Gut-derived metabolites mediating cognitive development in 5-year-old children: Early-life transplant in mice has lasting effects throughout adulthood

The gut microbiota has been causally linked to cognitive development. We aimed to identify metabolites mediating its effect on cognitive development, and foods or nutrients related to most promising metabolites. Faeces from 5-year-old children (DORIAN-PISAC cohort, including 90 general population families with infants, 42/48 females/males, born in 2011-2014) were transplanted (FMT) into C57BL/6 germ-free mice. Children and recipient mice were stratified by cognitive phenotype, or based on protective metabolites. Food frequency questionnaires were obtained in children. Cognitive measurements in mice included five Y-maze tests until 23 weeks post-FMT, and (at 23 weeks) PET-CT for brain metabolism and radiodensity, and ultrasound-based carotid vascular indices. Children (faeces, urine) and mice (faeces, plasma) metabolome was measured by 1H NMR spectroscopy, and the faecal microbiota was profiled in mice by 16S rRNA amplicon sequencing. Cognitive scores of children and recipient mice were correlated. FMT-dependent modifications of brain metabolism were observed. Mice receiving FMT from high-cognitive or protective metabolite-enriched children developed superior cognitive-behavioural performance. A panel of metabolites, namely xanthine, hypoxanthine, formate, mannose, tyrosine, phenylalanine, glutamine, was found to mediate the gut-cognitive axis in donor children and recipient mice. Vascular indices partially explained the metabolite-to-phenotype relationships. Children's consumption of legumes, whole-milk yogurt and eggs, and intake of iron, zinc and vitamin D appeared to support protective gut metabolites. Overall, metabolites involved in inflammation, purine metabolism and neurotransmitter synthesis mediate the gut-cognitive axis, and holds promise for screening. The related dietary and nutritional findings offer leads to microbiota-targeted interventions for cognitive protection, with long-lasting effects

Hepatocyte MyD88 affects bile acids, gut microbiota and metabolome contributing to regulate glucose and lipid metabolism

OBJECTIVE: To examine the role of hepatocyte myeloid differentiation primary-response gene 88 (MyD88) on glucose and lipid metabolism. DESIGN: To study the impact of the innate immune system at the level of the hepatocyte and metabolism, we generated mice harbouring hepatocyte-specific deletion of MyD88. We investigated the impact of the deletion on metabolism by feeding mice with a normal control diet or a high-fat diet for 8 weeks. We evaluated body weight, fat mass gain (using time-domain nuclear magnetic resonance), glucose metabolism and energy homeostasis (using metabolic chambers). We performed microarrays and quantitative PCRs in the liver. In addition, we investigated the gut microbiota composition, bile acid profile and both liver and plasma metabolome. We analysed the expression pattern of genes in the liver of obese humans developing non-alcoholic steatohepatitis (NASH). RESULTS: Hepatocyte-specific deletion of MyD88 predisposes to glucose intolerance, inflammation and hepatic insulin resistance independently of body weight and adiposity. These phenotypic differences were partially attributed to differences in gene expression, transcriptional factor activity (ie, peroxisome proliferator activator receptor-α, farnesoid X receptor (FXR), liver X receptors and STAT3) and bile acid profiles involved in glucose, lipid metabolism and inflammation. In addition to these alterations, the genetic deletion of MyD88 in hepatocytes changes the gut microbiota composition and their metabolomes, resembling those observed during diet-induced obesity. Finally, obese humans with NASH displayed a decreased expression of different cytochromes P450 involved in bioactive lipid synthesis. CONCLUSIONS: Our study identifies a new link between innate immunity and hepatic synthesis of bile acids and bioactive lipids. This dialogue appears to be involved in the susceptibility to alterations associated with obesity such as type 2 diabetes and NASH, both in mice and humans

Estudio metabolómico de la interacción huesped-microbiota intestinal en la enfermedad cardiometabólica. Detección temprana, prevención y tratamiento

La enfermedad cardiometabólica incluye un conjunto de factores de riesgo cardiometabólicos como son obesidad, hipertensión, enfermedad del hígado graso, diabetes tipo 2 y enfermedad cardiovascular. Estudios recientes muestran un papel del co-metabolismo de la microbiota huésped y las dietas occidentales en la aparición y desarrollo de esta enfermedad. Los hábitos alimentarios con dietas ricas en grasas y azúcares se encuentran entre las principales causas de mortalidad por problemas cardiometabólicos, experimentando un veloz incremento en la actualidad. El estudio de las vías metabólicas implicadas y la identificación de biomarcadores específicos para la detección precoz de la enfermedad cardiometabólica parece fundamental en el manejo de pacientes. Esta tesis tiene como objetivo mejorar nuestra comprensión de la progresión de la enfermedad cardiometabólica, descubrir las primeras alteraciones en el desarrollo de la enfermedad, así como identificar posibles biomarcadores subclínicos asociados, a través del análisis de cambios en el metabolismo sérico, urinario y fecal. Diseño y métodos: Se alimentaron ratas Wistar macho y hembra, de 16 semanas de edad, con una dieta alta en grasas y sucrosa durante 12 semanas para inducir alteraciones cardiometabólicas, tanto en condiciones de estabulación convencionales como libres de patógenos específicos. Además, ratas Wistar macho y hembra, de 3 semanas de edad, fueron alimentadas con una dieta alta en fructosa durante 16 semanas para inducir también alteraciones cardiometabólicas. Las muestras de suero, orina y heces y la diversidad de la microbiota se analizaron mediante resonancia magnética nuclear (1H NMR) y electroforesis en gel en gradiente desnaturalizante o secuenciación,respectivamente. Además, se analizó el efecto del trasplante de microbiota fecal y de los probióticos en la modulación de la microbiota. Resultados: Las dietas altas en grasa y azúcares (sucrosa y fructosa) indujeron alteraciones metabólicas y clínicas relacionadas con la enfermedad cardiometabólica en ratas jóvenes y adultas. El perfil metabolómico de las muestras de suero, orina y heces demostró diferencias en el metabolismo de los grupos con dietas altas en grasas y azúcares en diferentes vías metabólicas. Estas diferencias en el metaboloma de las ratas mostraron diferentes alteraciones en ratas macho y hembra. Además, los co-metabolitos de la microbiota del huésped también se vieron alterados por estas dietas. La secuenciación del microbioma y la DGGE de ADN fecal revelaron cambios en la composición de la microbiota que sugieren una menor diversidad de la microbiota en los grupos con dietas altas en grasas y azúcares. Curiosamente, la dieta alta en grasa induce fuertes cambios en la composición de la microbiota mientras que la dieta alta en fructosa parece que solo los modera. El perfil metabolómico longitudinal de ratas con dieta rica en grasas sugiere que los cambios en la composición de la microbiota preceden a las alteraciones en el metabolismo del hospedador en el desarrollo de la enferemedad en ratas. Además, nuestros resultados sugieren que la dieta tiene efectos más fuertes en la composición de la microbiota que una exposición restringida a ciertas comunidades bacterianas. Finalmente, la modulación de la microbiota con probióticos, pero no con el trasplante de microbiota fecal, mejora el desarrollo de la enfermedad cardiometabólica, aunque de manera diferente en machos y hembras. En conclusión, nuestro trabajo demuestra que la asociación entre el co-metabolismo de la microbiota del huésped y la enfermedad cardiometabólica dependen en gran medida de los patrones dietéticos, el sexo, la exposición ambiental a las comunidades bacterianas y la edad. Estas dependencias y el efecto metabólico de estos múltiples factores pueden detectarse mediante metabolómica por RMN. El perfil metabolómico puede ser una forma eficaz de mejorar el tratamiento clínico de la enfermedad cardiometabólica y la estratificación del riesgo del paciente.Cardiometabolic disease (CMD) is a clustering of cardiometabolic risk factors including obesity, hypertension, fatty liver disease, type 2 diabetes, and cardiovascular disease. Recent studies show a role for host-microbiota co-metabolism and Western diets in the onset and development of this disease. High-fat and high-sugar dietary habits are among the main causes of CMD mortality with fast increment nowadays. The study of the metabolic pathways involved and the identification of specific biomarkers for early detection of CMD seems essential in patient management. This thesis aims to improve our understanding of the progression of CMD, to discover the firsts alterations in the development of the disease, as well as to identify potential sub-clinical CMD biomarkers through the analysis of changes in serum, urine, and fecal metabolism. Design and methods: Male and female Wistar rats, 16 weeks old, were fed with a high-fat and sucrose diet (HFD) for 12 weeks to induce CMD, both in conventional and specific-pathogen-free (SPF) housing conditions. Moreover, male and female Wistar rats, 3 weeks old, were fed with a high-fructose diet (HFR) for 16 weeks to induce CMD. Serum, urine, and fecal samples and microbiota diversity were analyzed by Nuclear magnetic resonance (1H NMR) and Denaturant gradient gel electrophoresis (DGGE) or Sequencing, respectively. The effect of fecal microbiota transplantation (FMT) and probiotics were tested on the microbiota modulation. Results: HFD and HFR induced metabolic and clinical alterations related to CMD in young and adult rats. The metabolomic profile of serum, urine,and fecal samples demonstrated differences in the metabolism of HFD and HFR groups in different metabolic pathways and cores. These differences in the rats metabolome are sex specific with different alterations in male and female rats. Moreover, host-microbiota co-metabolites were also altered after HFD and HFR diets. Microbiome sequencing and fecal DNA DGGE revealed changes in the microbiota composition that suggest lower microbiota diversity in the HFD and HFR groups. Interestingly, HFD induces strong whereas HFR only moderate microbiota composition changes. The longitudinal metabolomic profiling of HFD rats suggest that microbiota composition changes precede alterations in host metabolism in the development of CMD in rats. Additionally, our results suggest that diet has stronger effects in microbiota composition than restricted exposure to bacterial communities. Finally, modulation of microbiota with probiotics, but not with fecal microbiota transplantation, ameliorates CMD in a sex specific manner. Overall our work demonstrates that the association between host-microbiota co-metabolism and cardiometabolic disease is highly dependent on dietary patterns, sex, environmental exposure to bacterial communities and age. These dependences and the metabolic effect of these multiple factors can be detected by NMR metabolomics. Metabolomics profiling may be an effective way for improving cardiometabolic disease clinical management and patient risk stratification

Microbiome-metabolome signatures in mice genetically prone to develop dementia, fed a normal or fatty diet.

Cognitive decline, obesity and gut dysfunction or microbial dysbiosis occur in association. Our aim was to identify gut microbiota-metabolomics signatures preceding dementia in genetically prone (3xtg) mice, with and without superimposed high-fat diet. We examined the composition and diversity of their gut microbiota, and serum and faecal metabolites. 3xtg mice showed brain hypometabolism typical of pre-demented stage, and lacked the physiological bacterial diversity between caecum and colon seen in controls. Cluster analyses revealed distinct profiles of microbiota, and serum and fecal metabolome across groups. Elevation in Firmicutes-to-Bacteroidetes abundance, and exclusive presence of Turicibacteraceae, Christensenellaceae, Anaeroplasmataceae and Ruminococcaceae, and lack of Bifidobacteriaceae, were also observed. Metabolome analysis revealed a deficiency in unsaturated fatty acids and choline, and an overabundance in ketone bodies, lactate, amino acids, TMA and TMAO in 3xtg mice, with additive effects of high-fat diet. These metabolic alterations were correlated with high prevalence of Enterococcaceae, Staphylococcus, Roseburia, Coprobacillus and Dorea, and low prevalence of S24.7, rc4.4 and Bifidobacterium, which in turn related to cognitive impairment and cerebral hypometabolism. Our results indicate an effect of transgenic background on gut microbiome-metabolome, enhanced by high-fat diet. The resulting profiles may precede overt cognitive impairment, suggesting their predictive or risk-stratifying potential

Hepatocyte MyD88 affects bile acids, gut microbiota and metabolome contributing to regulate glucose and lipid metabolism

Objective To examine the role of hepatocyte myeloid differentiation primary-response gene 88 (MyD88) on glucose and lipid metabolism. Design To study the impact of the innate immune system at the level of the hepatocyte and metabolism, we generated mice harbouring hepatocyte-specific deletion of MyD88. We investigated the impact of the deletion on metabolism by feeding mice with a normal control diet or a high-fat diet for 8 weeks. We evaluated body weight, fat mass gain (using time-domain nuclear magnetic resonance), glucose metabolism and energy homeostasis (using metabolic chambers). We performed microarrays and quantitative PCRs in the liver. In addition, we investigated the gut microbiota composition, bile acid profile and both liver and plasma metabolome. We analysed the expression pattern of genes in the liver of obese humans developing nonalcoholic steatohepatitis (NASH). Results Hepatocyte-specific deletion of MyD88 predisposes to glucose intolerance, inflammation and hepatic insulin resistance independently of body weight and adiposity. These phenotypic differences were partially attributed to differences in gene expression, transcriptional factor activity (ie, peroxisome proliferator activator receptor-alpha, farnesoid X receptor (FXR), liver X receptors and STAT3) and bile acid profiles involved in glucose, lipid metabolism and inflammation. In addition to these alterations, the genetic deletion of MyD88 in hepatocytes changes the gut microbiota composition and their metabolomes, resembling those observed during diet-induced obesity. Finally, obese humans with NASH displayed a decreased expression of different cytochromes P450 involved in bioactive lipid synthesis. Conclusions Our study identifies a new link between innate immunity and hepatic synthesis of bile acids and bioactive lipids. This dialogue appears to be involved in the susceptibility to alterations associated with obesity such as type 2 diabetes and NASH, both in mice and humans

Genomic and Metabolomic Profile Associated to Clustering of Cardio-Metabolic Risk Factors

<div><p>Background</p><p>To identify metabolomic and genomic markers associated with the presence of clustering of cardiometabolic risk factors (CMRFs) from a general population.</p><p>Methods and Findings</p><p>One thousand five hundred and two subjects, Caucasian, > 18 years, representative of the general population, were included. Blood pressure measurement, anthropometric parameters and metabolic markers were measured. Subjects were grouped according the number of CMRFs (Group 1: <2; Group 2: 2; Group 3: 3 or more CMRFs). Using SNPlex, 1251 SNPs potentially associated to clustering of three or more CMRFs were analyzed. Serum metabolomic profile was assessed by ¹H NMR spectra using a Brucker Advance DRX 600 spectrometer. From the total population, 1217 (mean age 54±19, 50.6% men) with high genotyping call rate were analysed. A differential metabolomic profile, which included products from mitochondrial metabolism, extra mitochondrial metabolism, branched amino acids and fatty acid signals were observed among the three groups. The comparison of metabolomic patterns between subjects of Groups 1 to 3 for each of the genotypes associated to those subjects with three or more CMRFs revealed two SNPs, the rs174577_AA of FADS2 gene and the rs3803_TT of GATA2 transcription factor gene, with minimal or no statistically significant differences. Subjects with and without three or more CMRFs who shared the same genotype and metabolomic profile differed in the pattern of CMRFS cluster. Subjects of <i>Group 3</i> and the AA genotype of the rs174577 had a lower prevalence of hypertension compared to the CC and CT genotype. In contrast, subjects of <i>Group 3</i> and the TT genotype of the rs3803 polymorphism had a lower prevalence of T2DM, although they were predominantly males and had higher values of plasma creatinine.</p><p>Conclusions</p><p>The results of the present study add information to the metabolomics profile and to the potential impact of genetic factors on the variants of clustering of cardiometabolic risk factors.</p></div

Patterns of statistical significance, calculated as p-values, for the comparison of metabolic profiles from subjects group 1 versus subjects from group 3 in the whole population (first column) and in individuals with different SNPs (rest of the columns).

<p>(white) p> 0.01; (white-gray) p< 0.01; (gray) p< 0.001; (black) p< 0.00001.</p

Metabolite relative levels in serum from subjects group 1 versus subjects from group 3.

<p>Metabolite relative levels in serum from subjects group 1 versus subjects from group 3.</p

Bar chart showing metabolic differences between Group 3 and Groups 1 normalized with respect to changes in group 3 (see Table 1).

<p>The bars represent the difference in the average metabolic levels between Group 3 and group 1 for each SNP divided by the same difference calculated for the entire cohort. SNPs with bars closer to 1 (dotted line) show CMRFs associated metabolic changes similar to those of the global population (irrespective of genotype). On the other hand, SNPs with bars closer to 0 exhibit minimal or no metabolic changes associated to CMRFs. Bars with negative values indicate a CMRF associated metabolic change opposite to that detected in global population. Metabolites from top to bottom are: tryptophan + choline; creatinine; phosphoethanolamine; creatine phosphate; tyrosine; creatine; methanol; proline; trimethylamine; lipids (= CH-CH2-CH2 =); citrate; 3-hydroxybutyrate; pyruvate; acetone; lipids (-CH2-CH3); N-acetylglutamine; acetate; lipids (-CH2-CH2_CO); alanine; 2-phenylpropionate; lactate; lipids (-CH2-)n; isobutyrate; valine; isoleucine; leucine; lipids (-CH3) and cholesterol.</p