Dataset Information

Alterations of the Gut Microbiome Associated to Methane Metabolism in Mexican Children with Obesity.

ABSTRACT: Gut microbiota is associated with the development of metabolic disorders. To study its association with childhood obesity, we performed a cross-sectional study with 46 children (6-12 years old). We collected fecal samples, food-frequency questionnaires (FFQs), and anthropometric measurements. Shotgun metagenomics were used to obtain the microbial taxonomic diversity and metabolic potential. We identified two dietary profiles characterized by complex carbohydrates and proteins (pattern 1) and saturated fat and simple carbohydrates (pattern 2). We classified each participant into normal weight (NW) or overweight and obese (OWOB) using their body mass index (BMI) z-score. The ratio of Firmicutes/Bacteroidetes and alpha diversity were not different between the BMI groups. Genera contributing to beta diversity between NW and OWOB groups included Bacteroides rodentium, B. intestinalis, B. eggerthii, Methanobrevibacter smithii, Eubacterium sp., and Roseburia sp. B. rodentium was associated with lower BMI and dietary pattern 1 intake. Eubacterium sp. and Roseburia sp. were associated with BMI increments and high consumption of dietary pattern 2. Methane and energy metabolism were found enriched in under-represented KEGG pathways of NW group compared to OWOB. Complex dietary and microbiome interaction leads to metabolic differences during childhood, which should be elucidated to prevent metabolic diseases in adolescence and adulthood.

SUBMITTER: Murga-Garrido SM

PROVIDER: S-EPMC8870140 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Alterations of the Gut Microbiome Associated to Methane Metabolism in Mexican Children with Obesity.

Murga-Garrido Sofía Magdalena SM Orbe-Orihuela Yaneth Citlalli YC Díaz-Benítez Cinthya Estefhany CE Castañeda-Márquez Ana Cristina AC Cornejo-Granados Fernanda F Ochoa-Leyva Adrian A Sanchez-Flores Alejandro A Cruz Miguel M Burguete-García Ana Isabel AI Lagunas-Martínez Alfredo A

Children (Basel, Switzerland) 20220124 2

Gut microbiota is associated with the development of metabolic disorders. To study its association with childhood obesity, we performed a cross-sectional study with 46 children (6-12 years old). We collected fecal samples, food-frequency questionnaires (FFQs), and anthropometric measurements. Shotgun metagenomics were used to obtain the microbial taxonomic diversity and metabolic potential. We identified two dietary profiles characterized by complex carbohydrates and proteins (pattern 1) and sat ...[more]

PMID: 35204867

Similar Datasets

Project description:Mexican Americans have a high prevalence of diabetes and burden of diabetes-related complications, highlighting the need for novel preventive strategies and noninvasive predictors of diabetes risk tailored to this population. Changes in the gut microbiome have the potential to predict diabetes. Here, we aimed to identify alterations in the gut microbiome associated with diabetes in the high-risk population of Mexican Americans in South Texas. Stool samples were collected from 216 subjects from the population-based Cameron County Hispanic Cohort. Among them, 75 had type 2 diabetes. Taxonomic and functional profiling of the stool samples were assessed by 16S and shotgun metagenomic sequencing, and the influence of genetic factors was explored. The gut microbiome of subjects with diabetes was enriched with proinflammatory Proteobacteria members (Enterobacteriaceae, Escherichia-Shigella) and depleted of butyrate-producing Clostridiales members (Faecalibacterium prausnitzii, Peptostreptococcaceae, and Clostridium sensu stricto 1). The accompanying metagenomic changes in subjects with diabetes suggested dysregulated amino acid metabolism, reduced galacturonate and glucuronate catabolism (correlating with Faecalibacterium prausnitzii abundance), and enriched heme biosynthesis (correlating with Enterobacteriaceae abundance). Polymorphism rs7129790 near MMP27 was strongly associated with high Proteobacteria abundance and was more frequent in this cohort and in individuals of Mexican ancestry than in Europeans. In conclusion, Mexican Americans in South Texas with diabetes display distinct gut microbiome and metagenomic signatures. These signatures may have utility in risk modeling and disease prevention in this high-risk population. IMPORTANCE The gut microbiome composition varies across ethnicities and geographical locations, yet studies on diabetes-associated microbiome changes specific to high-risk Mexican Americans are lacking. Here, we aimed to identify specific alterations associated with diabetes in this population, as well as host genetic factors that may explain increased disease susceptibility in this ethnic group. Using samples from a population-based cohort of Mexican Americans with a high prevalence of obesity and diabetes, we confirmed findings from studies on other ethnicities that suggested promotion of a chronic proinflammatory environment, loss of butyrate production, and compromised intestinal barrier integrity. High abundance of proinflammatory Proteobacteria was associated with a polymorphism that was more frequent in this cohort and in individuals of Mexican ancestry than in Europeans. Validation of microbiome-based risk models for diabetes should be evaluated in prospective cohort studies.

Project description:Changes in the gut microenvironment may influence the pathogenesis of autism spectrum disorders (ASD). Here, we investigated the composition of the gut microbiota and metabolites in children with ASD. Ninety-two children with ASD and 42 age-matched children exhibiting typical development (TD) were enrolled in the two-stage study. In the discovery stage, shotgun metagenomic sequencing and liquid chromatography-mass spectrometry (LC-MS) were performed simultaneously on fecal samples obtained from 43 children in the ASD group and 31 children in the TD group. Systematic bioinformatic analyses were performed to identify gut metabolites associated with altered gut microbiota composition. At the validation stage, differential metabolites were tested using LC-MS with an additional 49 and 11 children in the ASD and TD groups, respectively. Altered glutamate metabolites were found in the ASD group, along with a decline in 2-keto-glutaramic acid and an abundance of microbiota associated with glutamate metabolism. These changes in glutamate metabolism were correlated with lower levels of the highly abundant bacteria Bacteroides vulgatus and higher levels of the potentially harmful Eggerthella lenta and Clostridium botulinum. Lower gut cortisol levels have also been identified in the ASD group and associated with changes in gut microbiota glutamate metabolism. Finally, gut 2-keto-glutaramic acid was validated as a potential biomarker for ASD. The significant changes in the gut microenvironment in children with ASD may provide new insight into the cause of ASD and aid in the search for diagnostic and therapeutic approaches. IMPORTANCE Multiple lines of evidence suggest that the gut microbiota may play an important role in the pathogenesis of ASD, but the specific mechanism is still unclear. Through a comprehensive gut metagenomic and metabolome study of children with ASD, alterations in gut metabolite composition were found in children with ASD, and these alterations were linked to changes in gut microbiota composition. This may give us a deeper understanding of the role of gut microbiota in the pathogenesis of ASD.

Project description:BACKGROUND:In the last decade, increasing evidence has shown that changes in human gut microbiota are associated with diseases, such as obesity. The excreted/secreted proteins (secretome) of the gut microbiota affect the microbial composition, altering its colonization and persistence. Furthermore, it influences microbiota-host interactions by triggering inflammatory reactions and modulating the host's immune response. The metatranscriptome is essential to elucidate which genes are expressed under diseases. In this regard, little is known about the expressed secretome in the microbiome. Here, we use a metatranscriptomic approach to delineate the secretome of the gut microbiome of Mexican children with normal weight (NW) obesity (O) and obesity with metabolic syndrome (OMS). Additionally, we performed the 16S rRNA profiling of the gut microbiota. RESULTS:Out of the 115,712 metatranscriptome genes that codified for proteins, 30,024 (26%) were predicted to be secreted, constituting the Secrebiome of the gut microbiome. The 16S profiling confirmed an increased abundance in Firmicutes and decreased in Bacteroidetes in the obesity groups, and a significantly higher richness and diversity than the normal weight group. We found novel biomarkers for obesity with metabolic syndrome such as increased Coriobacteraceae, Collinsela, and Collinsella aerofaciens; Erysipelotrichaceae, Catenibacterium and Catenibacterium sp., and decreased Parabacteroides distasonis, which correlated with clinical and anthropometric parameters associated to obesity and metabolic syndrome. Related to the Secrebiome, 16 genes, homologous to F. prausniitzi, were overexpressed for the obese and 15 genes homologous to Bacteroides, were overexpressed in the obesity with metabolic syndrome. Furthermore, a significant enrichment of CAZy enzymes was found in the Secrebiome. Additionally, significant differences in the antigenic density of the Secrebiome were found between normal weight and obesity groups. CONCLUSIONS:These findings show, for the first time, the role of the Secrebiome in the functional human-microbiota interaction. Our results highlight the importance of metatranscriptomics to provide novel information about the gut microbiome's functions that could help us understand the impact of the Secrebiome on the homeostasis of its human host. Furthermore, the metatranscriptome and 16S profiling confirmed the importance of treating obesity and obesity with metabolic syndrome as separate conditions to better understand the interplay between microbiome and disease.

Project description:The gut microbiota is crucial in the pathogenesis of obesity. Abdominal obesity is known to significantly increase the risk of metabolic syndrome and cardiovascular disease, so further study is needed to investigate the changes of intestinal microorganisms in patients with excessive visceral fat. In our study, 41 people (n = 41) with normal body mass index (BMI) (18.5 ≤ BMI < 23.9) were included and divided into the low visceral fat area (L-VFA) group (n = 23, VFA < 100 cm2) and the high visceral fat area (H-VFA) group (n = 18, VFA ≥ 100 cm2). Several clinical indicators of the H-VFA group were significantly higher than those of the L-VFA group, including the waist circumference (WC), the fasting blood glucose (FBG), the triglyceride (TG), the total cholesterol (TC), the low-density lipoprotein cholesterol (LDL), the serum uric acid (SUA), the white blood cell count (WBC), the blood neutrophil count (NEC), and the blood lymphocyte count (LYC). Using whole-genome shotgun sequencing, we found that the types of the intestinal microbiota of H-VFA patients were different from those of the L-VFA patients, with 18 bacteria enriched in the H-VFA group and nine bacteria in the L-VFA group. A total of 16 species of gut microbes showed a strong correlation with VFA, and Escherichia coli has the strongest correlation, followed by Mitsuokella unclassified, Bifidobacterium longum, Escherichia unclassified, Ruminococcus torques, Dialister succinatiphilus, Eubacterium hallii, and Ruminococcus gnavus. Compared to the VFA, only two species show a strong correlation with BMI and WC. Further functional genetic studies suggested that the degradation of short-chain fatty acids (SCFAs) and the generation of lipopolysaccharide (LPS) might be related to visceral fat accumulation. Together, visceral fat was more closely correlated with the gut microbiome compared with BMI and WC. It suggested an intrinsic connection between the gut microbiome and visceral fat and its related metabolic disorders. Specific microbial species and pathways associated with visceral fat accumulation might contribute to new targeted therapies for visceral fat and its metabolic disorders.

Project description:Individuals with latent tuberculosis infection (LTBI) account for almost 30% of the population worldwide and have the potential to develop active tuberculosis (ATB). Despite this, the current understanding of the pathogenesis of LTBI is limited. The gut microbiome can be altered in tuberculosis patients, and an understanding of the changes associated with the progression from good health to LTBI to ATB can provide novel perspectives for understanding the pathogenesis of LTBI by identifying microbial and molecular biomarkers associated therewith. In this study, fecal samples from healthy controls (HC), individuals with LTBI and ATB patients were collected for gut microbiome and metabolomics analyses. Compared to HC and LTBI subjects, participants with ATB showed a significant decrease in gut bacterial α-diversity. Additionally, there were significant differences in gut microbial communities and metabolism among the HC, LTBI, and ATB groups. PICRUSt2 analysis revealed that microbiota metabolic pathways involving the degradation of purine and pyrimidine metabolites were upregulated in LTBI and ATB individuals relative to HCs. Metabolomic profiling similarly revealed that purine and pyrimidine metabolite levels were decreased in LTBI and ATB samples relative to those from HCs. Further correlation analyses revealed that the levels of purine and pyrimidine metabolites were negatively correlated with those of gut microbial genera represented by Ruminococcus_gnavus_group (R. gnavus), and the levels of R. gnavus were also positively correlated with adenosine nucleotide degradation II, which is a purine degradation pathway. Moreover, a combined signature including hypoxanthine and xanthine was found to effectively distinguish between LTBI and HC samples (area under the curve [AUC] of training set = 0.796; AUC of testing set = 0.924). Therefore, through gut microbiome and metabolomic analyses, these findings provide valuable clues regarding how alterations in gut purine and pyrimidine metabolism are linked to the pathogenesis of LTBI.IMPORTANCEThis study provides valuable insight into alterations in the gut microbiome and metabolomic profiles in a cohort of adults with LTBI and ATB. Perturbed gut purine and pyrimidine metabolism in LTBI was associated with the compositional alterations of gut microbiota, which may be an impetus for developing novel diagnostic strategies and interventions targeting LTBI.

Project description:Chronic gastrointestinal (GI) diseases are the most common diseases in captive common marmosets (Callithrix jacchus). Despite standardized housing, diet and husbandry, a recently described gastrointestinal syndrome characterized by duodenal ulcers and strictures was observed in a subset of marmosets sourced from the New England Primate Research Center. As changes in the gut microbiome have been associated with GI diseases, the gut microbiome of 52 healthy, non-stricture marmosets (153 samples) were compared to the gut microbiome of 21 captive marmosets diagnosed with a duodenal ulcer/stricture (57 samples). No significant changes were observed using alpha diversity metrics, and while the community structure was significantly different when comparing beta diversity between healthy and stricture cases, the results were inconclusive due to differences observed in the dispersion of both datasets. Differences in the abundance of individual taxa using ANCOM, as stricture-associated dysbiosis was characterized by Anaerobiospirillum loss and Clostridium perfringens increases. To identify microbial and serum biomarkers that could help classify stricture cases, we developed models using machine learning algorithms (random forest, classification and regression trees, support vector machines and k-nearest neighbors) to classify microbiome, serum chemistry or complete blood count (CBC) data. Random forest (RF) models were the most accurate models and correctly classified strictures using either 9 ASVs (amplicon sequence variants), 4 serum chemistry tests or 6 CBC tests. Based on the RF model and ANCOM results, C. perfringens was identified as a potential causative agent associated with the development of strictures. Clostridium perfringens was also isolated by microbiological culture in 4 of 9 duodenum samples from marmosets with histologically confirmed strictures. Due to the enrichment of C. perfringens in situ, we analyzed frozen duodenal tissues using both 16S microbiome profiling and RNAseq. Microbiome analysis of the duodenal tissues of 29 marmosets from the MIT colony confirmed an increased abundance of Clostridium in stricture cases. Comparison of the duodenal gene expression from stricture and non-stricture marmosets found enrichment of genes associated with intestinal absorption, and lipid metabolism, localization, and transport in stricture cases. Using machine learning, we identified increased abundance of C. perfringens, as a potential causative agent of GI disease and intestinal strictures in marmosets.

Dataset Information

Alterations of the Gut Microbiome Associated to Methane Metabolism in Mexican Children with Obesity.

Publications

Alterations of the Gut Microbiome Associated to Methane Metabolism in Mexican Children with Obesity.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets