Data from: Interpreting ELISA analyses from wild animal samples: some recurrent issues and solutions
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https://datadryad.org/dataset/doi:10.5061/dryad.0qk1h
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1. Many studies in disease and immunological ecology rely on the use of
assays that quantify the amount of specific antibodies (immunoglobulin) in
samples. Enzyme-Linked Immuno Sorbent Assays (ELISAs) are increasingly
used in ecology due to their availability for a broad array of antigens
and the limited amount of sampling material they require. Two recurrent
methodological issues are nevertheless faced by researchers: (i) the
limited availability of immunological assays and reagents developed for
non-model species, and (ii) the statistical determination of the cut-off
threshold used to distinguish individual samples that are likely to have
or not to have antibodies against a specific antigen. 2. Here, we outline
two solutions to deal with these issues. First, we show that implementing
two assays with differing detection methods can help validate the use of
reagents, such as antibodies, in species different from their intended
target. We illustrate this by comparing the quantification of specific
vaccinal antibodies against Newcastle Disease Virus (NDV) using two ELISA
approaches in four seabird species (Cory’s shearwater, European shag,
European storm petrel, and Southern rockhopper penguin). 3. Second, we
provide a simple way to determine from the distribution of ELISA values
whether the assayed samples are likely to be made of a single group of
individuals (likely negative) or of two groups of individuals (negative
and positive). We illustrate the use of this approach with two independent
datasets: NDV antibody levels following vaccination and anti-Borrelia
antibody levels following natural exposure. 4. The practical
implementation of these methodological approaches could provide a way to
efficiently apply ELISAs and other immune-based assays to address
questions in the growing fields of ecological immunology and disease
ecology.
提供机构:
Dryad
创建时间:
2017-06-21



