| Literature DB >> 30261694 |
Line Ledsgaard1, Timothy P Jenkins2, Kristian Davidsen3, Kamille Elvstrøm Krause4, Andrea Martos-Esteban5, Mikael Engmark6,7, Mikael Rørdam Andersen8, Ole Lund9, Andreas Hougaard Laustsen10.
Abstract
Antivenom cross-reactivity has been investigated for decades to determine which antivenoms can be used to treat snakebite envenomings from different snake species. Traditionally, the methods used for analyzing cross-reactivity have been immunodiffusion, immunoblotting, enzyme-linked immunosorbent assay (ELISA), enzymatic assays, and in vivo neutralization studies. In recent years, new methods for determination of cross-reactivity have emerged, including surface plasmon resonance, antivenomics, and high-density peptide microarray technology. Antivenomics involves a top-down assessment of the toxin-binding capacities of antivenoms, whereas high-density peptide microarray technology may be harnessed to provide in-depth knowledge on which toxin epitopes are recognized by antivenoms. This review provides an overview of both the classical and new methods used to investigate antivenom cross-reactivity, the advantages and disadvantages of each method, and examples of studies using the methods. A special focus is given to antivenomics and high-density peptide microarray technology as these high-throughput methods have recently been introduced in this field and may enable more detailed assessments of antivenom cross-reactivity.Entities:
Keywords: antivenom; antivenomics; cross-neutralization; cross-reactivity; high-density peptide microarray technology; snakebite envenoming; toxins; venom
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Year: 2018 PMID: 30261694 PMCID: PMC6215175 DOI: 10.3390/toxins10100393
Source DB: PubMed Journal: Toxins (Basel) ISSN: 2072-6651 Impact factor: 4.546
Figure 1Schematic representation of the paratope-epitope interaction between an antibody binding to an antigen. The antibody paratope is comprised of Complementarity Determining Regions (CDRs). In the upper row, a conformational epitope of the full antigen is bound by the antibody, while in the lower row, a linear epitopic element of said epitope is bound in a similar fashion, but with fewer points of interaction (stars).
Figure 2The evolution of the antivenomics methodology. (1G) First generation antivenomics involves the formation of toxin-antibody complexes (1), which are then either immunoprecipitated or forced through a Protein A column to separate toxin-antibody complexes from unbound toxins (2). Both fractions are then analyzed by reversed-phase high performance liquid chromatography (RP-HPLC), which allows for the identification of bound and unbound toxins. (2G) In second generation antivenomics, antivenom molecules (whole antibodies or fragments) are covalently immobilized onto a chromatographic matrix (immunoaffinity column), and the venom of interest is forced through this column, with the unbound toxins running straight through (1). Thereafter, the bound and unbound toxins are analyzed by RP-HPLC (2). Finally, quantitative comparisons of RP-HPLC chromatograms of whole venom and the immunoaffinity column eluates can be made, thus providing qualitative and quantitative information on both the set of toxins bearing antivenom-recognized epitopes and those toxins exhibiting poor immunoreactivity (3). (3G) Third generation antivenomics builds upon the concept of the immunoaffinity column applied in 2G antivenomics and repeats the same initial procedure (1). However, a range of venom-antivenom concentrations are tested to determine the maximal binding capacity of an antivenom against each toxin in a venom, as well as the quantification of the fraction of toxin-specific antibodies present in the antivenom (2).
Figure 3A stepwise visualization of the methodology behind the high-density peptide microarray approach. (1) In silico generation of a peptide library of k-mers, typically 7–16 amino acids in length, by tiling known sequences of snake venom toxins. (2) Expansion of the peptide library with point substitutions of every amino acid with a substitute amino acid, such as alanine. (3) Production of the microarray by mask-less photolithographic synthesis of peptides on a solid phase treated glass slide. (4) Binding of primary antivenom antibodies to peptides. (5) Binding of secondary fluorophore-labeled antibody to primary antivenom antibodies. (6) Image capture of the fluorescent signals and calculation of signal intensities. (7) Bioinformatic data normalization, analysis, and epitope mapping. (8) Visualization of the potential conformation of linear epitopic elements in generated 3D toxin models.