Smartphone-Linked and Electricity-Free Platforms for Rapid Colorimetric Molecular Detection of Poultry Respiratory Viruses at the Point of Need

Efficient control measures for respiratory diseases in humans and farm animals require accurate, specific, and rapid diagnostics. Traditional PCR-based molecular diagnostics are restricted to centralized laboratories, which results in significant, potentially catastrophic delays in test results. A case in point is the recent avian flu outbreak, which has culled more than 280 million poultry birds worldwide (over 157 million in the USA alone) since 2022; has spread to other farm animals, such as cattle; has further heightened the risk of a human pandemic; and threatens food security. To enable molecular diagnosis of bird respiratory diseases at the point of need, we employ loop-mediated isothermal amplification (LAMP) in two platforms: (A) portable devices linked to a smartphone and (B) an inexpensive, disposable, electricity-free, instrument-free device with closed-tube, colorimetric detection that can be produced with minimal resources. Smartphone integration offers an unexplored opportunity for spatiotemporal disease mapping, equipping policymakers with critical data for outbreak control. Our assays demonstrated 100% sensitivity and specificity compared to the gold standard, lab-based, quantitative PCR (qPCR). We tested contrived samples of the avian flu H5N1 virus, laryngotracheitis virus (ILTV), and infectious bronchitis virus (IBV) spiked into clinical samples, achieving a detection sensitivity adequate for early infection diagnosis in under 45 min. The test is simple, requires minimal training, and can be performed without refrigeration, making it well-suited for resource-limited settings.

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Publication Details

Journal
Biosensors
Published
2025-09-24
DOI
https://doi.org/10.3390/bios15100638
Primary Topic
Biosensors and Analytical Detection
Type
article
Field-Weighted Citation Impact
0.00

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article

Smartphone-Linked and Electricity-Free Platforms for Rapid Colorimetric Molecular Detection of Poultry Respiratory Viruses at the Point of Need

Alanoud Alalawi, Haim H. Bau, Mohamed El‐Tholoth, Rabiha Séboussi et al.
Biosensors
Biosensors and Analytical Detection
article

Smartphone-Linked and Electricity-Free Platforms for Rapid Colorimetric Molecular Detection of Poultry Respiratory Viruses at the Point of Need

Alanoud Alalawi, Haim H. Bau, Mohamed El‐Tholoth, Rabiha Séboussi, Mahmoud Hussein, Salameh Rahmdel
article en

Abstract

Efficient control measures for respiratory diseases in humans and farm animals require accurate, specific, and rapid diagnostics. Traditional PCR-based molecular diagnostics are restricted to centralized laboratories, which results in significant, potentially catastrophic delays in test results. A case in point is the recent avian flu outbreak, which has culled more than 280 million poultry birds worldwide (over 157 million in the USA alone) since 2022; has spread to other farm animals, such as cattle; has further heightened the risk of a human pandemic; and threatens food security. To enable molecular diagnosis of bird respiratory diseases at the point of need, we employ loop-mediated isothermal amplification (LAMP) in two platforms: (A) portable devices linked to a smartphone and (B) an inexpensive, disposable, electricity-free, instrument-free device with closed-tube, colorimetric detection that can be produced with minimal resources. Smartphone integration offers an unexplored opportunity for spatiotemporal disease mapping, equipping policymakers with critical data for outbreak control. Our assays demonstrated 100% sensitivity and specificity compared to the gold standard, lab-based, quantitative PCR (qPCR). We tested contrived samples of the avian flu H5N1 virus, laryngotracheitis virus (ILTV), and infectious bronchitis virus (IBV) spiked into clinical samples, achieving a detection sensitivity adequate for early infection diagnosis in under 45 min. The test is simple, requires minimal training, and can be performed without refrigeration, making it well-suited for resource-limited settings.

BiosensorsVol. 15(10)
Higher Colleges of Technology (AE), Mansoura University (EG), University of Sharjah (AE), University of Pennsylvania (US)
Chinese Academy of Sciences
Openalex Percentile: Top 75%
Biosensors and Analytical Detection
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