Back

2,4-Diacetylphloroglucinol Against Candida albicans: Biofilm Formation, Aspartyl Protease Production and Ultrastructure Changes

Stepanov, A. A.; Vasilchenko, A. S.

2022-04-26 microbiology
10.1101/2022.04.26.489565 bioRxiv
Show abstract

The dimorphic fungus Candida albicans is the one of the most important opportunistic pathogen of human. The use of fungicides against candida encounters sub-inhibitory effects, which are fungal stress response and undesirable for the host. In this work we investigated antifungal action of 2,4-diacetylphloroglucinol against Candida albicans ATCC 10231 with focus on they biofilm forming ability under the treatment. It was found that 2,4-DAPG reduced ability of candida cells to form biofilm, but complete inhibition or irradiation did not achieve. Moreover, Candida albicans cells in the adherent state have been characterized by reduced susceptibility to 2,4-DAPG comparing to planktonic cells. Investigation of mechanisms which could be explain the antibiofilm action of 2,4-DAPG has revealed the reduction in cells surface hydrophobicity and inhibition of yeast-to-hyphae transition. Biofilms formed under the sub-inhibitory concentrations of 2,4-DAPG were depleted in protein and carbohydrate content. Furthermore, we microscopically visualized the treated biofilms and have revealed numerous cannels localized on hyphae and associated with secretion of aspartyl proteases (Sap). We assumed what excretion of Sap is triggered by reactive oxygen generated upon affecting of mitochondrion respiration by 2,4-DAPG. Introducing of antioxidant Trolox simultaneously with 2,4-DAPG lead to reducing of Sap production. Thus, production of aspartyl proteases is a one of undesirable side effect of Candida albicans treatment, but using 2,4-DAPG in combination with antioxidants is the solution to overcome it.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.