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Sampling and detection of airborne influenza virus towards point-of-care applications

tetano

Editor, Senior Moderator
PLoS One. 2017 Mar 28;12(3):e0174314. doi: 10.1371/journal.pone.0174314. eCollection 2017.
[h=1]Sampling and detection of airborne influenza virus towards point-of-care applications.[/h] Ladhani L[SUP]1[/SUP], Pardon G[SUP]1[/SUP], Meeuws H[SUP]2[/SUP], van Wesenbeeck L[SUP]2[/SUP], Schmidt K[SUP]2[/SUP], Stuyver L[SUP]2[/SUP], van der Wijngaart W[SUP]1[/SUP].
[h=3]Author information[/h]

[h=3]Abstract[/h] Airborne transmission of the influenza virus contributes significantly to the spread of this infectious pathogen, particularly over large distances when carried by aerosol droplets with long survival times. Efficient sampling of virus-loaded aerosol in combination with a low limit of detection of the collected virus could enable rapid and early detection of airborne influenza virus at the point-of-care setting. Here, we demonstrate a successful sampling and detection of airborne influenza virus using a system specifically developed for such applications. Our system consists of a custom-made electrostatic precipitation (ESP)-based bioaerosol sampler that is coupled with downstream quantitative polymerase chain reaction (qPCR) analysis. Aerosolized viruses are sampled directly into a miniaturized collector with liquid volume of 150 μL, which constitutes a simple and direct interface with subsequent biological assays. This approach reduces sample dilution by at least one order of magnitude when compared to other liquid-based aerosol bio-samplers. Performance of our ESP-based sampler was evaluated using influenza virus-loaded sub-micron aerosols generated from both cultured and clinical samples. Despite the miniaturized collection volume, we demonstrate a collection efficiency of at least 10% and sensitive detection of a minimum of 3721 RNA copies. Furthermore, we show that an improved extraction protocol can allow viral recovery of down to 303 RNA copies and a maximum sampler collection efficiency of 47%. A device with such a performance would reduce sampling times dramatically, from a few hours with current sampling methods down to a couple of minutes with our ESP-based bioaerosol sampler.


PMID: 28350811 DOI: 10.1371/journal.pone.0174314
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