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

Kari Oline Bøifot, Jostein Gohli, Line Victoria Moen, Marius Dybwad
doi: https://doi.org/10.1101/744334
Kari Oline Bøifot
Norwegian Defence Research Establishment, P O Box 25, NO-2027 Kjeller, NorwayDepartment of Analytics, Environmental & Forensic Sciences, King’s College London, 150 Stamford Street, London SE1 9NH, UK
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Jostein Gohli
Norwegian Defence Research Establishment, P O Box 25, NO-2027 Kjeller, Norway
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Line Victoria Moen
Norwegian Defence Research Establishment, P O Box 25, NO-2027 Kjeller, Norway
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Marius Dybwad
Norwegian Defence Research Establishment, P O Box 25, NO-2027 Kjeller, NorwayDepartment of Analytics, Environmental & Forensic Sciences, King’s College London, 150 Stamford Street, London SE1 9NH, UK
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  • For correspondence: marius.dybwad@ffi.no
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ABSTRACT

Background Aerosol 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.

Results Here, 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.

Conclusions By 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.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted August 22, 2019.
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Performance evaluation of a new custom, multi-component DNA isolation method optimized for use in shotgun metagenomic sequencing-based aerosol microbiome research
Kari Oline Bøifot, Jostein Gohli, Line Victoria Moen, Marius Dybwad
bioRxiv 744334; doi: https://doi.org/10.1101/744334
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Performance evaluation of a new custom, multi-component DNA isolation method optimized for use in shotgun metagenomic sequencing-based aerosol microbiome research
Kari Oline Bøifot, Jostein Gohli, Line Victoria Moen, Marius Dybwad
bioRxiv 744334; doi: https://doi.org/10.1101/744334

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