Discovery of psoralen as a quorum sensing inhibitor suppresses Pseudomonas aeruginosa virulence.

Pseudomonas aeruginosa is a common opportunistic pathogen with growing resistance and presents heightened treatment challenges. Quorum sensing (QS) is a cell-to-cell communication system that contributes to the production of a variety of virulence factors and is also related to biofilm formation of P. aeruginosa. Compared to traditional antibiotics which kill bacteria directly, the anti-virulence strategy by targeting QS is a promising strategy for combating pseudomonal infections. In this study, the QS inhibition potential of the compounds derived from the Traditional Chinese Medicines was evaluated by using in silico, in vitro, and in vivo analyses. The results showed that psoralen, a natural furocoumarin compound derived from Psoralea corylifolia L., was capable of simultaneously inhibiting the three main QS regulators, LasR, RhlR, and PqsR of P. aeruginosa. Psoralen had no bactericidal activity but could widely inhibit the production of extracellular proteases, pyocyanin, and biofilm, and the cell motilities of the model and clinical P. aeruginosa strains. RNA-sequencing and quantitative PCR analyses further demonstrated that a majority of QS-activated genes in P. aeruginosa were suppressed by psoralen. The supplementation of psoralen could protect Caenorhabditis elegans from P. aeruginosa challenge, especially for the hypervirulent strain PA14. Moreover, psoralen showed synergistic antibacterial effects with polymyxin B, levofloxacin, and kanamycin. In conclusions, this study identifies the anti-QS and antibiofilm effects of psoralen against P. aeruginosa strains and sheds light on the discovery of anti-pseudomonal drugs among Traditional Chinese Medicines. KEY POINTS: • Psoralen derived from Psoralea corylifolia L. inhibits the virulence-related phenotypes of P. aeruginosa. • Psoralen simultaneously targets the three core regulators of P. aeruginosa QS system and inhibits the expression of a large part of downstream genes. • Psoralen protects C. elegans from P. aeruginosa challenge and enhances the susceptibility of P. aeruginosa to antibiotics.

Pien Tze Huang accelerated wound healing by inhibition of abnormal fibroblast apoptosis in Streptozotocin induced diabetic mice.

ETHNOPHARMACOLOGICAL RELEVANCE: Diabetic foot ulcer is one of the most serious complications of diabetes. Effective medical treatment regarding improvement of ulcer healing in patients is essential. Pien Tze Huang (PZH), a valuable Chinese traditional medicine, has been found significant efficacy on the curing of diabetic wound in clinic recently. AIM OF THE STUDY: This work was conducted to confirm the efficacy, and compare the therapeutic effect through the oral administration and local delivery route, providing a rationale for the new PZH form development; besides, the mechanisms through which PZH promoted the wound healing was also discussed. MATERIALS AND METHODS: First, the chemical composition of PZH was characterized by 1H-NMR and HPLC. The anti-apoptosis effects of PZH on high concentration glucose injured epidermal fibroblast (HFF-1) was investigated in a dose dependent way. Then, the effects of the systematical administration of PZH, and the topical used route on excisional wounds of Streptozotocin (STZ) induced diabetic mice were compared. RESULTS: The results illustrated that PZH decreased the reactive oxygen species (ROS) levels in cells, preventing cell damage/apoptosis through an ROS/Bcl-2/Bax/Caspase-3 pathway. The in vivo study proved that topical use of PZH exceeded the systematical route both in accelerating the wound closure and improving the healing quality. Meanwhile, PZH promoted wound closure through stimulating the secretion of Col-I, decreasing fibroblast apoptosis, and enhancing myo-fibroblast differentiation, in consistent with the mechanism study in vitro. CONCLUSIONS: Local used PZH improves wound healing by inhibiting the abnormal HFF-1 apoptosis and senescence. The study held a great promise for development of a topical dosage form of PZH for diabetic wound healing.

Robust statistical methods for hit selection in RNA interference high-throughput screening experiments.

RNA interference (RNAi) high-throughput screening (HTS) experiments carried out using large (>5000 short interfering [si]RNA) libraries generate a huge amount of data. In order to use these data to identify the most effective siRNAs tested, it is critical to adopt and develop appropriate statistical methods. To address the questions in hit selection of RNAi HTS, we proposed a quartile-based method which is robust to outliers, true hits and nonsymmetrical data. We compared it with the more traditional tests, mean +/- k standard deviation (SD) and median +/- 3 median of absolute deviation (MAD). The results suggested that the quartile-based method selected more hits than mean +/- k SD under the same preset error rate. The number of hits selected by median +/- k MAD was close to that by the quartile-based method. Further analysis suggested that the quartile-based method had the greatest power in detecting true hits, especially weak or moderate true hits. Our investigation also suggested that platewise analysis (determining effective siRNAs on a plate-by-plate basis) can adjust for systematic errors in different plates, while an experimentwise analysis, in which effective siRNAs are identified in an analysis of the entire experiment, cannot. However, experimentwise analysis may detect a cluster of true positive hits placed together in one or several plates, while platewise analysis may not. To display hit selection results, we designed a specific figure called a plate-well series plot. We thus suggest the following strategy for hit selection in RNAi HTS experiments. First, choose the quartile-based method, or median +/- k MAD, for identifying effective siRNAs. Second, perform the chosen method experimentwise on transformed/normalized data, such as percentage inhibition, to check the possibility of hit clusters. If a cluster of selected hits are observed, repeat the analysis based on untransformed data to determine whether the cluster is due to an artifact in the data. If no clusters of hits are observed, select hits by performing platewise analysis on transformed data. Third, adopt the plate-well series plot to visualize both the data and the hit selection results, as well as to check for artifacts.