基因组
采样(信号处理)
空气质量指数
环境科学
DNA提取
室内生物气溶胶
计算生物学
基因组DNA
环境DNA
DNA
生物
计算机科学
生态学
滤波器(信号处理)
聚合酶链反应
基因
遗传学
生物多样性
计算机视觉
作者
Piyanun Harnpicharnchai,Panyapon Pumkaeo,Paopit Siriarchawatana,Somsak Likhitrattanapisal,Sermsiri Mayteeworakoon,Lily Ingsrisawang,Worawongsin Boonsin,Lily Eurwilaichitr,Supawadee Ingsriswang
出处
期刊:PLOS ONE
[Public Library of Science]
日期:2023-06-29
卷期号:18 (6): e0287567-e0287567
被引量:17
标识
DOI:10.1371/journal.pone.0287567
摘要
Analyzing temporal and spatial distributions of airborne particles of biological origins is vital for the assessment and monitoring of air quality, especially with regard to public health, environmental ecology, and atmospheric chemistry. However, the analysis is frequently impeded by the low levels of biomass in the air, especially with metagenomic DNA analysis to explore diversity and composition of living organisms and their components in the air. To obtain sufficient amounts of metagenomic DNA from bioaerosols, researchers usually need a long sampling time with an expensive high-volume air sampler. This work shows the utilization of an air sampling device containing an economical, high-volume portable ventilation fan in combination with customized multi-sheet filter holders to effectively obtain high yields of genomic DNA in a relatively short time. The device, named ‘AirDNA’ sampler, performed better than other commercial air samplers, including MD8 Airport and Coriolis compact air samplers. Using the AirDNA sampler, an average DNA yield of 40.49 ng (12.47–23.24 ng at 95% CI) was obtained in only 1 hour of air sampling with a 0.85 probability of obtaining ≥10 ng of genomic DNA. The genomic DNA obtained by the AirDNA system is of suitable quantity and quality to be further used for amplicon metabarcoding sequencing of 16S, 18S, and cytochrome c oxidase I (COI) regions, indicating that it can be used to detect various prokaryotes and eukaryotes. Our results showed the effectiveness of our AirDNA sampling apparatus with a simple setup and affordable devices to obtain metagenomic DNA for short-term or long-term spatiotemporal analysis. The technique is well suited for monitoring air in built environments, especially monitoring bioaerosols for health purposes and for fine-scale spatiotemporal environmental studies.
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