The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is pressing public health systems around the world, and large population testing is a key step to control this pandemic disease. Here, we develop a high-throughput targeted proteomics assay to detect SARS-CoV-2 nucleoprotein peptides directly from nasopharyngeal and oropharyngeal swabs. A modified magnetic particle-based proteomics approach implemented on a robotic liquid handler enables fully automated preparation of 96 samples within 4 hours. A TFC-MS system allows multiplexed analysis of 4 samples within 10 min, enabling the processing of more than 500 samples per day. We validate this method qualitatively (Tier 3) and quantitatively (Tier 1) using 985 specimens previously analyzed by real-time RT-PCR, and detect up to 84% of the positive cases with up to 97% specificity. The presented strategy has high sample stability and should be considered as an option for SARS-CoV-2 testing in large populations.
The use of metabolomic and lipidomic strategies for selecting potential biomarkers for obstructive sleep apnoea (OSA) has been little explored. We examined adult male patients with OSA (defined by an apnoea-hypopnoea index ≥15 events/hour), as well as age-, gender-, and fat-composition-matched volunteers without OSA. All subjects were subjected to clinical evaluation, sleep questionnaires for detecting the risk of OSA (Berlin and NoSAS score), metabolomic analysis by gas chromatography coupled to mass spectrometry and lipidomic analysis with liquid chromatography followed by detection by MALDI-MS. This study included 37 patients with OSA and 16 controls. From the 6 metabolites and 22 lipids initially selected, those with the best association with OSA were glutamic acid, deoxy sugar and arachidonic acid (metabolites), and glycerophosphoethanolamines, sphingomyelin and lyso-phosphocholines (lipids). For the questionnaires, the NoSAS score performed best with screening for OSA (area under the curve [AUC] = 0.724, p = 0.003). The combination of the NoSAS score with metabolites or lipids resulted in an AUC for detecting OSA of 0.911 and 0.951, respectively. In conclusion, metabolomic and lipidomic strategies suggested potential early biomarkers in OSA that could also be helpful in screening for this sleep disorder beyond traditional questionnaires.
The current outbreak of severe acute respiratory syndrome associated with coronavirus 2 (SARS-CoV-2) is pressing public health systems around the world, and large population testing is a key step to control this pandemic disease. Real-time reverse-transcription PCR (real-time RT-PCR) is the gold standard test for virus detection but the soaring demand for this test resulted in shortage of reagents and instruments, severely limiting its applicability to large-scale screening. To be used either as an alternative, or as a complement, to real-time RT-PCR testing, we developed a high-throughput targeted proteomics assay to detect SARS-CoV-2 proteins directly from clinical respiratory tract samples. Sample preparation was fully automated by using a modified magnetic particle-based proteomics approach implemented on a robotic liquid handler, enabling a fast processing of samples. The use of turbulent flow chromatography included four times multiplexed on-line sample cleanup and UPLC separation. MS/MS detection of three peptides from SARS-CoV-2 nucleoprotein and a 15N-labeled internal global standard was achieved within 2.5 min, enabling the analysis of more than 500 samples per day. The method was validated using 562 specimens previously analyzed by real-time RT-PCR and was able to detect over 83% of positive cases. No interference was found with samples from common respiratory viruses, including other coronaviruses (NL63, OC43, HKU1, and 229E). The strategy here presented has high sample stability and low cost and should be considered as an option to large population testing.
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