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.

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The human intestinal microbiota is known to play an important role in human health and disease, and with the advent of novel molecular techniques, disease-specific variations in its composition have been found. However, analysis of the intestinal microbiota has not yet been applicable in large-scale clinical research or routine diagnostics because of the complex and expensive nature of the techniques needed. Here, we describe a new PCR-based profiling technique for high-throughput analysis of the human intestinal microbiota, which we have termed IS-pro. This technique combines bacterial species differentiation by the length of the 16S-23S rDNA interspace region with instant taxonomic classification by phylum-specific fluorescent labeling of PCR primers. We validated IS-pro in silico, in vitro, and in vivo, on human colonic biopsies and feces, and introduced a standardized protocol for data analysis. IS-pro is easy to implement in general clinical microbiological laboratories with access to capillary gel electrophoresis, and the high-throughput nature of the test makes analysis of large numbers of samples feasible. This combination renders IS-pro ideally suited for use in clinical research and routine diagnostics.

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.

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ObjectivesDisruption of the intestinal microbiota is considered an etiological factor in pediatric functional constipation. Scientifically based selection of potential beneficial probiotic strains in functional constipation therapy is not feasible due to insufficient knowledge of microbiota composition in affected subjects. The aim of this study was to describe microbial composition and diversity in children with functional constipation, compared to healthy controls.Study DesignFecal samples from 76 children diagnosed with functional constipation according to the Rome III criteria (median age 8.0 years; range 4.2–17.8) were analyzed by IS-pro, a PCR-based microbiota profiling method. Outcome was compared with intestinal microbiota profiles of 61 healthy children (median 8.6 years; range 4.1–17.9). Microbiota dissimilarity was depicted by principal coordinate analysis (PCoA), diversity was calculated by Shannon diversity index. To determine the most discriminative species, cross validated logistic ridge regression was performed.ResultsApplying total microbiota profiles (all phyla together) or per phylum analysis, no disease-specific separation was observed by PCoA and by calculation of diversity indices. By ridge regression, however, functional constipation and controls could be discriminated with 82% accuracy. Most discriminative species were Bacteroides fragilis, Bacteroides ovatus, Bifidobacterium longum, Parabacteroides species (increased in functional constipation) and Alistipes finegoldii (decreased in functional constipation).ConclusionsNone of the commonly used unsupervised statistical methods allowed for microbiota-based discrimination of children with functional constipation and controls. By ridge regression, however, both groups could be discriminated with 82% accuracy. Optimization of microbiota-based interventions in constipated children warrants further characterization of microbial signatures linked to clinical subgroups of functional constipation.

Numerous diseases linked to microbial imbalance can be traced back to childhood, illustrating the impact of the juvenile microbiota development from infancy toward adulthood. However, knowledge on this subject is currently very limited. The primary aim of this study was to characterize composition and short- and long-term stability of the intestinal microbiota in healthy children. Between November 2011 and June 2014, 61 children 2 to 18 yr of age from different areas in The Netherlands were included and instructed to collect fecal samples weekly, for 6 wk, and a follow-up sample after 18 mo. The intergenic spacer profiling technique (IS-pro) was used to analyze all available fecal samples. Microbial diversity was calculated by the Shannon diversity index and individual compositional stability by comparing all collection time points. Microbial stability varied per phylum (P< 0.0005), declined rapidly in a short time period, and subsequently stabilized on the long run with very gradual variation, leading to an overall compositional stability of 70% on average over a period of 18 mo. Higher species diversity was correlated to a higher overall compositional stability (P< 0.001). We observed an age-independent bacterial shared core consisting of a limited number of species. In conclusion, in this study, we showed that microbial composition stability in children varied per phylum, at both short-term and long-term intervals. Healthy children seem to share a microbiome core consisting of a limited number of species.-De Meij, T. G. J., Budding, A. E., de Groot, E. F. J., Jansen, F. M., Kneepkens, C. M. F., Benninga, M. A., Penders, J., van Bodegraven, A. A., Savelkoul, P. H. M. Composition and stability of intestinal microbiota of healthy children within a Dutch population.