Self-Interference Digital Optofluidic Genotyping for\nIntegrated and Automated Label-Free Pathogen Detection

Pathogen,\nprevalent in both natural and human environments, cause\napproximately 4.95 million deaths annually, ranking them among the\ntop contributors to global mortality. Traditional pathogen detection\nmethods, reliant on microscopy and cultivation, are slow and labor-intensive\nand often produce subjective results. While nucleic acid amplification\ntechniques such as polymerase chain reaction offer genetic accuracy,\nthey necessitate costly laboratory equipment and skilled personnel.\nConsequently, isothermal amplification methods like recombinase polymerase\namplification (RPA) have attracted interest for their rapid and straightforward\noperations. However, these methods face challenges in specificity\nand automated sample processing. In this study, we introduce a self-interferometric\ndigital optofluidic platform incorporating asymmetric direct solid-phase\nRPA for real-time, label-free, and automated pathogen genotyping.\nBy integration of digital microfluidics with a DNA monolayer detection\nmethod using hyperspectral interferometry, this platform enables rapid,\nspecific, and sensitive pathogen detection without the need for exogenous\nlabeling or complex procedures. The system demonstrated high sensitivity\n(10 CFU·mL<sup>–1</sup>), specificity (differentiating\nfour <i>Candida</i> species), detection efficiency (fully\nautomated within 50 min for Gram-negative bacteria), and throughput\n(simultaneous detection of four indices). This integrated approach\nto pathogen quantitation on a single microfluidic chip represents\na significant advancement in rapid pathogen diagnostics, providing\na practical solution for timely pathogen detection and analysis.

Publication Details

Journal
Figshare
Published
2024-11-19
DOI
https://doi.org/10.1021/acssensors.4c01520.s003
Primary Topic
Wheat and Barley Genetics and Pathology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Self-Interference Digital Optofluidic Genotyping for\nIntegrated and Automated Label-Free Pathogen Detection

Figshare
Wheat and Barley Genetics and Pathology
article

Self-Interference Digital Optofluidic Genotyping for\nIntegrated and Automated Label-Free Pathogen Detection

article en

Abstract

Pathogen,\nprevalent in both natural and human environments, cause\napproximately 4.95 million deaths annually, ranking them among the\ntop contributors to global mortality. Traditional pathogen detection\nmethods, reliant on microscopy and cultivation, are slow and labor-intensive\nand often produce subjective results. While nucleic acid amplification\ntechniques such as polymerase chain reaction offer genetic accuracy,\nthey necessitate costly laboratory equipment and skilled personnel.\nConsequently, isothermal amplification methods like recombinase polymerase\namplification (RPA) have attracted interest for their rapid and straightforward\noperations. However, these methods face challenges in specificity\nand automated sample processing. In this study, we introduce a self-interferometric\ndigital optofluidic platform incorporating asymmetric direct solid-phase\nRPA for real-time, label-free, and automated pathogen genotyping.\nBy integration of digital microfluidics with a DNA monolayer detection\nmethod using hyperspectral interferometry, this platform enables rapid,\nspecific, and sensitive pathogen detection without the need for exogenous\nlabeling or complex procedures. The system demonstrated high sensitivity\n(10 CFU·mL<sup>–1</sup>), specificity (differentiating\nfour <i>Candida</i> species), detection efficiency (fully\nautomated within 50 min for Gram-negative bacteria), and throughput\n(simultaneous detection of four indices). This integrated approach\nto pathogen quantitation on a single microfluidic chip represents\na significant advancement in rapid pathogen diagnostics, providing\na practical solution for timely pathogen detection and analysis.

Figshare
Openalex Percentile: Top 39%
Wheat and Barley Genetics and Pathology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Self-Interference Digital Optofluidic Genotyping for\nIntegrated and Automated Label-Free Pathogen Detection · Figshare (2024) | TGRS Research Map | TGRS