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. 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 a more comprehensive 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 air samples. All methods demonstrated similar performance regarding DNA yield and community representation with the mock community. However, with subway samples, the new method obtained drastically improved DNA yields, while SMS revealed that the new method reported higher diversity. The new method involves intermediate filter extract separation into a pellet and supernatant fraction. Using subway 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. 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.

中文翻译：

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一种新的定制的多组分DNA分离方法的性能评估，该方法已优化用于shot弹枪基于宏基因组测序的气溶胶微生物组研究

气溶胶微生物组研究提高了我们对生物气溶胶的理解，包括空气传播的微生物如何影响我们的健康和周围环境。传统的微生物/分子方法通常用于研究生物气溶胶，但不允许进行一般的，无偏见的微生物组分析。最近的研究已采用shot弹枪宏基因组测序（SMS）来解决此问题。但是，SMS需要相对较大的DNA输入，这在研究低生物量空气环境时具有挑战性，并且对空气采样，样品处理和DNA分离方案提出了很高的要求。因此，以前的SMS研究已经采用了各种缓解策略，包括长时间采样，样品池化和全基因组扩增，每种策略都有一些固有的缺点/局限性。在这里，我们演示一个新的习惯，优化的多组分DNA分离方法，用于基于SMS的气溶胶微生物组研究。该方法通过从整个过滤器提取物中分离DNA来提高过滤器收集的空气样品的DNA产量，并通过结合化学，酶促和机械裂解来确保更全面的微生物组表示。使用模拟微生物群落和现实世界的空气样本对两种最先进的DNA分离方法进行了基准测试。所有方法都显示出与模拟社区有关的DNA产量和社区代表性方面的相似性能。但是，对于地铁样品，该新方法获得了显着提高的DNA产量，而SMS则表明该新方法报告了更高的多样性。新方法涉及将中间过滤器提取物分离成沉淀物和上清液部分。使用地铁样本，我们证明了上清液的包埋可以提高DNA的产量。此外，沉淀和上清液级分的SMS揭示了总体上相似的分类学组成，但也发现了可能使微生物组谱偏倚的差异，强调了加工整个滤纸提取物的重要性。通过使用模拟微生物群落和现实世界的空气样本演示并基准化针对基于SMS的气溶胶微生物组研究而优化的新DNA分离方法，该研究有助于改进DNA分离方法的选择，统一和标准化。我们的发现强调了确保端到端样品完整性和使用具有明确定义的性能特征的方法的重要性。在一起