Multidimensional Pathogen Fingerprinting via DNA Scaffold-Confined Enzymatic Synthesis of Silicon Quantum Dots.
Journal:
Analytical chemistry
Published Date:
Jun 22, 2026
Abstract
Accurate and highly sensitive detection of pathogenic bacteria is essential to public health. Conventional biosensors often rely on bulk signal amplification, which suffers from diffusion-limited kinetics and high background signals. Herein, we present a programmable, surface-confined biosensing strategy that constructs a target-responsive nucleic acid-enzyme microenvironment directly on the bacterial surface, enabling localized catalytic reactions for ultrasensitive detection. Upon target recognition, the aptamer-primer (AP) strand triggers surface-confined rolling circle amplification (RCA) to form high-density DNA network scaffolds. These scaffolds recruit alkaline phosphatase (ALP), establishing a confined enzymatic reaction microenvironment. The localized ALP catalyzes the hydrolysis of p-aminophenol phosphate (APP) to generate p-aminophenol (PAP), creating a reducing microenvironment that drives in situ nucleation of silicon quantum dots (SiQDs) from the silane precursor N-[3-(trimethoxysilyl)propyl] ethylenediamine (DAMO). Using Staphylococcus aureus as a model pathogen, this approach provides dual-mode readouts: an ultrasensitive fluorescence response with a detection limit of 23 CFU mL-1 and a rapid colorimetric response with a detection limit of 134 CFU mL-1. Importantly, the recognition module was highly programmable. By simply replacing the target-specific aptamer domain within the AP strand, this strategy can be universally adapted for various pathogens. Moreover, by generating complementary multidimensional signals, including fluorescence, UV-vis absorbance, and hydrodynamic diameter, the strategy enables the construction of a multidimensional optical sensor array. Integration with machine-learning algorithms allows the platform to interpret distinct chemo-optical fingerprints, thereby enabling the accurate classification of multiple pathogenic bacteria. Overall, this strategy provides a versatile framework for intelligent multiplexed pathogen diagnostics by integrating programmable biomolecular recognition, spatially confined enzymatic nanosynthesis, and data-driven analyses.
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