25 26 Background 27 Aerosol microbiome research advances our understanding of bioaerosols, including how airborne 28 microorganisms affect our health and surrounding environment. Traditional 29 microbiological/molecular methods are commonly used to study bioaerosols, but do not allow for 30 generic, unbiased microbiome profiling. Recent studies have adopted shotgun metagenomic 31 sequencing (SMS) to address this issue. However, SMS requires relatively large DNA inputs, 32 which are challenging when studying low biomass air environments, and puts high requirements 33 on air sampling, sample processing and DNA isolation protocols. Previous SMS studies have 34 consequently adopted various mitigation strategies, including long-duration sampling, sample 35 pooling, and whole genome amplification, each associated with some inherent 36 drawbacks/limitations. 37 38 Results 39 Here, we demonstrate a new custom, multi-component DNA isolation method optimized for 40 SMS-based aerosol microbiome research. The method achieves improved DNA yields from 41 filter-collected air samples by isolating DNA from the entire filter extract, and ensures unbiased 42 microbiome representation by combining chemical, enzymatic and mechanical lysis. 43 Benchmarking against two state-of-the-art DNA isolation methods was performed with a mock 44 microbial community and real-world subway air samples. All methods demonstrated similar 45 performance regarding DNA yield and community representation with the mock community. 46 However, with subway air samples, the new method obtained drastically improved DNA yields, 47 while SMS revealed that the new method reported higher diversity and gave better taxonomic 48 3 coverage. The new method involves intermediate filter extract separation into a pellet and 49 supernatant fraction. Using subway air samples, we demonstrate that supernatant inclusion results 50 in improved DNA yields. Furthermore, SMS of pellet and supernatant fractions revealed overall 51 similar taxonomic composition but also identified differences that could bias the microbiome 52 profile, emphasizing the importance of processing the entire filter extract. 53 54 Conclusions 55 By demonstrating and benchmarking a new DNA isolation method optimized for SMS-based 56 aerosol microbiome research with both a mock microbial community and real-world air samples, 57 this study contributes to improved selection, harmonization, and standardization of DNA 58 isolation methods. Our findings highlight the importance of ensuring end-to-end sample integrity 59 and using methods with well-defined performance characteristics. Taken together, the 60 demonstrated performance characteristics suggest the new method could be used to improve the 61 quality of SMS-based aerosol microbiome research in low biomass air environments. 62 63 KEYWORDS 64 65 Aerosol Microbiome; Air Sampling; DNA Isolation; Shotgun Metagenomic Sequencing 66 67 68 69 70 71 72 4 BACKGROUND 73 74 The study of bioaerosols is an emerging and expanding research discipline [1], with several 75...