Wearable Collector for Noninvasive Sampling of SARS-CoV-2 from Exhaled Breath for Rapid Detection.
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ABSTRACT:
SUBMITTER: Soto F
PROVIDER: S-EPMC8406923 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Early detection of lung cancer is a key factor for increasing the survival rates of lung cancer patients. The analysis of exhaled breath is promising as a noninvasive diagnostic tool for diagnosis of lung cancer. We demonstrate the quantitative analysis of carbonyl volatile organic compounds (VOCs) and identification of lung cancer VOC markers in exhaled breath using unique silicon microreactor technology. The microreactor consists of thousands of micropillars coated with an ammonium aminooxy salt for capture of carbonyl VOCs in exhaled breath by means of oximation reactions. Captured aminooxy-VOC adducts are analyzed by nanoelectrospray Fourier transform-ion cyclotron resonance (FT-ICR) mass spectrometry (MS). The concentrations of 2-butanone, 2-hydroxyacetaldehyde, 3-hydroxy-2-butanone, and 4-hydroxyhexenal (4-HHE) in the exhaled breath of lung cancer patients (n = 97) were significantly higher than in the exhaled breath of healthy smoker and nonsmoker controls (n = 88) and patients with benign pulmonary nodules (n = 32). The concentration of 2-butanone in exhaled breath of patients (n = 51) with stages II though IV non-small cell lung cancer (NSCLC) was significantly higher than in exhaled breath of patients with stage I (n = 34). The carbonyl VOC profile in exhaled breath determined using this new silicon microreactor technology provides for the noninvasive detection of lung cancer.
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Project description:Face masks are used to protect the wearer from harmful external air and to prevent transmission of viruses from air exhaled by potentially infected wearers to the surrounding people. In this study, we examined the potential utility of masks for collecting viruses contained in exhaled breath and detected the collected viruses via various molecular tests. Using KF94 masks, the inner electrostatic filter was selected for virus collection, and an RNA extraction protocol was developed for the face mask. Virus detection in worn mask samples was performed using PCR and rolling circle amplification (RCA) tests and four different target genes (N, E, RdRp, and ORF1ab genes). The present study confirmed that the mask sample tests showed positive SARS-CoV-2 results, similar to the PCR tests using nasopharyngeal swab samples. In addition, the quantity of nucleic acid collected in the masks linearly increased with wearing time. These results suggest that samples for SARS-CoV-2 tests can be collected in a noninvasive, quick, and easy method by simply submitting worn masks from subjects, which can significantly reduce the hassle of waiting at airports or public places and concerns about cross-infection. In addition, it is expected that miniaturization technology will integrate PCR assays on face masks in the near future, and mask-based self-diagnosis would play a significant role in resolving the pandemic situation.
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Project description:BackgroundAn effective testing strategy is essential for pandemic control of the novel Coronavirus disease 2019 (COVID-19) caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Breath gas analysis can expand the available toolbox for diagnostic tests by using a rapid, cost-beneficial, high-throughput point-of-care test. We conducted a bi-center clinical pilot study in Germany to evaluate breath gas analysis using multi-capillary column ion mobility spectrometry (MCC-IMS) to detect SARS-CoV-2 infection.MethodsBetween September 23, 2020, and June 11, 2021, breath gas measurements were performed on 380 patients (SARS-CoV-2 real-time polymerase chain reaction (PCR) positive: 186; PCR negative: 194) presenting to the emergency department (ED) with respiratory symptoms.ResultsBreath gas analysis using MCC-IMS identified 110 peaks; 54 showed statistically significant differences in peak intensity between the SARS-CoV-2 PCR-negative and PCR-positive groups. A decision tree analysis classification resulted in a sensitivity of 83% and specificity of 86%, but limited robustness to dataset changes. Modest values for the sensitivity (74%) and specificity (52%) were obtained using linear discriminant analysis. A systematic search for peaks led to a sensitivity of 77% and specificity of 67%; however, validation by transferability to other data is questionable.ConclusionsDespite identifying several peaks by MCC-IMS with significant differences in peak intensity between PCR-negative and PCR-positive samples, finding a classification system that allows reliable differentiation between the two groups proved to be difficult. However, with some modifications to the setup, breath gas analysis using MCC-IMS may be a useful diagnostic toolbox for SARS-CoV-2 infection.Trial registrationThis study was registered at ClinicalTrials.gov on September 21, 2020 (NCT04556318; Study-ID: HC-N-H-2004).
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Project description:The diagnosis of COVID-19 is based on detection of SARS-CoV-2 in oro-/nasopharyngel swabs, but due to discomfort and minor risk during the swab procedure, detection of SARS-CoV-2 has been investigated in other biological matrixes. In this proof-of-concept study, individuals with confirmed SARS-CoV-2 infection performed a daily air sample for five days. Air samples were obtained through a non-invasive electrostatic air sampler. Detection of SARS-CoV-2 RNA was determined with qRT-PCR. The association of positive samples with different exposures was evaluated through mixed-effect models. We obtained 665 air samples from 111 included participants with confirmed SARS-CoV-2 infection. Overall, 52 individuals (46.8%) had at least one positive air sample, and 129 (19.4%) air samples were positive for SARS-CoV-2. Participants with symptoms or a symptom duration ≤ four days had significantly higher odds of having a positive air sample. Cycle threshold values were significantly lower in samples obtained ≤ 4 days from symptom onset. Neither variant of SARS-CoV-2 nor method of air sampling were associated with a positive air sample. We demonstrate that SARS-CoV-2 is detectable in human breath by electrostatic air sampling with the highest detection rate closest to symptom onset. We suggest further evaluation of the air sampling technique to increase sensitivity.
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Project description:Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) is transmitted through airborne particles in exhaled breath, causing severe respiratory disease, coronavirus disease-2019 (COVID-19), in some patients. Samples for SARS-CoV-2 testing are typically collected by nasopharyngeal swab, with the virus detected by PCR; however, patients can test positive for 3 months after infection. Without the capacity to assay SARS-CoV-2 in breath, it is not possible to understand the risk for transmission from infected individuals. To detect virus in breath, the Bubbler-a breathalyzer that reverse-transcribes RNA from SARS-CoV-2 particles into a sample-specific barcoded cDNA-was developed. In a study of 70 hospitalized patients, the Bubbler was both more predictive of lower respiratory tract involvement (abnormal chest X-ray) and less invasive than alternatives. Samples tested using the Bubbler were threefold more enriched for SARS-CoV-2 RNA than were samples from tongue swabs, implying that virus particles were being directly sampled. The barcode-enabled Bubbler was used for simultaneous diagnosis in large batches of pooled samples at a lower limit of detection of 334 genomic copies per sample. Diagnosis by sequencing can provide additional information, such as viral load and strain identity. The Bubbler was configured to sample nucleic acids in water droplets circulating in air, demonstrating its potential in environmental monitoring and the protective effect of adequate ventilation.
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Project description:ObjectivesWe performed exhaled breath (EB) and nasopharyngeal (NP) quantitative polymerase chain reaction (qPCR) and NP rapid antigen testing (NP RAT) of SARS-CoV-2 infections with different variants.MethodsWe included immuno-naïve alpha-infected (n = 11) and partly boosted omicron-infected patients (n = 8) as high-risk contacts. We compared peak NP and EB qPCR cycle time (ct) values between cohorts (Wilcoxon-Mann-Whitney test). Test positivity was compared for three infection phases using Cochran Q test.ResultsPeak median NP ct was 11.5 (interquartile range [IQR] 10.1-12.1) for alpha and 12.2 (IQR 11.1-15.3) for omicron infections. Peak median EB ct was 25.2 (IQR 24.5-26.9) and 28.3 (IQR 26.4-30.8) for alpha and omicron infections, respectively. Distributions did not differ between cohorts for NP (P = 0.19) or EB (P = 0.09). SARS-CoV-2 shedding peaked on day 1 in EB (confidence interval [CI] 0.0 - 4.5) and day 3 in NP (CI 1.5 - 6.0). EB qPCR positivity equaled NP qPCR positivity on D0-D1 (P = 0.44) and D2-D6 (P = 1.0). It superseded NP RAT positivity on D0-D1 (P = 0.003) and D2-D6 (P = 0.008). It was inferior to both on D7-D10 (P < 0.001).ConclusionPeak EB and nasopharynx shedding were comparable across variants. EB qPCR positivity matched NP qPCR and superseded NP RAT in the first week of infection.
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Project description:BackgroundExhaled breath condensate (EBC) sampling has been considered an inventive and novel method for the isolation of respiratory viruses.MethodsIn our study, 102 volunteers experiencing upper airway infection were recruited over the winter and early spring of 2008/2009 and the first half of the winter of 2009/2010. Ninety-nine EBCs were successfully obtained and screened for 14 commonly circulating respiratory viruses. To investigate the efficiency of virus isolation from EBC, a nasal swab was taken in parallel from a subset of volunteers. The combined use of the ECoVent device with the RTube™ allowed the registration of the exhaled volume and breathing frequency during collection. In this way, the number of exhaled viral particles per liter air or per minute can theoretically be estimated.ResultsViral screening resulted in the detection of 4 different viruses in EBC and/or nasal swabs: Rhinovirus, Human Respiratory Syncytial Virus B, Influenza A and Influenza B. Rhinovirus was detected in 6 EBCs and 1 EBC was Influenza B positive. We report a viral detection rate of 7% for the EBCs, which is much lower than the detection rate of 46.8% observed using nasal swabs.ConclusionAlthough very promising, EBC collection using the RTube™ is not reliable for diagnosis of respiratory infections.
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Project description:Exhaled breath condensate (EBC) is routinely collected and analyzed in breath research. Because it contains aerosol droplets, EBC samples from SARS-CoV-2 infected individuals harbor the virus and pose the threat of infectious exposure. We report for the first time a safe and consistent method to fully inactivate SARS-CoV-2 in EBC samples and make EBC samples safe for processing and analysis. EBC samples containing infectious SARS-CoV-2 were treated with several concentrations of acetonitrile. The most commonly used 10% acetonitrile treatment for EBC processing failed to completely inactivate the virus in samples and viable virus was detected by the assay of SARS-CoV-2 infection of Vero E6 cells in a biosafety level 3 laboratory. Treatment with either 50% or 90% acetonitrile was effective to completely inactivate the virus, resulting in safe, non-infectious EBC samples that can be used for metabolomic analysis. Our study provides SARS-CoV-2 inactivation protocol for the collection and processing of EBC samples in the clinical setting and for advancing to metabolic assessments in health and disease.
| S-EPMC9809239 | biostudies-literature
Project description:The growing use of 3D printing in the biomedical sciences demonstrates its utility for a wide range of research and healthcare applications, including its potential implementation in the discipline of breath analysis to overcome current limitations and substantial costs of commercial breath sampling interfaces. This technical note reports on the design and construction of a 3D-printed mouthpiece adapter for sampling exhaled breath using the commercial respiration collector for in-vitro analysis (ReCIVA) device. The paper presents the design and digital workflow transition of the adapter and its fabrication from three commercial resins (Surgical Guide, Tough v5, and BioMed Clear) using a Formlabs Form 3B stereolithography (SLA) printer. The use of the mouthpiece adapter in conjunction with a pulmonary function filter is appraised in comparison to the conventional commercial silicon facemask sampling interface. Besides its lower cost - investment cost of the printing equipment notwithstanding - the 3D-printed adapter has several benefits, including ensuring breath sampling via the mouth, reducing the likelihood of direct contact of the patient with the breath sampling tubes, and being autoclaveable to enable the repeated use of a single adapter, thereby reducing waste and associated environmental burden compared to current one-way disposable facemasks. The novel adapter for breath sampling presented in this technical note represents an additional field of application for 3D printing that further demonstrates its widespread applicability in biomedicine.
| S-EPMC9364600 | biostudies-literature
Project description:BackgroundNew technologies with novel and ambitious approaches are being developed to diagnose or screen for SARS-CoV-2, including breath tests. The US FDA approved the first breath test for COVID-19 under emergency use authorization in April 2022. Most breath-based assays measure volatile metabolites exhaled by persons to identify a host response to infection. We hypothesized that the breathprint of COVID-19 fluctuated after Omicron became the primary variant of transmission over the Delta variant.MethodsWe collected breath samples from 142 persons with and without a confirmed COVID-19 infection during the Delta and Omicron waves. Breath samples were analyzed by gas chromatography-mass spectrometry.ResultsHere we show that based on 63 exhaled compounds, a general COVID-19 model had an accuracy of 0.73 ± 0.06, which improved to 0.82 ± 0.12 when modeling only the Delta wave, and 0.84 ± 0.06 for the Omicron wave. The specificity improved for the Delta and Omicron models (0.79 ± 0.21 and 0.74 ± 0.12, respectively) relative to the general model (0.61 ± 0.13).ConclusionsWe report that the volatile signature of COVID-19 in breath differs between the Delta-predominant and Omicron-predominant variant waves, and accuracies improve when samples from these waves are modeled separately rather than as one universal approach. Our findings have important implications for groups developing breath-based assays for COVID-19 and other respiratory pathogens, as the host response to infection may significantly differ depending on variants or subtypes.
| S-EPMC9731983 | biostudies-literature