Genome-based taxonomic identification and safety assessment of an Enterococcus strain isolated from a homemade dairy product.

The aim of this study was to explore the taxonomic identification and evaluate the safety of a bacterium, Enterococcus lactis IDCC 2105, isolated from homemade cheese in Korea, using whole genome sequence (WGS) analysis. It sought to identify the species level of this Enterococcus spp., assess its antibiotic resistance, and evaluate its virulence potential. WGS analysis confirmed the bacterial strain IDCC 2105 as E. lactis and identified genes responsible for resistance to erythromycin and clindamycin, specifically msrC, and eatAv, which are chromosomally located, indicating a minimal risk for horizontal gene transfer. The absence of plasmids in E. lactis IDCC 2105 further diminishes the likelihood of resistance gene dissemination. Additionally, our investigation into seven virulence factors, including hemolysis, platelet aggregation, biofilm formation, hyaluronidase, gelatinase, ammonia production, and ß-glucuronidase activity, revealed no detectable virulence traits. Although bioinformatic analysis suggested the presence of collagen adhesion genes acm and scm, these were not corroborated by phenotypic virulence assays. Based on these findings, E. lactis IDCC 2105 presents as a safe strain for potential applications, contributing valuable information on its taxonomy, antibiotic resistance profile, and lack of virulence factors, supporting its use in food products.

Discovery of µ,δ-Opioid Receptor Dual-Biased Agonists That Overcome the Limitation of Prior Biased Agonists.

Morphine is widely used in pain management although the risk of side effects is significant. The use of biased agonists to the G protein of µ-opioid receptors has been suggested as a potential solution, although oliceridine and PZM21 have previously failed to demonstrate benefits in clinical studies. An amplification-induced confusion in the process of comparing G protein and beta-arrestin pathways may account for previously biased agonist misidentification. Here, we have devised a strategy to discover biased agonists with intrinsic efficacy. We computationally simulated 430 000 molecular dockings to the µ-opioid receptor to construct a compound library. Hits were then verified experimentally. Using the verified compounds, we performed simulations to build a second library with a common scaffold and selected compounds that showed a bias to µ- and δ-opioid receptors in a cell-based assay. Three compounds (ID110460001, ID110460002, and ID110460003) with a dual-biased agonistic effect for µ- and δ-opioid receptors were identified. These candidates are full agonists for the µ-opioid receptor and show specific binding modes. On the basis of our findings, we expect our novel compounds to act as more biased agonists compared to existing drugs, including oliceridine.