Constructing an ELISA for Detection of Anti-Borrelia in Wildlife and Agricultural Animals

TitleConstructing an ELISA for Detection of Anti-Borrelia in Wildlife and Agricultural Animals
Publication TypeJournal Article
Year of Publication2024
JournalMethods Mol Biol.
AuthorsBland J, McGowan C, Bush E, Lloyd VK
Keywordsagricultural animals, borrelia, cows, ELISA, horses, serology, wildlife
Abstract

Zoonotic diseases have major impacts on human and animal health, as well as being ecologically significant. Lyme Borreliosis or Lyme disease, caused by infection by pathogenic members of the Borrelia genus, is among these zoonotic diseases. Serology is one of the most accessible means for indirect surveillance of pathogen presence by monitoring the presence, abundance, and type of immune response to the pathogen or pathogen-associated epitopes. Serological surveillance of wild animals is important as wild animals are the primary reservoirs of many zoonotic diseases. Similarly, serological surveillance of agricultural animals is important due to their economic importance, in addition to animal welfare concerns. However, serology in any non-model animal such as wildlife or agricultural animals is difficult because serology necessarily relies on blood samples from the animals being tested. While companion or laboratory animals are generally sufficiently accustomed to humans that blood samples can be obtained, obtaining blood samples from wild or agricultural animals is more challenging. This initial challenge is compounded by the absence of validated serological tools to evaluate antibody titres in the sera. In this chapter, we provide methods for constructing an ELISA for the detection of anti-Borrelia antibodies in non-model animals, using studies on horses and cows as a proof of principle. The methods focus on the problems specific to non-model animals including obtaining sera, options for determining positive and negative controls without the ability to perform controlled infections, and methods for test optimization and validation.

URLhttps://link.springer.com/protocol/10.1007/978-1-0716-3561-2_4