Microfluidic Filtration Enrichment Cascade Nanozyme-Catalyzed Colorimetric Immunoassay for Rapid and Ultrasensitive Detection of Escherichia coli in Urine with Smartphone Readout

Abstract

Urinary tract infections rank among the most frequent bacterial infections globally, with the majority caused by uropathogenic strains of Escherichia coli (E. coli). Effective management requires timely and reliable diagnostic tools. This work introduced a compact smartphone-coupled microfluidic platform that incorporated dual filtration for sample preprocessing and Au@Pt nanozyme-catalyzed colorimetric immunoassay for sensitive and rapid detection of uropathogenic E. coli in urine. The dual-membrane microfluidic chip enables efficient bacterial separation and enrichment, while Au@Pt nanozyme probes conjugated with E. coli-specific antibody catalyze the chromogenic substrate to generate visible blue signal. The smartphone application quantitatively analyzes the chromogenic intensity. The proposed platform achieves a limit of detection of 105 CFU/mL within 15 min. Validation using 40 clinical urine samples demonstrated 100% agreement with the standard quantitative urine culture method. Owing to its simplicity, portability, and high diagnostic accuracy, the detection platform provides a promising point-of-care testing approach for rapid bacterial diagnostics. Furthermore, its modular design allows easy adaptation for enrichment and detection of other pathogenic bacteria or viruses in diverse biological samples, paving the way for intelligent, field-deployable biosensing in clinical and public health applications.

Supplementary files

Article information

Article type
Paper
Submitted
02 Apr 2026
Accepted
20 May 2026
First published
20 May 2026

Anal. Methods, 2026, Accepted Manuscript

Microfluidic Filtration Enrichment Cascade Nanozyme-Catalyzed Colorimetric Immunoassay for Rapid and Ultrasensitive Detection of Escherichia coli in Urine with Smartphone Readout

Y. Guo, T. Wang, Z. Tu, H. Chen, S. Wang, G. Sun and Z. Rong, Anal. Methods, 2026, Accepted Manuscript , DOI: 10.1039/D6AY00597G

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