Regulation of chromosomal replication initiation by oriC-proximal DnaA-box clusters in Bacillus subtilis

Bacterial chromosome replication is initiated by binding of DnaA to a DnaA-box cluster (DBC) within the replication origin (oriC). In Bacillus subtilis, six additional DBCs are found outside of oriC and some are known to be involved in transcriptional regulation of neighboring genes. A deletion mutant lacking the six DBCs (Δ6) initiated replication early. Further, inactivation of spo0J in Δ6 cells yielded a pleiotropic phenotype, accompanied by severe growth inhibition. However, a spontaneous suppressor in soj or a deletion of soj, which stimulates DnaA activity in the absence of Spo0J, counteracted these effects. Such abnormal phenotypic features were not observed in a mutant background in which replication initiation was driven by a plasmid-derived replication origin. Moreover, introduction of a single DBC at various ectopic positions within the Δ6 chromosome partly suppressed the early-initiation phenotype, but this was dependent on insertion location. We propose that DBCs negatively regulate replication initiation by interacting with DnaA molecules and play a major role, together with Spo0J/Soj, in regulating the activity of DnaA

Activation of the pentose phosphate pathway in macrophages is crucial for granuloma formation in sarcoidosis

肉芽腫形成に特異的な代謝経路の発見 --ペントースリン酸回路の制御による新規治療--. 京都大学プレスリリース. 2023-12-01.More than skin-deep: Kyoto researchers discover metabolic pathway specific to granuloma formation in patients. 京都大学プレスリリース. 2023-12-07.Sarcoidosis is a disease of unknown etiology in which granulomas form throughout the body and is typically treated with glucocorticoids, but there are no approved steroid-sparing alternatives. Here, we investigated the mechanism of granuloma formation using single-cell RNA-Seq in sarcoidosis patients. We observed that the percentages of triggering receptor expressed on myeloid cells 2–positive (TREM2-positive) macrophages expressing angiotensin-converting enzyme (ACE) and lysozyme, diagnostic makers of sarcoidosis, were increased in cutaneous sarcoidosis granulomas. Macrophages in the sarcoidosis lesion were hypermetabolic, especially in the pentose phosphate pathway (PPP). Expression of the PPP enzymes, such as fructose-1, 6-bisphosphatase 1 (FBP1), was elevated in both systemic granuloma lesions and serum of sarcoidosis patients. Granuloma formation was attenuated by the PPP inhibitors in in vitro giant cell and in vivo murine granuloma models. These results suggest that the PPP may be a promising target for developing therapeutics for sarcoidosis

Cancer-Chemotherapy-Related Regimen Checks Performed by Pharmacists of General Hospitals Other than Cancer Treatment Collaborative Base Hospitals: A Multicenter, Prospective Survey

Although prescription review is an important role for pharmacists in anticancer drug therapy, there are no guidelines in Japan that specify what pharmacists should check for in chemotherapy regimens. This prospective multicenter survey aimed to investigate the implementation of chemotherapy regimen checks by pharmacists in general hospitals by focusing on 19 recommended confirmation items designed to enhance chemotherapy safety. This study involved 14 hospitals within the National Hospital Organization in different regions of Japan. The top five cancers in Japan (gastric, colorectal, lung, breast, and gynecological) were targeted and specific chemotherapy regimens were analyzed. This study assessed the amount of time required for regimen checks, the number of confirmation items completed, the number and the content of inquiries raised regarding prescriptions, and the pharmacists’ opinions using a questionnaire that had a maximum score of 10 points. Pharmacists checked 345 and 375 chemotherapies of patients in the control group (CG) and recommended items group (RIG), respectively. The mean time periods required for completing a chemotherapy regimen check were 4 min and 14 s (SD ±1 min and 50 s) and 6 min and 18 s (SD, ±1 min and 7 s) in the CG and RIG, respectively. The mean of the recommended items for the CG = 12.4 and for the RIG = 18.6. The items that the pharmacists did not confirm included urine protein (sixty-nine cases, 18.4%), allergy history (four cases, 1%), previous history (two cases, 0.5%), and a previous history of hepatitis B virus (sixty-nine cases, 18.4%). The number of inquiries for a doctor’s prescription order was higher in the RIG than in the CG (41 vs. 27 cases). This multicenter survey demonstrated the potential effectiveness of implementing 19 recommended confirmation items in the regimen checks by pharmacists in general hospitals other than cancer treatment collaborative base hospitals

Potential identification of vitamin B6 responsiveness in autism spectrum disorder utilizing phenotype variables and machine learning methods

Abstract We investigated whether machine learning methods could potentially identify a subgroup of persons with autism spectrum disorder (ASD) who show vitamin B6 responsiveness by selected phenotype variables. We analyzed the existing data from our intervention study with 17 persons. First, we focused on signs and biomarkers that have been identified as candidates for vitamin B6 responsiveness indicators. Second, we conducted hypothesis testing among these selected variables and their combinations. Finally, we further investigated the results by conducting cluster analyses with two different algorithms, affinity propagation and k-medoids. Statistically significant variables for vitamin B6 responsiveness, including combination of hypersensitivity to sound and clumsiness, and plasma glutamine level, were included. As an a priori variable, the Pervasive Developmental Disorders Autism Society Japan Rating Scale (PARS) scores was also included. The affinity propagation analysis showed good classification of three potential vitamin B6-responsive persons with ASD. The k-medoids analysis also showed good classification. To our knowledge, this is the first study to attempt to identify subgroup of persons with ASD who show specific treatment responsiveness using selected phenotype variables. We applied machine learning methods to further investigate these variables’ ability to identify this subgroup of ASD, even when only a small sample size was available