Rapid Discrimination of Bacterial Drug Resistivity by Array-Based Cross-Validation Using 2D MoS₂

The precise discrimination of microbes based on family, class and drug resistivity is essential for the early diagnosis of infectious diseases. Information about the type and strength of drug resistivity can help the analyst to prescribe a suitable antibiotic at the proper dosage to completely eradicate microbes without giving them a chance to gain further resistance. Herein, we propose a sensor array based on the use of cationic two-dimensional MoS₂ units and green fluorescence protein as building blocks. Cationic surfaces of receptors with various functionality were suitable for tunable interaction with anionic surfaces of microbes. The array successfully discriminates six different bacterial strains. The versatile ability of the receptors to bind with the wild-type as well as the corresponding ampicillin-resistant strain contributed significantly to rapid detection with high sensitivity. The optimized array was able to classify five different types and three different extents of drug-resistant variants of Escherichia coli by using bacteria cells and lysates. Finally, we have introduced the cross identification method using both bacteria cells and lysates and we found a great enhancement of detection in sensitivity and accuracy. This is the first report of this approach, which can be extended to many other methods for better accuracy in array-based detection.