| Autor: |
Peng R; Department of Chemical and Environmental Engineering, University of California, Riverside, 900 University Ave, Riverside, CA 92507, USA. ke.du@ucr.edu., Chen X; Department of Chemical and Environmental Engineering, University of California, Riverside, 900 University Ave, Riverside, CA 92507, USA. ke.du@ucr.edu.; Department of Microsystems Engineering, Rochester Institute of Technology, 1 Lomb Memorial Dr, Rochester, NY 14623, USA., Xu F; Department of Chemical and Environmental Engineering, University of California, Riverside, 900 University Ave, Riverside, CA 92507, USA. ke.du@ucr.edu., Hailstone R; Center for Imaging Science, Rochester Institute of Technology, 1 Lomb Memorial Dr, Rochester, NY 14623, USA., Men Y; Department of Chemical and Environmental Engineering, University of California, Riverside, 900 University Ave, Riverside, CA 92507, USA. ke.du@ucr.edu., Du K; Department of Chemical and Environmental Engineering, University of California, Riverside, 900 University Ave, Riverside, CA 92507, USA. ke.du@ucr.edu. |
| Abstrakt: |
The increasing prevalence of antibiotic-resistant bacterial infections, particularly methicillin-resistant Staphylococcus aureus (MRSA), presents a significant public health concern. Timely detection of MRSA is crucial to enable prompt medical intervention, limit its spread, and reduce antimicrobial resistance. Here, we introduce a miniaturized nano-sieve device featuring a pneumatically-regulated chamber for highly efficient MRSA purification from human plasma samples. By using packed magnetic beads as a filter and leveraging the deformability of the nano-sieve channel, we achieved an on-chip concentration factor of ∼15-fold for MRSA. We integrated this device with recombinase polymerase amplification (RPA) and clustered regularly interspaced short palindromic repeats (CRISPR)-Cas detection system, resulting in an on-chip limit of detection (LOD) of approximately 100 CFU mL -1 . This developed approach provides a rapid, precise, and centrifuge-free solution suitable for point-of-care diagnostics, with the potential to significantly improve patient outcomes in resource-limited medical conditions. |
