From modeling and optimizing extraction of peels beetroot (Beta vulgaris L.) betalains to in silico probing of their antibacterial multitarget mechanisms

The heartening applications of betalains in food, pharmaceutical, and cosmetic sectors impose their strengthening by a suitable extraction protocol. Likewise, the antibacterial activity of beetroot betalains represents an option to develop the next-generation of antibacterial agents treating the wide bacterial infection spectrum. This study aimed to model and optimize the ethanloic extract of beetroot peels in betacyanin (Bc) and betaxanthin (Bx) and their activity against two foodborne pathogen bacteria (Staphylococcus aureus and Salmonella enterica) by using RSM (response surface methodology) and ANN (artificial neural network). The input variables considered were sample-to-solvent ratio, temperature, and extraction time. The higher Bc (5.87 g/L) and Bx (10.18 g/L) contents, and anti-Staphylococcus aureus (17.52 mm) and anti-Salmonella enterica (15.14 mm) activities were recorded at: sample-to-solvent ratio of 1:36, temperature of 44.54 degrees C, and extraction time equal to 93.03 min. Statistical analyses indicated that the models derived using RSM and ANN can be used to predict each response. Based on the coefficient of determination and mean square error, ANN model was found to be superior compared to RSM in the prediction of all responses. Molecular docking simulation stipulated that Bc and Bx could target multiple bacterial pathways including membrane permeability disruption by inhibiting MepR and AcrB efflux pump of S. aureus and S. enterica respectively. Both bioactive molecules showed a conceivable impairment of pathogenic bacteria replication and transcription vital processes by impeding DNA and RNA polymerase activities. These findings indicated that beet peel extracts can provide an excellent source of betalains for the color industry.