A metabolomic view of how the human gut microbiota impacts the host metabolome using humanized and gnotobiotic mice

Defining the functional status of host-associated microbial ecosystems has proven challenging owing to the vast number of predicted genes within the microbiome and relatively poor understanding of community dynamics and community–host interaction. Metabolomic approaches, in which a large number of small molecule metabolites can be defined in a biological sample, offer a promising avenue to ‘fingerprint'' microbiota functional status. Here, we examined the effects of the human gut microbiota on the fecal and urinary metabolome of a humanized (HUM) mouse using an optimized ultra performance liquid chromatography–mass spectrometry-based method. Differences between HUM and conventional mouse urine and fecal metabolomic profiles support host-specific aspects of the microbiota''s metabolomic contribution, consistent with distinct microbial compositions. Comparison of microbiota composition and metabolome of mice humanized with different human donors revealed that the vast majority of metabolomic features observed in donor samples are produced in the corresponding HUM mice, and individual-specific features suggest ‘personalized'' aspects of functionality can be reconstituted in mice. Feeding the mice a defined, custom diet resulted in modification of the metabolite signatures, illustrating that host diet provides an avenue for altering gut microbiota functionality, which in turn can be monitored via metabolomics. Using a defined model microbiota consisting of one or two species, we show that simplified communities can drive major changes in the host metabolomic profile. Our results demonstrate that metabolomics constitutes a powerful avenue for functional characterization of the intestinal microbiota and its interaction with the host.     

GC/MS-based metabolomic studies reveal key roles of glycine in regulating silk synthesis in silkworm,Bombyx mori

Metabolic profiling of silkworm, especially the factors that affect silk synthesis at the metabolic level, is little known. Herein, metabolomic method based on gas chromatography-mass spectrometry was applied to identify key metabolic changes in silk synthesis deficient silkworms. Forty-six differential metabolites were identified in Nd group with the defect of silk synthesis. Significant changes in the levels of glycine and uric acid (up-regulation), carbohydrates and free fatty acids (down-regulation) were observed. The further metabolomics of silk synthesis deficient silkworms by decreasing silk proteins synthesis using knocking out fibroin heavy chain gene or extirpating silk glands operation showed that the changes of the metabolites were almost consistent with those of the Nd group. Furthermore, the increased silk yields by supplying more glycine or its related metabolite confirmed that glycine is a key metabolite to regulate silk synthesis. These findings provide important insights into the regulation between metabolic profiling and silk synthesis.     

An interaction effect between glucokinase gene variation and carbohydrate intakes modulates the plasma triglyceride response to a fish oil supplementation

A large inter-individual variability in the plasma triglyceride (TG) response to fish oil consumption has been observed. The objective was to investigate the gene–diet interaction effects between single-nucleotide polymorphisms (SNPs) within glucokinase (GCK) gene and dietary carbohydrate intakes (CHO) on the plasma TG response to a fish oil supplementation. Two hundred and eight participants were recruited in the greater Quebec City area. The participants completed a 6-week fish oil supplementation (5 g fish oil/day: 1.9–2.2 g EPA and 1.1 g DHA). Thirteen SNPs within GCK gene were genotyped using TAQMAN methodology. A gene–diet interaction effect on the plasma TG response was observed with rs741038 and CHO adjusted for age, sex and BMI (p = 0.008). In order to compare the plasma TG response between genotypes according to CHO, participants were divided according to median CHO. Homozygotes of the minor C allele of rs741038 with high CHO >48.59 % had a greater decrease in their plasma TG concentrations following the intake of fish oil (p < 0.05) than C/C homozygotes with low CHO and also than the other genotypes either with high or low CHO. The plasma TG response to a fish oil supplementation may be modulated by gene–diet interaction effects involving GCK gene and CHO.

Electronic supplementary material

The online version of this article (doi:10.1007/s12263-014-0395-5) contains supplementary material, which is available to authorized users.     

Identifying biochemical phenotypic differences between cryptic species

Molecular genetic methods can distinguish divergent evolutionary lineages in what previously appeared to be single species, but it is not always clear what functional differences exist between such cryptic species. We used a metabolomic approach to profile biochemical phenotype (metabotype) differences between two putative cryptic species of the earthworm Lumbricus rubellus. There were no straightforward metabolite biomarkers of lineage, i.e. no metabolites that were always at higher concentration in one lineage. Multivariate methods, however, identified a small number of metabolites that together helped distinguish the lineages, including uncommon metabolites such as Nε-trimethyllysine, which is not usually found at high concentrations. This approach could be useful for characterizing functional trait differences, especially as it is applicable to essentially any species group, irrespective of its genome sequencing status.     

Gene-Gene and Gene-Environment Interactions in Meta-Analysis of Genetic Association Studies

Extensive genetic studies have identified a large number of causal genetic variations in many human phenotypes; however, these could not completely explain heritability in complex diseases. Some researchers have proposed that the “missing heritability” may be attributable to gene–gene and gene–environment interactions. Because there are billions of potential interaction combinations, the statistical power of a single study is often ineffective in detecting these interactions. Meta-analysis is a common method of increasing detection power; however, accessing individual data could be difficult. This study presents a simple method that employs aggregated summary values from a “case” group to detect these specific interactions that based on rare disease and independence assumptions. However, these assumptions, particularly the rare disease assumption, may be violated in real situations; therefore, this study further investigated the robustness of our proposed method when it violates the assumptions. In conclusion, we observed that the rare disease assumption is relatively nonessential, whereas the independence assumption is an essential component. Because single nucleotide polymorphisms (SNPs) are often unrelated to environmental factors and SNPs on other chromosomes, researchers should use this method to investigate gene–gene and gene–environment interactions when they are unable to obtain detailed individual patient data.     

HSD3B and Gene-Gene Interactions in a Pathway-Based Analysis of Genetic Susceptibility to Bladder Cancer

Bladder cancer is the 4^th most common cancer among men in the U.S. We analyzed variant genotypes hypothesized to modify major biological processes involved in bladder carcinogenesis, including hormone regulation, apoptosis, DNA repair, immune surveillance, metabolism, proliferation, and telomere maintenance. Logistic regression was used to assess the relationship between genetic variation affecting these processes and susceptibility in 563 genotyped urothelial cell carcinoma cases and 863 controls enrolled in a case–control study of incident bladder cancer conducted in New Hampshire, U.S. We evaluated gene–gene interactions using Multifactor Dimensionality Reduction (MDR) and Statistical Epistasis Network analysis. The 3′UTR flanking variant form of the hormone regulation gene HSD3B2 was associated with increased bladder cancer risk in the New Hampshire population (adjusted OR 1.85 95%CI 1.31–2.62). This finding was successfully replicated in the Texas Bladder Cancer Study with 957 controls, 497 cases (adjusted OR 3.66 95%CI 1.06–12.63). The effect of this prevalent SNP was stronger among males (OR 2.13 95%CI 1.40–3.25) than females (OR 1.56 95%CI 0.83–2.95), (SNP-gender interaction P = 0.048). We also identified a SNP-SNP interaction between T-cell activation related genes GATA3 and CD81 (interaction P = 0.0003). The fact that bladder cancer incidence is 3–4 times higher in males suggests the involvement of hormone levels. This biologic process-based analysis suggests candidate susceptibility markers and supports the theory that disrupted hormone regulation plays a role in bladder carcinogenesis.     

Transcript-Based Cloning of RRP46, a Regulator of rRNA Processing and R Gene–Independent Cell Death in Barley–Powdery Mildew Interactions

Programmed cell death (PCD) plays a pivotal role in plant development and defense. To investigate the interaction between PCD and R gene–mediated defense, we used the 22K Barley1 GeneChip to compare and contrast time-course expression profiles of Blumeria graminis f. sp hordei (Bgh) challenged barley (Hordeum vulgare) cultivar C.I. 16151 (harboring the Mla6 powdery mildew resistance allele) and its fast neutron–derived Bgh-induced tip cell death1 mutant, bcd1. Mixed linear model analysis identified genes associated with the cell death phenotype as opposed to R gene–mediated resistance. One-hundred fifty genes were found at the threshold P value < 0.0001 and a false discovery rate <0.6%. Of these, 124 were constitutively overexpressed in the bcd1 mutant. Gene Ontology and rice (Oryza sativa) alignment-based annotation indicated that 68 of the 124 overexpressed genes encode ribosomal proteins. A deletion harboring six genes on chromosome 5H cosegregates with bcd1-specified cell death and is associated with misprocessing of rRNAs but segregates independent of R gene–mediated resistance. Barley stripe mosaic virus-induced gene silencing of one of the six deleted genes, RRP46 (rRNA-processing protein 46), phenocopied bcd1-mediated tip cell death. These findings suggest that RRP46, a critical component of the exosome core, mediates RNA processing and degradation involved in cell death initiation as a result of attempted penetration by Bgh during the barley–powdery mildew interaction but is independent of gene-for-gene resistance.     

Gene–Gene and Gene-Sex Epistatic Interactions of MiR146a,IRF5, IKZF1, ETS1 and IL21 in Systemic Lupus Erythematosus

Several confirmed genetic susceptibility loci involved in the interferon signaling and Th17/B cell response for SLE in Chinese Han populations have been described. Available data also indicate that sex-specific genetic differences contribute to SLE susceptibility. The aim of this study was to test for gene–gene/gene-sex epistasis (interactions) in these known lupus susceptibility loci. Six single-nucleotide polymorphisms (SNPs) in MiR146a, IRF5, IKZF1, ETS1 and IL21 were genotyped by Sequenom MassArray system. A total of 1,825 subjects (858 SLE patients and 967 controls) were included in the final analysis. Epistasis was tested by additive model, multiplicative model and multifactor dimensionality reduction (MDR) method. Additive interaction analysis revealed interactions between IRF5 and IKZF1 (OR 2.26, 95% CI 1.48–3.44 [P = 1.21×10⁴]). A similar tendency was also observed between IL21 and ETS1 by parametric methods. In addition, multiple high dimensional gene-gene or gene-sex interactions (three-and four-way) were identified by MDR analysis. Our study identified novel gene–gene/gene-sex interactions in lupus. Furthermore, these findings highlight sex, interferon pathway, and Th17/B cells as important contributors to the pathogenesis of SLE.     

Bile acids promote the caveolae-associated entry of swine acute diarrhea syndrome coronavirus in porcine intestinal enteroids

Intestinal microbial metabolites have been increasingly recognized as important regulators of enteric viral infection. However, very little information is available about which specific microbiota-derived metabolites are crucial for swine enteric coronavirus (SECoV) infection in vivo. Using swine acute diarrhea syndrome (SADS)-CoV as a model, we were able to identify a greatly altered bile acid (BA) profile in the small intestine of infected piglets by untargeted metabolomic analysis. Using a newly established ex vivo model–the stem cell-derived porcine intestinal enteroid (PIE) culture–we demonstrated that certain BAs, cholic acid (CA) in particular, enhance SADS-CoV replication by acting on PIEs at the early phase of infection. We ruled out the possibility that CA exerts an augmenting effect on viral replication through classic farnesoid X receptor or Takeda G protein-coupled receptor 5 signaling, innate immune suppression or viral attachment. BA induced multiple cellular responses including rapid changes in caveolae-mediated endocytosis, endosomal acidification and dynamics of the endosomal/lysosomal system that are critical for SADS-CoV replication. Thus, our findings shed light on how SECoVs exploit microbiome-derived metabolite BAs to swiftly establish viral infection and accelerate replication within the intestinal microenvironment.     

Targeted metabolomics profiles are strongly correlated with nutritional patterns in women

Nutrition plays an important role in human metabolism and health. Metabolomics is a promising tool for clinical, genetic and nutritional studies. A key question is to what extent metabolomic profiles reflect nutritional patterns in an epidemiological setting. We assessed the relationship between metabolomic profiles and nutritional intake in women from a large cross-sectional community study. Food frequency questionnaires (FFQs) were applied to 1,003 women from the TwinsUK cohort with targeted metabolomic analyses of serum samples using the Biocrates Absolute-IDQ? Kit p150 (163 metabolites). We analyzed seven nutritional parameters: coffee intake, garlic intake and nutritional scores derived from the FFQs summarizing fruit and vegetable intake, alcohol intake, meat intake, hypo-caloric dieting and a “traditional English” diet. We studied the correlation between metabolite levels and dietary intake patterns in the larger population and identified for each trait between 14 and 20 independent monozygotic twins pairs discordant for nutritional intake and replicated results in this set. Results from both analyses were then meta-analyzed. For the metabolites associated with nutritional patterns, we calculated heritability using structural equation modelling. 42 metabolite nutrient intake associations were statistically significant in the discovery samples (Bonferroni P < 4 × 10^?5) and 11 metabolite nutrient intake associations remained significant after validation. We found the strongest associations for fruit and vegetables intake and a glycerophospholipid (Phosphatidylcholine diacyl C38:6, P = 1.39 × 10^?9) and a sphingolipid (Sphingomyeline C26:1, P = 6.95 × 10^?13). We also found significant associations for coffee (confirming a previous association with C10 reported in an independent study), garlic intake and hypo-caloric dieting. Using the twin study design we find that two thirds the metabolites associated with nutritional patterns have a significant genetic contribution, and the remaining third are solely environmentally determined. Our data confirm the value of metabolomic studies for nutritional epidemiologic research.     

Mass appeal: metabolite identification in mass spectrometry-focused untargeted metabolomics

Metabolomics has advanced significantly in the past 10 years with important developments related to hardware, software and methodologies and an increasing complexity of applications. In discovery-based investigations, applying untargeted analytical methods, thousands of metabolites can be detected with no or limited prior knowledge of the metabolite composition of samples. In these cases, metabolite identification is required following data acquisition and processing. Currently, the process of metabolite identification in untargeted metabolomic studies is a significant bottleneck in deriving biological knowledge from metabolomic studies. In this review we highlight the different traditional and emerging tools and strategies applied to identify subsets of metabolites detected in untargeted metabolomic studies applying various mass spectrometry platforms. We indicate the workflows which are routinely applied and highlight the current limitations which need to be overcome to provide efficient, accurate and robust identification of metabolites in untargeted metabolomic studies. These workflows apply to the identification of metabolites, for which the structure can be assigned based on entries in databases, and for those which are not yet stored in databases and which require a de novo structure elucidation.

     

Metabolomic analysis reveals reliance on secondary plant metabolites to facilitate carnivory in the Cape sundew,Drosera capensis

Background and AimsSecondary metabolites are integral to multiple key plant processes (growth regulation, pollinator attraction and interactions with conspecifics, competitors and symbionts) yet their role in plant adaptation remains an underexplored area of research. Carnivorous plants use secondary metabolites to acquire nutrients from prey, but the extent of the role of secondary metabolites in plant carnivory is not known. We aimed to determine the extent of the role of secondary metabolites in facilitating carnivory of the Cape sundew, Drosera capensis.MethodsWe conducted metabolomic analysis of 72 plants in a time-series experiment before and after simulated prey capture. We used ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC–MS/MS) and the retention time index to identify compounds in the leaf trap tissue that changed up to 72 h following simulated prey capture. We identified associated metabolic pathways, and cross-compared these compounds with metabolites previously known to be involved in carnivorous plants across taxa.Key ResultsFor the first time in a carnivorous plant, we have profiled the whole-leaf metabolome response to prey capture. Reliance on secondary plant metabolites was higher than previously thought – 2383 out of 3257 compounds in fed leaves had statistically significant concentration changes in comparison with unfed controls. Of these, ~34 compounds are also associated with carnivory in other species; 11 are unique to Nepenthales. At least 20 compounds had 10-fold changes in concentration, 12 of which had 30-fold changes and are typically associated with defence or attraction in non-carnivorous plants.ConclusionsSecondary plant metabolites are utilized in plant carnivory to an extent greater than previously thought – we found a whole-metabolome response to prey capture. Plant carnivory, at the metabolic level, likely evolved from at least two distinct functions: attraction and defence. Findings of this study support the hypothesis that secondary metabolites play an important role in plant diversification and adaptation to new environments.