Numerous threats from biological aerosol exposures, such as those from H1N1 influenza, SARS, bird flu, and bioterrorism activities necessitate the development of a real-time bioaerosol sensing system, which however is a long-standing challenge in the field. Here, we developed a real-time monitoring system for airborne influenza H3N2 viruses by integrating electronically addressable silicon nanowire (SiNW) sensor devices, microfluidics and bioaerosol-to-hydrosol air sampling techniques. When airborne influenza H3N2 virus samples were collected and delivered to antibody-modified SiNW devices, discrete nanowire conductance changes were observed within seconds. In contrast, the conductance levels remained relatively unchanged when indoor air or clean air samples were delivered. A 10-fold increase in virus concentration was found to give rise to about 20-30% increase in the sensor response. The selectivity of the sensing device was successfully demonstrated using H1N1 viruses and house dust allergens. From the simulated aerosol release to the detection, we observed a time scale of 1-2 min. Quantitative polymerase chain reaction (qPCR) tests revealed that higher virus concentrations in the air samples generally corresponded to higher conductance levels in the SiNW devices. In addition, the display of detection data on remote platforms such as cell phone and computer was also successfully demonstrated with a wireless module. The work here is expected to lead to innovative methods for biological aerosol monitoring, and further improvements in each of the integrated elements could extend the system to real world applications.
Exhaled breath condensate (EBC) is increasingly being used as a non-invasive method for disease diagnosis and environmental exposure assessment. By using hydrophobic surface, ice, and droplet scavenging, a simple impaction and condensing based collection method is reported here. Human subjects were recruited to exhale toward the device for 1, 2, 3, and 4 min. The exhaled breath quickly formed into tiny droplets on the hydrophobic surface, which were subsequently scavenged into a 10 µL rolling deionized water droplet. The collected EBC was further analyzed using culturing, DNA stain, Scanning Electron Microscope (SEM), polymerase chain reaction (PCR) and colorimetry (VITEK 2) for bacteria and viruses. Experimental data revealed that bacteria and viruses in EBC can be rapidly collected using the method developed here, with an observed efficiency of 100 µL EBC within 1 min. Culturing, DNA stain, SEM, and qPCR methods all detected high bacterial concentrations up to 7000 CFU/m3 in exhaled breath, including both viable and dead cells of various types. Sphingomonas paucimobilis and Kocuria variants were found dominant in EBC samples using VITEK 2 system. SEM images revealed that most bacteria in exhaled breath are detected in the size range of 0.5–1.0 µm, which is able to enable them to remain airborne for a longer time, thus presenting a risk for airborne transmission of potential diseases. Using qPCR, influenza A H3N2 viruses were also detected in one EBC sample. Different from other devices restricted solely to condensation, the developed method can be easily achieved both by impaction and condensation in a laboratory and could impact current practice of EBC collection. Nonetheless, the reported work is a proof-of-concept demonstration, and its performance in non-invasive disease diagnosis such as bacterimia and virus infections needs to be further validated including effects of its influencing matrix.
Poor air hygiene as a result of bioaerosol contamination has caused diverse forms of adverse health effects and diseases. In addition, global biosecurity is threatened by purposeful use of biowarfare agents and the vulnerability of people to the infectious agents. Accordingly, developments in high-volume biosampling, including aerosol-to-hydrosol techniques with low cut-off size, real-time bioaerosol detection, adequate biological quantification, and exposure control, as well as the investigation of the link between disease outcome and bioaerosol exposure, are current areas of bioaerosol research. Although milestone progress has been achieved both in bioaerosol sampling and analysis techniques since late 1800s, compared to atmospheric chemistry the bioaerosol field is still understudied. This is partially because of the lack of both bioaerosol scientists and multidisciplinary collaboration. It is becoming necessary to develop a pool of scientists with different expertise, e.g., bioaerosol scientists, environmental engineers, biomedical engineers, epidemiologists, microbiologists, chemists, physicists, as well as researchers in other engineering fields, in mitigating bioaerosol-related adverse health effects, eliminating diseases, and preventing and controlling epidemic outbreaks. This work is conducted to broadly review current state-of-the-art sciences and technologies in the bioaerosol field. In tackling the challenges ahead, the review also provides perspectives for bioaerosol research needs, and further reminds bioaerosol scientists of those existing technologies in other fields that can be leveraged. In view of the past, forward-looking hypotheses and revolutional perspectives are needed to be formed in order to allow the bioaerosol research have major impacts in the academic community in this new millennium.
Abstract Fluorescence spectra and UV‐Vis absorption spectra have been used to study the binding of bacteriophage mequindox (MEQ) with bovine serum albumin (BSA), which performed a dynamic quenching process. The quenching constants and thermodynamic parameters at different temperatures were calculated. The binding was primarily driven by entropy, and hydrophobic forces also played a significant role. The distance between BSA and MEQ was estimated to be 4.5 nm based on the theory of F?rster's non‐radioactive energy transfer. Furthermore, synchronous fluorescence spectra and 3‐dimensional fluorescence spectra were used to figure out the configuration of BSA in the presence or absence of MEQ, which indicated that it was basically the same.
In this study, biological collection efficiencies and culturable bacterial and fungal aerosol diversities were investigated when different bioaerosol sampling tools and culturing methods were applied. The samplers included Reuter centrifugal sampler (RCS) High Flow, BioSampler, electrostatic sampler, gelatin filter, BioStage impactor, mixed cellulose ester (MCE) filter as well as gravitational settling methods. For culturable bacterial aerosol diversity, the colony-forming units (CFUs) were washed off from the agar plates, and further went through polymerase chain reaction- and denaturing gradient gel electrophoresis (PCR–DGGE). For culturable fungal aerosol diversity, microscopic identification method was applied.
Influenza epidemics worldwide result in substantial economic and human costs annually. However, rapid and reliable flu diagnosis methods are significantly lacking. Here we have demonstrated the selective detection of influenza A viruses down to 29 viruses/μL in clinical exhaled breath condensate (EBC) samples (diluted by 100-fold) within minutes using silicon nanowire (SiNW) sensor devices. For 90% of the cases, we have observed that EBC samples tested positive or negative by gold standard method RT-qPCR generated corresponding positive or negative SiNW sensor responses. High selectivity of SiNW sensing was also demonstrated using H1N1 viruses, 8 iso PGF 2a, and inert nanoparticles. Finally, magnetic beads were shown capable of enhancing SiNW sensing directly for low level viruses and 8 iso PGF 2a. When calibrated by virus standards and EBC controls, our work suggests that the SiNW sensor device can be reliably applied to the diagnosis of flu in a clinical setting with 2 orders of magnitude less time compared to the gold standard method RT-qPCR.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)