Multiresistant microorganisms characterize infections related to high morbidity and mortality rates, especially in the hospital environment. One virulence mechanism presented by those bacterial strains involved with antimicrobial resistance is the biofilm formation, a structure that houses a community of microorganisms responsible for recurrent infections and for acting as a potential source of contamination. The need to identify natural compounds that inhibit resistance mechanisms becomes increasingly necessary due to treatment failures and the toxicity offered by antimicrobials. In this context, the present study aims to evaluate the inhibitory capacity of quercetin and genistein nutraceuticals against biofilm formation and to evaluate the susceptibility of multidrug resistant strains treated with them. It will be applied to the study the formation of a nanoparticle of natural compounds to verify the improvement in their pharmacokinetic and pharmacodynamic processes. The ionic gelation method will be used to formulate chitosan nanoparticles that will be characterized by Scanning Electron Microscopy and evaluated in spectrometry in relation to their drug release capacity. For antimicrobial evaluation of pure and nanoparticulate chitosan nutraceutical, minimum inhibitory concentration tests will be performed, together with the time-kill, chekerboard and fractional inhibitory concentration tests. The determination of the action of pure nutraceutical and chitosan nanoparticles on bacterial biofilms will be evaluated against the anti-biofilm activity tests in microtiter plate assays, as well as the effect of quercetin on exopolysaccharide production will also be interpreted. The biofilm structure will be analyzed by confocal laser scanning microscopy (CLSM), while anti-biofilm activity by coating nanoparticles in urethral silicone catheters will also be analyzed as quorum sensing (QS) modulation assays. C. violaceum ATCC 12472. The results will be considered significant at a significance level of 5% (p <0.05), giving them 95% confidence that the results were correct.
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