Background Multiple studies suggest a key role for gut microbiota in IgE-mediated food allergy (FA) development, but to date, none has studied it in the persistent state. Methods To characterize the gut microbiota composition and short-chain fatty acid (SCFAs) profiles associated with major food allergy groups, we recruited 233 patients with FA including milk (N = 66), sesame (N = 38), peanut (N = 71), and tree nuts (N = 58), and non-allergic controls (N = 58). DNA was isolated from fecal samples, and 16S rRNA gene sequences were analyzed. SCFAs in stool were analyzed from patients with a single allergy (N = 84) and controls (N = 31). Results The gut microbiota composition of allergic patients was significantly different compared to age-matched controls both in α-diversity and β-diversity. Distinct microbial signatures were noted for FA to different foods. Prevotella copri (P. copri) was the most overrepresented species in non-allergic controls. SCFAs levels were significantly higher in the non-allergic compared to the FA groups, whereas P. copri significantly correlated with all three SCFAs. We used these microbial differences to distinguish between FA patients and non-allergic healthy controls with an area under the curve of 0.90, and for the classification of FA patients according to their FA types using a supervised learning algorithm. Bacteroides and P. copri were identified as taxa potentially contributing to KEGG acetate-related pathways enriched in non-allergic compared to FA. In addition, overall pathway dissimilarities were found among different FAs. Conclusions Our results demonstrate a link between IgE-mediated FA and the composition and metabolic activity of the gut microbiota.

Background During aging, there is a physiological decline, an increase of morbidity and mortality, and a natural change in the gut microbiome. In this study, we investigated the influence of the gut microbiome on different metabolic parameters in adult and aged mice. Methods Fecal and blood samples from adult (n = 42, 100–300 days) and aging (n = 32, 550–750 days) mice were collected. Microbiome analysis was done using QIIME2. Mouse weight and body composition were measured using NMR, and insulin and leptin levels in the blood were measured with Mouse Adipokine Magnetic Bead Panel kit. Fecal microbiota transplantation experiments from adult and aged mice into young germ-free mice were carried out in order to examine the effect of the gut microbiome of adult and aging mice on weight, body composition, insulin, and leptin. Results We demonstrate that the microbiomes from adult and aged mice are distinguishable. We also report changes in metabolic parameters as we observed significantly higher weight and fat mass and low lean mass in aged compared to adult mice along with high insulin and leptin levels in the blood. The transplanted gut microbiome from aged mice transferred part of the phenotypes seen in aged mice. Fat body mass and insulin levels were higher in the mice who received feces from aged mice than mice receiving feces from adult mice. In addition, they consumed more food and had a higher respiratory quotient compared to mice receiving adult feces. Conclusions We conclude that aged mice have a gut microbiota with obesogenic characteristics. In addition, the gut bacterial population itself is sufficient to induce some of the manifestations of obesity.

The cohesin complex plays an important role in sister chromatin cohesion. Cohesin's core is composed of two structural maintenance of chromosome (SMC) proteins, called Smc1 and Smc3. SMC proteins are built from a globular hinge domain, a rod-shaped domain composed of long anti-parallel coiled-coil (CC), and a second globular adenosine triphosphatase domain called the head. The functions of both head and hinge domains have been studied extensively, yet the function of the CC region remains elusive. We identified a mutation in the CC of smc3 (L217P) that disrupts the function of the protein. Cells carrying the smc3-L217P allele have a strong cohesion defect and complexes containing smc3-L217P are not loaded onto the chromosomes. However, the mutation does not affect inter-protein interactions in either the core complex or with the Scc2 loader. We show by molecular dynamics and biochemistry that wild-type Smc3 can adopt distinct conformations, and that adenosine triphosphate (ATP) induces the conformational change. The L217P mutation restricts the ability of the mutated protein to switch between the conformations. We suggest that the function of the CC is to transfer ATP binding/hydrolysis signals between the head and the hinge domains. The results provide a new insight into the mechanism of cohesin activity.

Recently, several papers referred to the association of different bacteria with lupus in mice and humans. This is the first report to demonstrate the effect of a compound derived from helminths on the induction of remission in mice with lupus and its association with a bacterial change. We show that several genera, including Akkermansia, are associated with clinical and serological parameters of lupus, while other genera, including butyrate-producing bacteria, are associated with amelioration of disease following tuftsin and phosphorylcholine treatment.

Background Some microbiome composition can be associated with negative outcomes, including among others, obesity, disease and the failure to respond to treatment. Microbiota manipulation or supplementation have been argued to restore the microbiome associated with a healthy condition. Fecal Microbiota Transplantation (FMT) is among the most popular microbiome intervention procedures. Current practices are to choose the transplanted microbiome based on the donor phenotype, and not based on the expected recipient phenotype. However, the two differ drastically. We here propose an algorithm to predict the expected outcome of FMT from the donor phenotype, and optimize the FMT for different required outcomes. Results We here show, using multiple microbiome properties, that the donor and recipient phenotypes differ widely, and propose a tool to predict the recipient phenotype after the FMT using only the donors' microbiome and when available demographics for transplants from humans to either antibiotic treated mice, or other humans. We then extend the method to optimize the best-planned transplant (bacterial cocktails) by combining the predictor and a genetic algorithm (GA). We validate the predictor using a de-novo FMT experiment highlighting the possibility to choose transplants that optimize an array of required goals. We further show that a limited number of taxa is enough to produce an optimal FMT. Conclusions Over the shelf FMT require recipient independent optimized FMT selection. Such a transplant can be from an optimal donor, or from a cultured set of microbes. We have here shown the feasibility of both types of donations in antibiotic treated mice and for transplants between humans.