AirDNA sampler: An efficient and simple device enabling high-yield, high-quality airborne environment DNA for metagenomic applications.

Analyzing temporal and spatial distributions of airborne particles of biological origins is vital for the assessment and monitoring of air quality, especially with regard to public health, environmental ecology, and atmospheric chemistry. However, the analysis is frequently impeded by the low levels of biomass in the air, especially with metagenomic DNA analysis to explore diversity and composition of living organisms and their components in the air. To obtain sufficient amounts of metagenomic DNA from bioaerosols, researchers usually need a long sampling time with an expensive high-volume air sampler. This work shows the utilization of an air sampling device containing an economical, high-volume portable ventilation fan in combination with customized multi-sheet filter holders to effectively obtain high yields of genomic DNA in a relatively short time. The device, named 'AirDNA' sampler, performed better than other commercial air samplers, including MD8 Airport and Coriolis compact air samplers. Using the AirDNA sampler, an average DNA yield of 40.49 ng (12.47-23.24 ng at 95% CI) was obtained in only 1 hour of air sampling with a 0.85 probability of obtaining ≥10 ng of genomic DNA. The genomic DNA obtained by the AirDNA system is of suitable quantity and quality to be further used for amplicon metabarcoding sequencing of 16S, 18S, and cytochrome c oxidase I (COI) regions, indicating that it can be used to detect various prokaryotes and eukaryotes. Our results showed the effectiveness of our AirDNA sampling apparatus with a simple setup and affordable devices to obtain metagenomic DNA for short-term or long-term spatiotemporal analysis. The technique is well suited for monitoring air in built environments, especially monitoring bioaerosols for health purposes and for fine-scale spatiotemporal environmental studies.

Temporal, compositional, and functional differences in the microbiome of Bangkok subway air environment.

With the growing numbers of the urban population, an increasing number of commuters have relied on subway systems for rapid transportation in daily life. Analyzing the temporal distribution of air microbiomes in subway environments is crucial for the assessment and monitoring of air quality in the subway system, especially with regard to public health. This study employed culture-independent metabarcode sequencing to analyze bacterial diversity and variations in bacterial compositions associated with bioaerosols collected from a subway station in Bangkok over a four-month period. The bacteria obtained were found to consist primarily of Proteobacteria, Firmicutes, and Actinobacteria, with variations at the family, genus, and species levels among samples obtained in different months. The vast majority of these bacteria are most likely derived from outside environments and human body sources. Many of the bacteria found in Bangkok subway station were also identified as "core microorganisms" of subway environments around the world, as suggested by the MetaSUB Consortium. The diversity of bacterial communities was shown to be influenced by several air quality variables, especially ambient temperature and the quantity of particulate matters, which showed positive correlations with several bacterial species such as Acinetobacter lwoffii, Staphylococcus spp., and Moraxella osloensis. In addition, metabolic profiles inferred from metabarcode-derived bacterial diversity showed significant variations across different sampling times and sites and can be used as a starting point to further explore the functional roles of specific groups of bacteria in the subway environment. This study thus introduced the information required for surveillance of microbiological impacts and their contributions to the well-being of subway commuters in Bangkok.

Detection and monitoring of insect traces in bioaerosols.

Studies on bioaerosols have primarily focused on their chemical and biological compositions and their impact on public health and the ecosystem. However, most bioaerosol studies have only focused on viruses, bacteria, fungi, and pollen. To assess the diversity and composition of airborne insect material in particulate matter (PM) for the first time, we attempted to detect DNA traces of insect origin in dust samples collected over a two-year period. These samples were systematically collected at one-month intervals and categorized into two groups, PM2.5 and PM10, based on the aerodynamic diameter of the aerosol particles. Cytochrome-c oxidase I (COI) was the barcoding region used to identify the origins of the extracted DNA. The airborne insect community in these samples was analyzed using the Illumina MiSeq platform. The most abundant insect sequences belonged to the order Hemiptera (true bugs), whereas order Diptera were also detected in both PM2.5 and PM10 samples. Additionally, we inferred the presence of particulates of insect origin, such as brochosomes and integument particles, using scanning electron microscopy (SEM). This provided additional confirmation of the molecular results. In this study, we demonstrated the benefits of detection and monitoring of insect information in bioaerosols for understanding the source and composition. Our results suggest that the PM2.5 and PM10 groups are rich in insect diversity. Lastly, the development of databases can improve the identification accuracy of the analytical results.

Biological Trace Information Extracted from Bioaerosols Using NGS Analysis

Bioaerosols are atmospheric particles with a biological trace, such as viruses, bacteria, fungi, and plant material such as pollen and plant debris. In this study, we analyzed the biological information in bioaerosols using next generation sequencing of the trace DNA. The samples were collected using an Andersen air sampler and separated into two groups according to particulate matter (PM) size: small (PM2.5) and large (PM10). Amplification and sequencing of the bacterial 16S rDNA gene, prokaryotic internal transcribed spacer 1 (ITS1) region and DNA sequence of a plant chloroplast gene (rbcL) were carried out using several sets of specific primers targeting animal and plant sequences. Lots of bacterial information was detected from the bioaerosols. The most abundant bacteria in several samples were of the Actinobacteria (class), Alphaproteobacteria, Bacilli, and Clostridia. For the animal detection using internal transcribed spacer 1, only uncultured fungi were detected in more than half of the hits, with a high number of Cladosporium sp. in the samples. For the plant identification, the ITS1 information only matched fungal species. However, targeting of the rbcL region revealed diverse plant information, such as Medicago papillosa. In conclusion, traces of bacteria, fungi, and plants could be detected in the bioaerosols, but not of animals using our primers.

Bioconversion of AHX to AOH by resting cells of Burkholderia contaminans CH-1.

Fairy rings are zones of stimulated grass growth owing to the interaction between a fungus and a plant. We previously reported the discovery of two novel plant-growth regulating compounds related to forming fairy rings, 2-azahypoxanthine (AHX) and 2-aza-8-oxohypoxanthine (AOH). In this study, a bacterial strain CH-1 was isolated from an airborne-contaminated nutrient medium containing AHX. The strain converted AHX to AOH and identified as Burkholderia contaminans based on the gene sequence of its 16S rDNA. The quantitative production of AOH by resting cells of the strain was achieved. Among seven Burkholderia species, two bacteria and two yeasts tested, B. contaminans CH-1 showed the highest rate of conversion of AHX to AOH. By batch system, up to 10.6 mmol AHX was converted to AOH using the resting cells. The yield of this process reached at 91%.