An Improved Approach for Highly-Efficient, Concentrated Sampling of Aerosol Particles from 10 nm to 10 μm: Bioaerosol Applications

摘要

Bioaerosols have the potential to negatively impact human health. However, regular monitoring of bioaerosols are a difficult challenge. Current bioaerosol sampling methods are limited resulting in a lack of quality information about the airborne nature and effects of bioaerosols. Active sampling methods are common tools for the collection of bioaerosols in indoor environments. However, most active air sampling methods have strong particle size dependencies for their collection efficiency and impart mechanical stresses on the collected microorganisms. The condensation growth tube collector (CGTC) uses a three-stage, moderated laminar-flow condensation approach to enlarge airborne particles as small as 5 nm at moderate temperatures. The high humidity of the sample flow and the warm water blanket encapsulating the particles is advantageous for viable microorganism collection. Live laboratory-generated virus, bacteria and yeast particles tested a prototype high-flow (8 L/min) condensation growth sampler and compared the results to commonly used liquid impingers. The collection of infectious H1N1 influenza virus particles was 13 times higher than the commonly used SKC BioSampler (Lednickly et al., 2016). Pan et al. (2016) observed the fraction of MS2 particles that remained viable after capture was 100 times greater for the CGTC then the SKC BioSampler. The CGTC had a detection limit lower than one order of magnitude for the observed yeast aerosol compared to the SKC BioSampler, regardless of the media used (Pan et al. 2018). We also present a new collection technique using the CGTC that instantly preserves microbial genetic material upon capture. This innovative method is directly compatible with molecular biology analyses including quantitative PCR, targeted genomic amplifications, metagenomic DNA sequencing, RNA sequencing as well as targeted biopolymer analyses and proteomics (Nieto-Caballero 2019).