The relative contribution of novel fibers such as polydextrose and soluble corn fiber (SCF) to the human gut microbiome and its association with host physiology has not been well studied. This study was conducted to test the impact of polydextrose and SCF on the composition of the human gut microbiota using 454 pyrosequencing and to identify associations among fecal microbiota and fermentative end-products. Healthy adult men (n = 20) with a mean dietary fiber (DF) intake of 14 g/d were enrolled in a randomized, double-blind, placebo-controlled crossover study. Participants consumed 3 treatment snack bars/d during each 21-d period that contained no supplemental fiber (NFC), polydextrose (PDX; 21 g/d), or SCF (21 g/d) for 21 d. There were no washout periods. Fecal samples were collected on d 16-21 of each period; DNA was extracted, followed by amplification of the V4-V6 region of the 16S rRNA gene using barcoded primers. PDX and SCF significantly affected the relative abundance of bacteria at the class, genus, and species level. The consumption of PDX and SCF led to greater fecal Clostridiaceae and Veillonellaceae and lower Eubacteriaceae compared with a NFC. The abundance of Faecalibacterium, Phascolarctobacterium, and Dialister was greater (P < 0.05) in response to PDX and SCF intake, whereas Lactobacillus was greater (P < 0.05) only after SCF intake. Faecalibacterium prausnitzii, well known for its antiinflammatory properties, was greater (P < 0.05) after fiber consumption. Principal component analysis clearly indicated a distinct clustering of individuals consuming supplemental fibers. Our data demonstrate a beneficial shift in the gut microbiome of adults consuming PDX and SCF, with potential application as prebiotics.
[Show abstract][Hide abstract] ABSTRACT: It has been suggested that gut microbiota is altered in Type 2 Diabetes Mellitus (T2DM) patients.
This study was to evaluate the effect of the prebiotic xylooligosaccharide (XOS) on the gut microbiota in both healthy and prediabetic (Pre-DM) subjects, as well as impaired glucose tolerance (IGT) in Pre-DM.
Pre-DM (n = 13) or healthy (n = 16) subjects were randomized to receive 2 g/day XOS or placebo for 8-weeks. In Pre-DM subjects, body composition and oral glucose tolerance test (OGTT) was done at baseline and week 8. Stool from Pre-DM and healthy subjects at baseline and week 8 was analyzed for gut microbiota characterization using Illumina MiSeq sequencing.
We identified 40 Pre-DM associated bacterial taxa. Among them, the abundance of the genera Enterorhabdus, Howardella, and Slackia was higher in Pre-DM. XOS significantly decreased or reversed the increase in abundance of Howardella, Enterorhabdus, and Slackia observed in healthy or Pre-DM subjects. Abundance of the species Blautia hydrogenotrophica was lower in pre-DM subjects, while XOS increased its abundance. In Pre-DM, XOS showed a tendency to reduce OGTT 2-h insulin levels (P = 0.13), but had no effect on body composition, HOMA-IR, serum glucose, triglyceride, satiety hormones, and TNFα.
This is the first clinical observation of modifications of the gut microbiota by XOS in both healthy and Pre-DM subjects in a pilot study. Prebiotic XOS may be beneficial in reversing changes in the gut microbiota during the development of diabetes.
Frontiers in Physiology 09/2015; 1(6). DOI:10.3389/fphys.2015.00216 · 3.53 Impact Factor
"Most members of the family Veillonellaceae (for example, Veillonella and Megasphaera) ferment lactate , , which may explain a potential metabolic link between Veillonella and Prevotella as both genera Veillonella and Prevotella also appeared in the co-occurrence network . Other studies show that the abundance of the family Veillonellaceae increased when polydextrose and soluble corn fiber were part of an adult diet . However, in equine large intestines, abundance of Veillonellaceae remained constant even with diets with increased levels of sugar and starch . "
[Show abstract][Hide abstract] ABSTRACT: High proportions of autistic children suffer from gastrointestinal (GI) disorders, implying a link between autism and abnormalities in gut microbial functions. Increasing evidence from recent high-throughput sequencing analyses indicates that disturbances in composition and diversity of gut microbiome are associated with various disease conditions. However, microbiome-level studies on autism are limited and mostly focused on pathogenic bacteria. Therefore, here we aimed to define systemic changes in gut microbiome associated with autism and autism-related GI problems. We recruited 20 neurotypical and 20 autistic children accompanied by a survey of both autistic severity and GI symptoms. By pyrosequencing the V2/V3 regions in bacterial 16S rDNA from fecal DNA samples, we compared gut microbiomes of GI symptom-free neurotypical children with those of autistic children mostly presenting GI symptoms. Unexpectedly, the presence of autistic symptoms, rather than the severity of GI symptoms, was associated with less diverse gut microbiomes. Further, rigorous statistical tests with multiple testing corrections showed significantly lower abundances of the genera Prevotella, Coprococcus, and unclassified Veillonellaceae in autistic samples. These are intriguingly versatile carbohydrate-degrading and/or fermenting bacteria, suggesting a potential influence of unusual diet patterns observed in autistic children. However, multivariate analyses showed that autism-related changes in both overall diversity and individual genus abundances were correlated with the presence of autistic symptoms but not with their diet patterns. Taken together, autism and accompanying GI symptoms were characterized by distinct and less diverse gut microbial compositions with lower levels of Prevotella, Coprococcus, and unclassified Veillonellaceae.
PLoS ONE 07/2013; 8(7):e68322. DOI:10.1371/journal.pone.0068322 · 3.23 Impact Factor
"The aim of the present study was to examine whether diabetes mellitus might affect subgingival bacterial composition by high-throughput 16S rDNA sequencing with the 454 pyrosequencing technology , which has been widely adopted by numerous human microbiome projects including several studies characterizing the oral microbiome (e.g., , , , , , , ). Our study design included non-diabetic subjects without periodontitis (P−D−), non-diabetic subjects with periodontitis (P+D−), type 2 diabetic patients without periodontitis (P−D+), and type 2 diabetic patients with periodontitis (P+D+). "
[Show abstract][Hide abstract] ABSTRACT: Diabetes mellitus is a major risk factor for chronic periodontitis. We investigated the effects of type 2 diabetes on the subgingival plaque bacterial composition by applying culture-independent 16S rDNA sequencing to periodontal bacteria isolated from four groups of volunteers: non-diabetic subjects without periodontitis, non-diabetic subjects with periodontitis, type 2 diabetic patients without periodontitis, and type 2 diabetic patients with periodontitis. A total of 71,373 high-quality sequences were produced from the V1-V3 region of 16S rDNA genes by 454 pyrosequencing. Those 16S rDNA sequences were classified into 16 phyla, 27 classes, 48 orders, 85 families, 126 genera, and 1141 species-level OTUs. Comparing periodontally healthy samples with periodontitis samples identified 20 health-associated and 15 periodontitis-associated OTUs. In the subjects with healthy periodontium, the abundances of three genera (Prevotella, Pseudomonas, and Tannerella) and nine OTUs were significantly different between diabetic patients and their non-diabetic counterparts. In the subjects carrying periodontitis, the abundances of three phyla (Actinobacteria, Proteobacteria, and Bacteriodetes), two genera (Actinomyces and Aggregatibacter), and six OTUs were also significantly different between diabetics and non-diabetics. Our results show that type 2 diabetes mellitus could alter the bacterial composition in the subgingival plaque.
PLoS ONE 04/2013; 8(4):e61516. DOI:10.1371/journal.pone.0061516 · 3.23 Impact Factor
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.