Silver(I) 1,10-Phenanthroline Complexes Are Active against Fonsecaea pedrosoi Viability and Negatively Modulate Its Potential Virulence Attributes.
Ingrid S SousaTatiana D P VieiraRubem Figueiredo Sadoko Menna-BarretoAllan Jefferson GuimarãesPauraic McCarronMalachy McCannMichael DevereuxAndré Luis Souza Dos SantosLucimar F KneippPublished in: Journal of fungi (Basel, Switzerland) (2023)
The genus Fonsecaea is one of the etiological agents of chromoblastomycosis (CBM), a chronic subcutaneous disease that is difficult to treat. This work aimed to evaluate the effects of copper(II), manganese(II) and silver(I) complexes coordinated with 1,10-phenanthroline (phen)/1,10-phenanthroline-5,6-dione (phendione) on Fonsecaea spp. Our results revealed that most of these complexes were able to inhibit F. pedrosoi , F. monophora and F. nubica conidial viability with minimum inhibitory concentration (MIC) values ranging from 0.6 to 100 µM. The most effective complexes against F. pedrosoi planktonic conidial cells, the main etiologic agent of CBM, were [Ag(phen) 2 ]ClO 4 and [Ag 2 (3,6,9-tdda)(phen) 4 ].EtOH, (tdda: 3,6,9-trioxaundecanedioate), displaying MIC values equal to 1.2 and 0.6 µM, respectively. These complexes were effective in reducing the viability of F. pedrosoi biofilm formation and maturation. Silver(I)-tdda-phen, combined with itraconazole, reduced the viability and extracellular matrix during F. pedrosoi biofilm development. Moreover, both silver(I) complexes inhibited either metallo- or aspartic-type peptidase activities of F. pedrosoi as well as its conidia into mycelia transformation and melanin production. In addition, the complexes induced the production of intracellular reactive oxygen species in F. pedrosoi . Taken together, our data corroborate the antifungal action of metal-phen complexes, showing they represent a therapeutic option for fungal infections, including CBM.
Keyphrases
- biofilm formation
- pseudomonas aeruginosa
- gold nanoparticles
- staphylococcus aureus
- reactive oxygen species
- extracellular matrix
- escherichia coli
- candida albicans
- induced apoptosis
- quantum dots
- signaling pathway
- silver nanoparticles
- high glucose
- big data
- machine learning
- oxidative stress
- cystic fibrosis
- cell death
- diabetic rats
- endothelial cells