Air pollution and climate change are potential drivers for the increasing burden of allergic diseases. The molecular mechanisms by which air pollutants and climate parameters may influence allergic diseases, however, are complex and elusive. This article provides an overview of physical, chemical and biological interactions between air pollution, climate change, allergens, adjuvants and the immune system, addressing how these interactions may promote the development of allergies. We reviewed and synthesized key findings from atmospheric, climate, and biomedical research. The current state of knowledge, open questions, and future research perspectives are outlined and discussed. The Anthropocene, as the present era of globally pervasive anthropogenic influence on planet Earth and, thus, on the human environment, is characterized by a strong increase of carbon dioxide, ozone, nitrogen oxides, and combustion- or traffic-related particulate matter in the atmosphere. These environmental factors can enhance the abundance and induce chemical modifications of allergens, increase oxidative stress in the human body, and skew the immune system toward allergic reactions. In particular, air pollutants can act as adjuvants and alter the immunogenicity of allergenic proteins, while climate change affects the atmospheric abundance and human exposure to bioaerosols and aeroallergens. To fully understand and effectively mitigate the adverse effects of air pollution and climate change on allergic diseases, several challenges remain to be resolved. Among these are the identification and quantification of immunochemical reaction pathways involving allergens and adjuvants under relevant environmental and physiological conditions.

We present version 14 of the photolysis module JVAL. Taking atmospheric conditions as input, JVAL calculates photolysis rate coefficients, i.e. the speed of dissociation of atmospheric molecules in the sunlight. Computational efficiency is obtained through the use of parameters for polynomial curve fitting and lookup tables. Physical changes compared to the previous version include a parameterization of the Lyman-alpha absorption, and an update of the UV/VIS cross sections to the most recent recommended values. JVAL also includes the auxiliary program JVPP (JVal PreProcessor) which pre-calculates these parameters based on the absorption cross sections and quantum yields of the atmospheric molecules. It is possible to use JVAL either as a stand-alone program or as a module inside the Modular Earth Submodel System (MESSy). JVAL is a community model published under the GNU General Public License.

Fast and accurate determination of the protein content of a sample is an important and non-trivial task of many biochemical, biomedical, food chemical, pharmaceutical, and environmental research activities. Different methods of total protein determination are used for a wide range of proteins with highly variable properties in complex matrices. These methods usually work reasonably well for proteins under controlled conditions, but the results for non-standard and complex samples are often questionable. Here, we compare new and well-established methods, including traditional amino acid analysis (AAA), aromatic amino acid analysis (AAAA) based on the amino acids phenylalanine and tyrosine, reversed-phase liquid chromatography of intact proteins with UV absorbance measurements at 220 and 280 nm (LC-220, LC-280), and colorimetric assays like Coomassie Blue G-250 dye-binding assay (Bradford) and bicinchoninic acid (BCA) assay. We investigated different samples, including proteins with challenging properties, chemical modifications, mixtures, and complex matrices like air particulate matter and pollen extracts. All methods yielded accurate and precise results for the protein and matrix used for calibration. AAA, AAAA with fluorescence detection, and the LC-220 method yielded robust results even under more challenging conditions (variable analytes and matrices). These methods turned out to be well-suited for reliable determination of the protein content in a wide range of samples, such as air particulate matter and pollen.

Some biological particles and macromolecules are particularly efficient ice nuclei (IN), triggering ice formation at temperatures close to 0 ∘C. The impact of biological particles on cloud glaciation and the formation of precipitation is still poorly understood and constitutes a large gap in the scientific understanding of the interactions and coevolution of life and climate. Ice nucleation activity in fungi was first discovered in the cosmopolitan genus Fusarium, which is widespread in soil and plants, has been found in atmospheric aerosol and cloud water samples, and can be regarded as the best studied ice-nucleation-active (IN-active) fungus. The frequency and distribution of ice nucleation activity within Fusarium, however, remains elusive. Here, we tested more than 100 strains from 65 different Fusarium species for ice nucleation activity. In total, ∼11 % of all tested species included IN-active strains, and ∼16 % of all tested strains showed ice nucleation activity above −12 ∘C. Besides Fusarium species with known ice nucleation activity, F. armeniacum, F. begoniae, F. concentricum, and F. langsethiae were newly identified as IN-active. The cumulative number of IN per gram of mycelium for all tested Fusarium species was comparable to other biological IN like Sarocladium implicatum, Mortierella alpina, and Snomax®. Filtration experiments indicate that cell-free ice-nucleating macromolecules (INMs) from Fusarium are smaller than 100 kDa and that molecular aggregates can be formed in solution. Long-term storage and freeze–thaw cycle experiments revealed that the fungal IN in aqueous solution remain active over several months and in the course of repeated freezing and thawing. Exposure to ozone and nitrogen dioxide at atmospherically relevant concentration levels also did not affect the ice nucleation activity. Heat treatments at 40 to 98 ∘C, however, strongly reduced the observed IN concentrations, confirming earlier hypotheses that the INM in Fusarium largely consists of a proteinaceous compound. The frequency and the wide distribution of ice nucleation activity within the genus Fusarium, combined with the stability of the IN under atmospherically relevant conditions, suggest a larger implication of fungal IN on Earth’s water cycle and climate than previously assumed.

For efficient analysis and characterization of biological ice nuclei under immersion freezing conditions, we developed the Twin-plate Ice Nucleation Assay (TINA) for high-throughput droplet freezing experiments, in which the temperature profile and freezing of each droplet is tracked by an infrared detector. In the fully automated setup, a couple of independently cooled aluminum blocks carrying two 96-well plates and two 384-well plates, respectively, are available to study ice nucleation and freezing events simultaneously in hundreds of microliter-range droplets (0.1–40 µL). A cooling system with two refrigerant circulation loops is used for high-precision temperature control (uncertainty < 0.2 K), enabling measurements over a wide range of temperatures ( ∼ 272–233 K) at variable cooling rates (up to 10 K min⁻¹). The TINA instrument was tested and characterized in experiments with bacterial and fungal ice nuclei (IN) from Pseudomonas syringae (Snomax®) and Mortierella alpina, exhibiting freezing curves in good agreement with literature data. Moreover, TINA was applied to investigate the influence of chemical processing on the activity of biological IN, in particular the effects of oxidation and nitration reactions. Upon exposure of Snomax® to O₃ and NO₂, the cumulative number of IN active at 270–266 K decreased by more than 1 order of magnitude. Furthermore, TINA was used to study aqueous extracts of atmospheric aerosols, simultaneously investigating a multitude of samples that were pre-treated in different ways to distinguish different kinds of IN. For example, heat treatment and filtration indicated that most biological IN were larger than 5 µm. The results confirm that TINA is suitable for high-throughput experiments and efficient analysis of biological IN in laboratory and field samples.