AAAR 31st Annual Conference
October 8-12, 2012
Hyatt Regency Minneapolis
Minneapolis, Minnesota, USA
Abstract View
Comparing the Indoor Microbiome from Seven Different Bioaerosol Samplers
ANDREW HOISINGTON, Juan Pedro Maestre, Sungwoo Bae, Kerry Kinney, Jeffrey Siegel, Maria D. King, The University of Texas at Austin
Abstract Number: 359 Working Group: The Indoor Microbiome
Abstract Microorganisms are ubiquitous in the indoor environment and are of concern for a variety of reasons including infectious diseases transmission, and the potential to aggravate asthma or allergy symptoms. Several microbial indoor air samplers have been developed for characterizing the microbiome but limited studies have been conducted to provide a side-by-side comparison. The objective of this study is to compare the bacterial and fungal sequencing results obtained from simultaneously sampling the indoor environment with seven different microbial samplers. The sampling was repeated in two consecutive weeks at the same location, only altering the air exchange rate between events.
In this study, we operated five bioaerosol samplers (SKC biosampler, button sampler, PEM 2.5 sampler, Andersen 6-stage viable impactor and the wetted-wall cyclone collector system) simultaneously in the same occupied, indoor environment at different flow rates for three consecutive 15 min sampling periods. In addition, airborne dust samples were collected from the building HVAC filters and settled dust samples from two adjacent indoor surfaces. Microbial DNA was extracted and analyzed from all samples by pyrosequencing, targeting the bacterial 16S region and the fungal ITS and 28S regions. Sequences were processed with identical criteria for denoising, chimera removal, trimming, and BLASTn search. Operational taxonomic units, phylogenetic trees, alpha-diversity and beta-diversity indices were calculated to compare the molecular results.
Results to date indicate that the samplers identify different microbial species. The differences could be attributed to sampler design (e.g. aerodynamics, air-inflow rate, destruction of cells/DNA, capture efficiency, volume of sample) or limitations in taxonomic identification. Similarly, the alpha-diversity estimates were different in the samplers across both bacterial and fungal communities. All seven samplers identified different microbial communities compared to the outdoor microbiome. The data set generated represents the first side-by-side assessment of these techniques and may enhance comparisons between studies that utilize different samplers.