Abstract
The COVID-19 pandemic has revealed the importance of the detection of airborne pathogens. Here, we present composite air filters featuring a bioinspired liquid coating that facilitates the removal of captured aerosolized bacteria and viruses for further analysis. We tested three types of air filters: commercial polytetrafluoroethylene (PTFE), which is well known for creating stable liquid coatings, commercial high-efficiency particulate air (HEPA) filters, which are widely used, and in-house-manufactured cellulose nanofiber mats (CNFMs), which are made from sustainable materials. All filters were coated with omniphobic fluorinated liquid to maximize the release of pathogens. We found that coating both the PTFE and HEPA filters with liquid improved the rate at which Escherichia coli was recovered using a physical removal process compared to uncoated controls. Notably, the coated HEPA filters also increased the total number of recovered cells by 57%. Coating the CNFM filters did not improve either the rate of release or the total number of captured cells. The most promising materials, the liquid-coated HEPA, filters were then evaluated for their ability to facilitate the removal of pathogenic viruses via a chemical removal process. Recovery of infectious JC polyomavirus, a nonenveloped virus that attacks the central nervous system, was increased by 92% over uncoated controls; however, there was no significant difference in the total amount of genomic material recovered compared to that of controls. In contrast, significantly more genomic material was recovered for SARS-CoV-2, the airborne, enveloped virus, which causes COVID-19, from liquid-coated filters. Although the amount of infectious SARS-CoV-2 recovered was 58% higher, these results were not significantly different from uncoated filters due to high variability. These results suggest that the efficient recovery of airborne pathogens from liquid-coated filters could improve air sampling efforts, enhancing biosurveillance and global pathogen early warning.