A MXene@GQDs hybrid fluorescent array for rapid identification and quantification of foodborne pathogens

Rapid screening of foodborne pathogens requires analytical tools that are fast, low-cost, and tolerant to complex sample matrices-capabilities that are not always met by culture-based assays or amplification-dependent workflows. Here we present a fluorescence "fingerprinting" strategy that differentiates multiple bacterial species within minutes using an interfacial charge-regulated nanoarray. The fluorescence fingerprint of each bacterial sample refers to the combined multichannel fluorescence-response pattern generated by the three MXene@GQDs probes after bacterial incubation. Three nitrogen/sulfur co-doped graphene quantum dots with distinct photophysical behaviors (GQDs1-GQDs3) were anchored onto Ti₃C₂T_X MXene through a straightforward hydrothermal process, forming MXene@GQDs1, MXene@GQDs2, and MXene@GQDs3. The resulting 2D/0D hybrid interface may facilitate interfacial interactions and charge-transfer-related fluorescence modulation, thereby translating bacteria-surface interactions into distinguishable fluorescence response patterns. Using these pattern signatures, the constructed sensor array successfully discriminated six common foodborne pathogens (S. typhimurium, Shigella, E. coli, S. aureus, P. aeruginosa, and L. monocytogenes) and enabled their quantitative determination. Data-driven classification delivered 100% identification accuracy in 3 min, with the lowest experimentally validated concentration of 1.0 × 10³ CFU/mL under the present conditions. Notably, 100% accuracy was retained in tap water, milk, and mixed-bacteria samples, indicating promising analytical robustness under the tested conditions. The proposed array offers an environmentally benign and cost-effective solution for food contamination surveillance, particularly where resources are limited.