Predicting the severity of the grass pollen season and the effect of climate change in Northwest Europe.

Allergic rhinitis is an inflammation in the nose caused by overreaction of the immune system to allergens in the air. Managing allergic rhinitis symptoms is challenging and requires timely intervention. The following are major questions often posed by those with allergic rhinitis: How should I prepare for the forthcoming season? How will the season's severity develop over the years? No country yet provides clear guidance addressing these questions. We propose two previously unexplored approaches for forecasting the severity of the grass pollen season on the basis of statistical and mechanistic models. The results suggest annual severity is largely governed by preseasonal meteorological conditions. The mechanistic model suggests climate change will increase the season severity by up to 60%, in line with experimental chamber studies. These models can be used as forecasting tools for advising individuals with hay fever and health care professionals how to prepare for the grass pollen season.

Temperate airborne grass pollen defined by spatio-temporal shifts in community composition.

Grass pollen is the world's most harmful outdoor aeroallergen. However, it is unknown how airborne pollen assemblages change across time and space. Human sensitivity varies between different species of grass that flower at different times, but it is not known whether temporal turnover in species composition match terrestrial flowering or whether species richness steadily accumulates over the grass pollen season. Here, using targeted, high-throughput sequencing, we demonstrate that all grass genera displayed discrete, temporally restricted peaks of incidence, which varied with latitude and longitude throughout Great Britain, revealing that the taxonomic composition of grass pollen exposure changes substantially across the grass pollen season.

Differences in microbial activity and microbial populations of peat associated with suppression of damping-off disease caused by Pythium sylvaticum.

The microbiological characteristics associated with disease-suppressive peats are unclear. We used a bioassay for Pythium sylvaticum-induced damping-off of cress seedlings to identify conducive and suppressive peats. Microbial activity in unconditioned peats was negatively correlated with the counts of P. sylvaticum at the end of the bioassay. Denaturing gradient gel electrophoresis (DGGE) profiling and clone library analyses of small-subunit rRNA gene sequences from two suppressive and two conducive peats differed in the bacterial profiles generated and the diversity of sequence populations. There were also significant differences between bacterial sequence populations from suppressive and conducive peats. The frequencies of a number of microbial groups, including the Rhizobium-Agrobacterium group (specifically sequences similar to those for the genera Ochrobactrum and Zoogloea) and the Acidobacteria, increased specifically in the suppressive peats, although no single bacterial group was associated with disease suppression. Fungal DGGE profiles varied little over the course of the bioassay; however, two bands associated specifically with suppressive samples were detected. Sequences from these bands corresponded to Basidiomycete yeast genera. Although the DGGE profiles were similar, fungal sequence diversity also increased during the bioassay. Sequences highly similar to those of Cryptococcus increased in relative abundance during the bioassay, particularly in the suppressive samples. This study highlights the importance of using complementary approaches to molecular profiling of complex populations and provides the first report that basidiomycetous yeasts may be associated with the suppression of Pythium-induced diseases in peats.

Spatial and temporal analysis of the microbial community in slow sand filters used for treating horticultural irrigation water.

An experimental slow sand filter (SSF) was constructed to study the spatial and temporal structure of a bacterial community suppressive to an oomycete plant pathogen, Phytophthora cryptogea. Passage of water through the mature sand column resulted in complete removal of zoospores of the plant pathogen. To monitor global changes in the microbial community, bacterial and fungal numbers were estimated on selective media, direct viable counts of fungal spores were made, and the ATP content was measured. PCR amplification of 16S rRNA genes and denaturing gradient gel electrophoresis (DGGE) were used to study the dynamics of the bacterial community in detail. The top layer (1 cm) of the SSF column was dominated by a variable and active microbial population, whereas the middle (50 cm) and bottom (80 cm) layers were dominated by less active and diverse bacterial populations. The major changes in the microbial populations occurred during the first week of filter operation, and these populations then remained to the end of the study. Spatial and temporal nonlinear mapping of the DGGE bands provided a useful visual representation of the similarities between SSF samples. According to the DGGE profile, less than 2% of the dominating bands present in the SSF column were represented in the culturable population. Sequence analysis of DGGE bands from all depths of the SSF column indicated that a range of bacteria were present, with 16S rRNA gene sequences similar to groups such as Bacillus megaterium, Cytophaga, Desulfovibrio, Legionella, Rhodococcus rhodochrous, Sphingomonas, and an uncharacterized environmental clone. This study describes the characterization of the performance, and microbial composition, of SSFs used for the treatment of water for use in the horticultural industry. Utilization of naturally suppressive population of microorganisms either directly or by manipulation of the environment in an SSF may provide a more reproducible control method for the future.