Comprehensive analysis of different adhesives in aerobiological sampling using optical microscopy and high-throughput DNA sequencing

Decrypting seasonal patterns of key pollen taxa in cool temperate Australia: A multi-barcode metabarcoding analysis

Pollen allergies pose a considerable global public health concern. Allergy risk can vary significantly within plant families, yet some key pollen allergens can only be identified to family level by current optical methods. Pollen information with greater taxonomic resolution is therefore required to best support allergy prevention and self-management. We used environmental DNA (eDNA) metabarcoding to deepen taxonomic insights into the seasonal composition of airborne pollen in cool temperate Australia, a region with high rates of allergic respiratory disease. In Hobart, Tasmania, we collected routine weekly air samples from December 2018 until October 2020 and sequenced the internal transcribed spacer 2 (ITS2) and chloroplastic tRNA-Leucine tRNA-Phenylalanine intergenic spacer (trnL-trnF) regions in order to address the following questions: a) What is the genus-level diversity of known and potential aeroallergens in Hobart, in particular, in the families Poaceae, Cupressaceae and Myrtaceae? b) How do the atmospheric concentrations of these taxa change over time, and c) Does trnL-trnF enhance resolution of biodiversity when used in addition to ITS2? Our results suggest that individuals in the region are exposed to temperate grasses including Poa and Bromus in the peak grass pollen season, however low levels of exposure to the subtropical grass Cynodon may occur in autumn and winter. Within Cupressaceae, both metabarcodes showed that exposure is predominantly to pollen from the introduced genera Cupressus and Juniperus. Only ITS2 detected the native genus, Callitris. Both metabarcodes detected Eucalyptus as the major Myrtaceae genus, with trnL-trnF exhibiting primer bias for this family. These findings help refine our understanding of allergy triggers in Tasmania and highlight the utility of multiple metabarcodes in aerobiome studies.

Development of Novel Early Detection Technology for Hemlock Woolly Adelgid, Adelges tsugae (Hemiptera: Adelgidae)

Hemlock woolly adelgid (HWA), Adelges tsugae Annand, threatens hemlock forests throughout eastern North America. Management efforts focus on early detection of HWA to ensure rapid management responses to control and stop the spread of this pest. This study's goal was to identify an affordable, efficient trap to aid with airborne environmental DNA (eDNA) sampling approaches as an early monitoring tool for HWA. We initially compared HWA detection success between a standard sticky trap, commonly used for HWA monitoring, and trap designs potentially compatible with eDNA protocols (i.e., passive trap, funnel trap, and motorized trap). Passive, funnel, and motorized traps' estimated capture success probabilities compared to sticky traps were 0.87, 0.8, and 0.4, respectively. A secondary evaluation of a modified version of the motorized trap further assessed trap performance and determined the number of traps needed in a set area to efficiently detect HWA. By modifying the original motorized trap design, its estimated capture success probability increased to 0.67 compared to a sticky trap. Overall, the cumulative capture success over the 16-week sampling period for the motorized trap was 94% and 99% for the sticky trap. The number of traps did impact capture success, and trap elevation and distance to infested hemlocks influenced the number of adelgids captured per trap. As eDNA-based monitoring approaches continue to become incorporated into invasive species surveying, further refinement with these types of traps can be useful as an additional tool in the manager's toolbox.

Bioaerosols in the atmosphere at two sites in Northern Europe in spring 2021: Outline of an experimental campaign

A coordinated observational and modelling campaign targeting biogenic aerosols in the air was performed during spring 2021 at two locations in Northern Europe: Helsinki (Finland) and Siauliai (Lithuania), approximately 500 km from each other in north-south direction. The campaign started on March 1, 2021 in Siauliai (12 March in Helsinki) and continued till mid-May in Siauliai (end of May in Helsinki), thus recording the transition of the atmospheric biogenic aerosols profile from winter to summer. The observations included a variety of samplers working on different principles. The core of the program was based on 2- and 2.4--hourly sampling in Helsinki and Siauliai, respectively, with sticky slides (Hirst 24-h trap in Helsinki, Rapid-E slides in Siauliai). The slides were subsequently processed extracting the DNA from the collected aerosols, which was further sequenced using the 3-rd generation sequencing technology. The core sampling was accompanied with daily and daytime sampling using standard filter collectors. The hourly aerosol concentrations at the Helsinki monitoring site were obtained with a Poleno flow cytometer, which could recognize some of the aerosol types. The sampling campaign was supported by numerical modelling. For every sample, SILAM model was applied to calculate its footprint and to predict anthropogenic and natural aerosol concentrations, at both observation sites. The first results confirmed the feasibility of the DNA collection by the applied techniques: all but one delivered sufficient amount of DNA for the following analysis, in over 40% of the cases sufficient for direct DNA sequencing without the PCR step. A substantial variability of the DNA yield has been noticed, generally not following the diurnal variations of the total-aerosol concentrations, which themselves showed variability not related to daytime. An expected upward trend of the biological material amount towards summer was observed but the day-to-day variability was large. The campaign DNA analysis produced the first high-resolution dataset of bioaerosol composition in the North-European spring. It also highlighted the deficiency of generic DNA databases in applications to atmospheric biota: about 40% of samples were not identified with standard bioinformatic methods.

Assessing the lysis of diverse pollen from bulk environmental samples for DNA metabarcoding

Pollen is ubiquitous year-round in bulk environmental samples and can provide useful information on previous and current plant communities. Characterization of pollen has traditionally been completed based on morphology, requiring significant time and expertise. DNA metabarcoding is a promising approach for characterizing pollen from bulk environmental samples, but accuracy hinges on successful lysis of pollen grains to free template DNA. In this study, we assessed the lysis of morphologically and taxonomically diverse pollen from one of the most common bulk environmental sample types for DNA metabarcoding, surface soil. To achieve this, a four species artificial pollen mixture was spiked into surface soils collected from Colorado, North Carolina, and Pennsylvania, and subsequently subjected to DNA extraction using both the PowerSoil and PowerSoil Pro Kits (Qiagen) with a heated incubation (either 65 °C or 90 °C). Amplification and Illumina sequencing of the internal transcribed spacer subunit 2 (ITS2) was completed in duplicate for each sample (total n, 76), and the resulting sequencing reads taxonomically identified using GenBank. The PowerSoil Pro Kit statistically outperformed the PowerSoil Kit for total DNA yield. When using either kit, incubation temperature (65 °C or 90 °C) used had no impact on the recovery of DNA, plant amplicon sequence variants (ASVs), or total plant ITS2 reads. This study highlighted that lysis of pollen in bulk environmental samples is feasible using commercially available kits, and downstream DNA metabarcoding can be used to accurately characterize pollen DNA from such sample types.

DNA metabarcoding using nrITS2 provides highly qualitative and quantitative results for airborne pollen monitoring

Airborne pollen monitoring is of global socio-economic importance as it provides information on presence and prevalence of allergenic pollen in ambient air. Traditionally, this task has been performed by microscopic investigation, but novel techniques are being developed to automate this process. Among these, DNA metabarcoding has the highest potential of increasing the taxonomic resolution, but uncertainty exists about whether the results can be used to quantify pollen abundance. In this study, it is shown that DNA metabarcoding using trnL and nrITS2 provides highly improved taxonomic resolution for pollen from aerobiological samples from the Netherlands. A total of 168 species from 143 genera and 56 plant families were detected, while using a microscope only 23 genera and 22 plant families were identified. NrITS2 produced almost double the number of OTUs and a much higher percentage of identifications to species level (80.1%) than trnL (27.6%). Furthermore, regressing relative read abundances against the relative abundances of microscopically obtained pollen concentrations showed a better correlation for nrITS2 (R2 = 0.821) than for trnL (R2 = 0.620). Using three target taxa commonly encountered in early spring and fall in the Netherlands (Alnus sp., Cupressaceae/Taxaceae and Urticaceae) the nrITS2 results showed that all three taxa were dominated by one or two species (Alnus glutinosa/incana, Taxus baccata and Urtica dioica). Highly allergenic as well as artificial hybrid species were found using nrITS2 that could not be identified using trnL or microscopic investigation (Alnus × spaethii, Cupressus arizonica, Parietaria spp.). Furthermore, perMANOVA analysis indicated spatiotemporal patterns in airborne pollen trends that could be more clearly distinguished for all taxa using nrITS2 rather than trnL. All results indicate that nrITS2 should be the preferred marker of choice for molecular airborne pollen monitoring.

Impact of Climate Change on Olive Crop Production in Italy

The effects of climate change on agricultural systems raise important uncertainties about the future productivity and suitability of crops, especially in areas suffering from intense environmental changes. Olive groves occupy Mediterranean areas characterized by seasonal temporary droughts, which cause this cultivation to be highly dependent on local microclimatic conditions. Olive crop production can be reliably estimated using pollen intensity metrics together with post-pollination environmental conditions. In this study, we applied this kind of statistics-based models to identify the most relevant meteorological variables during the post-pollination periods for olive fruit production. Olive pollen time-series for the period of 1999–2012 was analyzed in 16 Italian provinces. Minimum and maximum temperature during spring and summer (March–August) showed a negative relationship with olive production, while precipitation always showed a positive correlation. The increase in aridity conditions observed in areas of Italy during the summer represents an important risk of decreasing olive crop production. The effect of climate change on the olive production trend is not clear because of the interactions between human and environmental factors, although some areas might show an increase in productivity in the near future under different climate change scenarios. However, as more drastic changes in temperature or precipitation take place, the risk to olive production will be considerably greater.