Size resolved characteristics of urban and suburban bacterial bioaerosols in Japan as assessed by 16S rRNA amplicon sequencing

Association among polydisperse aerodynamic size of bioaerosols, biodiversity and urbanization in kindergartens

The aerodynamic sizes of bioaerosols may significantly affect their behaviors, respiratory deposition and biodiversity. The respirable bacterial size, biodiversity, and human-associated bacteria (HAB) related bioaerosols were evaluated at three kindergartens in Taiwan. Kindergartens A, B, and C were in urban, semi-urban, and rural areas, respectively. A six-stage viable Andersen cascade impactor was used to collect bioaerosols and to determine their size distributions. The geometric mean diameter (GMD), geometric standard deviation (GSD), heat maps, and uniformity were used to evaluate the association of bacteria characteristics. A BD Phoenix-100 automated interpretation system was used to identify the airborne bacteria species. The results revealed that 1425 colonies of the sampled airborne bacteria contained 63 species in 29 genera, and overall, 63.0% were HABs. The most abundant phylum was Actinobacteria (56.6 ± 22.2%) and Firmicutes (31.6 ± 22.3%), and from the taxonomic analysis, both airborne Micrococcus and the Staphylococcus aureus are the dominant genus. All the bacteria aerodynamic particle size distributions were polydisperse distributions. The heat map and uniformity analysis had revealed most of the sampled bioaerosols distributed between 1.1-3.3 μm, and most of the polydisperse airborne Streptococcus spp. had a size in the respirable range, due to urbanization, they have potentially contributed to respiratory risk in the kindergartens. The Shannon diversity index (H) and inverse Simpson diversity index (D) of the bioaerosols in urban kindergarten were negatively correlated with GMD and GSD. The Pearson correlations revealed that the kindergarten in the rural area, with a higher temperature, a lower relative humidity, and a lower CO2 concentration than the others, tended to have the largest H and D values (P < 0.05). Multiple and stepwise regression revealed that bioaerosol aerodynamic size was statistically significantly correlated with H (P = 0.001) and D values (P = 0.002). This study sheds light on the characteristics of bioaerosols and their associations with microbiome.

Impact of cultivating different Ocimum species on bioaerosol bacterial communities and functional genome at an agricultural site

The effects of the surrounding environment on the bacterial composition of bioaerosol were well documented for polluted and contaminated sites. However, there is limited data on the impact of plant species, especially those that produce aromas, on bioaerosol composition at agricultural sites. Hence, the aim of this study is to evaluate the variability in bacterial communities present in bioaerosol samples collected from agricultural sites with aroma-producing crops. For this, PM2.5, PM10, and bioaerosol samples were collected from agricultural fields growing Ocimum [two varieties of O. sanctum (CIM-Aayu and CIM-Angana)] and O. kilimandscharicum (Kapoor), nearby traffic junctions and suburban areas. PM2.5 and PM10 concentrations at the agricultural site were in between the other two polluted sites. However, bioaerosol concentration was lower at agricultural sites than at other sites. The culturable bacteria Bacillus subtilis, Bacillus tequilensis, and Staphylococcus saprophyticus were more prevalent in agricultural sites than in other areas. However, the composition of non-culturable bacteria varied between sites and differed in three fields where Ocimum was cultivated. The CIM-Aayu cultivated area showed a high bacterial richness, lower Simpson and Shannon indices, and a distinctive metabolic profile. The sites CIM-Angana and CIM-Kapoor had a higher abundance of Aeromonas, while Pantoea and Pseudomonas were present at CIM-Aayu. Acinetobacter, Staphylococcus, and Bacillus were the dominant genera at the other two sites. Metabolic profiling showed that the CIM-Aayu site had a higher prevalence of pathways related to amino acid and carbohydrate metabolism and environmental information processing compared to other sites. The composition of bioaerosol among the three different Ocimum sites could be due to variations in the plant volatile and cross-feeding nature of bacterial isolates, which further needs to be explored.

Characteristics and Traceability Analysis of Microbial Assemblage in Fine Particulate Matter from a Pig House

Fine particulate matter (PM2.5) can carry numerous substances and penetrate deep into the respiratory tract due to its small particle size; associated harmful microorganisms are suspected to increase health risks for humans and animals. To find out the microbial compositions of PM2.5 in piggeries, their interaction and traceability, we collected PM2.5 samples from a piggery while continuously monitoring the environmental indicators. We also identified pathogenic bacteria and allergens in the samples using high-throughput sequencing technology. We analyzed the microbial differences of PM2.5 samples at different heights and during different times of day and investigated the microbial dynamics among the PM2.5 samples. To better understand the interaction between microorganisms and environmental factors among different microbial communities, we applied the network analysis method to identify the correlation among various variables. Finally, SourceTracker, a commonly used microbial traceability tool, was used to predict the source of airborne microorganisms in the pig house. We identified 14 potential pathogenic bacteria and 5 allergens from PM2.5 in the pig houses, of which Acinetobacter was the dominant bacterium in all samples (relative abundance > 1%), which warrants attention. We found that bacteria and fungi directly affected the the microbial community. The bacterial community mainly played a positive role in the microbial community. Environmental variables mainly indirectly and positively affected microbial abundance. In the SourceTracker analysis using fecal matter and feed as sources and PM2.5 sample as sink, we found that fecal matter made the greatest contribution to both bacterial and fungal components of PM2.5. Our findings provide important insights into the potential risks of pathogens in PM2.5 to human and animal health and their main sources.

Seasonal dynamics in bacterial communities of closed-cage broiler houses

The bacteria contained in air aerosols from poultry houses are closely connected to animal health and production. This study aimed to investigate the seasonal factors on microbial aerosol concentration, particle size and bacterial spectrum composition inside a closed-cage broiler house. Then, 16S rDNA sequencing technology was applied to analyze the characteristics of bacterial abundance and diversity. The results indicated that the concentration of bacterial aerosol in the broiler house varied significantly in different seasons, with a concentration range of 5.87–15.77 × 10³ CFU/m³, and the highest and lowest concentrations in the summer and winter, respectively. Microbiological analysis showed that the proportion of Gram-negative bacteria in autumn was significantly higher than that in summer (P < 0.05). In addition, the floral structure of potential pathogenic bacterial genera also differed by season. Escherichia-Shigella, Streptococcus, Acinetobacter, Pseudomonas were identified in the bacterial aerosols. Importantly, the relative abundance of Firmicutes in spring and autumn was much higher. In contrast, the relative abundance of Proteobacteria in spring and autumn was lower than that in summer and winter. Altogether, results revealed the effects of seasonal factors on the diversity and abundance of bacteria and the distribution characteristics of major opportunistic pathogens in the air of closed-cage broiler houses. These results will provide important information for exploring the potential risk of aerosols from poultry houses all four seasons.

Airborne Prokaryotic, Fungal and Eukaryotic Communities of an Urban Environment in the UK

Bioaerosols often contain human pathogens and allergens affecting public health. However, relatively little attention has been given to bioaerosols compared with non-biological aerosols. In this study, we aimed to identify bioaerosol compositions in Manchester, UK by applying high throughput sequencing methods and to find potential sources. Samples were collected at Manchester Air Quality Super Site at the Firs Environmental Research Station in November 2019 and in February 2020. Total DNA has been extracted and sequenced targeting the 16S rRNA gene of prokaryotes, ITS region of fungal DNA and 18S rRNA gene of eukaryotes. We found marine environment-associated bacteria and archaea were relatively more abundant in the February 2020 samples compared with the November 2019 samples, consistent with the North West marine origin based on wind back-trajectory analysis. In contrast, an OTU belonging to Methylobacterium, which includes many species resistant to heavy metals, was relatively more abundant in November 2019 when there were higher metal concentrations. Fungal taxa that fruit all year were relatively more abundant in the February 2020 samples while autumn fruiting species generally had higher relative abundance in the November 2019 samples. There were higher relative abundances of land plants and algae in the February 2020 samples based on 18S rRNA gene sequencing. One of the OTUs belonging to the coniferous yew genus Taxus was more abundant in the February 2020 samples agreeing with the usual pollen season of yews in the UK which is from mid-January until late April. The result from this study suggests a potential application of bioaerosol profiling for tracing the source of atmospheric particles.

Urban Aerobiome and Effects on Human Health: A Systematic Review and Missing Evidence

Urban air pollutants are a major public health concern and include biological matters which composes about 25% of the atmospheric aerosol particles. Airborne microorganisms were traditionally characterized by culture-based methods recognizing just 1.5–15.3% of the total bacterial diversity that was evaluable by genome signature in the air environment (aerobiome). Despite the large number of exposed people, urban aerobiomes are still weakly described even if recently advanced literature has been published. This paper aims to systematically review the state of knowledge on the urban aerobiome and human health effects. A total of 24 papers that used next generation sequencing (NGS) techniques for characterization and comprised a seasonal analysis have been included. A core of Proteobacteria, Actinobacteria, Firmicutes, and Bacteroides and various factors that influenced the community structure were detected. Heterogenic methods and results were reported, for both sampling and aerobiome diversity analysis, highlighting the necessity of in-depth and homogenized assessment thus reducing the risk of bias. The aerobiome can include threats for human health, such as pathogens and resistome spreading; however, its diversity seems to be protective for human health and reduced by high levels of air pollution. Evidence of the urban aerobiome effects on human health need to be filled up quickly for urban public health purposes.

Airborne microbial community structure and potential pathogen identification across the PM size fractions and seasons in the urban atmosphere

As a vital component of airborne bioaerosols, bacteria and fungi seriously endanger human health as pathogens and allergens. However, comprehensive effects of environmental variables on airborne microbial community structures remain poorly understood across the PM sizes and seasons. We collected atmospheric PM_1.0, PM_2.5, and PM₁₀ samples in Hefei, a typical rapidly-developing city in East China, across three seasons, and performed a comprehensive analysis of airborne microbial community structures using qPCR and high-throughput sequencing. Overall the bacterial and fungal abundances in PM_1.0 were one to two orders of magnitude higher than those in PM_2.5 and PM₁₀ across seasons, but their α-diversity tended to increase from PM_1.0 to PM₁₀. The bacterial gene abundances showed a strong positive correlation (P < 0.05) with atmospheric SO₂ and NO₂ concentrations and air quality index. The bacterial gene abundances were significantly higher (P = 0.001) than fungi, and the bacterial diversity showed stronger seasonality. The PM sizes influenced distribution patterns for airborne microbial communities within the same season. Source-tracking analysis indicated that soils, plants, human and animal feces represented important sources of airborne bacteria with a total relative abundance of more than 60% in summer, but total abundance from the unidentified sources surpassed in fall and winter. Total 10 potential bacterial and 12 potential fungal pathogens were identified at the species level with the highest relative abundances in summer, and their abundances increased with the PM sizes. Together, our results indicated that a complex set of environmental factors, including water-soluble ions in PM, changes in air pollutant levels and meteorological conditions, and shifts in the relative importance of available microbial sources, acted to control the seasonal compositions of microbial communities in the urban atmosphere.

Bacterial Diversity of Root Nodule and Rhizosphere Soil Samples of Green Soybean (Edamame) in Japan

We analyzed the bacterial diversity of root nodule and rhizosphere soil samples of edamame collected in Ebina, Japan. The major population identified from the nodules belonged to the genus Bradyrhizobium, and the rhizosphere soil in the open field has a higher abundance of the Rhizobiales order bacteria than that in the greenhouse.

Identifying optimal bioinformatics protocols for aerosol microbial community data

Microbes are fundamental to Earth’s ecosystems, thus understanding ecosystem connectivity through microbial dispersal is key to predicting future ecosystem changes in a warming world. However, aerial microbial dispersal remains poorly understood. Few studies have been performed on bioaerosols (microorganisms and biological fragments suspended in the atmosphere), despite them harboring pathogens and allergens. Most environmental microbes grow poorly in culture, therefore molecular approaches are required to characterize aerial diversity. Bioinformatic tools are needed for processing the next generation sequencing (NGS) data generated from these molecular approaches; however, there are numerous options and choices in the process. These choices can markedly affect key aspects of the data output including relative abundances, diversity, and taxonomy. Bioaerosol samples have relatively little DNA, and often contain novel and proportionally high levels of contaminant organisms, that are difficult to identify. Therefore, bioinformatics choices are of crucial importance. A bioaerosol dataset for bacteria and fungi based on the 16S rRNA gene (16S) and internal transcribed spacer (ITS) DNA sequencing from parks in the metropolitan area of Auckland, Aotearoa New Zealand was used to develop a process for determining the bioinformatics pipeline that would maximize the data amount and quality generated. Two popular tools (Dada2 and USEARCH) were compared for amplicon sequence variant (ASV) inference and generation of an ASV table. A scorecard was created and used to assess multiple outputs and make systematic choices about the most suitable option. The read number and ASVs were assessed, alpha diversity was calculated (Hill numbers), beta diversity (Bray–Curtis distances), differential abundance by site and consistency of ASVs were considered. USEARCH was selected, due to higher consistency in ASVs identified and greater read counts. Taxonomic assignment is highly dependent on the taxonomic database used. Two popular taxonomy databases were compared in terms of number and confidence of assignments, and a combined approach developed that uses information in both databases to maximize the number and confidence of taxonomic assignments. This approach increased the assignment rate by 12–15%, depending on amplicon and the overall assignment was 77% for bacteria and 47% for fungi. Assessment of decontamination using “decontam” and “microDecon” was performed, based on review of ASVs identified as contaminants by each and consideration of the probability of them being legitimate members of the bioaerosol community. For this example, “microDecon’s” subtraction approach for removing background contamination was selected. This study demonstrates a systematic approach to determining the optimal bioinformatics pipeline using a multi-criteria scorecard for microbial bioaerosol data. Example code in the R environment for this data processing pipeline is provided.

Bacterial Contamination in Health Care Centers: Differences between Urban and Rural Settings

This study aims to assess the airborne bioburden of rural and urban Portuguese Primary Health Care Centers (PHCC) using active and passive sampling methods and identify the potential differences in airborne microbiota between both environments. The highest total aerobic mesophilic bacterial load in indoor air were found in the Vaccination Room (448 CFU.m−3) in the Rural PHCC and in the Waiting Room (420 CFU.m−3) for Urban PHCC. The total coliforms contamination level in indoor air was detected only in the Cleaning Supplies Room (4 CFU.m−3) in the Urban PHCC. The most frequent bacteria genera identified was Micrococcus (21% Rural PHCC; 31% Urban PHCC). The surface samples showed a highest total aerobic mesophilic bacterial contamination in the Treatment Room (86 × 103 CFU.m−2) from the Rural PHCC and in the Front Office (200 × 103 CFU.m−2) from the Urban PHCC. The electrostatic dust cloth (EDC) samples showed a highest bacterial load in the Urban PHCC. Total aerobic mesophilic bacterial load in settled dust and in the Heating, Ventilating and Air Conditioning (HVAC) filter samples in the Urban PHCC (8 CFU.g−1 and 6 × 103 CFU.m−2) presented higher values compared with the Rural PHCC (1 CFU.g−1 and 2.5 × 103 CFU.m−2). Urban PHCC presented higher bacterial airborne contamination compared with the Rural PHCC for the majority of sampling sites, and when compared with the indoor air quality (IAQ) Portuguese legislation it was the Rural PHCC in two sampling places who did not comply with the established criteria.

Size fractionation of bioaerosol emissions from green-waste composting

Particle size is a significant factor in determining the dispersal and inhalation risk from bioaerosols. Green-waste composting is a significant source of bioaerosols (including pathogens), but little is known about the distribution of specific taxa across size fractions. To characterise size fractionated bioaerosol emissions from a compost facility, we used a Spectral Intensity Bioaerosol Sensor (SIBS) to quantify total bioaerosols and qPCR and metabarcoding to quantify microbial bioaerosols. Overall, sub-micron bioaerosols predominated, but molecular analysis showed that most (>75%) of the airborne microorganisms were associated with the larger size fractions (>3.3 µm d_a). The microbial taxa varied significantly by size, with Bacilli dominating the larger, and Actinobacteria the smaller, size fractions. The human pathogen Aspergillus fumigatus dominated the intermediate size fractions (>50% d_a 1.1-4.7 µm), indicating that it has the potential to disperse widely and once inhaled may penetrate deep into the respiratory system. The abundance of Actinobacteria (>60% at d_a < 2.1 µm) and other sub-micron bioaerosols suggest that the main health effects from composting bioaerosols may come from allergenic respiratory sensitisation rather than directly via infection. These results emphasise the need to better understand the size distributions of bioaerosols across all taxa in order to model their dispersal and to inform risk assessments of human health related to composting facilities.