How Do Prebiotics Affect Human Intestinal Bacteria?-Assessment of Bacterial Growth with Inulin and XOS In Vitro.

Prebiotics are believed to exhibit high specificity in stimulating the growth or activity of a limited number of commensal microorganisms, thereby conferring health benefits to the host. However, the mechanism of action of prebiotics depends on multiple factors, including the composition of an individual's gut microbiota, and is therefore difficult to predict. It is known that different bacteria can utilize inulin and xylooligosaccharides (XOS), but an overview of which bacteria in the human gut may be affected is lacking. Detailed knowledge of how bacterial growth is affected by prebiotics is furthermore useful for the development of new synbiotics, which combine a living microorganism with a selective substrate to confer a health benefit to the host. Hence, we developed a statistical model to compare growth in vitro among typical human gut bacteria from different phylogenetic lineages. Based on continuous observation of the optical density (OD600), we compare maximal growth rates (rmax), maximal attained OD600 (ODmax), and area under the growth curve (AUC) of bacteria grown on inulin or XOS. The consideration of these three parameters suggests strain-specific preferences for inulin or XOS and reveals previously unknown preferences such as Streptococcus salivarius growth on XOS.

Assessment of the Gut Microbiota during Juice Fasting with and without Inulin Supplementation: A Feasibility Study in Healthy Volunteers.

Prebiotic inulin consumption provides health benefits to the host and has also been associated with a reduction in hunger cravings. We conducted a pilot crossover study to investigate the feasibility of a juice fasting intervention with and without inulin supplementation. We also examined trends of how the microbial community in the human gut adapts to juice fasting as well as to inulin intake during juice fasting. Six healthy volunteers were fasting for three consecutive days consuming a total of 300 kcal daily provided by vegetable juices, framed by two days with a total daily calorie intake of 800 kcal, respectively. During one fasting period, participants consumed additionally 24 g of inulin daily. Stool samples were collected for the analysis of the microbial composition using 16S rRNA gene sequencing. Although no significant uniform changes were observed on the microbiome, quantitative changes in the microbial composition suggest a stronger decrease in alpha-diversity after fasting compared to the fasting intervention with additional inulin intake. The intake of inulin did not affect compliance for the fasting intervention but appeared to increase relative abundance of Bifidobacteria in participants who tolerated it well. Further studies with a larger sample size to overcome inter-individual microbiota differences are warranted to verify our observations.

Eigen-Epistasis for detecting gene-gene interactions.

BACKGROUND: A large amount of research has been devoted to the detection and investigation of epistatic interactions in genome-wide association studies (GWASs). Most of the literature focuses on low-order interactions between single-nucleotide polymorphisms (SNPs) with significant main effects. RESULTS: In this paper we propose an original approach for detecting epistasis at the gene level, without systematically filtering on significant genes. We first compute interaction variables for each gene pair by finding its Eigen-Epistasis component, defined as the linear combination of Gene SNPs having the highest correlation with the phenotype. The selection of significant effects is done using a penalized regression method based on Group Lasso controlling the False Discovery Rate. CONCLUSION: The method is tested against two recent alternative proposals from the literature using synthetic data, and shows good performances in different settings. We demonstrate the power of our approach by detecting new gene-gene interactions on three genome-wide association studies.

The Relationship Between Apparent Temperature and Daily Number of Live Births in Montreal.

OBJECTIVES: Temperature is a hypothesized determinant of early delivery, but seasonal and long term trends, delayed effects of temperature, and the influence of extreme cold temperatures have not yet been addressed. We aim to study the influence of apparent temperature on daily number of births, considering lag structures, seasonality and long term trends. METHODS: We used daily number of births in conjunction with apparent outdoor temperatures between 1981 and 2010 in Montreal. We used Poisson regression combined with a distributed lag nonlinear model to consider non-linear relationships between temperature and daily number of births across specific lag periods. RESULTS: We found that apparent temperature was associated with the daily number of births in Montreal, with a 1-day delay. We found an increase in births on hot days, and decrease on cold days, both offset by a harvesting effect after 4 and 5 days. CONCLUSIONS FOR PRACTICE: This study suggests that the number of births is affected by extreme temperatures. Obstetric and perinatal service providers should be prepared for spikes in the number of births caused by extreme temperatures.