The development of COPMAN-Air: A highly sensitive method for detecting SARS-CoV-2 in air

The development of COPMAN-Air: A highly sensitive method for detecting SARS-CoV-2 in air | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The development of COPMAN-Air: A highly sensitive method for detecting SARS-CoV-2 in air Tomoyo Yoshinaga, Yoshinori Ando, Yumi Sato, Takeru Kishida, Masaaki Kitajima This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5995479/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Apr, 2025 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract Several studies have successfully detected SARS-CoV-2 in air samples; however, in most of these, the focus was on validating the air collection method, and there was no report on the development of a virus-detection method. In this study, to detect viruses in air samples more sensitively than conventional detection methods, we applied COPMAN, a highly sensitive virus-detection method using wastewater samples, to air samples to develop COPMAN-Air. Briefly, with this method, the extremely low amount of viral RNA in air samples is efficiently detected via three reaction steps: RT, preamplification, and qPCR, as with COPMAN. We evaluated COPMAN-Air using samples from a fever clinic for COVID-19 patients. COPMAN-Air demonstrated a higher detection rate of viral RNA compared to conventional methods: 22 (95.7%) vs. 14 (60.9%) out of 23 samples. Additionally, a positive correlation (r=0.70) was found between the amount of viral RNA detected by COPMAN-Air and the number of confirmed COVID-19 cases, suggesting that COPMAN-Air could estimate the number of SARS-CoV-2-positive individuals in a given space based on the quantitative values of SARS-CoV-2 RNA in air samples. Surveillance systems for pathogens in the air using COPMAN-Air are expected to be valuable for assessing the number of infected individuals and for the implementation of public health measures. Biological sciences/Microbiology/Virology/Viral transmission Health sciences/Health care/Public health Biological sciences/Microbiology/Environmental microbiology/Air microbiology Air sampling COPMAN COPMAN-Air Fever clinic qPCR SARS-CoV-2 Figures Figure 1 Figure 2 Figure 3 Introduction SARS-CoV-2 is a virus that infects the human respiratory tract. It can be spread not only through direct and indirect contact, but also through the inhalation of droplets and aerosols 1 – 6 . Generally, people infected with COVID-19 exhibit symptoms similar to those of the common cold or influenza and recover after several days, except for vulnerable people such as the elderly and those with underlying health conditions 7 , 8 . In addition, it has been reported that some people infected with SARS-CoV-2 show no symptoms, and it is possible that these asymptomatic people may inadvertently play a role as spreaders of the virus 9 – 12 . Because environmental tests, which detect pathogens contained in the environment, are non-invasive and are regarded as more cost-effective than clinical tests, they are attracting attention as an alternative or complement to clinical testing 13 . SARS-CoV-2 is widely accepted as a virus that spreads through airborne transmission; therefore, one way to prevent its spread is to help people to know if the air around them contains the virus. Air sampling to detect the virus has been vigorously taken into consideration. Many of these studies have been conducted in healthcare settings, such as isolation rooms for COVID-19 patients in hospitals and quarantine hotels, where high concentrations of SARS-CoV-2-containing aerosols are expected to fill the space 6 , 14 – 16 . However, considering the social implementations of the virus, it is necessary to conduct a feasibility study in a more practical community setting. Some reports have successfully detected SARS-CoV-2 in public places such as student dormitories, schools, cafeterias, offices, shopping centers, airports, and public transport 16 – 19 . Nevertheless, because it is difficult to grasp the number of SARS-CoV-2-infected individuals who have been or are presently in such spaces during air sampling, it is not possible to accurately confirm the validity of the virus detection method. Furthermore, it cannot be determined whether the method is available for the early detection of infected individuals. The major detection method for SARS-CoV-2 in the air is the quantitative measurement of viral RNA derived from an air sample via reverse transcription-quantitative polymerase chain reaction (RT-qPCR) 15 , 16 , 18 . There have been many reports on air sampling methods 16 , 20 . Since the number of SARS-CoV-2-containing aerosols in a space is expected to be extremely low, the optimization of the protocol to be used after air sampling is also needed, to improve sensitivity of virus detection using RT-qPCR. In addition, the protocol must be able to handle a large number of air samples for virus monitoring in many spaces, to achieve worthwhile social implementation. To our knowledge, however, such efforts have not yet been sufficiently verified. Recently, our group developed the COPMAN (COagulation and Proteolysis method using MAgnetic beads for Nucleic acids in wastewater) method, which can detect SARS-CoV-2 RNA from wastewater samples with both high sensitivity and high throughput 21 , 22 . In this study, we developed COPMAN-Air, a new method that applies the near full-automation-available COPMAN technology and investigated the detection sensitivity of SARS-CoV-2 RNA derived from air samples taken from a Thermo Fisher Scientific AerosolSense Sampler. Some reports have clearly shown that this active air sampler is helpful in collecting SARS-CoV-2-containing aerosols; however, considering the reported sensitivity and the throughput estimated from the method used, there could still be room for improvement in the detection method for social implementation. Furthermore, using our method, we measured the amount of SARS-CoV-2 RNA in air samples collected at a so-called “fever clinic,” where outpatients with cold symptoms are examined. Results Development of the COPMAN-Air method We developed a new method (COPMAN-Air) for extracting nucleic acids from the aerosol-absorbed media collected by the AerosolSense sampler. COPMAN-Air is based on the COPMAN method and allows for the quantitative measurement of the amount of SARS-CoV-2 RNA in air samples. Additionally, we confirmed its ability to detect SARS-CoV-2 RNA from a sampler spiked with inactivated SARS-CoV-2 using the COPMAN-Air method. To compare the sensitivity of COMPAN-Air with the conventional method, we assessed its ability to detect and quantify SARS-CoV-2 RNA from media spiked with 50, 100, and 1000 copies of inactivated SARS-CoV-2. The theoretical limit of detection (LOD) of the COPMAN-Air test was lower than conventional methods, which use 5 µL of RNA, as 14 µL of RNA are subjected to qPCR detection with the COPMAN-Air method. We compared the observed concentrations between the two methods, since both were able to detect quantifiable amounts of SARS-CoV-2 RNA from the media spiked with 1,000 copies of the virus. COPMAN-Air showed a higher observed concentration (516.2 copies/sampler) than the conventional method (319.5 copies/sampler (N gene), 224.1 copies/sampler (ORF1ab gene), 54.1 copies/sampler (S gene)). A t-test was conducted to compare COPMAN-Air with the conventional method (N gene) and revealed a significant difference ( p < 0.05). (Fig. 1 a). The COPMAN-Air method exhibited greater accuracy, compared to the conventional method, because its coefficient of variation was 7.2%, whereas those of the conventional methods were 24.9% (N gene), 21.7% (ORF1ab gene), and 20.3% (S gene). When spiked with 50 copies of the virus, which is close to the LOD levels, COPMAN-Air exhibited a greater detection rate than the conventional method (Fig. 1 b). COPMAN-Air can be considered a more sensitive method, compared to the conventional method, due to its lower theoretical LOD and greater observed concentrations and detection rates. Validation of COPMAN-Air and its comparison with the conventional method at a fever clinic To compare COPMAN-Air with the conventional method using field aerosol samplers, we conducted air sampling at a fever clinic during the 5th wave of COVID-19 infections in Japan and evaluated these samples. Based on the measurement results, COPMAN-Air was able to detect SARS-CoV-2 more accurately in 22 (95.7%) out of 23 samples, with mean concentrations of 1217 copies/sampler, whereas the conventional method detected the virus in only 14 (60.9%) out of 23 samples (Fig. 2 ). These findings from the clinic experiment led us to conclude that COPMAN-Air demonstrated superior detection sensitivity than the conventional method. As a result, we have decided to use COPMAN in our future clinic experiments. Correlation analysis of SARS-CoV-2 in air samples with the number of COVID-19 patients COPMAN-Air could detect SARS-CoV-2 even when only a few COVID-19 patients were present (Fig. 2 and Supplementary Table S1 ). To compare this with the total number of patients, we conducted extensive additional air sampling at the fever clinic during the 6th and 7th waves of COVID-19 in Japan (Supplementary Table S1 ). We evaluated the correlation between the number of COVID-19 patients and the amount of SARS-CoV-2 virus RNA detected in the air samples using COPMAN-Air (Fig. 3 ). The data points plotted on a scatter plot closely aligned along an approximate straight line (y = 1.066x + 1.590), suggesting a linear relationship between the number of COVID-19 patients and the viral RNA detected in the air samples. The results of the Pearson correlation test revealed a positive correlation between the number of COVID-19 patients and the results of copy numbers of SARS-CoV-2 RNA found the air samples measured using COPMAN-Air (r = 0.70). Discussion In most of the air samples available in this study, we were able to obtain quantitative data for SARS-CoV-2 RNA using COPMAN-Air. There are two possible reasons why COPMAN-Air showed a higher observed concentration and lower theoretical LOD compared to the conventional method. Although the protocols are completely different between them, the most influential procedure against this difference is considered the nucleic acid extraction step from the aerosol-absorbed media. In the conventional method, the media is infiltrated into PBS, but in this case, there is a possibility that the virus particles, once suspended in PBS, may be re-adsorbed to the media. By contrast, because in the COPMAN-Air approach the media is infiltrated into lysis buffer, virus particles are completely destroyed and could not adsorb to the media again. Therefore, it is assumed that viral RNA can be extracted from media more efficiently. In addition, it is not difficult to imagine that the amount of SARS-CoV-2 in air samples is extremely low, compared to nasal swab and saliva samples derived from COVID-19 patients. With this in mind, we incorporated a pre-amplification step into both the COPMAN-Air and COPMAN methods for wastewater samples, to increase the equivalent RNA volume introduced during the qPCR detection step, thereby successfully improving the detection sensitivity of viral RNA 21 – 23 . As we saw during COVID-19, once a pandemic occurs, the demand for air sample tests will increase markedly, because room-by-room pathogen monitoring will be required in a significant number and type of facilities, such as hospitals, nursing homes, schools, hotels, and restaurants. There will be concerns about shortages of the resources necessary for virus testing, just as concerns arose about clinical sample tests. The COPMAN method for wastewater testing is an inspection approach that allows near full-automation using LabDroid 22 . The COPMAN-Air method detailed in this study was developed based on the COPMAN. With COPMAN-Air, the procedure after the RNA extraction step from the media is almost the same as in COPMAN, so it is possible to establish a timely and large-scale testing system for both air and wastewater samples. In many previous reports, as air collection methods, cyclones, filters, impactors, impingers, and water-based condensation have been adopted and the sampling volume, flow rate, sampling time, and collection medium of each method have been studied in detail 16 , 20 . The AerosolSense sampler was determined suitable for use in this study because previous works have reported its detection of SARS-CoV-2 RNA, and it was assumed that it would not be difficult to combine it with the COPMAN approach 18 , 24 , 25 . However, the combination of COPMAN-Air with other air sampling methods is not yet available and one of the matters to be handled in the future. In this study, we conducted air sampling in a fever clinic. This setting can be described as a level between a clinical setting for COVID-19 inpatients in a hospital and a community setting where an indefinite number of infected individuals visit temporarily. Further, it promised to mix COVID-19-confirmed individuals and SARS-CoV-2-uninfected individuals. As shown in Fig. 3 , we found a positive correlation between the amount of SARS-CoV-2 RNA in air samples and the number of COVID-19 patients in this setting. These data suggested that, as the number of individuals excreting SARS-CoV-2-containing aerosols increases, the amount of viral RNA in the air sample also increases. This allowed us to verify the correlation between the number of COVID-19 patients and the amount of SARS-CoV-2 RNA in air samples. In our data obtained from the fever clinic, while viral RNA was detected in air samples derived from one COVID-19 patient, it was also detected during periods when no COVID-19 patients were present. Two possible reasons for this can be considered. First, because this fever clinic does not perform a complete cleanup every day, it is possible that the virus had adhered to the floor or equipment as droplets the day before and was then re-aerosolized and detected once it was re-suspended in the air. Second, in addition to patients with cold symptoms, doctors and nurses are also present in the fever clinic, and some of them might have been infected asymptomatically, because they were not tested daily for SARS-CoV-2. In other words, it is possible that not all the viral RNA detected in this setting was derived from COVID-19 patients who were present during air sampling. In any case, we succeeded in the quantitative detection of viral RNA using air samples collected from a setting featuring a mix of COVID-19-confirmed individuals and uninfected individuals. However, the setting of this study does not fully mimic the community setting. This is because the asymptomatically infected individuals, who play an important role in viral transmission in community settings, are not completely included. In addition, other environmental factors, especially the varying temperature and humidity levels of each public space, and the influence of air flow caused by air conditioning and ventilation systems, could not be taken into consideration. Therefore, in the future, it will be necessary to verify whether our method enables us to detect viruses released from asymptomatically infected individuals into the air, and it is considered that the early detection of infected individuals may not be generalized, but rather must be validated for each public space according to its environment. Taken together, the data reported here strongly suggest that highly sensitive detection methods targeting airborne viruses could be helpful for monitoring air conditions to prevent their aerosol transmission. Quantitative values of viral RNA in air samples could be used to estimate the number of infected individuals who have been in each space, and air sample tests have the potential to serve as a complement to common clinical tests. This approach may also be applicable to other viruses, such as influenza viruses and respiratory syncytial viruses, that are transmitted between humans via aerosol and/or air. These viruses are spread seasonally; however, if a new strain with a mutation that makes it highly virulent or reduces the effectiveness of available vaccines and drugs emerges, it is not difficult to imagine that such viruses, like SARS-CoV-2, could spread quickly around the world. Finally, compared to clinical testing intended for individuals, this air sample test can serve multiple people in one sample, rendering it obviously cost-effective and similar to other environmental tests. Based on these matters, surveillance systems for pathogens contained in the air are expected to function as one of the public health measures that should be taken normally and thereby used to establish a society that is resilient against the next pandemic. Materials and Methods Preparation of inactivated SARS-CoV-2 An isolated SARS-CoV-2 strain (hCoV-19/Japan/TY-WK-521/2020, GISAID Accession ID: EPI_ISL_408667) was provided by the National Institute of Infectious Diseases, Japan. SARS-CoV-2 was propagated in VeroE6-TMPRSS2 cells (JCRB1819) 26 , and the virus was inactivated by heating at 65°C for 30 min 27 . After inactivation treatment, the virus solution was aliquoted and stored at -80°C. The copy number of the stock solution was 1.58 × 10 5 copies/µL. Virus quantification from air samples based on the COPMAN-Air The newly developed COPMAN-Air method consists of sample collection using an AerosolSense sampler (Thermo Fisher Scientific, Waltham, MA, USA), followed by RNA extraction, RT-preamplification, and qPCR using the COPMAN method 21 , 22 . The AerosolSense sampler, which is capable of sustained sampling over a long period of time, was used for air sampling and then RNA was purified by a method based on the COPMAN method from the AerosolSense cartridges (Thermo Fisher Scientific). Briefly, after aerosol-absorbed media were infiltrated with the lysis buffer, which included DTT and proteinase, it was squeezed out and heated at 56°C for 10 min. Crude RNA was extracted with phenol/chloroform/isoamyl alcohol (25:24:1), then purified with magnetic beads to obtain an RNA extract. Viral RNA was quantified using the measurement protocol established by the COPMAN method. An aliquot of 14 µL total RNA was subjected to cDNA synthesis using the Reliance Select cDNA synthesis kit (Bio-Rad Laboratories, Hercules, CA, USA) under the following conditions: 50°C for 60 min, and then at 95°C for 1 min in 20-µL reaction mix with 2 pmol of reverse primer of SARS-CoV-2 (N1 gene). The resultant cDNAs of SARS-CoV-2 were pre-amplified for 10 cycles using Biotaq HS (Bioline Reagents Ltd., London, UK) under the following conditions: 95°C for 10 min, and 10 cycles of 95°C for 15 s, 55°C for 15 s, and 72°C for 30 s, in a 30-µL volume reaction mix containing 9 pmol each of forward and reverse primers of SARS-CoV-2 (N1 gene). Finally, viral RNA was quantified from 2.5 µL of the preamplification (preamp) product for SARS-CoV-2 by qPCR using the TaqMan Environmental Master Mix 2.0 (Thermo Fisher Scientific) under the following conditions: 95°C for 10 min, and 45 cycles of 95°C for 15 s and 60°C for 30 s, in a 20-µL singleplex reaction mix containing 10 pmol each of reverse and forward primers and 7.5 pmol of TaqMan probe. Virus quantification from air samples according to the conventional method The conventional method consists of sample collection using the AerosolSense sampler, followed by RNA extraction using the MagMAX Viral/Pathogen Nucleic Acid Isolation Kit (Thermo Fisher Scientific) and subsequent quantification through RT-qPCR. RNA purification from the AerosolSense cartridges was carried out using the MagMAX Viral/Pathogen Nucleic Acid Isolation Kit. Briefly, after the aerosol-absorbed media were infiltrated with PBS, squeezed out, and mixed with proteinase K (ProK) and the total nucleic acid magnetic beads, it was heated at 65°C for 5 min. A final RNA sample was eluted from the beads after washing. The RNA was quantified by RT-PCR using a TaqPath New SARS-CoV-2 Real-time PCR Detection Kit (Thermo Fisher Scientific), according to the manufacturer's instructions, under the following conditions: 25°C for 2 min, 53°C for 10 min, 95°C for 2 min, and 40 cycles of 95°C for 3 s and 60°C for 30 s, in 25-µL reaction mix containing three primer/probe sets specific to different SARS-CoV-2 genomic regions (open reading frame 1ab (ORF1ab), spike (S) protein and nucleocapsid (N) protein-encoding genes). The comparison of the COPMAN-Air and conventional methods The aerosol-absorbed media of the AerosolSense cartridges were spiked with 50, 100, and 1000 copies of inactivated SARS-CoV-2. Nucleic acids from the cartridges were extracted by the COPMAN-Air or conventional method. Then, target viral genes were quantified by each method. LOD was calculated assuming that each method could detect as little as one copy of target cDNA in a qPCR reaction. Air sampling A sampling of airborne aerosols was conducted at a fever clinic in Fukuoka City, Japan. This fever clinic is intended for use by all outpatients with cold symptoms, including COVID-19. It is determined through a subsequent doctor’s examination and/or a clinical test whether or not the patient has contracted COVID-19. The sampling was carried out by placing AerosolSense samplers with AerosolSense cartridges at two points in the fever clinic. One sampler was positioned on the floor (Point A), while the other was placed on a low table, approximately 30 centimeters above the floor (Point B). Sampling was performed in July and September 2022 (the 5th wave of COVID-19 infections in Japan), and in March (6th wave), July, and August 2023 (7th wave). The sampling durations ranged from approximately 3 to 10 hours. Depending on the time, during or after the peak period of the wave of COVID-19 infections, the number of positive cases per day varied from zero to several dozen. In addition, outpatients attended the clinic for less than one hour, including SARS-CoV-2-infected individuals, unlike inpatients (Supplementary Table S1 ). Statistical analysis All statistical analyses were performed using GraphPad Prism 8.4.3. Declarations Competing Interests Tomoyo Yoshinaga, Yoshinori Ando, and Yumi Sato are employees of Shionogi & Co., Ltd. Masaaki Kitajima received research funding and patent royalties from Shionogi & Co., Ltd. Funding Conduct of the study and editorial support were funded by Shionogi & Co., Ltd. Author Contribution Conceptualization: T.Y., Y.A. and M.K. Methodology: T.Y., Y.A., Y.S. and M.K. Air sampling: T.Y., Y.A., T.K. and M.K. Analysis: T.Y. and Y.A. Writing the article: T.Y. and Y.A. Reviewing and Editing the article: all authors. Acknowledgement The authors thank Shinji Tsukamoto, Shun Kishida, Fumi Kishida, and the staff members of the Kishida Clinic for their assistance with air sampling. Data Availability The authors confirm that the data supporting the findings of this study are available within this article and its Supplementary Information files. References Beggs, C. B. et al. Airborne transmission of SARS-CoV-2: The contrast between indoors and outdoors. Fluids 9 , 54 (2024). Chakravarty, A., Panchagnula, M. V. & Patankar, N. A. Inhalation of virus-loaded droplets as a clinically plausible pathway to deep lung infection. Front. Physiol. 14 , 1073165 (2023). Greenhalgh, T. et al. Ten scientific reasons in support of airborne transmission of SARS-CoV-2. Lancet 397 , 1603–1605 (2021). Jarvis, M. C. 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Supplementary Files YoshinagaTetalSupplementaryInformationv2.docx Cite Share Download PDF Status: Published Journal Publication published 24 Apr, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 10 Mar, 2025 Reviews received at journal 03 Mar, 2025 Reviewers agreed at journal 26 Feb, 2025 Reviews received at journal 21 Feb, 2025 Reviewers agreed at journal 20 Feb, 2025 Reviewers agreed at journal 20 Feb, 2025 Reviewers invited by journal 19 Feb, 2025 Editor assigned by journal 19 Feb, 2025 Editor invited by journal 13 Feb, 2025 Submission checks completed at journal 13 Feb, 2025 First submitted to journal 09 Feb, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5995479","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":416507460,"identity":"95a5596d-c6e7-4b11-a17a-fa9986c89131","order_by":0,"name":"Tomoyo Yoshinaga","email":"","orcid":"","institution":"Shionogi \u0026 Co., Ltd","correspondingAuthor":false,"prefix":"","firstName":"Tomoyo","middleName":"","lastName":"Yoshinaga","suffix":""},{"id":416507461,"identity":"ccbc3348-2239-4d9e-b818-f5a1462a13d7","order_by":1,"name":"Yoshinori Ando","email":"data:image/png;base64,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","orcid":"","institution":"Shionogi \u0026 Co., Ltd","correspondingAuthor":true,"prefix":"","firstName":"Yoshinori","middleName":"","lastName":"Ando","suffix":""},{"id":416507462,"identity":"bd156d04-3d57-440d-9323-8f7d101536db","order_by":2,"name":"Yumi Sato","email":"","orcid":"","institution":"Shionogi \u0026 Co., Ltd","correspondingAuthor":false,"prefix":"","firstName":"Yumi","middleName":"","lastName":"Sato","suffix":""},{"id":416507463,"identity":"f3645cad-7217-4126-88c4-76f695465f8f","order_by":3,"name":"Takeru Kishida","email":"","orcid":"","institution":"Kishida Clinic","correspondingAuthor":false,"prefix":"","firstName":"Takeru","middleName":"","lastName":"Kishida","suffix":""},{"id":416507464,"identity":"0ec27556-7b44-49da-b76a-9bb3d4295193","order_by":4,"name":"Masaaki Kitajima","email":"","orcid":"","institution":"The University of Tokyo","correspondingAuthor":false,"prefix":"","firstName":"Masaaki","middleName":"","lastName":"Kitajima","suffix":""}],"badges":[],"createdAt":"2025-02-10 04:23:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5995479/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5995479/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-99365-2","type":"published","date":"2025-04-24T15:57:01+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":76572163,"identity":"b4d0524a-bea2-47c0-ab32-84155f977952","added_by":"auto","created_at":"2025-02-18 13:48:41","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":98614,"visible":true,"origin":"","legend":"\u003cp\u003eComparative verification of the COPMAN-Air and the conventional method using virus-spiked samples. SARS-CoV-2 RNA shown when (a) 50 and (b) 1000 copies of heat-inactivated SARS-CoV-2 viruses were spiked and recovered from the sampler via the COPMAN-Air or conventional method. Each bar shows the mean and standard deviation when viral RNA was detected in 3/3 samples. ND is shown when no signal was detected and when the signal was detected below the LOD. If only one or two out of three samples were detected, only the respective values are displayed. \u003cem\u003eP\u003c/em\u003e-values were calculated using an unpaired t-test for the COPMAN-Air vs. the conventional method, per spiked copy of heat-inactivated SARS-CoV-2 (*\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05, **\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5995479/v1/e4fb85f9d0e994ba96d8dd68.png"},{"id":76573566,"identity":"6994f71e-93a0-42de-a793-afc166548b7a","added_by":"auto","created_at":"2025-02-18 13:56:41","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":81099,"visible":true,"origin":"","legend":"\u003cp\u003eComparative verification of the COPMAN-Air and conventional methods using samples from the fever clinic. SARS-CoV-2 RNA was measured via the COPMAN method (N1 gene, filled circle) or conventional methods (N gene, open circle; ORF1ab gene, open triangle; S gene, open diamond) using 23 samples obtained in duplicate from the fever clinic.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5995479/v1/916e9c256e8b15170744632f.png"},{"id":76572159,"identity":"deb0f3e2-ca62-4905-89fd-18b1e888ec6c","added_by":"auto","created_at":"2025-02-18 13:48:41","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":53463,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between the number of COVID-19 patients and the amount of SARS-CoV-2 RNA from air samples. A scatter plot shows the amount of SARS-CoV-2 RNA in air samples using the COPMAN-Air method and the number of COVID-19 patients. A correlation analysis was performed using Pearson’s correlation test.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5995479/v1/d01288d077c0c3774d00b9da.png"},{"id":81569614,"identity":"225e480d-2f5b-416f-8c83-0e7a7b9f17a3","added_by":"auto","created_at":"2025-04-28 16:08:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":577413,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5995479/v1/135b568c-0975-4eb1-a743-2c228fa5667f.pdf"},{"id":76573568,"identity":"f48df3f0-8fe0-4568-a581-df3e38f56048","added_by":"auto","created_at":"2025-02-18 13:56:41","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":35936,"visible":true,"origin":"","legend":"","description":"","filename":"YoshinagaTetalSupplementaryInformationv2.docx","url":"https://assets-eu.researchsquare.com/files/rs-5995479/v1/b74803de736dfbefe8553db8.docx"}],"financialInterests":"Competing interest reported. Tomoyo Yoshinaga, Yoshinori Ando, and Yumi Sato are employees of Shionogi \u0026 Co., Ltd. Masaaki Kitajima received research funding and patent royalties from Shionogi \u0026 Co., Ltd.","formattedTitle":"The development of COPMAN-Air: A highly sensitive method for detecting SARS-CoV-2 in air","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSARS-CoV-2 is a virus that infects the human respiratory tract. It can be spread not only through direct and indirect contact, but also through the inhalation of droplets and aerosols \u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Generally, people infected with COVID-19 exhibit symptoms similar to those of the common cold or influenza and recover after several days, except for vulnerable people such as the elderly and those with underlying health conditions \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. In addition, it has been reported that some people infected with SARS-CoV-2 show no symptoms, and it is possible that these asymptomatic people may inadvertently play a role as spreaders of the virus \u003csup\u003e\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Because environmental tests, which detect pathogens contained in the environment, are non-invasive and are regarded as more cost-effective than clinical tests, they are attracting attention as an alternative or complement to clinical testing \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSARS-CoV-2 is widely accepted as a virus that spreads through airborne transmission; therefore, one way to prevent its spread is to help people to know if the air around them contains the virus. Air sampling to detect the virus has been vigorously taken into consideration. Many of these studies have been conducted in healthcare settings, such as isolation rooms for COVID-19 patients in hospitals and quarantine hotels, where high concentrations of SARS-CoV-2-containing aerosols are expected to fill the space \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. However, considering the social implementations of the virus, it is necessary to conduct a feasibility study in a more practical community setting. Some reports have successfully detected SARS-CoV-2 in public places such as student dormitories, schools, cafeterias, offices, shopping centers, airports, and public transport \u003csup\u003e\u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Nevertheless, because it is difficult to grasp the number of SARS-CoV-2-infected individuals who have been or are presently in such spaces during air sampling, it is not possible to accurately confirm the validity of the virus detection method. Furthermore, it cannot be determined whether the method is available for the early detection of infected individuals.\u003c/p\u003e \u003cp\u003eThe major detection method for SARS-CoV-2 in the air is the quantitative measurement of viral RNA derived from an air sample via reverse transcription-quantitative polymerase chain reaction (RT-qPCR) \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. There have been many reports on air sampling methods \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Since the number of SARS-CoV-2-containing aerosols in a space is expected to be extremely low, the optimization of the protocol to be used after air sampling is also needed, to improve sensitivity of virus detection using RT-qPCR. In addition, the protocol must be able to handle a large number of air samples for virus monitoring in many spaces, to achieve worthwhile social implementation. To our knowledge, however, such efforts have not yet been sufficiently verified.\u003c/p\u003e \u003cp\u003eRecently, our group developed the COPMAN (COagulation and Proteolysis method using MAgnetic beads for Nucleic acids in wastewater) method, which can detect SARS-CoV-2 RNA from wastewater samples with both high sensitivity and high throughput \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. In this study, we developed COPMAN-Air, a new method that applies the near full-automation-available COPMAN technology and investigated the detection sensitivity of SARS-CoV-2 RNA derived from air samples taken from a Thermo Fisher Scientific AerosolSense Sampler. Some reports have clearly shown that this active air sampler is helpful in collecting SARS-CoV-2-containing aerosols; however, considering the reported sensitivity and the throughput estimated from the method used, there could still be room for improvement in the detection method for social implementation. Furthermore, using our method, we measured the amount of SARS-CoV-2 RNA in air samples collected at a so-called \u0026ldquo;fever clinic,\u0026rdquo; where outpatients with cold symptoms are examined.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eDevelopment of the COPMAN-Air method\u003c/p\u003e \u003cp\u003eWe developed a new method (COPMAN-Air) for extracting nucleic acids from the aerosol-absorbed media collected by the AerosolSense sampler. COPMAN-Air is based on the COPMAN method and allows for the quantitative measurement of the amount of SARS-CoV-2 RNA in air samples. Additionally, we confirmed its ability to detect SARS-CoV-2 RNA from a sampler spiked with inactivated SARS-CoV-2 using the COPMAN-Air method.\u003c/p\u003e \u003cp\u003eTo compare the sensitivity of COMPAN-Air with the conventional method, we assessed its ability to detect and quantify SARS-CoV-2 RNA from media spiked with 50, 100, and 1000 copies of inactivated SARS-CoV-2. The theoretical limit of detection (LOD) of the COPMAN-Air test was lower than conventional methods, which use 5 \u0026micro;L of RNA, as 14 \u0026micro;L of RNA are subjected to qPCR detection with the COPMAN-Air method. We compared the observed concentrations between the two methods, since both were able to detect quantifiable amounts of SARS-CoV-2 RNA from the media spiked with 1,000 copies of the virus. COPMAN-Air showed a higher observed concentration (516.2 copies/sampler) than the conventional method (319.5 copies/sampler (N gene), 224.1 copies/sampler (ORF1ab gene), 54.1 copies/sampler (S gene)). A t-test was conducted to compare COPMAN-Air with the conventional method (N gene) and revealed a significant difference (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe COPMAN-Air method exhibited greater accuracy, compared to the conventional method, because its coefficient of variation was 7.2%, whereas those of the conventional methods were 24.9% (N gene), 21.7% (ORF1ab gene), and 20.3% (S gene).\u003c/p\u003e \u003cp\u003eWhen spiked with 50 copies of the virus, which is close to the LOD levels, COPMAN-Air exhibited a greater detection rate than the conventional method (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). COPMAN-Air can be considered a more sensitive method, compared to the conventional method, due to its lower theoretical LOD and greater observed concentrations and detection rates.\u003c/p\u003e \u003cp\u003eValidation of COPMAN-Air and its comparison with the conventional method at a fever clinic\u003c/p\u003e \u003cp\u003eTo compare COPMAN-Air with the conventional method using field aerosol samplers, we conducted air sampling at a fever clinic during the 5th wave of COVID-19 infections in Japan and evaluated these samples. Based on the measurement results, COPMAN-Air was able to detect SARS-CoV-2 more accurately in 22 (95.7%) out of 23 samples, with mean concentrations of 1217 copies/sampler, whereas the conventional method detected the virus in only 14 (60.9%) out of 23 samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These findings from the clinic experiment led us to conclude that COPMAN-Air demonstrated superior detection sensitivity than the conventional method. As a result, we have decided to use COPMAN in our future clinic experiments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCorrelation analysis of SARS-CoV-2 in air samples with the number of COVID-19 patients\u003c/p\u003e \u003cp\u003eCOPMAN-Air could detect SARS-CoV-2 even when only a few COVID-19 patients were present (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). To compare this with the total number of patients, we conducted extensive additional air sampling at the fever clinic during the 6th and 7th waves of COVID-19 in Japan (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). We evaluated the correlation between the number of COVID-19 patients and the amount of SARS-CoV-2 virus RNA detected in the air samples using COPMAN-Air (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The data points plotted on a scatter plot closely aligned along an approximate straight line (y\u0026thinsp;=\u0026thinsp;1.066x\u0026thinsp;+\u0026thinsp;1.590), suggesting a linear relationship between the number of COVID-19 patients and the viral RNA detected in the air samples. The results of the Pearson correlation test revealed a positive correlation between the number of COVID-19 patients and the results of copy numbers of SARS-CoV-2 RNA found the air samples measured using COPMAN-Air (r\u0026thinsp;=\u0026thinsp;0.70).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn most of the air samples available in this study, we were able to obtain quantitative data for SARS-CoV-2 RNA using COPMAN-Air. There are two possible reasons why COPMAN-Air showed a higher observed concentration and lower theoretical LOD compared to the conventional method. Although the protocols are completely different between them, the most influential procedure against this difference is considered the nucleic acid extraction step from the aerosol-absorbed media. In the conventional method, the media is infiltrated into PBS, but in this case, there is a possibility that the virus particles, once suspended in PBS, may be re-adsorbed to the media. By contrast, because in the COPMAN-Air approach the media is infiltrated into lysis buffer, virus particles are completely destroyed and could not adsorb to the media again. Therefore, it is assumed that viral RNA can be extracted from media more efficiently. In addition, it is not difficult to imagine that the amount of SARS-CoV-2 in air samples is extremely low, compared to nasal swab and saliva samples derived from COVID-19 patients. With this in mind, we incorporated a pre-amplification step into both the COPMAN-Air and COPMAN methods for wastewater samples, to increase the equivalent RNA volume introduced during the qPCR detection step, thereby successfully improving the detection sensitivity of viral RNA \u003csup\u003e\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAs we saw during COVID-19, once a pandemic occurs, the demand for air sample tests will increase markedly, because room-by-room pathogen monitoring will be required in a significant number and type of facilities, such as hospitals, nursing homes, schools, hotels, and restaurants. There will be concerns about shortages of the resources necessary for virus testing, just as concerns arose about clinical sample tests. The COPMAN method for wastewater testing is an inspection approach that allows near full-automation using LabDroid \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. The COPMAN-Air method detailed in this study was developed based on the COPMAN. With COPMAN-Air, the procedure after the RNA extraction step from the media is almost the same as in COPMAN, so it is possible to establish a timely and large-scale testing system for both air and wastewater samples. In many previous reports, as air collection methods, cyclones, filters, impactors, impingers, and water-based condensation have been adopted and the sampling volume, flow rate, sampling time, and collection medium of each method have been studied in detail \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The AerosolSense sampler was determined suitable for use in this study because previous works have reported its detection of SARS-CoV-2 RNA, and it was assumed that it would not be difficult to combine it with the COPMAN approach \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. However, the combination of COPMAN-Air with other air sampling methods is not yet available and one of the matters to be handled in the future.\u003c/p\u003e \u003cp\u003eIn this study, we conducted air sampling in a fever clinic. This setting can be described as a level between a clinical setting for COVID-19 inpatients in a hospital and a community setting where an indefinite number of infected individuals visit temporarily. Further, it promised to mix COVID-19-confirmed individuals and SARS-CoV-2-uninfected individuals. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, we found a positive correlation between the amount of SARS-CoV-2 RNA in air samples and the number of COVID-19 patients in this setting. These data suggested that, as the number of individuals excreting SARS-CoV-2-containing aerosols increases, the amount of viral RNA in the air sample also increases. This allowed us to verify the correlation between the number of COVID-19 patients and the amount of SARS-CoV-2 RNA in air samples. In our data obtained from the fever clinic, while viral RNA was detected in air samples derived from one COVID-19 patient, it was also detected during periods when no COVID-19 patients were present. Two possible reasons for this can be considered. First, because this fever clinic does not perform a complete cleanup every day, it is possible that the virus had adhered to the floor or equipment as droplets the day before and was then re-aerosolized and detected once it was re-suspended in the air. Second, in addition to patients with cold symptoms, doctors and nurses are also present in the fever clinic, and some of them might have been infected asymptomatically, because they were not tested daily for SARS-CoV-2. In other words, it is possible that not all the viral RNA detected in this setting was derived from COVID-19 patients who were present during air sampling. In any case, we succeeded in the quantitative detection of viral RNA using air samples collected from a setting featuring a mix of COVID-19-confirmed individuals and uninfected individuals. However, the setting of this study does not fully mimic the community setting. This is because the asymptomatically infected individuals, who play an important role in viral transmission in community settings, are not completely included. In addition, other environmental factors, especially the varying temperature and humidity levels of each public space, and the influence of air flow caused by air conditioning and ventilation systems, could not be taken into consideration. Therefore, in the future, it will be necessary to verify whether our method enables us to detect viruses released from asymptomatically infected individuals into the air, and it is considered that the early detection of infected individuals may not be generalized, but rather must be validated for each public space according to its environment.\u003c/p\u003e \u003cp\u003eTaken together, the data reported here strongly suggest that highly sensitive detection methods targeting airborne viruses could be helpful for monitoring air conditions to prevent their aerosol transmission. Quantitative values of viral RNA in air samples could be used to estimate the number of infected individuals who have been in each space, and air sample tests have the potential to serve as a complement to common clinical tests. This approach may also be applicable to other viruses, such as influenza viruses and respiratory syncytial viruses, that are transmitted between humans via aerosol and/or air. These viruses are spread seasonally; however, if a new strain with a mutation that makes it highly virulent or reduces the effectiveness of available vaccines and drugs emerges, it is not difficult to imagine that such viruses, like SARS-CoV-2, could spread quickly around the world. Finally, compared to clinical testing intended for individuals, this air sample test can serve multiple people in one sample, rendering it obviously cost-effective and similar to other environmental tests. Based on these matters, surveillance systems for pathogens contained in the air are expected to function as one of the public health measures that should be taken normally and thereby used to establish a society that is resilient against the next pandemic.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003ePreparation of inactivated SARS-CoV-2\u003c/p\u003e \u003cp\u003e An isolated SARS-CoV-2 strain (hCoV-19/Japan/TY-WK-521/2020, GISAID Accession ID: EPI_ISL_408667) was provided by the National Institute of Infectious Diseases, Japan. SARS-CoV-2 was propagated in VeroE6-TMPRSS2 cells (JCRB1819) \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, and the virus was inactivated by heating at 65\u0026deg;C for 30 min \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. After inactivation treatment, the virus solution was aliquoted and stored at -80\u0026deg;C. The copy number of the stock solution was 1.58 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e copies/\u0026micro;L.\u003c/p\u003e \u003cp\u003eVirus quantification from air samples based on the COPMAN-Air\u003c/p\u003e \u003cp\u003eThe newly developed COPMAN-Air method consists of sample collection using an AerosolSense sampler (Thermo Fisher Scientific, Waltham, MA, USA), followed by RNA extraction, RT-preamplification, and qPCR using the COPMAN method \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe AerosolSense sampler, which is capable of sustained sampling over a long period of time, was used for air sampling and then RNA was purified by a method based on the COPMAN method from the AerosolSense cartridges (Thermo Fisher Scientific). Briefly, after aerosol-absorbed media were infiltrated with the lysis buffer, which included DTT and proteinase, it was squeezed out and heated at 56\u0026deg;C for 10 min. Crude RNA was extracted with phenol/chloroform/isoamyl alcohol (25:24:1), then purified with magnetic beads to obtain an RNA extract. Viral RNA was quantified using the measurement protocol established by the COPMAN method. An aliquot of 14 \u0026micro;L total RNA was subjected to cDNA synthesis using the Reliance Select cDNA synthesis kit (Bio-Rad Laboratories, Hercules, CA, USA) under the following conditions: 50\u0026deg;C for 60 min, and then at 95\u0026deg;C for 1 min in 20-\u0026micro;L reaction mix with 2 pmol of reverse primer of SARS-CoV-2 (N1 gene). The resultant cDNAs of SARS-CoV-2 were pre-amplified for 10 cycles using Biotaq HS (Bioline Reagents Ltd., London, UK) under the following conditions: 95\u0026deg;C for 10 min, and 10 cycles of 95\u0026deg;C for 15 s, 55\u0026deg;C for 15 s, and 72\u0026deg;C for 30 s, in a 30-\u0026micro;L volume reaction mix containing 9 pmol each of forward and reverse primers of SARS-CoV-2 (N1 gene). Finally, viral RNA was quantified from 2.5 \u0026micro;L of the preamplification (preamp) product for SARS-CoV-2 by qPCR using the TaqMan Environmental Master Mix 2.0 (Thermo Fisher Scientific) under the following conditions: 95\u0026deg;C for 10 min, and 45 cycles of 95\u0026deg;C for 15 s and 60\u0026deg;C for 30 s, in a 20-\u0026micro;L singleplex reaction mix containing 10 pmol each of reverse and forward primers and 7.5 pmol of TaqMan probe.\u003c/p\u003e \u003cp\u003eVirus quantification from air samples according to the conventional method\u003c/p\u003e \u003cp\u003e The conventional method consists of sample collection using the AerosolSense sampler, followed by RNA extraction using the MagMAX Viral/Pathogen Nucleic Acid Isolation Kit (Thermo Fisher Scientific) and subsequent quantification through RT-qPCR. RNA purification from the AerosolSense cartridges was carried out using the MagMAX Viral/Pathogen Nucleic Acid Isolation Kit. Briefly, after the aerosol-absorbed media were infiltrated with PBS, squeezed out, and mixed with proteinase K (ProK) and the total nucleic acid magnetic beads, it was heated at 65\u0026deg;C for 5 min. A final RNA sample was eluted from the beads after washing. The RNA was quantified by RT-PCR using a TaqPath New SARS-CoV-2 Real-time PCR Detection Kit (Thermo Fisher Scientific), according to the manufacturer's instructions, under the following conditions: 25\u0026deg;C for 2 min, 53\u0026deg;C for 10 min, 95\u0026deg;C for 2 min, and 40 cycles of 95\u0026deg;C for 3 s and 60\u0026deg;C for 30 s, in 25-\u0026micro;L reaction mix containing three primer/probe sets specific to different SARS-CoV-2 genomic regions (open reading frame 1ab (ORF1ab), spike (S) protein and nucleocapsid (N) protein-encoding genes).\u003c/p\u003e \u003cp\u003eThe comparison of the COPMAN-Air and conventional methods\u003c/p\u003e \u003cp\u003eThe aerosol-absorbed media of the AerosolSense cartridges were spiked with 50, 100, and 1000 copies of inactivated SARS-CoV-2. Nucleic acids from the cartridges were extracted by the COPMAN-Air or conventional method. Then, target viral genes were quantified by each method. LOD was calculated assuming that each method could detect as little as one copy of target cDNA in a qPCR reaction.\u003c/p\u003e \u003cp\u003eAir sampling\u003c/p\u003e \u003cp\u003eA sampling of airborne aerosols was conducted at a fever clinic in Fukuoka City, Japan. This fever clinic is intended for use by all outpatients with cold symptoms, including COVID-19. It is determined through a subsequent doctor\u0026rsquo;s examination and/or a clinical test whether or not the patient has contracted COVID-19.\u003c/p\u003e \u003cp\u003eThe sampling was carried out by placing AerosolSense samplers with AerosolSense cartridges at two points in the fever clinic. One sampler was positioned on the floor (Point A), while the other was placed on a low table, approximately 30 centimeters above the floor (Point B).\u003c/p\u003e \u003cp\u003eSampling was performed in July and September 2022 (the 5th wave of COVID-19 infections in Japan), and in March (6th wave), July, and August 2023 (7th wave). The sampling durations ranged from approximately 3 to 10 hours. Depending on the time, during or after the peak period of the wave of COVID-19 infections, the number of positive cases per day varied from zero to several dozen. In addition, outpatients attended the clinic for less than one hour, including SARS-CoV-2-infected individuals, unlike inpatients (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed using GraphPad Prism 8.4.3.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eCompeting Interests\u003c/p\u003e\n\u003cp\u003eTomoyo Yoshinaga, Yoshinori Ando, and Yumi Sato are employees of Shionogi \u0026amp; Co., Ltd. Masaaki Kitajima received research funding and patent royalties from Shionogi \u0026amp; Co., Ltd.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eConduct of the study and editorial support were funded by Shionogi \u0026amp; Co., Ltd.\u003c/p\u003e\n\u003cp\u003eAuthor Contribution\u003c/p\u003e\n\u003cp\u003eConceptualization: T.Y., Y.A. and M.K. Methodology: T.Y., Y.A., Y.S. and M.K. Air sampling: T.Y., Y.A., T.K. and M.K. Analysis: T.Y. and Y.A. Writing the article: T.Y. and Y.A. Reviewing and Editing the article: all authors.\u003c/p\u003e\n\u003cp\u003eAcknowledgement\u003c/p\u003e\n\u003cp\u003eThe authors thank Shinji Tsukamoto, Shun Kishida, Fumi Kishida, and the staff members of the Kishida Clinic for their assistance with air sampling.\u003c/p\u003e\n\u003cp\u003eData Availability\u003c/p\u003e\n\u003cp\u003eThe authors confirm that the data supporting the findings of this study are available within this article and its Supplementary Information files.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBeggs, C. B. \u003cem\u003eet al.\u003c/em\u003e Airborne transmission of SARS-CoV-2: The contrast between indoors and outdoors. \u003cem\u003eFluids\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 54 (2024).\u003c/li\u003e\n \u003cli\u003eChakravarty, A., Panchagnula, M. V. \u0026amp; Patankar, N. A. Inhalation of virus-loaded droplets as a clinically plausible pathway to deep lung infection. \u003cem\u003eFront. 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SARS-CoV-2 Detection in air samples from inside heating, ventilation, and air conditioning (HVAC) systems- COVID surveillance in student dorms. \u003cem\u003eAm. J. Infect. Control\u003c/em\u003e \u003cstrong\u003e50\u003c/strong\u003e, 330\u0026ndash;335 (2022).\u003c/li\u003e\n \u003cli\u003eTan, K. S. \u003cem\u003eet al.\u003c/em\u003e Detection of hospital environmental contamination during SARS-CoV-2 Omicron predominance using a highly sensitive air sampling device. \u003cem\u003eFront. Public Health\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 1067575 (2022).\u003c/li\u003e\n \u003cli\u003eMatsuyama, S. \u003cem\u003eet al.\u003c/em\u003e Enhanced isolation of SARS-CoV-2 by TMPRSS2-expressing cells. \u003cem\u003eProc. Natl. Acad. Sci. U. S. A.\u003c/em\u003e \u003cstrong\u003e117\u003c/strong\u003e, 7001\u0026ndash;7003 (2020).\u003c/li\u003e\n \u003cli\u003eKim, Y.-I. \u003cem\u003eet al.\u003c/em\u003e Development of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) thermal inactivation method with preservation of diagnostic sensitivity. \u003cem\u003eJ. Microbiol.\u003c/em\u003e \u003cstrong\u003e58\u003c/strong\u003e, 886\u0026ndash;891 (2020).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Air sampling, COPMAN, COPMAN-Air, Fever clinic, qPCR, SARS-CoV-2","lastPublishedDoi":"10.21203/rs.3.rs-5995479/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5995479/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSeveral studies have successfully detected SARS-CoV-2 in air samples; however, in most of these, the focus was on validating the air collection method, and there was no report on the development of a virus-detection method. In this study, to detect viruses in air samples more sensitively than conventional detection methods, we applied COPMAN, a highly sensitive virus-detection method using wastewater samples, to air samples to develop COPMAN-Air. Briefly, with this method, the extremely low amount of viral RNA in air samples is efficiently detected via three reaction steps: RT, preamplification, and qPCR, as with COPMAN. We evaluated COPMAN-Air using samples from a fever clinic for COVID-19 patients. COPMAN-Air demonstrated a higher detection rate of viral RNA compared to conventional methods: 22 (95.7%) vs. 14 (60.9%) out of 23 samples. Additionally, a positive correlation (r=0.70) was found between the amount of viral RNA detected by COPMAN-Air and the number of confirmed COVID-19 cases, suggesting that COPMAN-Air could estimate the number of SARS-CoV-2-positive individuals in a given space based on the quantitative values of SARS-CoV-2 RNA in air samples. Surveillance systems for pathogens in the air using COPMAN-Air are expected to be valuable for assessing the number of infected individuals and for the implementation of public health measures.\u003c/p\u003e","manuscriptTitle":"The development of COPMAN-Air: A highly sensitive method for detecting SARS-CoV-2 in air","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-18 13:48:36","doi":"10.21203/rs.3.rs-5995479/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-03-10T10:58:20+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-03T16:32:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"76412994774185166628155914640384345879","date":"2025-02-26T05:44:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-02-21T08:26:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"77134174196620184279989425327869729730","date":"2025-02-20T08:42:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"120964864474506310030913917209036302110","date":"2025-02-20T05:08:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-02-20T01:32:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-02-20T01:18:18+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-02-13T11:16:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-02-13T07:33:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-02-10T04:12:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d60de85a-27f0-4f3b-b702-51b972280ccb","owner":[],"postedDate":"February 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":44409651,"name":"Biological sciences/Microbiology/Virology/Viral transmission"},{"id":44409652,"name":"Health sciences/Health care/Public health"},{"id":44409653,"name":"Biological sciences/Microbiology/Environmental microbiology/Air microbiology"}],"tags":[],"updatedAt":"2025-04-28T16:01:10+00:00","versionOfRecord":{"articleIdentity":"rs-5995479","link":"https://doi.org/10.1038/s41598-025-99365-2","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-04-24 15:57:01","publishedOnDateReadable":"April 24th, 2025"},"versionCreatedAt":"2025-02-18 13:48:36","video":"","vorDoi":"10.1038/s41598-025-99365-2","vorDoiUrl":"https://doi.org/10.1038/s41598-025-99365-2","workflowStages":[]},"version":"v1","identity":"rs-5995479","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5995479","identity":"rs-5995479","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}