Quantifying diet-induced metabolic changes of the human gut microbiome

The human gut microbiome is known to be associated with various human disorders, but a major challenge is to go beyond association studies and elucidate causalities. Mathematical modeling of the human gut microbiome at a genome scale is a useful tool to decipher microbe-microbe, diet-microbe and microbe-host interactions. Here, we describe the CASINO (Community And Systems-level INteractive Optimization) toolbox, a comprehensive computational platform for analysis of microbial communities through metabolic modeling. We first validated the toolbox by simulating and testing the performance of single bacteria and whole communities in vitro. Focusing on metabolic interactions between the diet, gut microbiota, and host metabolism, we demonstrated the predictive power of the toolbox in a diet-intervention study of 45 obese and overweight individuals and validated our predictions by fecal and blood metabolomics data. Thus, modeling could quantitatively describe altered fecal and serum amino acid levels in response to diet intervention.

Serum estradiol: oocyte ratio as a predictor of reproductive outcome: an analysis of data from >9000 IVF cycles in the Republic of Ireland

Purpose The purpose of this study was to evaluate the serum estradiol (E2) per oocyte ratio (EOR) as a function of selected embryology events and reproductive outcomes with IVF. Methods This retrospective analysis included all IVF cycles where oocyte collection and fresh transfer occurred between January 2001 and November 2012 at a single institution. Patients were divided by three age groups (<35, 35–39, and ≥40 years) and further stratified into nine groups based on EOR (measured in pmol/L/oocyte). Terminal serum E2 (pmol/mL) was recorded on day of hCG trigger administration, and fertilization rate, cleavage rate, number of good quality embryos, and reproductive outcomes were recorded for each IVF cycle. Results During the study interval, 9109 oocyte retrievals were performed for 5499 IVF patients (mean = 1.7 cycles/patient). A total of 63.4 % of transfers were performed on day 3 (n = 4926), while 36.6 % were carried out on day 5 (n = 2843). Clinical pregnancy rates were highest in patients with EOR of 250–750 and declined as this ratio increased, independent of patient age. While the odds ratio (OR) for clinical pregnancy where EOR = 250–750 vs. EOR > 1500 was 3.4 (p < 0.001; 95 % CI 2.67–4.34), no statistically significant correlation was seen in fertilization, cleavage rates or number of good quality embryos as a function of EOR. Conclusions Predicting reproductive outcomes with IVF has great utility both for patients and providers. The former have the opportunity to build realistic expectations, and the latter are better able to counsel according to measured clinical parameters. A better understanding of follicular dynamics and ovarian response to gonadotropin stimulation could optimize IVF treatments going forward.