Temperate phages infect bacteria by injecting their DNA into bacterial cells, where it becomes incorporated into the host genome as a prophage. In the genome of Bacillus subtilis 168, an active prophage, SPβ, is inserted into a polysaccharide synthesis gene, spsM. Here, we show that a rearrangement occurs during sporulation to reconstitute a functional composite spsM gene by precise excision of SPβ from the chromosome. SPβ excision requires a putative site-specific recombinase, SprA, and an accessory protein, SprB. A minimized SPβ, where all the SPβ genes were deleted, except sprA and sprB, retained the SPβ excision activity during sporulation, demonstrating that sprA and sprB are necessary and sufficient for the excision. While expression of sprA was observed during vegetative growth, sprB was induced during sporulation and upon mitomycin C treatment, which triggers the phage lytic cycle. We also demonstrated that overexpression of sprB (but not of sprA) resulted in SPβ prophage excision without triggering the lytic cycle. These results suggest that sprB is the factor that controls the timing of phage excision. Furthermore, we provide evidence that spsM is essential for the addition of polysaccharides to the spore envelope. The presence of polysaccharides on the spore surface renders the spore hydrophilic in water. This property may be beneficial in allowing spores to disperse in natural environments via water flow. A similar rearrangement occurs in Bacillus amyloliquefaciens FZB42, where a SPβ-like element is excised during sporulation to reconstitute a polysaccharide synthesis gene, suggesting that this type of gene rearrangement is common in spore-forming bacteria because it can be spread by phage infection.

PurposeAlthough the definitive risk factors for parastomal hernia development remain unclear, potential contributing factors have been reported from Western countries. The aim of this study was to identify the risk factors for parastomal hernia in Japanese patients with permanent colostomies.MethodsAll patients who received abdominoperineal resection or total pelvic exenteration at our institution between December 2004 and December 2011 were reviewed. Patient-related, operation-related and postoperative variables were evaluated, in both univariate and multivariate analyses, to identify the risk factors for parastomal hernia formation.ResultsOf the 80 patients who underwent colostomy, 22 (27.5 %) developed a parastomal hernia during a median follow-up period of 953 days (range 15–2792 days). Hernia development was significantly associated with increasing patient age and body mass index, a laparoscopic surgical approach and the transperitoneal route of colostomy formation. In the multivariate analysis, the body mass index (p = 0.022), the laparoscopic approach (p = 0.043) and transperitoneal stoma creation (p = 0.021) retained statistical significance.ConclusionsOur findings in Japanese ostomates match those from Western countries: a higher body mass index, the use of a laparoscopic approach and a transperitoneal colostomy are significant independent risk factors for parastomal hernia formation. The precise role of the stoma creation route remains unclear.

Irritable bowel syndrome (IBS) is diagnosed by subjective clinical symptoms. We aimed to establish an objective IBS prediction model based on gut microbiome analyses employing machine learning. We collected fecal samples and clinical data from 85 adult patients who met the Rome III criteria for IBS, as well as from 26 healthy controls. The fecal gut microbiome profiles were analyzed by 16S ribosomal RNA sequencing, and the determination of short-chain fatty acids was performed by gas chromatography–mass spectrometry. The IBS prediction model based on gut microbiome data after machine learning was validated for its consistency for clinical diagnosis. The fecal microbiome alpha-diversity indices were significantly smaller in the IBS group than in the healthy controls. The amount of propionic acid and the difference between butyric acid and valerate were significantly higher in the IBS group than in the healthy controls (p < 0.05). Using LASSO logistic regression, we extracted a featured group of bacteria to distinguish IBS patients from healthy controls. Using the data for these featured bacteria, we established a prediction model for identifying IBS patients by machine learning (sensitivity >80%; specificity >90%). Gut microbiome analysis using machine learning is useful for identifying patients with IBS.

These results suggested that the peptide epitope of the IgA1 hinge region which was aberrantly exposed by underglycosylation could induce the humoral immune response in IgAN.

The correlation between moment arms and muscle function has significant effects on treatment efficacy. Information on the balance of moments around the ankle will assist in achieving optimal biomechanical behavior following operative treatments.