1H NMR based sulfonation reaction kinetics of wine relevant thiols in comparison with known carbonyls.

Sulfite addition is a common tool for ensuring wines' oxidative stability via the activity of its free and weakly bound molecular fraction. As a nucleophile, bisulfite forms covalent adducts with wine's most relevant electrophiles, such as carbonyls, polyphenols, and thiols. The equilibrium in these reactions is often represented as dissociation rather than formation. Recent studies from our laboratory demonstrate, first, the acetaldehyde sulfonate dissociation, and second, the chemical stability of cysteine and epicatechin sulfonates under wine aging conditions. Thus, the objective of this study was to monitor by 1H NMR the binding specificity of known carbonyl-derived SO2 binders (acetaldehyde and pyruvic acid) in the presence of S-containing compounds (cysteine and glutathione). We report that during simulated wine aging, the sulfur dioxide that is rapidly bound to carbonyl compounds will be released and will bind to cysteine and glutathione, demonstrating the long-term sulfur dioxide binding potential of S-containing compounds. These results are meant to serve as a complement to existing literature reviews focused on molecular markers related to wines' oxidative stability and emphasize once more the importance of S-containing compounds in wine aging chemical mechanisms.

Evolution of E. coli in a mouse model of inflammatory bowel disease leads to a disease-specific bacterial genotype and trade-offs with clinical relevance.

Inflammatory bowel disease (IBD) is a persistent inflammatory condition that affects the gastrointestinal tract and presents significant challenges in its management and treatment. Despite the knowledge that within-host bacterial evolution occurs in the intestine, the disease has rarely been studied from an evolutionary perspective. In this study, we aimed to investigate the evolution of resident bacteria during intestinal inflammation and whether- and how disease-related bacterial genetic changes may present trade-offs with potential therapeutic importance. Here, we perform an in vivo evolution experiment of E. coli in a gnotobiotic mouse model of IBD, followed by multiomic analyses to identify disease-specific genetic and phenotypic changes in bacteria that evolved in an inflamed versus a non-inflamed control environment. Our results demonstrate distinct evolutionary changes in E. coli specific to inflammation, including a single nucleotide variant that independently reached high frequency in all inflamed mice. Using ex vivo fitness assays, we find that these changes are associated with a higher fitness in an inflamed environment compared to isolates derived from non-inflamed mice. Further, using large-scale phenotypic assays, we show that bacterial adaptation to inflammation results in clinically relevant phenotypes, which intriguingly include collateral sensitivity to antibiotics. Bacterial evolution in an inflamed gut yields specific genetic and phenotypic signatures. These results may serve as a basis for developing novel evolution-informed treatment approaches for patients with intestinal inflammation.

Cluster Analysis Statistical Spectroscopy for the Identification of Metabolites in 1H NMR Metabolomics.

Metabolite identification in non-targeted NMR-based metabolomics remains a challenge. While many peaks of frequently occurring metabolites are assigned, there is a high number of unknowns in high-resolution NMR spectra, hampering biological conclusions for biomarker analysis. Here, we use a cluster analysis approach to guide peak assignment via statistical correlations, which gives important information on possible structural and/or biological correlations from the NMR spectrum. Unknown peaks that cluster in close proximity to known peaks form hypotheses for their metabolite identities, thus, facilitating metabolite annotation. Subsequently, metabolite identification based on a database search, 2D NMR analysis and standard spiking is performed, whereas without a hypothesis, a full structural elucidation approach would be required. The approach allows a higher identification yield in NMR spectra, especially once pathway-related subclusters are identified.

Bezafibrate Reduces Elevated Hepatic Fumarate in Insulin-Deficient Mice.

Glucotoxic metabolites and pathways play a crucial role in diabetic complications, and new treatment options which improve glucotoxicity are highly warranted. In this study, we analyzed bezafibrate (BEZ) treated, streptozotocin (STZ) injected mice, which showed an improved glucose metabolism compared to untreated STZ animals. In order to identify key molecules and pathways which participate in the beneficial effects of BEZ, we studied plasma, skeletal muscle, white adipose tissue (WAT) and liver samples using non-targeted metabolomics (NMR spectroscopy), targeted metabolomics (mass spectrometry), microarrays and mitochondrial enzyme activity measurements, with a particular focus on the liver. The analysis of muscle and WAT demonstrated that STZ treatment elevated inflammatory pathways and reduced insulin signaling and lipid pathways, whereas BEZ decreased inflammatory pathways and increased insulin signaling and lipid pathways, which can partly explain the beneficial effects of BEZ on glucose metabolism. Furthermore, lysophosphatidylcholine levels were lower in the liver and skeletal muscle of STZ mice, which were reverted in BEZ-treated animals. BEZ also improved circulating and hepatic glucose levels as well as lipid profiles. In the liver, BEZ treatment reduced elevated fumarate levels in STZ mice, which was probably due to a decreased expression of urea cycle genes. Since fumarate has been shown to participate in glucotoxic pathways, our data suggests that BEZ treatment attenuates the urea cycle in the liver, decreases fumarate levels and, in turn, ameliorates glucotoxicity and reduces insulin resistance in STZ mice.

Data Processing Optimization in Untargeted Metabolomics of Urine Using Voigt Lineshape Model Non-Linear Regression Analysis.

Nuclear magnetic resonance (NMR) spectroscopy is well-established to address questions in large-scale untargeted metabolomics. Although several approaches in data processing and analysis are available, significant issues remain. NMR spectroscopy of urine generates information-rich but complex spectra in which signals often overlap. Furthermore, slight changes in pH and salt concentrations cause peak shifting, which introduces, in combination with baseline irregularities, un-informative noise in statistical analysis. Within this work, a straight-forward data processing tool addresses these problems by applying a non-linear curve fitting model based on Voigt function line shape and integration of the underlying peak areas. This method allows a rapid untargeted analysis of urine metabolomics datasets without relying on time-consuming 2D-spectra based deconvolution or information from spectral libraries. The approach is validated with spiking experiments and tested on a human urine 1H dataset compared to conventionally used methods and aims to facilitate metabolomics data analysis.

Asc-1 regulates white versus beige adipocyte fate in a subcutaneous stromal cell population.

Adipose tissue expansion, as seen in obesity, is often metabolically detrimental causing insulin resistance and the metabolic syndrome. However, white adipose tissue expansion at early ages is essential to establish a functional metabolism. To understand the differences between adolescent and adult adipose tissue expansion, we studied the cellular composition of the stromal vascular fraction of subcutaneous adipose tissue of two and eight weeks old mice using single cell RNA sequencing. We identified a subset of adolescent preadipocytes expressing the mature white adipocyte marker Asc-1 that showed a low ability to differentiate into beige adipocytes compared to Asc-1 negative cells in vitro. Loss of Asc-1 in subcutaneous preadipocytes resulted in spontaneous differentiation of beige adipocytes in vitro and in vivo. Mechanistically, this was mediated by a function of the amino acid transporter ASC-1 specifically in proliferating preadipocytes involving the intracellular accumulation of the ASC-1 cargo D-serine.

Milk-Derived Amadori Products in Feces of Formula-Fed Infants.

Food processing of infant formula alters chemical structures, including the formation of Maillard reaction products between proteins and sugars. We detected early Maillard reaction products, so-called Amadori products, in stool samples of formula-fed infants. In total, four Amadori products (N-deoxylactulosyllysine, N-deoxyfructosyllysine, N-deoxylactulosylleucylisoleucine, N-deoxyfructosylleucylisoleucine) were identified by a combination of complementary nontargeted and targeted metabolomics approaches. Chemical structures were confirmed by preparation and isolation of reference compounds, LC-MS/MS, and NMR. The leucylisoleucine Amadori compounds, which most likely originate from ß-lactoglobulin, were excreted throughout the first year of life in feces of formula-fed infants but were absent in feces of breastfed infants. Despite high inter- and intraindividual differences of Amadori products in the infants' stool, solid food introduction resulted in a continuous decrease, proving infant formula as the major source of the excreted Amadori products.

Chronic d-serine supplementation impairs insulin secretion.

OBJECTIVE: The metabolic role of d-serine, a non-proteinogenic NMDA receptor co-agonist, is poorly understood. Conversely, inhibition of pancreatic NMDA receptors as well as loss of the d-serine producing enzyme serine racemase have been shown to modulate insulin secretion. Thus, we aim to study the impact of chronic and acute d-serine supplementation on insulin secretion and other parameters of glucose homeostasis. METHODS: We apply MALDI FT-ICR mass spectrometry imaging, NMR based metabolomics, 16s rRNA gene sequencing of gut microbiota in combination with a detailed physiological characterization to unravel the metabolic action of d-serine in mice acutely and chronically treated with 1% d-serine in drinking water in combination with either chow or high fat diet feeding. Moreover, we identify SNPs in SRR, the enzyme converting L-to d-serine and two subunits of the NMDA receptor to associate with insulin secretion in humans, based on the analysis of 2760 non-diabetic Caucasian individuals. RESULTS: We show that chronic elevation of d-serine results in reduced high fat diet intake. In addition, d-serine leads to diet-independent hyperglycemia due to blunted insulin secretion from pancreatic beta cells. Inhibition of alpha 2-adrenergic receptors rapidly restores glycemia and glucose tolerance in d-serine supplemented mice. Moreover, we show that single nucleotide polymorphisms (SNPs) in SRR as well as in individual NMDAR subunits are associated with insulin secretion in humans. CONCLUSION: Thus, we identify a novel role of d-serine in regulating systemic glucose metabolism through modulating insulin secretion.

Increased urinary osmolyte excretion indicates chronic kidney disease severity and progression rate.

Background: Chronic kidney disease (CKD) is a recognized global health problem. While some CKD patients remain stable after initial diagnosis, others can rapidly progress towards end-stage renal disease (ESRD). This makes biomarkers capable of detecting progressive forms of CKD extremely valuable, especially in non-invasive biofluids such as urine. Screening for metabolite markers using non-targeted metabolomic techniques like nuclear magnetic resonance spectroscopy is increasingly applied to CKD research. Methods: A cohort of CKD patients (n = 227) with estimated glomerular filtration rates (eGFRs) ranging from 9.4-130 mL/min/1.73 m2 was evaluated and urine metabolite profiles were characterized in relation to declining eGFR. Nested in this cohort, a retrospective subset (n = 57) was investigated for prognostic metabolite markers of CKD progression, independent of baseline eGFR. A transcriptomic analysis of murine models of renal failure was performed to validate selected metabolomic findings. Results: General linear modeling revealed 11 urinary metabolites with significant associations to reduced eGFR. Linear modelling specifically showed that increased urine concentrations of betaine (P < 0.05) and myo-inositol (P < 0.05) are significant prognostic markers of CKD progression. Conclusions: Renal organic osmolytes, betaine and myo-inositol play a critical role in protecting renal cells from hyperosmotic stress. Kidney tissue transcriptomics of murine preclinical experimentation identified decreased expression of Slc6a12 and Slc5a11 mRNA in renal tissue consistent with defective tubular transport of these osmolytes. Imbalances in renal osmolyte regulation lead to increased renal cell damage and thus more progressive forms of CKD. Increases in renal osmolytes in urine could provide clinical diagnostic and prognostic information on CKD outcomes.

Tandem HILIC-RP liquid chromatography for increased polarity coverage in food analysis.

Comprehensive non-targeted analysis of food products normally requires two complementary chromatographic runs to achieve maximum compound coverage. In this study, we present a sensitive tandem-LC method, which combines RP and HILIC separation in a single run. The setup consists of a C18 trap column and two subsequently coupled analytical columns (HILIC and C18) which are operated in parallel. First, hydrophobic compounds are retained on the RP trap column while rather hydrophilic compounds are directly transferred onto a HILIC phase. Next, the pre-fractionated sample composition is analyzed by HILIC or RP chromatography, respectively. The presented setup allows individual and independent gradient elution as well as interfacing with mass spectrometry. The performance of the method has been proven by means of food relevant standards and analysis of complex food samples (e.g. red wine, meat extract). The simple and robust setup provides high flexibility in the selection of column combinations and does not require sophisticated instrumental setups or software. The method significantly increases the covered polarity range compared to classical one-dimensional chromatography. Our results indicate that tandem LC is a valuable and universal tool in the non-targeted screening of various types of complex food samples.

Impact of Dietary Resistant Starch on the Human Gut Microbiome, Metaproteome, and Metabolome.

Diet can influence the composition of the human microbiome, and yet relatively few dietary ingredients have been systematically investigated with respect to their impact on the functional potential of the microbiome. Dietary resistant starch (RS) has been shown to have health benefits, but we lack a mechanistic understanding of the metabolic processes that occur in the gut during digestion of RS. Here, we collected samples during a dietary crossover study with diets containing large or small amounts of RS. We determined the impact of RS on the gut microbiome and metabolic pathways in the gut, using a combination of "omics" approaches, including 16S rRNA gene sequencing, metaproteomics, and metabolomics. This multiomics approach captured changes in the abundance of specific bacterial species, proteins, and metabolites after a diet high in resistant starch (HRS), providing key insights into the influence of dietary interventions on the gut microbiome. The combined data showed that a high-RS diet caused an increase in the ratio of Firmicutes to Bacteroidetes, including increases in relative abundances of some specific members of the Firmicutes and concurrent increases in enzymatic pathways and metabolites involved in lipid metabolism in the gut.IMPORTANCE This work was undertaken to obtain a mechanistic understanding of the complex interplay between diet and the microorganisms residing in the intestine. Although it is known that gut microbes play a key role in digestion of the food that we consume, the specific contributions of different microorganisms are not well understood. In addition, the metabolic pathways and resultant products of metabolism during digestion are highly complex. To address these knowledge gaps, we used a combination of molecular approaches to determine the identities of the microorganisms in the gut during digestion of dietary starch as well as the metabolic pathways that they carry out. Together, these data provide a more complete picture of the function of the gut microbiome in digestion, including links between an RS diet and lipid metabolism and novel linkages between specific gut microbes and their metabolites and proteins produced in the gut.

Sulfonolipids as novel metabolite markers of Alistipes and Odoribacter affected by high-fat diets.

The gut microbiota generates a huge pool of unknown metabolites, and their identification and characterization is a key challenge in metabolomics. However, there are still gaps on the studies of gut microbiota and their chemical structures. In this investigation, an unusual class of bacterial sulfonolipids (SLs) is detected in mouse cecum, which was originally found in environmental microbes. We have performed a detailed molecular level characterization of this class of lipids by combining high-resolution mass spectrometry and liquid chromatography analysis. Eighteen SLs that differ in their capnoid and fatty acid chain compositions were identified. The SL called "sulfobacin B" was isolated, characterized, and was significantly increased in mice fed with high-fat diets. To reveal bacterial producers of SLs, metagenome analysis was acquired and only two bacterial genera, i.e., Alistipes and Odoribacter, were revealed to be responsible for their production. This knowledge enables explaining a part of the molecular complexity introduced by microbes to the mammalian gastrointestinal tract and can be used as chemotaxonomic evidence in gut microbiota.

Chemical messages from an ancient buried bottle: metabolomics for wine archeochemistry.

Restoration works in the old Clunisian Saint-Vivant monastery in Burgundy revealed an unidentified wine bottle (SV1) dating between 1772 and 1860. Chemical evidence for SV1 origin and nature are presented here using non-targeted Fourier Transform Ion Cyclotron Resonance Mass Spectrometry and Nuclear Magnetic Resonance analyses. The SV1 chemical diversity was compared to red wines (Pinot Noir) from the Romanée Saint Vivant appellation and from six different vintages spanning from 1915 to 2009. The close metabolomic signature between SV1 and Romanée Saint Vivant wines spoke in favor of a filiation between these wines, in particular considering the Pinot noir grape variety. A further statistical comparison with up to 77 Pinot noir wines from Burgundy and vintages from nearly all the 20th century, confirmed that SV1 must have been made more than one hundred years ago. The increasing number of detected high masses and of nitrogen containing compounds with the ageing of the wine was in accordance with known ageing mechanisms. Besides, resveratrol was shown here to be preserved for more than one hundred years in wine. For the first time, the age of an old unknown wine along with its grape variety have been assessed through non-targeted metabolomic analyses.

Relationship of Serum Trimethylamine N-Oxide (TMAO) Levels with early Atherosclerosis in Humans.

Circulating trimethylamine N-Oxide (TMAO) levels predict cardiovascular disease (CVD), possibly by impacting on cholesterol metabolism and oxidative stress. Because hepatic TMAO production is regulated by insulin signalling and it is unclear whether and to what extent circulating TMAO levels associate with CVD risk, independently of insulin resistance and its important determinants fatty liver and visceral obesity, we have now addressed this question in 220 subjects who participated in the Tübingen Lifestyle Intervention Program. Visceral fat mass (r = 0.40, p < 0.0001), liver fat content (r = 0.23, p = 0.0005) and TMAO levels (r = 0.26, p < 0.0001) associated positively, and insulin sensitivity associated negatively (r = -0.18, p = 0.009) with carotid intima-media thickness (cIMT). Higher TMAO levels (std.-Beta 0.11, p = 0.03) predicted increased cIMT, independently of age, sex and visceral fat mass. While during the lifestyle intervention most cardiovascular risk parameters improved, mean TMAO levels did not change (p = 0.18). However, cIMT decreased significantly (p = 0.0056) only in subjects in the tertile with the largest decrease of TMAO levels (>20%). We provide novel information that increased serum TMAO levels associate with increased cIMT, independently of established cardiovascular risk markers, including insulin resistance, visceral obesity and fatty liver. Furthermore, the decrease of cIMT during a lifestyle intervention may be related to the decrease of TMAO levels.

(1)H NMR-based metabolite profiling workflow to reduce inter-sample chemical shift variations in urine samples for improved biomarker discovery.

Metabolite profiling of urine has seen much advancement in recent years, and its analysis by nuclear magnetic resonance (NMR) spectroscopy has become well established. However, the highly variable nature of human urine still requires improved protocols despite some standardization. In particular, diseases such as kidney disease can have a profound effect on the composition of urine and generate a highly diverse sample set for clinical studies. Large variations in pH and the cationic concentration of urine play an important role in creating positional noise within datasets generated from NMR. We demonstrate positional noise to be a confounding variable for multivariate statistical tools such as statistical total correlation spectroscopy (STOCSY), thereby hindering the process of biomarker discovery. We present a two-dimensional buffering system using potassium fluoride (KF) and phosphate buffer to reduce positional noise in metabolomic data generated from urine samples with various levels of proteinuria. KF reduces positional noise in citrate peaks, by decreasing the mean relative standard deviation (RSD) from 0.17 to 0.09. By reducing positional noise with KF, STOCSY analysis of citrate peaks saw significant improvement. We further aligned spectral data using a recursive segment-wise peak alignment (RSPA) method, which leads to further improvement of the positional noise (RSD = 0.06). These results were validated using diverse selection of metabolites which lead to an overall improvement in positional noise using the suggested protocol. In summary, we provide an improved workflow for urine metabolite biomarker discovery to achieve higher data quality for better pathophysiological understanding of human diseases. Graphical abstract Citrate peaks in the range 2.75-2.5 ppm from datasets with different sample preparation protocols and with/without in silico alignment. A Citrate peaks with standard phosphate buffering and without in silico alignment. B citrate peaks with standard phosphate buffering and with in silico alignment. C citrate peak with additional potassium fluoride and standard phosphate buffering without in silico alignment. D citrate peaks with additional potassium fluoride and standard phosphate buffering with in silico alignment. Below the respective spectrum are displayed the percent relative standard deviation (RSD) of the respective citrate peaks. This is a measure of the positional noise of peaks within a (1)H NMR analysis. It can be seen that D performs the best in reducing positional noise of citrate peaks. E-H STOCSY analysis of correlating spectral features with the driver peak at 2.675 ppm (see red arrow) to identify structural correlations. As a, b, c, and d are known to be structurally correlated, STOCSY analysis should reveal r (2) = 1 if data is perfectly aligned and can therefore be used as a measure of peak alignment. E Strong positional noise does not allow identifying the c and d peaks of the AB system to be correlated. F, G Neither in silico alignment or KF addition alone can completely improve the alignment and therefore increase the correlations. H Highly improved alignment by combining both KF addition and in silico alignment reduces positional noise and elucidates all four citrate peaks to be strongly correlated.

Challenges of metabolomics in human gut microbiota research.

The review highlights the role of metabolomics in studying human gut microbial metabolism. Microbial communities in our gut exert a multitude of functions with huge impact on human health and disease. Within the meta-omics discipline, gut microbiome is studied by (meta)genomics, (meta)transcriptomics, (meta)proteomics and metabolomics. The goal of metabolomics research applied to fecal samples is to perform their metabolic profiling, to quantify compounds and classes of interest, to characterize small molecules produced by gut microbes. Nuclear magnetic resonance spectroscopy and mass spectrometry are main technologies that are applied in fecal metabolomics. Metabolomics studies have been increasingly used in gut microbiota related research regarding health and disease with main focus on understanding inflammatory bowel diseases. The elucidated metabolites in this field are summarized in this review. We also addressed the main challenges of metabolomics in current and future gut microbiota research. The first challenge reflects the need of adequate analytical tools and pipelines, including sample handling, selection of appropriate equipment, and statistical evaluation to enable meaningful biological interpretation. The second challenge is related to the choice of the right animal model for studies on gut microbiota. We exemplified this using NMR spectroscopy for the investigation of cross-species comparison of fecal metabolite profiles. Finally, we present the problem of variability of human gut microbiota and metabolome that has important consequences on the concepts of personalized nutrition and medicine.

Neonatal environment exerts a sustained influence on the development of the intestinal microbiota and metabolic phenotype.

The postnatal environment, including factors such as weaning and acquisition of the gut microbiota, has been causally linked to the development of later immunological diseases such as allergy and autoimmunity, and has also been associated with a predisposition to metabolic disorders. We show that the very early-life environment influences the development of both the gut microbiota and host metabolic phenotype in a porcine model of human infants. Farm piglets were nursed by their mothers for 1 day, before removal to highly controlled, individual isolators where they received formula milk until weaning at 21 days. The experiment was repeated, to create two batches, which differed only in minor environmental fluctuations during the first day. At day 1 after birth, metabolic profiling of serum by (1)H nuclear magnetic resonance spectroscopy demonstrated significant, systemic, inter-batch variation which persisted until weaning. However, the urinary metabolic profiles demonstrated that significant inter-batch effects on 3-hydroxyisovalerate, trimethylamine-N-oxide and mannitol persisted beyond weaning to at least 35 days. Batch effects were linked to significant differences in the composition of colonic microbiota at 35 days, determined by 16 S pyrosequencing. Different weaning diets modulated both the microbiota and metabolic phenotype independently of the persistent batch effects. We demonstrate that the environment during the first day of life influences development of the microbiota and metabolic phenotype and thus should be taken into account when interrogating experimental outcomes. In addition, we suggest that intervention at this early time could provide 'metabolic rescue' for at-risk infants who have undergone aberrant patterns of initial intestinal colonisation.

2-Furoylglycine as a Candidate Biomarker of Coffee Consumption.

Specific and sensitive food biomarkers are necessary to support dietary intake assessment and link nutritional habits to potential impact on human health. A multistep nutritional intervention study was conducted to suggest novel biomarkers for coffee consumption. (1)H NMR metabolic profiling combined with multivariate data analysis resolved 2-furoylglycine (2-FG) as a novel putative biomarker for coffee consumption. We relatively quantified 2-FG in the urine of coffee drinkers and investigated its origin, metabolism, and excretion kinetics. When searching for its potential precursors, we found different furan derivatives in coffee products, which are known to get metabolized to 2-FG. Maximal urinary excretion of 2-FG occurred 2 h after consumption (p = 0.0002) and returned to baseline after 24 h (p = 0.74). The biomarker was not excreted after consumption of coffee substitutes such as tea and chicory coffee and might therefore be a promising acute biomarker for the detection of coffee consumption in human urine.

Gut metabolites and bacterial community networks during a pilot intervention study with flaxseeds in healthy adult men.

SCOPE: Flaxseeds contain the phytoestrogens lignans that must be activated to enterolignans by intestinal bacteria. We investigated the impact of flaxseeds on fecal bacterial communities and their associations with fecal and blood metabolites. METHODS AND RESULTS: Nine healthy male adult subjects ingested 0.3 g/kg/day flaxseeds during 1 week. Gut bacteria as well as blood and fecal metabolites were analyzed. Ingestion of flaxseeds triggered a significant increase in the blood concentration of enterolignans, accompanied by fecal excretion of propionate and glycerol. Overall diversity and composition of dominant fecal bacteria remained individual specific throughout the study. Enterolactone production was linked to the abundance of two molecular species identified as Ruminococcus bromii and Ruminococcus lactaris. Most dominant species of the order Bacteroidales were positively associated with fecal concentrations of either acetic, isovaleric, or isobutyric acid, the latter being negatively correlated with blood levels of triglycerides. The relative sequence abundance of one Gemmiger species (Ruminococcaceae) and of Coprococcus comes (Lachnospiraceae) correlated positively with blood levels of LDL cholesterol and triglycerides, respectively. CONCLUSION: Flaxseeds increase enterolignan production but do not markedly alter fecal metabolome and dominant bacterial communities. The data underline the possible role of members of the family Ruminococcaceae in the regulation of enterolignan production and blood lipids.