Using molecular genetics to understand grass species pollen deposition; enhancing bio-aerosol models and implications for human health

Project: Externally funded research

Project Details


In this proposal, we aim to revolutionise the way that pollen is measured, model the spatial and temporal deposition of different species of grass pollen and identify linkages to human health.
In the UK population ~5% suffer from allergic reactions (ranging from hay fever to asthma attacks) and further 22% are sensitised to grass pollen (i.e. they have antibodies capable of causing reactions). Grass pollen is the single most important outdoor aeroallergen closely followed by tree pollen. Similar to tree pollen, sensitivity towards grass pollen varies between species. However, we have no way of detecting, modelling or forecasting the aerial-dispersion of pollen from different species of grass. These limitations are due to complete lack of detailed source maps reflecting both the presence and abundance of different species of grass and because grass pollen, contrary to tree pollen, can not be separated into species using traditional observational methods. Therefore, combinations of the approximately 150 different species of grass pollen that are monitored (using approaches that remain unchanged since World War II) are lumped into a single category and form the foundation of the pollen forecast. In this project we will both develop new models and new methods of detection that address these major shortcomings.
The present situation means that hay fever suffers and health practitioners do not know what species, or combination of species cause present symptoms. Individuals can be tested for against particular grass species, but there are ca. 16 million people sensitised to grass pollen, allergic reactions are complex and testing the population against 150 different grass species species is an overwhelming task. The alternative is to take an environmental approach by developing exposure models and identify the environmental conditions that induce the allergic response, which then can be profiled to human health.
Recent developments in the generation of a UK plant DNA "barcode" library and DNA sequencing technologies have provided a unique and timely opportunity to identify the species, or combinations of species of grass that are associated with the allergic response. The important development of the UK plant DNA barcode library now gives us the ability to not only target individual species in molecular genetic analyses, but also assign identities to sequences derived from very high throughput molecular meta-analyses of complex mixtures of pollen grains. Similarly, recent developments in next generation air quality models and the advancement of computing power, has enabled the extension of these models into aerobiology in order to study the release, dispersion and transformation of bioaerosols and how this affects the environment.
Here, a group of multidisciplinary researchers specialising in aerobiological modelling, DNA barcoding/molecular genetic identification and environmental health have teamed up with the UK Met Office in order to (a.) develop a novel and high-throughput molecular genetic way of measuring the geographical spread and abundance of different allergenic species of grass across the summer months, (b.) develop novel pollen bio-aerosol models and (c.) identify which species, or combinations of species are linked to the most severe public health outcomes of the allergic response (i.e. asthma).
The work will provide information that healthcare professionals and charities will be able to translate into helping individuals live healthier and more productive lives. The information will help those with long term health conditions effectively self-manage their conditions, contribute more effectively to the workplace and be less reliant on the health system with accompanied economic benefits. Employers will benefit from greater employer productivity and pharmaceutical companies will be able to better target the distribution of their products and therapies.
Effective start/end date01 Mar 201631 Dec 2020


  • Natural Environment Research Council (NE/N001710/1): £154,939.51

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 10 - Reduced Inequalities
  • SDG 11 - Sustainable Cities and Communities
  • SDG 13 - Climate Action
  • SDG 15 - Life on Land


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