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Highly Efficient Capture and Quantification of the Airborne Fungal Pathogen Sclerotinia sclerotiorum Employing a Nanoelectrode-Activated Microwell Array
[Image: see text] In this study, we present a microdevice for the capture and quantification of Sclerotinia sclerotiorum spores, pathogenic agents of one of the most harmful infectious diseases of crops, Sclerotinia stem rot. The early prognosis of an outbreak is critical to avoid severe economic lo...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8756577/ https://www.ncbi.nlm.nih.gov/pubmed/35036715 http://dx.doi.org/10.1021/acsomega.1c04878 |
Sumario: | [Image: see text] In this study, we present a microdevice for the capture and quantification of Sclerotinia sclerotiorum spores, pathogenic agents of one of the most harmful infectious diseases of crops, Sclerotinia stem rot. The early prognosis of an outbreak is critical to avoid severe economic losses and can be achieved by the detection of a small number of airborne spores. However, the current lack of simple and effective methods to quantify fungal airborne pathogens has hindered the development of an accurate early warning system. We developed a device that remedies these limitations based on a microfluidic design that contains a nanothick aluminum electrode structure integrated with a picoliter well array for dielectrophoresis-driven capture of spores and on-chip quantitative detection employing impedimetric sensing. Based on experimental results, we demonstrated a highly efficient spore trapping rate of more than 90% with an effective impedimetric sensing method that allowed the spore quantification of each column in the array and achieved a sensitivity of 2%/spore at 5 kHz and 1.6%/spore at 20 kHz, enabling single spore detection. We envision that our device will contribute to the development of a low-cost microfluidic platform that could be integrated into an infectious plant disease forecasting tool for crop protection. |
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