pAQ monitor: innovative device provides real-time surveillance of SARS-CoV-2 aerosols

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In a recent study published in Nature Communications, researchers presented the proof-of-concept of a pathogen Air Quality (pAQ) monitor that could detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) aerosols even in low virus concentration environments.

Study: Real-time environmental surveillance of SARS-CoV-2 aerosols. Image Credit: RainerFuhrmann/Shutterstock.comStudy: Real-time environmental surveillance of SARS-CoV-2 aerosols. Image Credit: RainerFuhrmann/Shutterstock.com

Background

Widespread adoption and use of real-time surveillance technologies to detect airborne SARS-CoV-2 could help implement rapid coronavirus disease 2019 (COVID-19) mitigation strategies in crowded public places and indoors. However, there remains an unmet need for such technologies since the beginning of the COVID-19 pandemic. 

As is already known, SARS-CoV-2 transmits from one infected person to another through respiratory droplets expelled during coughing, sneezing, speaking, and even breathing.

So, while social distancing, mandatory masking in public spaces, and quarantining SARS-CoV-2-infected individuals could help decrease the risk of airborne transmission, these measures also adversely affect people's daily social lives. 

As the need to combat airborne transmission of SARS-CoV-2 is still critical, a surveillance device that could detect SARS-CoV-2 aerosols in the air directly, rapidly, noninvasively, and in real-time appears to be a promising and effective solution. It could help manage viral spread, implement infection mitigation strategies and resume normal activities.

In this context, earlier used offline air sampling technologies, e.g., particle into liquid samplers (PILS), detected airborne viruses but had a longer turnaround time of up to 24 hours, required skilled professionals, and did not fetch results in real-time.

Due to two main reasons, automated and real-time detection devices for airborne SARS-CoV-2 are currently unavailable commercially. First, such devices need a highly efficient high-flow virus aerosol sampler that could work with a real-time virus detector.

Second, these devices should have a rapid, accurate, and sensitive virus detection protocol to quantify airborne viruses, often present in low concentrations in ambient air. 

Despite significant advancements in developing PILS devices, there is a lack of integrable real-time sensor devices for rapid and real-time virus detection. Biosensors offer a quicker, more sensitive, and affordable substitute of quantitative reverse transcription-polymerase chain reaction (RT-qPCR) for SARS-CoV-2 aerosol detection. 

Several previous studies have shown their efficacy in detecting SARS-CoV-2 aerosols in exhaled breath condensate samples, saliva, and nasal swabs achieving better results than RT-qPCR.

Yet, biosensors have not been utilized in real-world settings, especially indoor environments, such as schools, apartments, offices, conference halls, and public places, where real-time pathogen monitoring could help public health officials limit airborne pathogen transmission.

About the study

In the present study, researchers devised the concept of a pAQ monitor for detecting SARS-CoV-2 in the air at five minutes time resolution.

It comprised a customized high-flow wet-wall cyclone PILS having a liquid collection medium to directly sample virus-laden aerosols coupled to a llama-derived nanobody attached to a micro-immunoelectron (MIE) biosensor to detect the SARS-CoV-2 spike (S)-protein with high specificity. Accordingly, this unit could detect and report the presence of SARS-CoV-2 within 30 seconds. 

The team acquired the biosensor baseline reading before air sample measurements. Next, they performed square wave voltammetry (SWV) to measure the oxidation peak height corresponding to the oxidized tyrosine in the viral particle, which occurred at ~0.65 volts (V).

Further, the team normalized the oxidation peak height for every test sample and that collected for virus-free air sample (control) to categorize the signal as positive or negative reading.

After ten sampling cycles, the team injected ~15 mL of hypochlorous acid to decontaminate the wet cyclone. While the MIE biosensor unit analyzed an air sample, the wet cyclone began collecting the next sample.

Further, the team compared wet cyclone performance with two commercially available low-flow PILS, viz., BioSampler® and Liquid Spot Sampler™ (LSS). They performed the chamber experiments for 10 minutes to ensure sufficient virus concentration in these two PLISes for RT-qPCR analysis.

Furthermore, they validated the performance and sensitivity of the pAQ monitor in the laboratory using inactivated SARS-CoV-2 variants.

Results and discussion

Before air sampling, the team filled the wet cyclone with nearly 15 mL of phosphate-buffered saline. The pressure drop drew in ambient air rapidly, producing a rotating film of PBS liquid on the inner side of the wet cyclone that captured aerosols in the liquid media. 

A high-efficiency particulate absorbing (HEPA) filter collected the aerosols that exited from the top of the wet cyclone. 

After five minutes of sampling, the pAQ monitor transferred air containing concentrated aerosol and PBS to the MIE biosensor detector, which detected the tyrosine amino acid in the SARS-CoV-2 S protein as peak oxidation current at ~0.65 V. The magnitude of the current indicated the virus concentration in each air sample.

The computational fluid dynamics (CFD) model results showed that the wet cyclone worked at more than 95% collection efficiency for particles of size greater than one μm and a cut off diameter of 0.4 μm, where the collection efficiency was 50%.

Compared to BioSampler® and LSS, wet cyclone measured SARS-CoV-2 RNA copies/mL of collection media, i.e., virus concentration after ten minutes of sampling was ~10 and ~50 times higher, respectively. Intriguingly, wet cyclone recovered the WA-1 RNA even at low concentrations, while RNA recovered by both BioSampler® and LSS samples were unquantifiable by RT-qPCR. 

Clearly, in 10 minutes, owing to its extremely high flow rate, the wet cyclone recovered high amounts of SARS-CoV-2 RNA by sampling a larger volume of air (~10 m3), which makes it an ideal device for high-time resolution monitoring in real-world settings, hospitals and patient isolation rooms where airborne SARS-CoV-2 RNA concentrations remain between 2–94,000 copies/m3.

The samples collected from infected households were weakly SARS-CoV-2 positive and had low RNA concentration because both SARS-CoV-2-positive patients self-reported being asymptomatic during the sampling period. Yet, all seven air samples collected using the wet cyclone tested SARS-CoV-2-positive based on RT-qPCR results.

For different SARS-CoV-2 variants, the pAQ monitor had a limit of detection (LoD) of 35, seven, nine, and 23 RNA copies/m3 of air, and the observed varying LoDs most likely arose due to variant-specific mutations in the S-protein that bound the nanobody used in this monitor.

It also led to variable nanobody binding efficiency, which altered the biosensor signal strength. However, the pAQ was similar to other recently developed rapid biosensors in terms of sensitivity and displayed a detection time of under 10 minutes. 

Conclusion

To summarize, this study demonstrated a proof-of-concept pAQ monitor with a wet cyclone with high viral aerosol capturing efficiency even in environments with low pathogen aerosol concentrations. It exhibited sensitivity between 77 and 83%, high time resolution, and low LoD ranging between seven and 35 RNA copies/m3.

Its automation capability makes it an ideal tool for affordable real-time detection of viral aerosols in indoor environments.

Yet, future studies should further test and validate the use of the pAQ monitor for real-world applications in environments with varying aerosol compositions because that could markedly interfere with biosensor performance.

Journal reference:
Neha Mathur

Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.

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