Molecular, proteomic and immunological parameters of allergens provide inclusion criteria for new candidates within established grass and tree homologous groups

Abstract

Background: Our knowledge of allergen structure and function continues to rise and new scientific data on the homology and cross-reactivity of allergen sources should be considered to extend the work of Lorenz et al., 2009 (Int Arch Allergy Immunol. 148(1):1-1, 2009) and the concept of homologous groups. In addition to this, sophisticated techniques such as mass spectrometry (MS) are increasingly utilised to better characterise the complex mix and nature of allergen extracts.

Methods: Homology models were used of Fag s 1 (Beech) and Cyn d 1 (Bermuda grass) and compared with template crystal structures of Bet v 1 and Phl p 1 from the 'exemplar' species of Birch and Timothy grass, respectively. ELISA experiments were performed to assess cross-reactivity of Beech (tree) and Bermuda (grass) extracts to rabbit sera raised to either "3-Tree" (Birch, Alder and Hazel) extract or "Grass" (12-grass mix extract), respectively. The comparability of biochemical stability of different allergen sources was assessed through statistical methods for a range of tree and grass species.

Results: Allergen cross-reactivity and/or structural homology have been described providing justification for inclusion of Beech within the Birch homologous tree group. Data from Bermuda grass (Cyn d 1) provides further justification for the inclusion of this species into the homologous group of the sweet grasses. However, further characterisation of relevant allergens from Bermuda grass and, in particular, comparison of cross-reactive patterns between subjects specifically in areas with high abundance of both Pooideae and Chloridoideae is sought.

Conclusion: MS allows the possibility to identify individual proteins or allergens from complex mixes by mass and/or sequence, and this has been extensively applied to the allergen field. New data on the homology, cross-reactivity and biological parameters of allergen sources have been considered to extend the work of Lorenz et al., 2009 in the context of tree and grass species. The concept of homologous groups is certainly dynamic allowing the flexibility and potential in streamlining quality parameters, such as stability profiles, due to extrapolation of exemplar data to a wider range of allergens.

Keywords: Allergens; Cross-reactivity; Grass; Homology; Structure; Tree.

Figure 1

Allergen sample preparation and analysis.

Figure 2

Structural homology of Fag s 1. (i) Superimposed Ribbon drawing of the Fag s 1 (green) homology model superimposed onto the template crystal structure of Bet v 1 major allergen (magenta) (ii) Space filling model of Fag s 1; conserved amino acid residues are coloured in red, different residues in white, homologous substitutions in blue (69% identity/80% similarity).

Figure 3

Cross-reactivity of grouped and ungrouped (Beech) trees against 3-Tree (Birch, Alder, Hazel) positive rabbit sera. Error bars represent the standard deviation from 4 replicates.

Figure 4

Species and time interaction effect coefficients and 95% confidence intervals for protein content (using Birch as reference).

Figure 5

Structural homology of Cyn d 1. (i) Superimposed Ribbon drawing of the Cyn d 1 (green) homology model superimposed onto the template crystal structure of Phl p 1 major allergen (magenta) (ii) Space filling model of Cyn d 1, conserved amino acid residues are coloured in red, different residues in white, homologous substitutions in blue (68% identity/76% homology).

Figure 6

Cross-reactivity of grouped and non-grouped (Bermuda) grass species against 12-grass positive rabbit sera. Error bars represent the standard deviation from 4 replicates.

Figure 7

Allergen and time interaction effect coefficients and 95% confidence intervals for protein content (using 12-grass as reference).