Rapid and reliable identification of pathogenic microorganisms is of great importance for human and animal health. Most conventional approaches are time-consuming and require expensive reagents, sophisticated equipment, trained personnel, and special storage and handling conditions. Sensor arrays based on small molecules offer a chemically stable and cost-effective alternative. Here we present a ratiometric fluorescent sensor array based on the derivatives of 2-(4'- N, N-dimethylamino)-3-hydroxyflavone and investigate its ability to provide a dual-channel ratiometric response. We demonstrate that, by using discriminant analysis of the sensor array responses, it is possible to effectively distinguish between eight bacterial species and recognize their Gram status. Thus, multiple parameters can be derived from the same data set. Moreover, the predictive potential of this sensor array is discussed, and its ability to analyze unknown samples beyond the list of species used for the training matrix is demonstrated. The proposed sensor array and analysis strategies open new avenues for the development of advanced ratiometric sensors for multiparametric analysis.
Keywords: 3-hydroxyflavone; ESIPT; Gram status; chemical nose; discriminant analysis; multiparametric sensing; pattern analysis; predictive analysis.