Rapid Detection of SARS-CoV-2 Variants of Concern by Genomic Surveillance Techniques

Paul C Guest; Steve F C Hawkins; Hassan Rahmoune

doi:10.1007/978-3-031-28012-2_27

Rapid Detection of SARS-CoV-2 Variants of Concern by Genomic Surveillance Techniques

Adv Exp Med Biol. 2023:1412:491-509. doi: 10.1007/978-3-031-28012-2_27.

Authors

Paul C Guest^{1

2

3}, Steve F C Hawkins⁴, Hassan Rahmoune⁵

Affiliations

¹ Laboratory of Neuroproteomics, Department of Biochemistry and Tissue Biology, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil.
² Department of Psychiatry, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany.
³ Laboratory of Translational Psychiatry, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany.
⁴ Meridian Bioscience, Unit 16, The Edge Business Centre, London, UK.
⁵ Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK.

PMID: 37378785
DOI: 10.1007/978-3-031-28012-2_27

Abstract

This chapter describes the application of genomic, transcriptomic, proteomic, and metabolomic methods in the study of SARS-CoV-2 variants of concern. We also describe the important role of machine learning tools to identify the most significant biomarker signatures and discuss the latest point-of-care devices that can be used to translate these findings to the physician's office or to bedside care. The main emphasis is placed on increasing our diagnostic capacity and predictability of disease outcomes to guide the most appropriate treatment strategies.

Keywords: COVID-19; Diagnosis; Disease management; Lab-on-a-chip; POC; Point-of-care; SARS-COV-2.

MeSH terms

COVID-19* / diagnosis
COVID-19* / genetics
Genomics
Humans
Proteomics
SARS-CoV-2* / genetics

Supplementary concepts

SARS-CoV-2 variants