms. Our results suggest that treatment with a microbial synbiotic has the potential to restore healthy gut microbiome function after stress and merits further investigation in clinical studies.

Functional response to a microbial synbiotic in the gastrointestinal system of children: a randomized clinical trial.

BACKGROUND: Oral microbial therapy has been studied as an intervention for a range of gastrointestinal disorders. Though research suggests that microbial exposure may affect the gastrointestinal system, motility, and host immunity in a pediatric population, data have been inconsistent, with most prior studies being in neither a randomized nor placebo-controlled setting. The aim of this randomized, placebo-controlled study was to evaluate the efficacy of a synbiotic on increasing weekly bowel movements (WBMs) in constipated children. METHODS: Sixty-four children (3-17 years of age) were randomized to receive a synbiotic (n = 33) comprising mixed-chain length oligosaccharides and nine microbial strains, or placebo (n = 31) for 84 days. Stool microbiota was analyzed on samples collected at baseline and completion. The primary outcome was a change from baseline of WBMs in the treatment group compared to placebo. RESULTS: Treatment increased (p < 0.05) the number of WBMs in children with low baseline WBMs, despite broadly distinctive baseline microbiome signatures. Sequencing revealed that low baseline microbial richness in the treatment group significantly anticipated improvements in constipation (p = 0.00074). CONCLUSIONS: These findings suggest the potential for (i) multi-species-synbiotic interventions to improve digestive health in a pediatric population and (ii) bioinformatics-based methods to predict response to microbial interventions in children. IMPACT: Synbiotic microbial treatment improved the number of spontaneous weekly bowel movements in children compared to placebo. Intervention induced an increased abundance of bifidobacteria in children, compared to placebo. All administered probiotic species were enriched in the gut microbiome of the intervention group compared to placebo. Baseline microbial richness demonstrated potential as a predictive biomarker for response to intervention.

SHOGUN: a modular, accurate and scalable framework for microbiome quantification.

SUMMARY: The software pipeline SHOGUN profiles known taxonomic and gene abundances of short-read shotgun metagenomics sequencing data. The pipeline is scalable, modular and flexible. Data analysis and transformation steps can be run individually or together in an automated workflow. Users can easily create new reference databases and can select one of three DNA alignment tools, ranging from ultra-fast low-RAM k-mer-based database search to fully exhaustive gapped DNA alignment, to best fit their analysis needs and computational resources. The pipeline includes an implementation of a published method for taxonomy assignment disambiguation with empirical Bayesian redistribution. The software is installable via the conda resource management framework, has plugins for the QIIME2 and QIITA packages and produces both taxonomy and gene abundance profile tables with a single command, thus promoting convenient and reproducible metagenomics research. AVAILABILITY AND IMPLEMENTATION: https://github.com/knights-lab/SHOGUN.

Wild primate microbiomes prevent weight gain in germ-free mice.

BACKGROUND: The gut microbiome harbors trillions of bacteria that play a major role in dietary nutrient extraction and host metabolism. Metabolic diseases such as obesity and diabetes are associated with shifts in microbiome composition and have been on the rise in Westernized or highly industrialized countries. At the same time, Westernized diets low in dietary fiber have been shown to cause loss of gut microbial diversity. However, the link between microbiome composition, loss of dietary fiber, and obesity has not been well defined. RESULTS: To study the interactions between gut microbiota, dietary fiber, and weight gain, we transplanted captive and wild douc gut microbiota into germ-free mice and then exposed them to either a high- or low-fiber diet. The group receiving captive douc microbiota gained significantly more weight, regardless of diet, while mice receiving a high-fiber diet and wild douc microbiota remained lean. In the presence of a low-fiber diet, the wild douc microbiota partially prevented weight gain. Using 16S rRNA gene amplicon sequencing we identified key bacterial taxa in each group, specifically a high relative abundance of Bacteroides and Akkermansia in captive douc FMT mice and a higher relative abundance of Lactobacillus and Clostridium in the wild douc FMT mice. CONCLUSIONS: In the context of our germ-free mouse experiment, wild douc microbiota could serve as a reservoir for microbes for cross-species transplants. Our results suggest that wild douc microbiota are tailored to diverse fiber diets and can prevent weight gain when exposed to a native diet.

Phylogenomics of 10,575 genomes reveals evolutionary proximity between domains Bacteria and Archaea.

Rapid growth of genome data provides opportunities for updating microbial evolutionary relationships, but this is challenged by the discordant evolution of individual genes. Here we build a reference phylogeny of 10,575 evenly-sampled bacterial and archaeal genomes, based on a comprehensive set of 381 markers, using multiple strategies. Our trees indicate remarkably closer evolutionary proximity between Archaea and Bacteria than previous estimates that were limited to fewer "core" genes, such as the ribosomal proteins. The robustness of the results was tested with respect to several variables, including taxon and site sampling, amino acid substitution heterogeneity and saturation, non-vertical evolution, and the impact of exclusion of candidate phyla radiation (CPR) taxa. Our results provide an updated view of domain-level relationships.

Author Correction: Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Daily Sampling Reveals Personalized Diet-Microbiome Associations in Humans.

Diet is a key determinant of human gut microbiome variation. However, the fine-scale relationships between daily food choices and human gut microbiome composition remain unexplored. Here, we used multivariate methods to integrate 24-h food records and fecal shotgun metagenomes from 34 healthy human subjects collected daily over 17 days. Microbiome composition depended on multiple days of dietary history and was more strongly associated with food choices than with conventional nutrient profiles, and daily microbial responses to diet were highly personalized. Data from two subjects consuming only meal replacement beverages suggest that a monotonous diet does not induce microbiome stability in humans, and instead, overall dietary diversity associates with microbiome stability. Our work provides key methodological insights for future diet-microbiome studies and suggests that food-based interventions seeking to modulate the gut microbiota may need to be tailored to the individual microbiome. Trial Registration: ClinicalTrials.gov: NCT03610477.

Bacterial community structure and function distinguish gut sites in captive red-shanked doucs (Pygathrix nemaeus).

The mammalian order primates contains wide species diversity. Members of the subfamily Colobinae are unique amongst extant primates in that their gastrointestinal systems more closely resemble those of ruminants than other members of the primate order. In the growing literature surrounding nonhuman primate microbiomes, analysis of microbial communities has been limited to the hindgut, since few studies have captured data on other gut sites, including the foregut of colobine primates. In this study, we used the red-shanked douc (Pygathrix nemaeus) as a model for colobine primates to study the relationship between gastrointestinal bacterial community structure and gut site within and between subjects. We analyzed fecal and pregastric stomach content samples, representative of the hindgut and foregut respectively, using 16S recombinant DNA (rDNA) sequencing and identified microbiota using closed-reference operational taxonomic unit (OTU) picking against the GreenGenes database. Our results show divergent bacterial communities clearly distinguish the foregut and hindgut microbiomes. We found higher bacterial biodiversity and a higher Firmicutes:Bacteroides ratio in the hindgut as opposed to the foregut. These gut sites showed strong associations with bacterial function. Specifically, energy metabolism was upregulated in the hindgut, whereas detoxification was increased in the foregut. Our results suggest a red-shanked douc's foregut microbiome is no more concordant with its own hindgut than it is with any other red-shanked douc's hindgut microbiome, thus reinforcing the notion that the bacterial communities of the foregut and hindgut are distinctly unique. OPEN PRACTICES: This article has been awarded Open Materials and Open Data badges. All materials and data are publicly accessible via the IRIS Repository at https://www.iris-database.org/iris/app/home/detail?id=york:934328. Learn more about the Open Practices badges from the Center for Open Science: https://osf.io/tvyxz/wiki.

Distribution of Bacterial α1,3-Galactosyltransferase Genes in the Human Gut Microbiome.

Because of a loss-of-function mutation in the GGTA1 gene, humans are unable to synthetize α1,3-Galactose (Gal) decorated glycans and develop high levels of circulating anti-α1,3-Galactose antibodies (anti-Gal Abs). Anti-Gal Abs have been identified as a major obstacle of organ xenotransplantation and play a role in several host-pathogen relationships including potential susceptibility to infection. Anti-Gal Abs are supposed to stem from immunization against the gut microbiota, an assumption derived from the observation that some pathogens display α1,3-Gal and that antibiotic treatment decreases the level of anti-Gal. However, there is little information to date concerning the microorganisms producing α1,3-Gal in the human gut microbiome. Here, available α1,3-Galactosyltransferase (GT) gene sequences from gut bacteria were selectively quantified for the first time in the gut microbiome shotgun sequences of 163 adult individuals from three published population-based metagenomics analyses. We showed that most of the gut microbiome of adult individuals contained a small set of bacteria bearing α1,3-GT genes. These bacteria belong mainly to the Enterobacteriaceae family, including Escherichia coli, but also to Pasteurellaceae genera, Haemophilus influenza and Lactobacillus species. α1,3-Gal antigens and α1,3-GT activity were detected in healthy stools of individuals exhibiting α1,3-GT bacterial gene sequences in their shotgun data.

US Immigration Westernizes the Human Gut Microbiome.

Many US immigrant populations develop metabolic diseases post immigration, but the causes are not well understood. Although the microbiome plays a role in metabolic disease, there have been no studies measuring the effects of US immigration on the gut microbiome. We collected stool, dietary recalls, and anthropometrics from 514 Hmong and Karen individuals living in Thailand and the United States, including first- and second-generation immigrants and 19 Karen individuals sampled before and after immigration, as well as from 36 US-born European American individuals. Using 16S and deep shotgun metagenomic DNA sequencing, we found that migration from a non-Western country to the United States is associated with immediate loss of gut microbiome diversity and function in which US-associated strains and functions displace native strains and functions. These effects increase with duration of US residence and are compounded by obesity and across generations.

Evaluating the Information Content of Shallow Shotgun Metagenomics.

Although microbial communities are associated with human, environmental, plant, and animal health, there exists no cost-effective method for precisely characterizing species and genes in such communities. While deep whole-metagenome shotgun (WMS) sequencing provides high taxonomic and functional resolution, it is often prohibitively expensive for large-scale studies. The prevailing alternative, 16S rRNA gene amplicon (16S) sequencing, often does not resolve taxonomy past the genus level and provides only moderately accurate predictions of the functional profile; thus, there is currently no widely accepted approach to affordable, high-resolution, taxonomic, and functional microbiome analysis. To address this technology gap, we evaluated the information content of shallow shotgun sequencing with as low as 0.5 million sequences per sample as an alternative to 16S sequencing for large human microbiome studies. We describe a library preparation protocol enabling shallow shotgun sequencing at approximately the same per-sample cost as 16S sequencing. We analyzed multiple real and simulated biological data sets, including two novel human stool samples with ultradeep sequencing of 2.5 billion sequences per sample, and found that shallow shotgun sequencing recovers more-accurate species-level taxonomic and functional profiles of the human microbiome than 16S sequencing. We discuss the inherent limitations of shallow shotgun sequencing and note that 16S sequencing remains a valuable and important method for taxonomic profiling of novel environments. Although deep WMS sequencing remains the gold standard for high-resolution microbiome analysis, we recommend that researchers consider shallow shotgun sequencing as a useful alternative to 16S sequencing for large-scale human microbiome research studies where WMS sequencing may be cost-prohibitive. IMPORTANCE A common refrain in recent microbiome-related academic meetings is that the field needs to move away from broad taxonomic surveys using 16S sequencing and toward more powerful longitudinal studies using shotgun sequencing. However, performing deep shotgun sequencing in large longitudinal studies remains prohibitively expensive for all but the most well-funded research labs and consortia, which leads many researchers to choose 16S sequencing for large studies, followed by deep shotgun sequencing on a subset of targeted samples. Here, we show that shallow- or moderate-depth shotgun sequencing may be used by researchers to obtain species-level taxonomic and functional data at approximately the same cost as amplicon sequencing. While shallow shotgun sequencing is not intended to replace deep shotgun sequencing for strain-level characterization, we recommend that microbiome scientists consider using shallow shotgun sequencing instead of 16S sequencing for large-scale human microbiome studies.

High-Throughput flaA Short Variable Region Sequencing to Assess Campylobacter Diversity in Fecal Samples From Birds.

Current approach to identify sources of human pathogens is largely dependent on the cultivation and isolation of target bacteria. For rapid pathogen source identification, culture-independent strain typing method is necessary. In this study, we designed new primer set that broadly covers flaA short variable region (SVR) of various Campylobacter species, and applied the flaA SVR sequencing method to examine the diversity of Campylobacter spp. in geese fecal samples (n = 16) with and without bacteria cultivation. Twenty-three Campylobacter strains isolated from the 16 geese fecal samples were grouped similarly by conventional flaA restriction fragment length polymorphism (RFLP) method and by the flaA SVR sequencing method, but higher discriminant power was observed in the flaA SVR sequencing approach. For culture-independent flaA SVR sequencing analysis, we developed and optimized the sequence data analysis pipeline to identify as many genotypes as possible, while minimizing the detection of genotypes generated by sequencing errors. By using this pipeline, 51,629 high-quality flaA sequence reads were clustered into 16 operational taxonomic units (=genotypes) by using 98% sequence similarity and >50 sequence duplicates. Almost all flaA genotypes obtained by culture-dependent method were also identified by culture-independent flaA SVR MiSeq sequencing method. In addition, more flaA genotypes were identified probably due to high throughput nature of the MiSeq sequencing. These results suggest that the flaA SVR sequencing could be used to analyze the diversity of Campylobacter spp. without bacteria isolation. This method is promising to rapidly identify potential sources of Campylobacter pathogens.

Urinary microbiome associated with chronic allograft dysfunction in kidney transplant recipients.

BACKGROUND: We performed a study to identify differences in the urinary microbiome associated with chronic allograft dysfunction (CAD) and compared the urinary microbiome of male and female transplant recipients with CAD. METHODS: This case-control study enrolled 67 patients within the Deterioration of Kidney Allograft Function (DeKAF) Genomics cohort at two transplant centers. CAD was defined as a greater than 25% rise in serum creatinine relative to a 3 month post-transplant baseline. Urine samples from patients with and without CAD were analyzed using 16S V4 bacterial ribosomal DNA sequences. RESULTS: Corynebacterium was more prevalent in female and male patients with CAD compared to non-CAD female patients (P = 0.0005). A total 21 distinct Operational Taxonomic Unit (OTUs) were identified as significantly different when comparing CAD and non-CAD patients using Kruskal-Wallis (P < 0.01). A subset analysis of female patients with CAD compared to non-CAD females identified similar differentially abundant OTUs, including the genera Corynebacterium and Staphylococcus (Kruskal-Wallis; P = 0.01; P = 0.004, respectively). Male CAD vs female CAD analysis showed greater abundance of phylum Proteobacteria in males. CONCLUSION: There were differences in the urinary microbiome when comparing female and male CAD patients with their female non-CAD counterparts and these differences persisted in the subset analysis limited to female patients only.

CLOUD: a non-parametric detection test for microbiome outliers.

BACKGROUND: Dysbiosis of the human gut microbiome is defined as a maladaptive or clinically relevant deviation of the community profile from the healthy or normal state. Dysbiosis has been implicated in an extensive set of metabolic, auto-immune, and infectious diseases, and yet there is substantial inter-individual variation in microbiome composition even within body sites of healthy humans. An individual's microbiome varies over time in a high-dimensional space to form their personal microbiome cloud. This cloud may or may not be similar to that of other people, both in terms of the average microbiome profile (conformity) and the diameter of the cloud (stability). However, there is currently no robust non-parametric test that determines whether a patient's microbiome cloud is an outlier with respect to a reference group of healthy individuals with widely varying microbiome profiles. METHODS: Here, we propose a test for outliers' detection in the human gut microbiome that accounts for the wide range of microbiome phenotypes observed in a typical set of healthy individuals and for intra-individual temporal variation. Our robust nonparametric outlier detection test, the CLOUD test, performs two assessments of a patient's microbiome health: conformity, the extent to which the patient's microbiome cloud is ecologically similar to a subset of healthy subjects; and stability, which compares the cloud diameter of a patient to those of healthy subjects. The CLOUD test is based on locally linear embedded ecological distances, allowing it to account for widely varying microbiome compositions among reference individuals. It also leverages temporal variability within patients and reference individuals to increase the robustness of the test. RESULTS: We describe the CLOUD test, and we apply it to one novel and two previously published cohorts of patients receiving fecal microbiota transplantation for recurrent Clostridium difficile colitis, as well as to two known healthy cohorts, demonstrating high concordance of the CLOUD conformity and stability indices with clinical outcomes. CONCLUSIONS: Although the CLOUD test is not, on its own, a test for clinical dysbiosis, it nonetheless provides a framework for outlier testing that could be incorporated into evaluation of suspected dysbiosis, which may play a role in diagnosis and prognosis of numerous pediatric and adult diseases.

Antibiotic-induced acceleration of type 1 diabetes alters maturation of innate intestinal immunity.

The early-life intestinal microbiota plays a key role in shaping host immune system development. We found that a single early-life antibiotic course (1PAT) accelerated type 1 diabetes (T1D) development in male NOD mice. The single course had deep and persistent effects on the intestinal microbiome, leading to altered cecal, hepatic, and serum metabolites. The exposure elicited sex-specific effects on chromatin states in the ileum and liver and perturbed ileal gene expression, altering normal maturational patterns. The global signature changes included specific genes controlling both innate and adaptive immunity. Microbiome analysis revealed four taxa each that potentially protect against or accelerate T1D onset, that were linked in a network model to specific differences in ileal gene expression. This simplified animal model reveals multiple potential pathways to understand pathogenesis by which early-life gut microbiome perturbations alter a global suite of intestinal responses, contributing to the accelerated and enhanced T1D development.

Associations Between Nutrition, Gut Microbiome, and Health in A Novel Nonhuman Primate Model.

Red-shanked doucs (Pygathrix nemaeus) are endangered, foregut-fermenting colobine primates which are difficult to maintain in captivity. There are critical gaps in our understanding of their natural lifestyle, including dietary habits such as consumption of leaves, unripe fruit, flowers, seeds, and other plant parts. There is also a lack of understanding of enteric adaptations, including their unique microflora. To address these knowledge gaps, we used the douc as a model to study relationships between gastrointestinal microbial community structure and lifestyle. We analyzed published fecal samples as well as detailed dietary history from doucs with four distinct lifestyles (wild, semi-wild, semi-captive, and captive) and determined gastrointestinal bacterial microbiome composition using 16S rRNA sequencing. A clear gradient of microbiome composition was revealed along an axis of natural lifestyle disruption, including significant associations with diet, biodiversity, and microbial function. We also identified potential microbial biomarkers of douc dysbiosis, including Bacteroides and Prevotella, which may be related to health. Our results suggest a gradient-like shift in captivity causes an attendant shift to severe gut dysbiosis, thereby resulting in gastrointestinal issues.

SHI7 Is a Self-Learning Pipeline for Multipurpose Short-Read DNA Quality Control.

Next-generation sequencing technology is of great importance for many biological disciplines; however, due to technical and biological limitations, the short DNA sequences produced by modern sequencers require numerous quality control (QC) measures to reduce errors, remove technical contaminants, or merge paired-end reads together into longer or higher-quality contigs. Many tools for each step exist, but choosing the appropriate methods and usage parameters can be challenging because the parameterization of each step depends on the particularities of the sequencing technology used, the type of samples being analyzed, and the stochasticity of the instrumentation and sample preparation. Furthermore, end users may not know all of the relevant information about how their data were generated, such as the expected overlap for paired-end sequences or type of adaptors used to make informed choices. This increasing complexity and nuance demand a pipeline that combines existing steps together in a user-friendly way and, when possible, learns reasonable quality parameters from the data automatically. We propose a user-friendly quality control pipeline called SHI7 (canonically pronounced "shizen"), which aims to simplify quality control of short-read data for the end user by predicting presence and/or type of common sequencing adaptors, what quality scores to trim, whether the data set is shotgun or amplicon sequencing, whether reads are paired end or single end, and whether pairs are stitchable, including the expected amount of pair overlap. We hope that SHI7 will make it easier for all researchers, expert and novice alike, to follow reasonable practices for short-read data quality control. IMPORTANCE Quality control of high-throughput DNA sequencing data is an important but sometimes laborious task requiring background knowledge of the sequencing protocol used (such as adaptor type, sequencing technology, insert size/stitchability, paired-endedness, etc.). Quality control protocols typically require applying this background knowledge to selecting and executing numerous quality control steps with the appropriate parameters, which is especially difficult when working with public data or data from collaborators who use different protocols. We have created a streamlined quality control pipeline intended to substantially simplify the process of DNA quality control from raw machine output files to actionable sequence data. In contrast to other methods, our proposed pipeline is easy to install and use and attempts to learn the necessary parameters from the data automatically with a single command.

Pretransplant Gut Colonization with Intrinsically Vancomycin-Resistant Enterococci (E. gallinarum and E. casseliflavus) and Outcomes of Allogeneic Hematopoietic Cell Transplantation.

Pretransplant gut colonization with intrinsically vancomycin-resistant enterococci (iVRE) (Enterococcus gallinarum and Enterococcus casseliflavus) is uncommon and with unknown clinical impact. In a matched-pairs analysis of patients with versus without iVRE colonization (n = 18 in each group), we demonstrated significantly higher 2-year overall survival (86% [95% confidence interval, 52% to 96%] versus 35% [95% confidence interval, 8% to 65]; P <.01) and lower nonrelapse mortality (P <.01) among colonized patients. Putative metabolomes differentiated iVRE from E. faecalis/faecium and may contribute to a healthier gut microbiome in iVRE-colonized patients.