The bacteria we breath in everyday
In a recent study published in the journal PNAS, researchers surveyed the global airborne bacterial communities to understand their community structure and biogeographic distribution patterns. In addition, they examined their interactions with Earth’s other microbiomes, particularly surface habitats.
Background
The atmosphere is the most untouched microbial habitat on the Earth, and airborne bacteria are the most complex and dynamic communities influencing the Earth’s microbiomes. There are more than 1 × 104 bacterial cells/m3 and hundreds of unique taxa in the air. Large-scale studies have systemically documented the microbial features in soil, ocean, and human waste. Also, they have suggested an interrelationship between airborne microbiomes and surface environments. However, there is a lack of studies documenting airborne microorganisms, especially concerning their community structure.
Microbes do not live in isolation. Instead, they have multiple ecological relationships, ranging from mutualism to competition. Thus, determining their biogeographic distribution patterns and interactions with Earth’s other microbiomes, which define their origins, could shed light on the effects of changing climate/environment and anthropogenic activities.
About the study
In the present study, researchers first developed a global airborne bacterial dataset to assess their degree of commonality and interrelationships. This dataset comprised 76 newly gathered air particulate samples combined with 294 samples collected for previous studies from 63 sites worldwide. The sampling sites were diverse in terms of altitude and geography and encompassed ground level to rooftops (from 1.5m to 25 m high) to mountains 5,380 m above sea level, densely populated urban cities, and the remote Arctic Circle.
The team obtained the dataset for comparison from the Earth Microbiome Project (EMP), which accumulated 5,000+ samples from 23 surface environments. The airborne bacterial reference catalog had more than 27 million non-redundant 16S ribosomal RNA (rRNA) gene sequences.
Further, the researchers constructed a global airborne community co-occurrence network encompassing 5,038 significant correlation relationships (Spearman’s ρ > 0.6) among 482 connected operational taxonomic units (OTUs). OTUs are analytical units grouped by DNA sequence similarity in microbial ecology. Finally, the team used structural equation modeling (SEM) to explore the mechanisms driving microbial communities. Likewise, they calculated the total effects of environmental filtering and bacterial interactions on shaping communities.
Study findings
There were 10,897 taxa detected from 370 individual air samples, and most bacterial sequences belonged to five phyla. Firmicutes, Alphaproteobacteria, Gammaproteobacteria, Actinobacteria, and Bacteroidetes constituted 24.8%, 19.7%, 18.4%, 18.1%, and 8.6% of these bacterial sequences, respectively. The abundance–occupancy relationship (AOR) between the samples a bacterial taxon occupied and its average mass in the global air showed a sigmoid curve, similar to the observed pattern for wild animals and plant distribution on Earth.
Air is a free-flowing, dynamic ecosystem enabling the long-range transport of bacterial communities it carries. However, its bacterial community appeared well connected to local environments, especially the source contributions and air quality conditions resulting from anthropogenic activities. Reduced environmental filtering effects and elevated human-related source contributions have led to fewer biomass loadings, higher pathogenic bacteria abundance, and more destabilized network structures.
Notably, compared to their counterparts in topsoil and marine environments, airborne
bacteria were not closely interconnected, having an average intranode connection of 5.24. They had a random clustering approach, and the topology had low resistance to changes. The observed distant relationships and loose clusters of the network suggested that the airborne bacterial community was more liable to be perturbed as a function of environmental conditions that usually lead to drastic changes in bacterial composition. The functions of atmospheric bacterial taxa were inferred based on their genetic information in other habitats.
The team found potential associations between airborne bacterial communities and other surface microbial habitats. The estimated total abundance of global airborne bacteria (1.72 × 1024 cells) was comparable to those of the hydrosphere and one to three orders of magnitude lower than other habitats (e.g., soil).
Of the 23 major Earth habitats studied in the current study, terrestrial air exhibited more similarity to human- and animal environments, while offshore air showed a closer relationship to oceanic systems. Furthermore, evaluations based on Bayesian methods showed that the characteristics of the corresponding surface environment determined the dominant sources of airborne bacteria. Notably, human-related sources contributed more to the airborne bacteria in urban areas, especially on onshore sites, a finding that was majorly ignored in previous emission modeling studies.
The authors noted no substantial disparities in the richness of airborne bacterial communities between urban and natural areas within the same latitude range. However, the geographic location did have a role to play. Thus, the evenness of the bacterial communities was much lower in urban air. For instance, the relative abundance of pathogenic species, Burkholderia and Pseudomonas, was higher in urban areas versus natural areas (5.56 and 2.50% vs. 1.44 and 1.11%). Furthermore, the bacteria contributed less to particulate matter (PM) mass in urban than in natural areas, indicating that urbanization increased the proportion of non-biological particulates in the air (e.g., dust).
The pathogens with the highest risk of mortality, Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species (ESKAPE) were more abundant in urban air. The co-occurrence network of urban airborne bacterial communities indicated that anthropogenic impacts destabilized their network structure, which, in turn, also altered the bacterial taxonomic composition.
The authors noted that multiple factors impacted airborne bacterial communities—for instance, the geographic locations together with typical environmental factors. The biotic interactions among keystone and core bacterial communities, as well as bacterial richness, interacted significantly. Of all deterministic processes, environmental filtering was the primary determinant of the structure and distribution of airborne microbial communities.
Conclusions
To summarize, nearly 46.3% of the airborne bacteria originated from surrounding environments, and stochastic processes primarily shaped community assembly. Furthermore, the distinguishing feature of airborne bacteria in urban areas was its increasing proportion comprised of potential pathogens from human-related sources. Lastly, airborne bacterial source profiles affected a substantially higher percentage of the structural variations than that for air quality and local meteorological conditions (43.7% vs. 29.4% and 25.8%), as assessed via the variation partition analysis (VPA).
Comments