Background: The therapeutic potential of faecal microbiota transplantation (FMT) is under investigation for a range of inflammatory conditions. While mechanisms of benefit are poorly understood, most models rely on the viability of transplanted microbes. We hypothesised that protocols commonly used in the preparation of faecal transplants will substantially reduce the number, diversity and functional potential of viable microbes. Methods: Stools from eight screened donors were processed under strict anaerobic conditions, in ambient air, and freeze-thawed. Propidium monoazide (PMA) sample treatment was combined with quantitative PCR, 16S rRNA gene amplicon sequencing and short-chain fatty acid (SCFA) analysis to define the viable microbiota composition and functional potential. Findings: Approximately 50% of bacterial content of stool processed immediately under strict anaerobic conditions was non-viable. Homogenisation in ambient air or freeze-thaw reduced viability to 19% and 23% respectively. Processing of samples in ambient air resulted in up to 12-fold reductions in the abundance of important commensal taxa, including the highly butyrogenic species Faecalibacterium prausnitzii, Subdoligranulum variable, and Eubacterium hallii. The adverse impact of atmospheric oxygen exposure on the capacity of the transplanted microbiota to support SCFA biosynthesis was demonstrated by significantly reduced butyrate and acetate production by faecal slurries processed in ambient air. In contrast, while reducing overall levels of viable bacteria, freeze-thaw did not significantly alter viable microbiota composition. Interpretation: The practice of preparing material for faecal transplantation in ambient air profoundly affects viable microbial content, disproportionately reducing the abundance of anaerobic commensals and the capacity for biosynthesis of important anti-inflammatory metabolites.

In addition to providing nutritional and bioactive factors necessary for infant development, human breast milk contains bacteria that contribute to the establishment of commensal microbiota in the infant. However, the composition of this bacterial community differs considerably between studies. We hypothesised that bacterial DnA extraction methodology from breast milk samples are a substantial contributor to these inter-study differences. We tested this hypothesis by applying five widely employed methodologies to a mock breast milk sample and four individual human breast milk samples. Significant differences in DNA yield and purity were observed between methods (P < 0.05). Microbiota composition, assessed by 16S rRNA gene amplicon sequencing, also differed significantly with extraction methodology (P < 0.05), including in the contribution of contaminant signal. Concerningly, many of the bacterial taxa identified here as contaminants have been reported as components of the breast milk microbiome in other studies. These findings highlight the importance of using stringent, well-validated, DNA extraction methodologies for analysis of the breast milk microbiome, and exercising caution interpreting microbiota data from low-biomass contexts. In addition to nutrients and bioactive components, human breast milk contains bacteria 1 , commonly referred to as the breast milk microbiome. These bacterial populations are thought to contribute to the establishment of commensal bacterial communities in the infant, as well as supporting the maturation of the gut, and development of the immune system 1,2. The potential importance of microbes introduced with breast milk on early-life development has led to increasing efforts to accurately define them. Early culture-and PCR-based methods, predominantly reported the presence of members of the Staphylococcus, Streptococcus, Lactobacillus and Bifidobacterium genera 3-12. More recently, 16S rRNA gene amplicon sequencing has become an increasingly popular approach to characterising the bacterial content of breast milk samples 13-33. By enabling the detection of species that are refractory to standard culture methodologies, as well as providing insight into the relative abundance of constitutive bacteria, 16S rRNA gene sequencing offers substantial analytical advantages. However, the composition of the breast milk microbiome reported in sequencing-based studies varies substantially. For example, while two studies have described a "core" human breast milk microbiome (bacteria that are present in all samples analysed) from healthy mothers, consisting of 7 and 9 taxa respectively, only three of these taxa were present in both (Propionibacterium, Staphylococcus, and Streptococcus) 27,34. Notably, many of the other bacterial taxa often reported as part of the breast milk microbiome, including

BackgroundHost factors and complications have been associated with higher mortality in infective endocarditis (IE). We sought to develop and validate a model of clinical characteristics to predict 6‐month mortality in IE.Methods and ResultsUsing a large multinational prospective registry of definite IE (International Collaboration on Endocarditis [ICE]–Prospective Cohort Study [PCS], 2000–2006, n=4049), a model to predict 6‐month survival was developed by Cox proportional hazards modeling with inverse probability weighting for surgery treatment and was internally validated by the bootstrapping method. This model was externally validated in an independent prospective registry (ICE‐PLUS, 2008–2012, n=1197). The 6‐month mortality was 971 of 4049 (24.0%) in the ICE‐PCS cohort and 342 of 1197 (28.6%) in the ICE‐PLUS cohort. Surgery during the index hospitalization was performed in 48.1% and 54.0% of the cohorts, respectively. In the derivation model, variables related to host factors (age, dialysis), IE characteristics (prosthetic or nosocomial IE, causative organism, left‐sided valve vegetation), and IE complications (severe heart failure, stroke, paravalvular complication, and persistent bacteremia) were independently associated with 6‐month mortality, and surgery was associated with a lower risk of mortality (Harrell's C statistic 0.715). In the validation model, these variables had similar hazard ratios (Harrell's C statistic 0.682), with a similar, independent benefit of surgery (hazard ratio 0.74, 95% CI 0.62–0.89). A simplified risk model was developed by weight adjustment of these variables.ConclusionsSix‐month mortality after IE is ≈25% and is predicted by host factors, IE characteristics, and IE complications. Surgery during the index hospitalization is associated with lower mortality but is performed less frequently in the highest risk patients. A simplified risk model may be used to identify specific risk subgroups in IE.