A Systematically Enhanced LAMP Chip for Rapid, Sensitive, and Contamination-Free Pathogen Detection

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 <i>Phytophthora infestans</i>. 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 <i>P. infestans</i> 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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Publication Details

Journal
ACS Measurement Science Au
Published
2025-12-25
DOI
https://doi.org/10.1021/acsmeasuresciau.5c00155
Citations
1
Primary Topic
Biosensors and Analytical Detection
Type
article
Field-Weighted Citation Impact
0.67
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A Systematically Enhanced LAMP Chip for Rapid, Sensitive, and Contamination-Free Pathogen Detection

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article

A Systematically Enhanced LAMP Chip for Rapid, Sensitive, and Contamination-Free Pathogen Detection

Sajid Uchayash, Md Iqbal Kabir, Junqi Song, Jinping Zhao, Long Que
article en
1 citations

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 <i>Phytophthora infestans</i>. 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 <i>P. infestans</i> 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.

ACS Measurement Science AuVol. 6(1)
Texas A&M University System (US), Iowa State University (US), Mitchell Institute (US), Texas A&M University (US)
Zero hunger
Openalex Percentile: Top 23%
Biosensors and Analytical Detection
0.67
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