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Hydrogen/deuterium exchange memory NMR reveals structural epitopes involved in IgE cross-reactivity of allergenic lipid transfer proteins.

Martina Di MuzioSabrina WildnerSara HuberMichael HauserEva VejvarWerner AuzingerChristof ReglJosef LaimerDanila ZennaroNicole WopfnerChristian G HuberRonald van ReeAdriano MariPeter LacknerFatima FerreiraMario SchubertGabriele Gadermaier
Published in: The Journal of biological chemistry (2020)
Identification of antibody binding epitopes is crucial to understand immunological mechanisms. It is of particular interest for allergenic proteins with high cross-reactivity as observed in the lipid transfer protein (LTP) syndrome that is characterized by severe allergic reactions. Art v 3, a pollen LTP from mugwort is frequently involved in this cross-reactivity, but no antibody binding epitopes have been determined so far.  To reveal human IgE binding regions of Art v 3, we produced three murine high-affinity monoclonal antibodies (mAbs), which showed 70-90% coverage of the allergenic epitopes from mugwort pollen allergic patients. As reliable methods to determine structural epitopes with tightly interacting intact antibodies under native conditions are lacking, we developed a straightforward NMR approach termed hydrogen/deuterium exchange memory (HDXMEM). It relies on the slow exchange between the invisible antigen-mAb complex and the free 15N-labeled antigen whose 1H-15N correlations are detected. Due to a memory effect, changes of NH protection during antibody binding are measured. Differences in H/D exchange rates and analyses of mAb reactivity to homologous LTPs revealed three structural epitopes: two partially cross-reactive regions around α-helices 2 and 4, as well as a novel Art v 3-specific epitope at the C-terminus. Protein variants with exchanged epitope residues confirmed the antibody-binding sites and revealed strongly reduced IgE reactivity. Using the novel HDXMEM for NMR epitope mapping allowed identification of the first structural epitopes of an allergenic pollen LTP. This knowledge enables improved cross-reactivity prediction for patients suffering from LTP-allergy and facilitates design of therapeutics.
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