Plasmonic metasurface microfluidic accelerates redox reactions for rapid phenotypic antibiotic susceptibility testing
Year: 2026
Type: article
Abstract: Electron-accepting chain reactions play crucial roles in diagnostics for bacterial infections, from nucleic acid amplification for bacterial identification to metabolic assays for phenotypic antibiotic susceptibility testing. When coupled with redox mediators, these reactions can be interrogated using an electroanalytical method. We demonstrate kinetic acceleration of loop-mediated isothermal amplification-based identification and resazurin-based phenotypic antibiotic susceptibility profiling through enhanced electromagnetic fields and modulated hot electron injection at the multilayered plasmonic metasurface-fluidic interface. We systematically investigate rounded versus sharp-apex plasmonic architectures, quantifying near-field magnitude and decay to identify geometries that maximize kinetic amplification under electrochemical readout. This approach is further combined with machine learning-assisted Gaussian fitting to improve data quantification and interpretation. Across diverse bacterial species, we achieved rapid identification with no cross-reactivity and phenotypic antibiotic susceptibility testing without overnight culture. In a prospective pilot clinical study of urine specimens directly from patients with suspected urinary tract infections, we observe high accuracy and strong essential and categorical agreement with standard clinical microbiology assays for bacterial identification and antibiotic susceptibility testing.
Source: Science Advances
Authors: Roozbeh Siavash Moakhar, Mahsa Jalali, Tamer AbdElFatah, Sripadh Guptha Yedire, Max Petkun, Carolina del Real Mata, Ziwei He, Hamed Shieh, Geoffrey A. McKay, Rachel Corsini, Grace Reszetnik, Seyed Vahid Hamidi, Sahar Sadat Mahshid, Sahar Sadat Mahshid, Cedric P. Yansouni, Dao Nguyen, Sara Mahshid, Sara Mahshid
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $4,500
OpenAlex ID: W7221784397
