Modelling nanoparticles parameters for antimicrobial activity

Abstract

The current study reveals the antimicrobial activity of various nanoparticles (NPs) against numerous microorganisms through statistical models that define suitable parameters to improve the antimicrobial efficacy of NPs. The antimicrobial data on NPs were collected from previously published studies, focusing on parameters such as the NPs type and size (nm), microbial strains and their initial density (O.D.600nm), inhibition zone (IZ) size (mm), contact time (h), well and disc diffusion size (mm) and minimum inhibitory concentration (MIC) (μg/mL). A correlation between these parameters was modelled by using a multiple correspondence analysis (MCA) and a principal component analysis (PCA) for qualitative and quantitative analysis, respectively. Results showed a significant positive correlation between the IZ size and the following parameters: MIC, well size and disc diffusion size with a Pearson ratio of 95.98%, 93.99% and 94.82% (α = 0.5), respectively. Antimicrobial efficacy by Ag, SiO2 and ZnO NPs with a significant IZ for various gram positive bacterial strains was demonstrated. In addition, gram negative bacteria and fungi were deactivated by La-ZnO and AgNPs. Antimicrobial tests with NPs could be improved by varying the NPs concentration for improved efficacy. The NPs type should also be chosen as a function of the target bacteria characteristics, i.e. gram staining, for higher efficacy