In a longitudinal study of fecal microbiota of children from 5 weeks through 6 to 11 years, we tracked changes in diversity and composition associated with the development of allergies and asthma.

Appropriate isolation methods are essential for unravelling the relative contribution of extracellular vesicles (EVs) and the EV-free secretome to homeostasis and disease. We hypothesized that ultrafiltration followed by size exclusion chromatography (UF-SEC) provides well-matched concentrates of EVs and free secreted molecules for proteomic and functional studies. Conditioned media of BEAS-2B bronchial epithelial cells were concentrated on 10 kDa centrifuge filters, followed by separation of EVs and free protein using sepharose CL-4B SEC. Alternatively, EVs were isolated by ultracentrifugation. EV recovery was estimated by bead-coupled flow cytometry and tuneable resistive pulse sensing. The proteomic composition of EV isolates and SEC protein fractions was characterized by nano LC-MS/MS. UF-SEC EVs tended to have a higher yield and EV-to-protein rate of purity than ultracentrifugation EVs. UF-SEC EVs and ultracentrifugation EVs showed similar fold-enrichments for biological pathways that were distinct from those of UF-SEC protein. Treatment of BEAS-2B cells with UF-SEC protein, but not with either type of EV isolate increased the IL-8 concentration in the media whereas EVs, but not protein induced monocyte adhesion to endothelial cells. Thus, UF-SEC is a useful alternative for ultracentrifugation and allows comparing the proteomic composition and functional effects of EVs and free secreted molecules.

Large-scale cohort studies are currently being designed to investigate the human microbiome in health and disease. Adequate sampling strategies are required to limit bias due to shifts in microbial communities during sampling and storage. Therefore, we examined the impact of different sampling and storage conditions on the stability of fecal microbial communities in healthy and diseased subjects. Fecal samples from 10 healthy controls, 10 irritable bowel syndrome and 8 inflammatory bowel disease patients were collected on site, aliquoted immediately after defecation and stored at -80°C, -20°C for 1 week, at +4°C or room temperature for 24 hours. Fecal transport swabs (FecalSwab, Copan) were collected and stored for 48-72 hours at room temperature. We used pyrosequencing of the 16S gene to investigate the stability of microbial communities. Alpha diversity did not differ between all storage methods and -80°C, except for the fecal swabs. UPGMA clustering and principal coordinate analysis showed significant clustering by test subject (p<0.001) but not by storage method. Bray-Curtis dissimilarity and (un)weighted UniFrac showed a significant higher distance between fecal swabs and -80°C versus the other methods and -80°C samples (p<0.009). The relative abundance of Ruminococcus and Enterobacteriaceae did not differ between the storage methods versus -80°C, but was higher in fecal swabs (p<0.05). Storage up to 24 hours (at +4°C or room temperature) or freezing at -20°C did not significantly alter the fecal microbial community structure compared to direct freezing of samples from healthy subjects and patients with gastrointestinal disorders.

The composition of the gut microbiota is associated with various disease states, most notably inflammatory bowel disease, obesity and malnutrition. This underlines that analysis of intestinal microbiota is potentially an interesting target for clinical diagnostics. Currently, the most commonly used sample types are feces and mucosal biopsy specimens. Because sampling method, storage and processing of samples impact microbiota analysis, each sample type has its own limitations. An ideal sample type for use in routine diagnostics should be easy to obtain in a standardized fashion without perturbation of the microbiota. Rectal swabs may satisfy these criteria, but little is known about microbiota analysis on these sample types. In this study we investigated the characteristics and applicability of rectal swabs for gut microbiota profiling in a clinical routine setting in patients presenting with various gastro-intestinal disorders. We found that rectal swabs appeared to be a convenient means of sampling the human gut microbiota. Swabs can be performed on demand, whenever a patient presents; swab-derived microbiota profiles are reproducible, whether they are gathered at home by patients or by medical professionals in an outpatient setting and may be ideally suited for clinical diagnostics and large-scale studies.

STUDY QUESTION Is the presence or absence of certain vaginal bacteria associated with failure or success to become pregnant after an in vitro fertilization (IVF) or IVF with intracytoplasmic sperm injection (IVF-ICSI) treatment? SUMMARY ANSWER Microbiome profiling with the use of interspace profiling (IS-pro) technique enables stratification of the chance of becoming pregnant prior to the start of an IVF or IVF-ICSI treatment. WHAT IS KNOWN ALREADY Live-birth rates for an IVF or IVF-ICSI treatment vary between 25 and 35% per cycle and it is difficult to predict who will or will not get pregnant after embryo transfer (ET). Recently, it was suggested that the composition of the vaginal microbiota prior to treatment might predict pregnancy outcome. Analysis of the vaginal microbiome prior to treatment might, therefore, offer an opportunity to improve the success rate of IVF or IVF-ICSI. STUDY DESIGN, SIZE, DURATION In a prospective cohort study, 303 women (age, 20–42 years) undergoing IVF or IVF-ICSI treatment in the Netherlands were included between June 2015 and March 2016. PARTICIPANTS/MATERIALS, SETTING, METHODS Study subjects provided a vaginal sample before the start of the IVF or IVF-ICSI procedure. The vaginal microbiota composition was determined using the IS-pro technique. IS-pro is a eubacterial technique based on the detection and categorization of the length of the 16S–23S rRNA gene interspace region. Microbiome profiles were assigned to community state types based on the dominant bacterial species. The predictive accuracy of the microbiome profiles for IVF and IVF-ICSI outcome of fresh ET was evaluated by a combined prediction model based on a small number of bacterial species. From this cohort, a model was built to predict outcome of fertility treatment. This model was externally validated in a cohort of 50 women who were undergoing IVF or IVF-ICSI treatment between March 2018 and May 2018 in the Dutch division of the MVZ VivaNeo Kinderwunschzentrum Düsseldorf, Germany. MAIN RESULTS AND THE ROLE OF CHANCE In total, the vaginal microbiota of 192 women who underwent a fresh ET could be analysed. Women with a low percentage of Lactobacillus in their vaginal sample were less likely to have a successful embryo implantation. The prediction model identified a subgroup of women (17.7%, n = 34) who had a low chance to become pregnant following fresh ET. This failure was correctly predicted in 32 out of 34 women based on the vaginal microbiota composition, resulting in a predictive accuracy of 94% (sensitivity, 26%; specificity, 97%). Additionally, the degree of dominance of Lactobacillus crispatus was an important factor in predicting pregnancy. Women who had a favourable profile as well as <60% L. crispatus had a high chance of pregnancy: more than half of these women (50 out of 95) became pregnant. In the external validation cohort, none of the women who had a negative prediction (low chance of pregnancy) became pregnant. LIMITATIONS, REASONS FOR CAUTION Because our study uses a well-defined study population, the results will be limited to the IVF or IVF-ICSI population. Whether these results can be extrapolated to the general population trying to achieve pregnancy without ART cannot be determined from these data. WIDER IMPLICATIONS OF THE FINDINGS Our results indicate that vaginal microbiome profiling using the IS-pro technique enables stratification of the chance of becoming pregnant prior to the start of an IVF or IVF-ICSI treatment. Knowledge of their vaginal microbiota may enable couples to make a more balanced decision regarding timing and continuation of their IVF or IVF-ICSI treatment cycles. STUDY FUNDING/COMPETING INTEREST(S) This study was financed by NGI Pre-Seed 2014–2016, RedMedTech Discovery Fund 2014–2017, STW Valorisation grant 1 2014–2015, STW Take-off early phase trajectory 2015–2016 and Eurostars VALBIOME grant (reference number: 8884). The employer of W.J.S.S.C. has in collaboration with ARTPred acquired a MIND subsidy to cover part of the costs of this collaboration project. The following grants are received but not used to finance this study: grants from Innovatie Prestatie Contract, MIT Haalbaarheid, other from Dutch R&D tax credit WBSO, RedMedTech Discovery Fund, (J.D.d.J.). Grants from Ferring (J.S.E.L., K.F., C.B.L. and J.M.J.S.S.), Merck Serono (K.F. and C.B.L.), Dutch Heart Foundation (J.S.E.L.), Metagenics Inc. (J.S.E.L.), GoodLife (K.F.), Guerbet (C.B.L.). R.K. is employed by ARTPred B.V. during her PhD at Erasmus Medical Centre (MC). S.A.M. has a 100% University appointment. I.S.P.H.M.S., S.A.M. and A.E.B. are co-owners of IS-Diagnostics Ltd. J.D.d.J. is co-owner of ARTPred B.V., from which he reports personal fees. P.H.M.S. reports non-financial support from ARTPred B.V. P.H.M.S., J.D.d.J. and A.E.B. have obtained patents `Microbial population analysis’ (9506109) and `Microbial population analysis’ (20170159108), both licenced to ARTPred B.V. J.D.d.J. and A.E.B. report patent applications `Method and kit for predicting the outcome of an assisted reproductive technology procedure’ (392EPP0) and patent `Method and kit for altering the outcome of an assisted reproductive technology procedure’ by ARTPred. W.J.S.S.C. received personal consultancy and educational fees from Goodlife Fertility B.V. J.S.E.L. reports personal consultancy fees from ARTPred B.V., Titus Health B.V., Danone, Euroscreen and Roche during the conduct of the study. J.S.E.L. and N.G.M.B. are co-applicants on an Erasmus MC patent (New method and kit for prediction success of in vitro fertilization) licenced to ARTPred B.V. F.J.M.B. reports personal fees from Advisory Board Ferring, Advisory Board Merck Serono, Advisory Board Gedeon Richter and personal fees from Educational activities for Ferring, outside the submitted work. K.F. reports personal fees from Ferring (commercial sponsor) and personal fees from GoodLife (commercial sponsor). C.B.L. received speakers’ fee from Ferring. J.M.J.S.S. reports personal fees and other from Merck Serono and personal fees from Ferring, unrelated to the submitted paper. The other authors declare that they have no competing interests. TRIAL REGISTRATION NUMBER ISRCTN83157250. Registered 17 August 2018. Retrospectively registered.

Disease-specific variations in intestinal microbiome composition have been found for a number of intestinal disorders, but little is known about diverticulitis. The purpose of this study was to compare the fecal microbiota of diverticulitis patients with control subjects from a general gastroenterological practice and to investigate the feasibility of predictive diagnostics based on complex microbiota data. Thirty-one patients with computed tomography (CT)-proven left-sided uncomplicated acute diverticulitis were included and compared with 25 control subjects evaluated for a range of gastrointestinal indications. A high-throughput polymerase chain reaction (PCR)-based profiling technique (IS-pro) was performed on DNA isolates from baseline fecal samples. Differences in bacterial phylum abundance and diversity (Shannon index) of the resulting profiles were assessed by conventional statistics. Dissimilarity in microbiome composition was analyzed with principal coordinate analysis (PCoA) based on cosine distance measures. To develop a prediction model for the diagnosis of diverticulitis, we used cross-validated partial least squares discriminant analysis (PLS-DA). Firmicutes/Bacteroidetes ratios and Proteobacteria load were comparable among patients and controls (p = 0.20). The Shannon index indicated a higher diversity in diverticulitis for Proteobacteria (p < 0.00002) and all phyla combined (p = 0.002). PCoA based on Proteobacteria profiles resulted in visually separate clusters of patients and controls. The diagnostic accuracy of the cross-validated PLS-DA regression model was 84 %. The most discriminative species derived largely from the family Enterobacteriaceae. Diverticulitis patients have a higher diversity of fecal microbiota than controls from a mixed population, with the phylum Proteobacteria defining the difference. The analysis of intestinal microbiota offers a novel way to diagnose diverticulitis.

No abstract

A new methicillin-resistant Staphylococcus aureus (MRSA) clone related to pig and cattle farming was detected in the Netherlands. We investigated the extent of S. aureus presence in meat and found 36 S. aureus strains in 79 samples. Two strains were MRSA; 1 was multilocus sequence type 398, the clone related to farming.