RESULTS:

Introduction. The human oral cavity comprises various niches such as teeth gingiva tongue soft and hard palate and various dental prostheses all inhabited by different bacterial species. Although more than 600 taxa belong to the oral cavity identifying Staphylococcus arlettae an incompletely understood bacterium has been rare.

Methods. Three patients who underwent periodontal flap surgeries were reported with the incidental finding of S. arlettae associated with the intra-oral sutures placed. Environmental sampling was performed to establish the exact source of this bacterium.

Results. Staphylococcus arlettae was isolated in three patients’ intra-oral sutures. All environmental samples were negative for the presence of the bacterium.

Conclusion. To this date no studies have identified such an occurrence of Staphylococcus arlettae with intra-oral sutures. Its identification in association with foreign materials such as sutures can be considered a potential for surgical site infections and requires further investigation.

The problem of antibiotic resistance among pathogenic bacteria has reached a crisis level. The treatment options against infections caused by multiple drug-resistant bacteria are shrinking gradually. The current pace of the discovery of new antibacterial entities is lagging behind the rate of development of new resistance. Efflux pumps play a central role in making a bacterium resistant to multiple antibiotics due to their ability to expel a wide range of structurally diverse compounds. Besides providing an escape from antibacterial compounds efflux pumps are also involved in bacterial stress response virulence biofilm formation and altering host physiology. Efflux pumps are unique yet challenging targets for the discovery of novel efflux pump inhibitors (EPIs). EPIs could help rejuvenate our currently dried pipeline of antibacterial drug discovery. The current article highlights the recent developments in the field of efflux pumps challenges faced during the development of EPIs and potential approaches for their development. Additionally this review highlights the utility of resources such as natural products and machine learning to expand our EPIs arsenal using these latest technologies.