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Amplification of Escherichia coli in a Continuous-Flow-PCR Microfluidic Chip and Its Detection with a Capillary Electrophoresis System
Published on: November 21, 2023
A Systematically Enhanced LAMP Chip for Rapid, Sensitive, and Contamination-Free Pathogen Detection
Sajid Uchayash1, Jinping Zhao2, Md Iqbal Kabir1
1Department of Electrical and Computer Engineering, Iowa State University, Ames, Iowa 50011, United States.
Abstract:
Main techniques for pathogen detection include molecular or nucleic acid-based methods, such as polymerase chain reaction (PCR) and loop-mediated isothermal amplification (LAMP). Among these, chip-based LAMP provides a particularly promising platform for point-of-care diagnostics. To ensure accurate, reliable, and robust pathogen detection, systematic optimization of the LAMP-chip system is essential. Building on our previously developed LAMP-chip platform, we report a systematically advanced version for the rapid and sensitive detection of Phytophthora infestans. By systematically investigating the effects of primer concentrations, immobilization ratios, and reaction conditions, we identified an optimal configuration involving immobilized forward inner primers (FIP) on the sensor surface and unmodified backward inner primers (BIP) in solution. This approach enabled the detection of P. infestans DNA at concentrations as low as 1 fg/μL, with a transducing optical signal shift of up to 4.33 nm after a 30 min reaction. Further refinement reduced detection time to under 20 min, a 33% reduction of conventional LAMP detection time, without compromising sensitivity. Notably, the use of EDC-NHS chemistry for primer immobilization on the anodic aluminum oxide (AAO) nanopore surface of the LAMP chip effectively minimizes carryover contamination by strictly confining amplification to the chip, representing a major advance over conventional LAMP approaches. This robust, label-free, and user-friendly system offers a promising solution for point-of-care plant pathogen diagnostics, enabling accurate and rapid field-based detection to support timely disease management and improve agricultural outcomes.
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