ACE2 and TMPRSS2 SARS-CoV-2 infectivity genes: deep mutational scanning and characterization of missense variants. Issue 24 (21st July 2022)

• Record Type: Journal Article
• Authors: Zhang, Lingxin; Sarangi, Vivekananda; Liu, Duan; Ho, Ming-Fen; Grassi, Angela R; Wei, Lixuan; Moon, Irene; Vierkant, Robert A; Larson, Nicholas B; Lazaridis, Konstantinos N; Athreya, Arjun P; Wang, Liewei; Weinshilboum, Richard
• Is Part Of: Human molecular genetics. Volume 31:Issue 24(2022)
• Page Start: 4183
• Page End: 4192
• Publication Date: 2022-07-21
• Subjects: Human molecular genetics -- Periodicals; Human chromosome abnormalities -- Periodicals; 572.8
• DOI: 10.1093/hmg/ddac157
• Languages: English
• ISSNs: 0964-6906

Abstract

Abstract: The human angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) proteins play key roles in the cellular internalization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the coronavirus responsible for the coronavirus disease of 2019 (COVID-19) pandemic. We set out to functionally characterize the ACE2 and TMPRSS2 protein abundance for variant alleles encoding these proteins that contained non-synonymous single-nucleotide polymorphisms (nsSNPs) in their open reading frames (ORFs). Specifically, a high-throughput assay, deep mutational scanning (DMS), was employed to test the functional implications of nsSNPs, which are variants of uncertain significance in these two genes. Specifically, we used a 'landing pad' system designed to quantify the protein expression for 433 nsSNPs that have been observed in the ACE2 and TMPRSS2 ORFs and found that 8 of 127 ACE2, 19 of 157 TMPRSS2 isoform 1 and 13 of 149 TMPRSS2 isoform 2 variant proteins displayed less than ~25% of the wild-type protein expression, whereas 4 ACE2 variants displayed 25% or greater increases in protein expression. As a result, we concluded that nsSNPs in genes encoding ACE2 and TMPRSS2 might potentially influence SARS-CoV-2 infectivity. These results can now be applied to DNA sequence data for patients infected with SARS-CoV-2 to determine the possible impact of patient-based DNA sequence variation on the clinical course of SARS-CoV-2 infection.