Cargando…

Establishing a mass spectrometry-based system for rapid detection of SARS-CoV-2 in large clinical sample cohorts

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 nucleoprotei...

Descripción completa

Detalles Bibliográficos
Autores principales: Cardozo, Karina Helena Morais, Lebkuchen, Adriana, Okai, Guilherme Gonçalves, Schuch, Rodrigo Andrade, Viana, Luciana Godoy, Olive, Aline Nogueira, Lazari, Carolina dos Santos, Fraga, Ana Maria, Granato, Celso Francisco Hernandes, Pintão, Maria Carolina Tostes, Carvalho, Valdemir Melechco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7713649/
https://www.ncbi.nlm.nih.gov/pubmed/33273458
http://dx.doi.org/10.1038/s41467-020-19925-0
Descripción
Sumario: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.