Abstract
Pathogenic microorganisms responsible for infectious diseases pose a significant global threat to human health. Existing detection methods, such as qPCR and ELISA, fail to simultaneously meet the requirements for high sensitivity, high specificity, and rapid detection. This study presents an innovative approach for the rapid, specific, and highly sensitive detection of pathogenic microorganisms, particularly Escherichia coli O157:H7 (E. coli O157:H7) and varicella-zoster virus (VZV), by combining recombinase polymerase amplification (RPA) with terahertz time-domain spectroscopy (THz-TDS). The qualitative and quantitative detection method for pathogenic microorganisms was developed and evaluated. The stable and efficient RPA reaction systems were established to specifically amplify the key conserved genes of these pathogens. Then the RPA products were purified, and enriched with MBs. The absorbance spectra were obtained using THz-TDS technology. The linear range of the RPA-THz for detecting E. coli O157:H7 was 0.55 to 5.5 × 104 pg/mL, while for VZV, it was 0.75 to 7.5 × 103 pg/mL. The limit of detection (LOD) for bacteria and viruses was 0.226 pg/mL and 0.528 pg/mL, respectively, demonstrating better sensitivity than the qPCR (550 pg/mL and 750 pg/mL, respectively). In addition, the whole amplification and detection process was completed in about 35 minutes. Compared to traditional pathogen detection techniques, the primary advantage of the developed RPA-THz method exhibited high accuracy, good reproducibility, and short detection times, enabling non-ionizing, label-free analysis for rapid detection with high sensitivity and specificity of pathogenic microorganisms. This study provides a theoretical foundation and practical demonstration for the fast and precise detection of pathogenic microorganisms. It establishes a crucial research basis for further development of RPA-THz sensors, advancing technological progress in the field of food safety, medical diagnostics, environmental monitoring, and public health.
| Original language | English |
|---|---|
| Pages (from-to) | 949-964 |
| Number of pages | 16 |
| Journal | Biomedical Optics Express |
| Volume | 16 |
| Issue number | 3 |
| DOIs | |
| State | Published - 1 Mar 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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