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Atopic dermatitis is a common pruritic and inflammatory skin disorder with unknown etiology. Most commonly occurring during early childhood, atopic dermatitis is associated with eczematous lesions and lichenification, in which the epidermis becomes hypertrophied resulting in thickening of the skin. In this study, we report an atopic dermatitis-like pathophysiology results in a murine model following the expression of the high-risk Human Papillomavirus (HPV) 16 oncoprotein E7 in keratinocytes under the Keratin 14 promoter. We show that HPV 16 E7 expression in the skin is associated with skin thickening, acanthosis and light spongiosis. Locally, HPV 16 E7 expressing skin secreted high levels of TSLP and contained increased numbers of ILCs. High levels of circulating IgE were associated with increased susceptibility to skin allergy in a model of cutaneous challenge, and to airway bronchiolar inflammation, enhanced airway goblet cell metaplasia and mucus production in a model of atopic march. Surprisingly, skin pathology occurred independently of T-cells and mast cells. Thus, our findings suggest that the expression of a single HPV oncogene in the skin can drive the onset of atopic dermatitis-like pathology through the induction of TSLP and type 2 ILC infiltration.

Inhalation of grass pollen can result in acute exacerbation of asthma, prompting questions about how grass pollen reaches metropolitan areas. We establish typical atmospheric Poaceae (grass) pollen concentrations recorded at two pollen samplers within the Sydney basin in eastern Australia and analyse their correlation with each other and meteorological variables. We determine the effect of synoptic and regional airflow on Poaceae pollen transport during a period of extreme (≥ 100 grains m−3 air) concentration and characterise the meteorology. Finally, we tested the hypothesis that most Poaceae pollen captured by the pollen samplers originated from local sources. Fifteen months of daily pollen data, three days of hourly atmospheric Poaceae pollen concentrations and fifteen months of hourly meteorology from two locations within the Sydney basin were used. Weather Research Forecasting (WRF), Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) modelling and conditional bivariate probability functions (CBPF) were used to assess Poaceae pollen transport. Most Poaceae pollen collected was estimated to be from local sources under low wind speeds. Extreme daily Poaceae pollen concentrations were rare, and there was no strong evidence to support long-distance Poaceae pollen transport into the Sydney basin or across the greater Sydney metropolitan area. Daily average pollen concentrations mask sudden increases in atmospheric Poaceae pollen, which may put a significant and sudden strain on the healthcare system. Mapping of Poaceae pollen sources within Sydney and accurate prediction of pollen concentrations are the first steps to an advanced warning system necessary to pre-empt the healthcare resources needed during pollen season.