Industrialized human gut microbiota increases CD8+ T cells and mucus thickness in humanized mouse gut

Immigration to a highly industrialized nation has been associated with metabolic disease and simultaneous shifts in microbiota composition, but the underlying mechanisms are challenging to test in human studies. Here, we conducted a pilot study to assess the differential effects of human gut microbiota collected from the United States (US) and rural Thailand on the murine gut mucosa and immune system. Colonization of germ-free mice with microbiota from US individuals resulted in an increased accumulation of innate-like CD8 T cells in the small intestine lamina propria and intra-epithelial compartments when compared to colonization with microbiota from Thai individuals. Both TCRγδ and CD8αα T cells showed a marked increase in mice receiving Western microbiota and, interestingly, this phenotype was also associated with an increase in intestinal mucus thickness. Serendipitously, an accidentally infected group of mice corroborated this association between elevated inflammatory response and increased mucus thickness. These results suggest that Western-associated human gut microbes contribute to a pro-inflammatory immune response.

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.

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.

US Immigration Is Associated With Rapid and Persistent Acquisition of Antibiotic Resistance Genes in the Gut

Little is known about the effect of human migration on gut microbiome antibiotic resistance gene (ARG) carriage. Using deep shotgun stool metagenomics analysis, we found a rapid increase in gut microbiome ARG richness and abundance in women from 2 independent ethnic groups relocating from Thailand to the United States.

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.

Dietary Patterns Correspond with Microbiome Composition (FS07-02-19)

Objectives

Previous studies have defined dietary patterns for comparison with microbiome features using factor analysis from food frequency questionnaires. In this study, we applied a new tree-based method to directly define dietary patterns from 24-hour food records. We aimed to determine if these patterns corresponded with microbial features.

Methods

Daily fecal samples and daily 24-hour food records (ASA24–2016) were collected from 32 healthy adults over 17 days. Dietary patterns were derived using all reported foods for each subject. Foods were arranged into a tree structure using USDA food groups. Tree-based weighted Unifrac food distances (QIIME 1.9.1) were used for principal coordinate analysis to define five dietary patterns. Each pattern was named after its most influential food groups. Average microbiome composition was determined from metagenomic sequencing. Dietary patterns were compared with subjects’ average microbiome composition using correlation analysis. Spearman correlations were corrected for multiple comparisons within each taxonomy level. Constrained redundancy analysis (RDA) was used to determine the explanatory power of dietary patterns.

Results

Four of the five most discriminatory dietary patterns (DPs) were associated with microbial taxa (A). DP1 was positively correlated with an unclassified family in the order Burkholderiales and negatively correlated with the species Lachnospiraceae bacterium TF01–11. DP3, DP4, DP5 were most representative of a western diet. DP3 was negatively correlated with family Pasteurellaceae. DP4 was positively correlated with family Erysipelotrichaceae and negatively correlated with family Sutterellaceae. DP5 was positively correlated with members of class Bacteroidia including two specific Bacteroides speciesHMSC073E02 and HMSC067B03. Constrained RDA using the five dietary patterns revealed a gradient of Phylum Bacteroidetes along an axis driven by DP3, DP4, and DP5 (B).

Conclusions

The dietary patterns derived using our tree-based method reveal relationships between diet microbial taxa. In agreement with previous studies, our tree-based patterns show that the western diet corresponds to increased Bacteroidetes, demonstrating the utility of this method.

Funding Sources

Funding for this study was provided by General Mills.

Supporting Tables, Images and/or Graphs

Microbiome Learning Repo (ML Repo): A public repository of microbiome regression and classification tasks

The use of machine learning in high-dimensional biological applications, such as the human microbiome, has grown exponentially in recent years, but algorithm developers often lack the domain expertise required for interpretation and curation of the heterogeneous microbiome datasets. We present Microbiome Learning Repo (ML Repo, available at https://knights-lab.github.io/MLRepo/), a public, web-based repository of 33 curated classification and regression tasks from 15 published human microbiome datasets. We highlight the use of ML Repo in several use cases to demonstrate its wide application, and we expect it to be an important resource for algorithm developers.

Fecal concentrations of bacterially derived vitamin K forms are associated with gut microbiota composition but not plasma or fecal cytokine concentrations in healthy adults

Background: Emerging evidence suggests novel roles for bacterially derived vitamin K forms known as menaquinones in health and disease, which may be attributable in part to anti-inflammatory effects. However, the relevance of menaquinones produced by gut bacteria to vitamin K requirements and inflammation is undetermined.Objective: This study aimed to quantify fecal menaquinone concentrations and identify associations between fecal menaquinone concentrations and serum vitamin K concentrations, gut microbiota composition, and inflammation.Design: Fecal and serum menaquinone concentrations, fecal microbiota composition, and plasma and fecal cytokine concentrations were measured in 80 men and postmenopausal women (48 men, 32 women, age 40-65 y) enrolled in a randomized, parallel-arm, provided-food trial. After consuming a run-in diet for 2 wk, participants were randomly assigned to consume a whole grain-rich (WG) or a refined grain-based (RG) diet for 6 wk. Outcomes were measured at weeks 2 and 8.Results: The median total daily excretion of menaquinones in feces was 850 nmol/d but was highly variable (range: 64-5358 nmol/d). The total median (IQR) fecal concentrations of menaquinones decreased in the WG diet compared with the RG diet [-6.8 nmol/g (13.0 nmol/g) dry weight for WG compared with 1.8 nmol/g (12.3 nmol/g) dry weight for RG; P < 0.01)]. However, interindividual variability in fecal menaquinone concentrations partitioned individuals into 2 distinct groups based on interindividual differences in concentrations of different menaquinone forms rather than the diet group or the time point. The relative abundances of several gut bacteria taxa, Bacteroides and Prevotella in particular, differed between these groups, and 42% of identified genera were associated with ≥1 menaquinone form. Menaquinones were not detected in serum, and neither fecal concentrations of individual menaquinones nor the menaquinone group was associated with any marker of inflammation.Conclusion: Menaquinone concentrations in the human gut appear highly variable and are associated with gut microbiota composition. However, the health implications remain unclear. This trial was registered at clinicaltrials.gov as NCT01902394.

Substituting whole grains for refined grains in a 6-wk randomized trial favorably affects energy-balance metrics in healthy men and postmenopausal women

Background: The effect of whole grains on the regulation of energy balance remains controversial.Objective: We aimed to determine the effects of substituting whole grains for refined grains, independent of body weight changes, on energy-metabolism metrics and glycemic control.Design: The study was a randomized, controlled, parallel-arm controlled-feeding trial that was conducted in 81 men and postmenopausal women [49 men and 32 women; age range: 40-65 y; body mass index (in kg/m²): <35.0]. After a 2-wk run-in period, participants were randomly assigned to consume 1 of 2 weight-maintenance diets for 6 wk. Diets differed in whole-grain and fiber contents [mean ± SDs: whole grain-rich diet: 207 ± 39 g whole grains plus 40 ± 5 g dietary fiber/d; refined grain-based diet: 0 g whole grains plus 21 ± 3 g dietary fiber/d] but were otherwise similar. Energy metabolism and body-composition metrics, appetite, markers of glycemic control, and gut microbiota were measured at 2 and 8 wk.Results: By design, body weight was maintained in both groups. Plasma alkylresorcinols, which are biomarkers of whole-grain intake, increased in the whole grain-rich diet group (WG) but not in the refined grain-based diet group (RG) (P-diet-by-time interaction < 0.0001). Beta ± SE changes (ΔWG compared with ΔRG) in the resting metabolic rate (RMR) (43 ± 25 kcal/d; P = 0.04), stool weight (76 ± 12 g/d; P < 0.0001), and stool energy content (57 ± 17 kcal/d; P = 0.003), but not in stool energy density, were higher in the WG. When combined, the favorable energetic effects in the WG translated into a 92-kcal/d (95% CI: 28, 156-kcal/d) higher net daily energy loss compared with that of the RG (P = 0.005). Prospective consumption (P = 0.07) and glycemia after an oral-glucose-tolerance test (P = 0.10) trended toward being lower in the WG than in the RG. When nonadherent participants were excluded, between-group differences in stool energy content and glucose tolerance increased, and between-group differences in the RMR and prospective consumption were not statistically significant.Conclusion: These findings suggest positive effects of whole grains on the RMR and stool energy excretion that favorably influence energy balance and may help explain epidemiologic associations between whole-grain consumption and reduced body weight and adiposity. This trial was registered at clinicaltrials.gov as NCT01902394.

Substituting whole grains for refined grains in a 6-wk randomized trial has a modest effect on gut microbiota and immune and inflammatory markers of healthy adults

Background: Observational studies suggest an inverse association between whole-grain (WG) consumption and inflammation. However, evidence from interventional studies is limited, and few studies have included measurements of cell-mediated immunity.Objective: We assessed the effects of diets rich in WGs compared with refined grains (RGs) on immune and inflammatory responses, gut microbiota, and microbial products in healthy adults while maintaining subject body weights.Design: After a 2-wk provided-food run-in period of consuming a Western-style diet, 49 men and 32 postmenopausal women [age range: 40-65 y, body mass index (in kg/m2) <35] were assigned to consume 1 of 2 provided-food weight-maintenance diets for 6 wk.Results: Compared with the RG group, the WG group had increased plasma total alkyresorcinols (a measure of WG intake) (P < 0.0001), stool weight (P < 0.0001), stool frequency (P = 0.02), and short-chain fatty acid (SCFA) producer Lachnospira [false-discovery rate (FDR)-corrected P = 0.25] but decreased pro-inflammatory Enterobacteriaceae (FDR-corrected P = 0.25). Changes in stool acetate (P = 0.02) and total SCFAs (P = 0.05) were higher in the WG group than in the RG group. A positive association was shown between Lachnospira and acetate (FDR-corrected P = 0.002) or butyrate (FDR-corrected P = 0.005). We also showed that there was a higher percentage of terminal effector memory T cells (P = 0.03) and LPS-stimulated ex vivo production of tumor necrosis factor-α (P = 0.04) in the WG group than in the RG group, which were positively associated with plasma alkylresorcinol concentrations.Conclusion: The short-term consumption of WGs in a weight-maintenance diet increases stool weight and frequency and has modest positive effects on gut microbiota, SCFAs, effector memory T cells, and the acute innate immune response and no effect on other markers of cell-mediated immunity or systemic and gut inflammation. This trial was registered at clinicaltrials.gov as NCT01902394.

Antibiotic-mediated gut microbiome perturbation accelerates development of type 1 diabetes in mice

The early life microbiome plays important roles in host immunological and metabolic development. Because the incidence of type 1 diabetes (T1D) has been increasing substantially in recent decades, we hypothesized that early-life antibiotic use alters gut microbiota, which predisposes to disease. Using non-obese diabetic mice that are genetically susceptible to T1D, we examined the effects of exposure to either continuous low-dose antibiotics or pulsed therapeutic antibiotics (PAT) early in life, mimicking childhood exposures. We found that in mice receiving PAT, T1D incidence was significantly higher, and microbial community composition and structure differed compared with controls. In pre-diabetic male PAT mice, the intestinal lamina propria had lower Th17 and Treg proportions and intestinal SAA expression than in controls, suggesting key roles in transducing the altered microbiota signals. PAT affected microbial lipid metabolism and host cholesterol biosynthetic gene expression. These findings show that early-life antibiotic treatments alter the gut microbiota and its metabolic capacities, intestinal gene expression and T-cell populations, accelerating T1D onset in non-obese diabetic mice.

Antibiotics, pediatric dysbiosis, and disease

Antibiotics are by far the most common medications prescribed for children. Recent epidemiological data suggests an association between early antibiotic use and disease phenotypes in adulthood. Antibiotic use during infancy induces imbalances in gut microbiota, called dysbiosis. The gut microbiome's responses to antibiotics and its potential link to disease development are especially complex to study in the changing infant gut. Here, we synthesize current knowledge linking antibiotics, dysbiosis, and disease and propose a framework for studying antibiotic-related dysbiosis in children. We recommend future studies into the microbiome-mediated effects of antibiotics focused on four types of dysbiosis: loss of keystone taxa, loss of diversity, shifts in metabolic capacity, and blooms of pathogens. Establishment of a large and diverse baseline cohort to define healthy infant microbiome development is essential to advancing diagnosis, interpretation, and eventual treatment of pediatric dysbiosis. This approach will also help provide evidence-based recommendations for antibiotic usage in infancy.

Chemotherapy-driven dysbiosis in the intestinal microbiome

BACKGROUND

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

AIM

To identify functional mechanisms by which the intestinal microbiome may play a key role in the pathophysiology of GI mucositis, we applied high-throughput DNA-sequencing analysis to identify microbes and microbial functions that are modulated following chemotherapy.

METHODS

We amplified and sequenced 16S rRNA genes from faecal samples before and after chemotherapy in 28 patients with non-Hodgkin's lymphoma who received the same myeloablative conditioning regimen and no other concomitant therapy such as antibiotics.

RESULTS

We found that faecal samples collected after chemotherapy exhibited significant decreases in abundances of Firmicutes (P = 0.0002) and Actinobacteria (P = 0.002) and significant increases in abundances of Proteobacteria (P = 0.0002) compared to samples collected before chemotherapy. Following chemotherapy, patients had reduced capacity for nucleotide metabolism (P = 0.0001), energy metabolism (P = 0.001), metabolism of cofactors and vitamins (P = 0.006), and increased capacity for glycan metabolism (P = 0.0002), signal transduction (P = 0.0002) and xenobiotics biodegradation (P = 0.002).

CONCLUSIONS

Our study identifies a severe compositional and functional imbalance in the gut microbial community associated with chemotherapy-induced GI mucositis. The functional pathways implicated in our analysis suggest potential directions for the development of intestinal microbiome-targeted interventions in cancer patients.

The guts of obesity: progress and challenges in linking gut microbes to obesity

The sharp rise in prevalence of obesity in recent decades has been suggestively labeled as an "epidemic," and the lack of fully explanatory causal factors has challenged existing understandings of obesity's etiology from a purely energetic standpoint. Much recent attention has been focused on the microbial members of the human gut for insights into their role in potentially causing or promoting obesity. The human gut is home to trillions of microbes, among which hundreds of distinct species of bacteria interact to form the human gut microbiome, and numerous studies in humans and animal models have linked shifts in the gut microbiome to obesity. In this review we explore contemporary understandings of the relationship between obesity and the microbiome from a high-level ecological and functional perspective, along with a survey of recently proposed interventions. We highlight areas of consensus and areas for further study in the field.

Complex host genetics influence the microbiome in inflammatory bowel disease

BACKGROUND

Human genetics and host-associated microbial communities have been associated independently with a wide range of chronic diseases. One of the strongest associations in each case is inflammatory bowel disease (IBD), but disease risk cannot be explained fully by either factor individually. Recent findings point to interactions between host genetics and microbial exposures as important contributors to disease risk in IBD. These include evidence of the partial heritability of the gut microbiota and the conferral of gut mucosal inflammation by microbiome transplant even when the dysbiosis was initially genetically derived. Although there have been several tests for association of individual genetic loci with bacterial taxa, there has been no direct comparison of complex genome-microbiome associations in large cohorts of patients with an immunity-related disease.

METHODS

We obtained 16S ribosomal RNA (rRNA) gene sequences from intestinal biopsies as well as host genotype via Immunochip in three independent cohorts totaling 474 individuals. We tested for correlation between relative abundance of bacterial taxa and number of minor alleles at known IBD risk loci, including fine mapping of multiple risk alleles in the Nucleotide-binding oligomerization domain-containing protein 2 (NOD2) gene exon. We identified host polymorphisms whose associations with bacterial taxa were conserved across two or more cohorts, and we tested related genes for enrichment of host functional pathways.

RESULTS

We identified and confirmed in two cohorts a significant association between NOD2 risk allele count and increased relative abundance of Enterobacteriaceae, with directionality of the effect conserved in the third cohort. Forty-eight additional IBD-related SNPs have directionality of their associations with bacterial taxa significantly conserved across two or three cohorts, implicating genes enriched for regulation of innate immune response, the JAK-STAT cascade, and other immunity-related pathways.

CONCLUSIONS

These results suggest complex interactions between genetically altered host functional pathways and the structure of the microbiome. Our findings demonstrate the ability to uncover novel associations from paired genome-microbiome data, and they suggest a complex link between host genetics and microbial dysbiosis in subjects with IBD across independent cohorts.

Classification of Listeria monocytogenes persistence in retail delicatessen environments using expert elicitation and machine learning

Increasing evidence suggests that persistence of Listeria monocytogenes in food processing plants has been the underlying cause of a number of human listeriosis outbreaks. This study extracts criteria used by food safety experts in determining bacterial persistence in the environment, using retail delicatessen operations as a model. Using the Delphi method, we conducted an expert elicitation with 10 food safety experts from academia, industry, and government to classify L. monocytogenes persistence based on environmental sampling results collected over six months for 30 retail delicatessen stores. The results were modeled using variations of random forest, support vector machine, logistic regression, and linear regression; variable importance values of random forest and support vector machine models were consolidated to rank important variables in the experts' classifications. The duration of subtype isolation ranked most important across all expert categories. Sampling site category also ranked high in importance and validation errors doubled when this covariate was removed. Support vector machine and random forest models successfully classified the data with average validation errors of 3.1% and 2.2% (n = 144), respectively. Our findings indicate that (i) the frequency of isolations over time and sampling site information are critical factors for experts determining subtype persistence, (ii) food safety experts from different sectors may not use the same criteria in determining persistence, and (iii) machine learning models have potential for future use in environmental surveillance and risk management programs. Future work is necessary to validate the accuracy of expert and machine classification against biological measurement of L. monocytogenes persistence.

Refinement of the Listeria monocytogenes σB regulon through quantitative proteomic analysis

σ(B) is an alternative σ factor that regulates stress response and virulence genes in the foodborne pathogen Listeria monocytogenes. To gain further insight into σ(B)-dependent regulatory mechanisms in L. monocytogenes, we (i) performed quantitative proteomic comparisons between the L. monocytogenes parent strain 10403S and an isogenic ΔsigB mutant and (ii) conducted a meta-analysis of published microarray studies on the 10403S σ(B) regulon. A total of 134 genes were found to be significantly positively regulated by σ(B) at the transcriptomic level with >75 % of these genes preceded by putative σ(B)-dependent promoters; 21 of these 134 genes were also found to be positively regulated by σ(B) through proteomics. In addition, 15 proteins were only found to be positively regulated by σ(B) through proteomics analyses, including Lmo1349, a putative glycine cleavage system protein. The lmo1349 gene is preceded by a 5' UTR that functions as a glycine riboswitch, which suggests regulation of glycine metabolism by σ(B) in L. monocytogenes. Herein, we propose a model where σ(B) upregulates pathways that facilitate biosynthesis and uptake of glycine, which may then activate this riboswitch. Our data also (i) identified a number of σ(B)-dependent proteins that appear to be encoded by genes that are co-regulated by multiple transcriptional regulators, in particular PrfA, and (ii) found σ(B)-dependent genes and proteins to be overrepresented in the 'energy metabolism' role category, highlighting contributions of the σ(B) regulon to L. monocytogenes energy metabolism as well as a role of PrfA and σ(B) interaction in regulating aspects of energy metabolism in L. monocytogenes.

Food microbe tracker: a web-based tool for storage and comparison of food-associated microbes

Large amounts of molecular subtyping information are generated by the private sector, academia, and government agencies. However, use of subtype data is limited by a lack of effective data storage and sharing mechanisms that allow comparison of subtype data from multiple sources. Currently available subtype databases are generally limited in scope to a few data types (e.g., MLST. net) or are not publicly available (e.g., PulseNet). We describe the development and initial implementation of Food Microbe Tracker, a public Web-based database that allows archiving and exchange of a variety of molecular subtype data that can be cross-referenced with isolate source data, genetic data, and phenotypic characteristics. Data can be queried with a variety of search criteria, including DNA sequences and banding pattern data (e.g., ribotype or pulsed-field gel electrophoresis type). Food Microbe Tracker allows the deposition of data on any bacterial genus and species, bacteriophages, and other viruses. The bacterial genera and species that currently have the most entries in this database are Listeria monocytogenes, Salmonella, Streptococcus spp., Pseudomonas spp., Bacillus spp., and Paenibacillus spp., with over 40,000 isolates. The combination of pathogen and spoilage microorganism data in the database will facilitate source tracking and outbreak detection, improve discovery of emerging subtypes, and increase our understanding of transmission and ecology of these microbes. Continued addition of subtyping, genetic or phenotypic data for a variety of microbial species will broaden the database and facilitate large-scale studies on the diversity of food-associated microbes.