Changes in Human Fecal Microbiota Due to Chemotherapy Analyzed by TaqMan-PCR, 454 Sequencing and PCR-DGGE Fingerprinting

BACKGROUND: We investigated whether chemotherapy with the presence or absence of antibiotics against different kinds of cancer changed the gastrointestinal microbiota. METHODOLOGY/PRINCIPAL FINDINGS: Feces of 17 ambulant patients receiving chemotherapy with or without concomitant antibiotics were analyzed before and after the chemotherapy cycle at four time points in comparison to 17 gender-, age- and lifestyle-matched healthy controls. We targeted 16S rRNA genes of all bacteria, Bacteroides, bifidobacteria, Clostridium cluster IV and XIVa as well as C. difficile with TaqMan qPCR, denaturing gradient gel electrophoresis (DGGE) fingerprinting and high-throughput sequencing. After a significant drop in the abundance of microbiota (p = 0.037) following a single treatment the microbiota recovered within a few days. The chemotherapeutical treatment marginally affected the Bacteroides while the Clostridium cluster IV and XIVa were significantly more sensitive to chemotherapy and antibiotic treatment. DGGE fingerprinting showed decreased diversity of Clostridium cluster IV and XIVa in response to chemotherapy with cluster IV diversity being particularly affected by antibiotics. The occurrence of C. difficile in three out of seventeen subjects was accompanied by a decrease in the genera Bifidobacterium, Lactobacillus, Veillonella and Faecalibacterium prausnitzii. Enterococcus faecium increased following chemotherapy. CONCLUSIONS/SIGNIFICANCE: Despite high individual variations, these results suggest that the observed changes in the human gut microbiota may favor colonization with C. difficile and Enterococcus faecium. Perturbed microbiota may be a target for specific mitigation with safe pre- and probiotics

Therapeutic perspectives of epigenetically active nutrients

Many nutrients are known for a wide range of activities in prevention and alleviation of various diseases. Recently, their potential role in epigenetics regulating human health has become evident, although specific mechanisms are still unclear. Thus, nutriepigenetics/nutriepigenomics has emerged as a new and promising field in current epigenetics research in the past few years. In particular, polyphenols, as part of the central dynamic interaction between the genome and the environment with specificity at physiological concentrations, are well known to affect mechanisms underlying human health. This review summarizes the effects of dietary compounds on epigenetic mechanisms in the regulation of gene expression including expression of enzymes and other molecules responsible for drug absorption, distribution, metabolism, and excretion in cancer, metabolic syndrome, neurodegenerative disorders, and hormonal dysfunctions

Supplementary Material for: <b><i>Interleukin-6</i></b> CpG Methylation and Body Weight Correlate Differently in Type 2 Diabetes Patients Compared to Obese and Lean Controls

<b><i>Background/Aims:</i></b> Diabetes mellitus type 2 (DMT2) is accompanied by systemic low-grade inflammation with elevated levels of interleukin-6 (IL-6), which is encoded by a gene <i>(IL-6)</i> previously shown to be regulated by DNA methylation. We investigated seven CpG sites in <i>IL-6</i> in individuals with DMT2, obese individuals and lean controls. Further, the DMT2 group received the glucagon-like peptide 1 agonist liraglutide. <b><i>Methods:</i></b> Blood samples were taken at the beginning of the study and after 4 months. The DNA methylation was assessed using pyrosequencing. <b><i>Results:</i></b> Methylation levels at the CpG sites -664, -628 and +13 at the first sampling time point (T1) and at -666 and -664 at the second sampling time point (T2) correlated negatively with initial body weight in the DMT2 group. We found positive correlations for the obese and the lean control group. In the obese group, CpG +27 methylation at T1 correlated with initial body weight (r = 0.685; p = 0.014). In the lean group, CpG -664 at T1 (r = 0.874; p = 0.005) and CpG -628 at T2 (r = 0.632; p = 0.050) correlated with initial body weight. <b><i>Conclusion:</i></b> These findings are an informative basis for further studies to elucidate epigenetic mechanisms underlying DMT2. Additionally, our results might provide starting points for the development of biomarkers for prevention and therapy strategies

Timing of food intake impacts daily rhythms of human salivary microbiota: a randomized, crossover study

The composition of the diet (what we eat) has been widely related to the microbiota profile. However, whether the timing of food consumption (when we eat) influences microbiota in humans is unknown. A randomized, crossover study was performed in 10 healthy normal-weight young women to test the effect of the timing of food intake on the human microbiota in the saliva and fecal samples. More specifically, to determine whether eating late alters daily rhythms of human salivary microbiota, we interrogated salivary microbiota in samples obtained at 4 specific time points over 24 h, to achieve a better understanding of the relationship between food timing and metabolic alterations in humans. Results revealed significant diurnal rhythms in salivary diversity and bacterial relative abundance (i.e., TM7 and Fusobacteria) across both early and late eating conditions. More importantly, meal timing affected diurnal rhythms in diversity of salivary microbiota toward an inverted rhythm between the eating conditions, and eating late increased the number of putative proinflammatory taxa, showing a diurnal rhythm in the saliva. In a randomized, crossover study, we showed for the first time the impact of the timing of food intake on human salivary microbiota. Eating the main meal late inverts the daily rhythm of salivary microbiota diversity which may have a deleterious effect on the metabolism of the hostThis work was supported by Spanish Government of Economy and Competitiveness (MINECO) Grants AGL2015-707487-P (to M.C.C.) and SAF2014-52480R; the European Regional Development Fund (ERDF); U.S. National Institutes of Health (NIH) National Institute of Diabetes and Digestive and Kidney Diseases Grants R01DK102696 and DK1-R01DK_105072-01A1 (to M.G.), and R01 DK099512 and R01DK105072 (to F.A.J.L.S.); and NIH National, Heart, Lung, and Blood Institute Grants R01 HL094806, R01 HL140574 and R01 HL118601 (to F.A.J.L.S.). F.A.J.L.S. has received speaker fees from Bayer Healthcare, Sentara Healthcare, Philips, and Kellogg Company. The remaining authors declare no conflicts of interest.Peer reviewe