Gohli, J. | Search bioRxiv

bioRxiv2025

Spatial and Temporal Patterns of Public Transit Aerobiomes

BackgroundAerobiome diversity is extensive, however community structure at the species level remains elusive. Likewise, microbiomes of public transit systems are of public interest due to their importance for health, though few studies have focused on these ecosystems whilst utilising shotgun metagenomics. Aerosol studies have focused predominantly on individual cities, with limited between-city comparisons suggesting specific community structures. Longitudinal studies show aerobiome diversity as dynamic, fluctuating during seasonal and daily cycles, though an annual cycle remains to be considered. Further, a bacterial bias has limited fungal aerobiome studies, with few considering both fractions collectively. As such, the objective of this study was to examine spatial and temporal patterns in the species diversity of public transit aerobiomes, with an emphasis on bacteria and fungi. ResultsAir samples taken over a three-year period (2017-2019) from six global cities were subjected to shotgun metagenomic sequencing. Improved classification databases, notably for fungi, applying stringent parameters for trimming, exogenous contamination removal and classification yielded high species-level resolution. Microbial diversity varied substantially among cities, while human and environmental factors, recorded in parallel, were of secondary significance. Bacteria dominated the public transit aerobiome with increased presence in cities with higher population densities. All aerobiomes had complex compositions, consisting of hundreds to thousands of species. Annual variation had limited significance on the public transit aerobiome diversity and community structure. ConclusionsCities were the most important factor contributing to diversity and community structure, demonstrating specific bacterial and fungal signatures. Further, a correlation between geographical distance and the genetic signatures of aerobiomes is suggested. Bacteria are the most abundant constituent of public transit aerobiomes, though no single species is globally dominant, conversely indicating a large inter-city variation in community structure. The presence of a ubiquitous global species core is rejected, though an aerobiome sub-core is confirmed. For the first time, local public transit aerobiome cores are presented for each city and related to ecological niches. Further, the importance of a robust bioinformatics analysis pipeline to identify and remove exogenous contaminants for studying low biomass samples is highlighted. Lastly, a core and sub-core definition of contaminant aerobiome species with taxon tables, to facilitate future environmental studies, is presented.

microbiology↗

bioRxiv2019

Performance evaluation of a new custom, multi-component DNA isolation method optimized for use in shotgun metagenomic sequencing-based aerosol microbiome research

BackgroundAerosol microbiome research advances our understanding of bioaerosols, including how airborne microorganisms affect our health and surrounding environment. Traditional microbiological/molecular methods are commonly used to study bioaerosols, but do not allow for generic, unbiased microbiome profiling. Recent studies have adopted shotgun metagenomic sequencing (SMS) to address this issue. However, SMS requires relatively large DNA inputs, which are challenging when studying low biomass air environments, and puts high requirements on air sampling, sample processing and DNA isolation protocols. Previous SMS studies have consequently adopted various mitigation strategies, including long-duration sampling, sample pooling, and whole genome amplification, each associated with some inherent drawbacks/limitations.\n\nResultsHere, we demonstrate a new custom, multi-component DNA isolation method optimized for SMS-based aerosol microbiome research. The method achieves improved DNA yields from filter-collected air samples by isolating DNA from the entire filter extract, and ensures unbiased microbiome representation by combining chemical, enzymatic and mechanical lysis. Benchmarking against two state-of-the-art DNA isolation methods was performed with a mock microbial community and real-world subway air samples. All methods demonstrated similar performance regarding DNA yield and community representation with the mock community. However, with subway air samples, the new method obtained drastically improved DNA yields, while SMS revealed that the new method reported higher diversity and gave better taxonomic coverage. The new method involves intermediate filter extract separation into a pellet and supernatant fraction. Using subway air samples, we demonstrate that supernatant inclusion results in improved DNA yields. Furthermore, SMS of pellet and supernatant fractions revealed overall similar taxonomic composition but also identified differences that could bias the microbiome profile, emphasizing the importance of processing the entire filter extract.\n\nConclusionsBy demonstrating and benchmarking a new DNA isolation method optimized for SMS-based aerosol microbiome research with both a mock microbial community and real-world air samples, this study contributes to improved selection, harmonization, and standardization of DNA isolation methods. Our findings highlight the importance of ensuring end-to-end sample integrity and using methods with well-defined performance characteristics. Taken together, the demonstrated performance characteristics suggest the new method could be used to improve the quality of SMS-based aerosol microbiome research in low biomass air environments.

molecular biology↗