Accurate supervision of animal’s health and livestock management have a high impact on the productivity of meat and dairy industry. However, relevant veterinary parameters still lack effective diagnostic tools. An important example is the determination of bovine estrous, which is the optimal time for cow’s artificial insemination. Estrous is often determined based on animal behavior, but it could be inaccurate and misleading. Another case is bovine mastitis, a disease that has one of the highest economic impacts in the dairy industry. The gold standard diagnostic technique for mastitis is somatic cell count, a laboratory-based technique that require trained personnel and is time-consuming. Point-of-care (POC) diagnostic tests are rapid, user-friendly, cost-effective, and can be performed on-farm. To cover the previously mentioned needs, we are developing two independent lateral flow immunoassays. The first test determines the exact time window of bovine estrous. Heat is characterized by levels of progesterone in blood lower than 2 ng/mL. To achieve a device with the optimum sensitivity threshold, we exploited the optical properties of gold nanoparticles in a competitive immunoassay. The second device classifying udder health in three levels: healthy, subclinical mastitis, and clinical mastitis. The test is based on a multiplexing strategy, targeting two biomarkers present in milk. We explored different enzymes involved in tissue breakdown, such as N-Acetyl-β-D-Glucosaminidase and Lactate Dehydrogenase as mastitis early biomarkers. On the other hand, bovine immunoglobulin G is a suitable late biomarker, due to its increased concentration in secondary inflammatory stages of the disease. Both assays show good performances in their respective biological matrices. Finally, to assess the two devices’ performances, an extensive on-farm validation is underway with real cow’s blood and milk samples.

Lateral flow assays for on-farm veterinary monitoring and livestock management

Helena Torne Morato;Pier Paolo Pompa
2023-01-01

Abstract

Accurate supervision of animal’s health and livestock management have a high impact on the productivity of meat and dairy industry. However, relevant veterinary parameters still lack effective diagnostic tools. An important example is the determination of bovine estrous, which is the optimal time for cow’s artificial insemination. Estrous is often determined based on animal behavior, but it could be inaccurate and misleading. Another case is bovine mastitis, a disease that has one of the highest economic impacts in the dairy industry. The gold standard diagnostic technique for mastitis is somatic cell count, a laboratory-based technique that require trained personnel and is time-consuming. Point-of-care (POC) diagnostic tests are rapid, user-friendly, cost-effective, and can be performed on-farm. To cover the previously mentioned needs, we are developing two independent lateral flow immunoassays. The first test determines the exact time window of bovine estrous. Heat is characterized by levels of progesterone in blood lower than 2 ng/mL. To achieve a device with the optimum sensitivity threshold, we exploited the optical properties of gold nanoparticles in a competitive immunoassay. The second device classifying udder health in three levels: healthy, subclinical mastitis, and clinical mastitis. The test is based on a multiplexing strategy, targeting two biomarkers present in milk. We explored different enzymes involved in tissue breakdown, such as N-Acetyl-β-D-Glucosaminidase and Lactate Dehydrogenase as mastitis early biomarkers. On the other hand, bovine immunoglobulin G is a suitable late biomarker, due to its increased concentration in secondary inflammatory stages of the disease. Both assays show good performances in their respective biological matrices. Finally, to assess the two devices’ performances, an extensive on-farm validation is underway with real cow’s blood and milk samples.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1132078
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