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Stool metabolome-microbiota evaluation among children and adolescents with obesity, overweight, and normal-weight using 1H NMR and 16S rRNA gene profiling.

ABSTRACT: Characterization of metabolites and microbiota composition from human stool provides powerful insight into the molecular phenotypic difference between subjects with normal weight and those with overweight/obesity. The aim of this study was to identify potential metabolic and bacterial signatures from stool that distinguish the overweight/obesity state in children/adolescents. Using 1H NMR spectral analysis and 16S rRNA gene profiling, the fecal metabolic profile and bacterial composition from 52 children aged 7 to 16 was evaluated. The children were classified into three groups (16 with normal-weight, 17 with overweight, 19 with obesity). The metabolomic analysis identified four metabolites that were significantly different (p < 0.05) among the study groups based on one-way ANOVA testing: arabinose, butyrate, galactose, and trimethylamine. Significantly different (p < 0.01) genus-level taxa based on edgeR differential abundance tests were genus Escherichia and Tyzzerella subgroup 3. No significant difference in alpha-diversity was detected among the three study groups, and no significant correlations were found between the significant taxa and metabolites. The findings support the hypothesis of increased energy harvest in obesity by human gut bacteria through the growing observation of increased fecal butyrate in children with overweight/obesity, as well as an increase of certain monosaccharides in the stool. Also supported is the increase of trimethylamine as an indicator of an unhealthy state.

SUBMITTER: Jaimes JD

PROVIDER: S-EPMC7993802 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundMultiple factors can influence stool sample integrity upon sample collection. Preservation of faecal samples for microbiome studies is therefore an important step, particularly in tropical regions where resources are limited and high temperatures may significantly influence microbiota profiles. Freezing is the accepted standard to preserve faecal samples however, cold chain methods are often unfeasible in fieldwork scenarios particularly in low and middle-income countries and alternatives are required. This study therefore aimed to address the impact of different preservative methods, time-to-freezing at ambient tropical temperatures, and stool heterogeneity on stool microbiome diversity and composition under real-life physical environments found in resource-limited fieldwork conditions.MethodsInner and outer stool samples collected from one specimen obtained from three children were stored using different storage preservation methods (raw, ethanol and RNAlater) in a Ugandan field setting. Mixed stool was also stored using these techniques and frozen at different time-to-freezing intervals post-collection from 0-32 h. Metataxonomic profiling was used to profile samples, targeting the V1-V2 regions of 16S rRNA with samples run on a MiSeq platform. Reads were trimmed, combined and aligned to the Greengenes database. Microbial diversity and composition data were generated and analysed using Quantitative Insights Into Microbial Ecology and R software.ResultsChild donor was the greatest predictor of microbiome variation between the stool samples, with all samples remaining identifiable to their child of origin despite the stool being stored under a variety of conditions. However, significant differences were observed in composition and diversity between preservation techniques, but intra-preservation technique variation was minimal for all preservation methods, and across the time-to-freezing range (0-32 h) used. Stool heterogeneity yielded no apparent microbiome differences.ConclusionsStool collected in a fieldwork setting for comparative microbiome analyses should ideally be stored as consistently as possible using the same preservation method throughout.

Project description:Infants born prematurely, particularly extremely low birth weight infants (ELBW) have altered gut microbial communities. Factors such as maternal health, gut immaturity, delivery mode, and antibiotic treatments are associated with microbiota disturbances, and are linked to an increased risk of certain diseases such as necrotising enterocolitis. Therefore, there is a requirement to optimally characterise microbial profiles in this at-risk cohort, via standardisation of methods, particularly for studying the influence of microbiota therapies (e.g. probiotic supplementation) on community profiles and health outcomes. Profiling of faecal samples using the 16S rRNA gene is a cost-efficient method for large-scale clinical studies to gain insights into the gut microbiota and additionally allows characterisation of cohorts were sample quantities are compromised (e.g. ELBW infants). However, DNA extraction method, and the 16S rRNA region targeted can significantly change bacterial community profiles obtained, and so confound comparisons between studies. Thus, we sought to optimise a 16S rRNA profiling protocol to allow standardisation for studying ELBW infant faecal samples, with or without probiotic supplementation.Using ELBW faecal samples, we compared three different DNA extraction methods, and subsequently PCR amplified and sequenced three hypervariable regions of the 16S rRNA gene (V1 + V2 + V3), (V4 + V5) and (V6 + V7 + V8), and compared two bioinformatics approaches to analyse results (OTU and paired end). Paired shotgun metagenomics was used as a 'gold-standard'.Results indicated a longer bead-beating step was required for optimal bacterial DNA extraction and that sequencing regions (V1 + V2 + V3) and (V6 + V7 + V8) provided the most representative taxonomic profiles, which was confirmed via shotgun analysis. Samples sequenced using the (V4 + V5) region were found to be underrepresented in specific taxa including Bifidobacterium, and had altered diversity profiles. Both bioinformatics 16S rRNA pipelines used in this study (OTU and paired end) presented similar taxonomic profiles at genus level.We determined that DNA extraction from ELBW faecal samples, particularly those infants receiving probiotic supplementation, should include a prolonged beat-beating step. Furthermore, use of the 16S rRNA (V1 + V2 + V3) and (V6 + V7 + V8) regions provides reliable representation of ELBW microbiota profiles, while inclusion of the (V4 + V5) region may not be appropriate for studies where Bifidobacterium constitutes a resident microbiota member.

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Stool metabolome-microbiota evaluation among children and adolescents with obesity, overweight, and normal-weight using 1H NMR and 16S rRNA gene profiling.

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