Robust Atmospheric Microbiome Assessment with Nanopore Shotgun Sequencing — biorxiv.org
Editor’s note: When entering a spacecraft or arriving on a new inhabited world, you’ll probably want a tricorder so you can easily measure the atmosphere you and your team may soon be breathing. Here we present his one approach to consider when designing tricorders that use nanopore shotgun sequences.
Atmospheric microbiomes and their diversity are known to be essential for human health and ecosystem resilience, but there is currently a lack of comprehensive monitoring of atmospheric microbial diversity. Little is known about the composition, distribution, and functional impact of the atmospheric microbiome.
Here we show that nanopore shotgun sequences can be combined with active air sampling with liquid impingement and customized computational analysis to reliably assess the air microbiome. We provide laboratory and computational protocols for air microbiome profiling to reliably assess the taxonomic composition of the core air microbiome in controlled natural environments.
Based on de novo assembly from long sequence reads, we further identify several atmospheric microbiota taxa down to the species level and annotate their ecosystem functions, including their potential roles in natural biodegradation processes.
Because air monitoring by nanopore sequencing can be used in an automated, fast, and portable manner for field applications around the world, we believe that this approach will help comprehensively explore the role of the air microbiome. I am.
Robust atmospheric microbiome assessment with nanopore shotgun sequencing. A. Liquid impingement and nanopore sequence setup in a greenhouse (Gh) as a controlled environment. B. Nanopore sequencing read length distribution across 1h and 3-Gh samples. CD. C. Total number of sequencing reads across 1h- and D. 3-Gh samples and number of reads mapped to the taxonomic and genus level as well as to the 20 most prevalent genera using Kraken2 (Materials and Methods) . The downsampling threshold across the sample is indicated by a horizontal dashed line. EF. Taxonomic composition of the E. 1hand F. 3h sample after downsampling based on the 20 most prevalent genera across the sample. G. Monitoring the air microbiome in natural environments (Nat). H. Nanopore sequencing read length distribution across 3h-Nat and 6h-Nat samples. IJ. Total number of sequence reads using Kraken2 across I. 3h- and J. 6-Gh samples and number of reads mapping to the taxonomic phylum and genus level as well as to the 20 most predominant genera. The downsampling threshold across the sample is indicated by a horizontal dashed line. KL. Taxonomic composition of K. 3h and L. 6h samples after downsampling based on the 20 most prevalent genera across samples. — biorxiv.org
Air monitoring by nanopore sequencingbiorxiv.org
astrobiology,
