Enzyme immunoassays for the investigation of protein nitration by air pollutants

Thomas Franze, Michael G. Weller, Reinhard Niessner, Ulrich Pöschl

Research output: Contribution to journalArticlepeer-review

57 Scopus citations

Abstract

Two enzyme immunoassays have been developed, characterised, and applied to investigate protein nitration in birch pollen extract (BPE) and bovine serum albumin (BSA) samples exposed to air pollutants. The monoclonal antibody CAY-189542 against nitrotyrosine (raised against peroxynitrite-treated keyhole limpet hemocyanine) was characterised in an indirect competitive assay (affinity and cross-reactivities) and applied in a new one-sided enzyme immunoassay for nitrated proteins. The one-sided assay was calibrated against a nitrated BSA standard with an average of 14 nitrotyrosine residues per molecule (nitro-(14)-BSA; detection limit 8.3 pmol L-1), and the sensitivity of the test was found to be significantly enhanced by a multivalent binding mode of the monoclonal antibody (bonus effect of multivalency). The same antibody and a polyclonal antibody against Bet v 1, the most prominent birch pollen allergen, were used in a new sandwich immunoassay for specific determination of nitrated Bet v 1. This assay was calibrated against a nitrated Bet v1 standard with an average of 3 nitrotyrosine residues per molecule (nitro-(3)-Bet v 1; detection limit 0.2 nmol L-1). Bet v I and BSA exposed to polluted urban outdoor air and to synthetic gas mixtures containing NO2 and O3 at atmospherically relevant concentration levels were found to be efficiently nitrated within hours to days. Pronounced correlations of nitro-(14)-BSA equivalent concentrations with exposure time and with nitro-(3)-Bet v 1 equivalent concentrations in nitrated BPE samples were observed. Test experiments indicated that the efficiency of protein nitration was strongly enhanced by reactive species formed upon interaction of NO2 with O3 and H2O (e.g. NO3 and HNO3). Potential implications of protein nitration by air pollutants are outlined and discussed.

Original languageEnglish
Pages (from-to)824-831
Number of pages8
JournalAnalyst
Volume128
Issue number7
DOIs
StatePublished - 1 Jul 2003

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