Tokiinshi, a traditional Japanese medicine (Kampo), suppresses Panton-Valentine leukocidin production in the methicillin-resistant Staphylococcus aureus USA300 clone.
Yuka MaezawaHidemasa NakaminamiShunsuke TakadamaMinami HayashiTakeaki WajimaKeisuke NakaseTetsuya YamadaHideaki IkoshiNorihisa NoguchiPublished in: PloS one (2019)
It is necessary to develop agents other than antimicrobials for the treatment of Staphylococcus aureus infections to prevent the emergence of antimicrobial-resistant strains. Particularly, anti-virulence agents against the Panton-Valentine leukocidin (PVL)-positive methicillin-resistant S. aureus (MRSA), USA300 clone, is desired due to its high pathogenicity. Here, we investigated the potential anti-virulence effect of Tokiinshi, which is a traditional Japanese medicine (Kampo) used for skin diseases, against the USA300 clone. A growth inhibition assay showed that a conventional dose (20 mg/ml) of Tokiinshi has bactericidal effects against the clinical USA300 clones. Notably, the growth inhibition effects of Tokiinshi against S. epidermidis strains, which are the major constituents of the skin microbiome, was a bacteriostatic effect. The data suggested that Tokiinshi is unlikely to affect skin flora of S. epidermidis. Furthermore, PVL production and the expression of its gene were significantly suppressed in the USA300 clone by a lower concentration (5 mg/ml) of Tokiinshi. This did not affect the number of viable bacteria. Moreover, Tokiinshi significantly suppressed the expression of the agrA gene, which regulates PVL gene expression. For the first time, our findings strongly suggest that Tokiinshi has the potential to attenuate the virulence of the USA300 clone by suppressing PVL production via agrA gene suppression.
Keyphrases
- staphylococcus aureus
- methicillin resistant staphylococcus aureus
- biofilm formation
- gene expression
- escherichia coli
- copy number
- poor prognosis
- genome wide
- soft tissue
- dna methylation
- wound healing
- electronic health record
- binding protein
- climate change
- long non coding rna
- genome wide identification
- machine learning
- transcription factor
- cystic fibrosis
- artificial intelligence