TY - JOUR
T1 - Rapid Collection and Aptamer-Based Sensitive Electrochemical Detection of Soybean Rust Fungi Airborne Urediniospores
AU - Krivitsky, Vadim
AU - Granot, Eran
AU - Avidor, Yoav
AU - Borberg, Ella
AU - Voegele, Ralf T.
AU - Patolsky, Fernando
N1 - Publisher Copyright:
©
PY - 2021/3/26
Y1 - 2021/3/26
N2 - Plants are the central source of food for humans around the world. Unfortunately, plants can be negatively affected by diverse kinds of diseases that are responsible for major economic losses worldwide. Thus, monitoring plant health and early detection of pathogens are essential to reduce disease spread and facilitate effective management practices. Various detection approaches are currently practiced. These methods mainly include visual inspection and laboratory tests. Nonetheless, these methods are labor-intensive, time-consuming, expensive, and inefficient in the early stages of infection. Thus, it is extremely important to detect diseases at the early stages of the epidemic. Here, we would like to present a fast, sensitive, and reliable electrochemical sensing platform for the detection of airborne soybean rust spores. The suspected airborne soybean rust spores are first collected and trapped inside a carbon 3D electrode matrix by high-capacity air-sampling means. Then, a specific biotinylated aptamer, suitable to target specific sites of soybean rust spores is applied. This aptamer agent binds to the surface of the collected spores on the electrode. Finally, spore-bound aptamer units are incubated with a streptavidin-alkaline phosphatase agent leading to the enzymatic formation of p-nitrophenol, which is characterized by its unique electrochemical properties. Our method allows for the rapid (ca. 2 min), selective, and sensitive collection and detection of soybean rust spores (down to the limit of 100-200 collected spores per cm2 of electrode area). This method could be further optimized for its sensitivity and applied to the future multiplex early detection of various airborne plant diseases.
AB - Plants are the central source of food for humans around the world. Unfortunately, plants can be negatively affected by diverse kinds of diseases that are responsible for major economic losses worldwide. Thus, monitoring plant health and early detection of pathogens are essential to reduce disease spread and facilitate effective management practices. Various detection approaches are currently practiced. These methods mainly include visual inspection and laboratory tests. Nonetheless, these methods are labor-intensive, time-consuming, expensive, and inefficient in the early stages of infection. Thus, it is extremely important to detect diseases at the early stages of the epidemic. Here, we would like to present a fast, sensitive, and reliable electrochemical sensing platform for the detection of airborne soybean rust spores. The suspected airborne soybean rust spores are first collected and trapped inside a carbon 3D electrode matrix by high-capacity air-sampling means. Then, a specific biotinylated aptamer, suitable to target specific sites of soybean rust spores is applied. This aptamer agent binds to the surface of the collected spores on the electrode. Finally, spore-bound aptamer units are incubated with a streptavidin-alkaline phosphatase agent leading to the enzymatic formation of p-nitrophenol, which is characterized by its unique electrochemical properties. Our method allows for the rapid (ca. 2 min), selective, and sensitive collection and detection of soybean rust spores (down to the limit of 100-200 collected spores per cm2 of electrode area). This method could be further optimized for its sensitivity and applied to the future multiplex early detection of various airborne plant diseases.
KW - aptamers
KW - electrochemistry
KW - enzyme
KW - fungi
KW - spores
UR - http://www.scopus.com/inward/record.url?scp=85100824680&partnerID=8YFLogxK
U2 - 10.1021/acssensors.0c02452
DO - 10.1021/acssensors.0c02452
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C2 - 33507747
AN - SCOPUS:85100824680
SN - 2379-3694
VL - 6
SP - 1187
EP - 1198
JO - ACS Sensors
JF - ACS Sensors
IS - 3
ER -