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. 2023 Nov 5;11(11):2711.
doi: 10.3390/microorganisms11112711.

Characterization of SARS-CoV-2 Variants in Military and Civilian Personnel of an Air Force Airport during Three Pandemic Waves in Italy

Affiliations

Characterization of SARS-CoV-2 Variants in Military and Civilian Personnel of an Air Force Airport during Three Pandemic Waves in Italy

Michele Equestre et al. Microorganisms. .

Abstract

We investigated SARS-CoV-2 variants circulating, from November 2020 to March 2022, among military and civilian personnel at an Air Force airport in Italy in order to classify viral isolates in a potential hotspot for virus spread. Positive samples were subjected to Next-Generation Sequencing (NGS) of the whole viral genome and Sanger sequencing of the spike coding region. Phylogenetic analysis classified viral isolates and traced their evolutionary relationships. Clusters were identified using 70% cut-off. Sequencing methods yielded comparable results in terms of variant classification. In 2020 and 2021, we identified several variants, including B.1.258 (4/67), B.1.177 (9/67), Alpha (B.1.1.7, 9/67), Gamma (P.1.1, 4/67), and Delta (4/67). In 2022, only Omicron and its sub-lineage variants were observed (37/67). SARS-CoV-2 isolates were screened to detect naturally occurring resistance in genomic regions, the target of new therapies, comparing them to the Wuhan Hu-1 reference strain. Interestingly, 2/30 non-Omicron isolates carried the G15S 3CLpro substitution responsible for reduced susceptibility to protease inhibitors. On the other hand, Omicron isolates carried unusual substitutions A1803V, D1809N, and A949T on PLpro, and the D216N on 3CLpro. Finally, the P323L substitution on RdRp coding regions was not associated with the mutational pattern related to polymerase inhibitor resistance. This study highlights the importance of continuous genomic surveillance to monitor SARS-CoV-2 evolution in the general population, as well as in restricted communities.

Keywords: 3CLpro; Next-Generation Sequencing; Plpro; RdRp; SARS-CoV-2 variant; Sanger; mutations; nucleocapsid; spike.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Study design. NPSs, nasopharyngeal swabs; NAAT, Nucleic Acid Amplification; NGS, Next-Generation Sequencing.
Figure 2
Figure 2
SARS-CoV-2 variants dynamic distribution between December 2020 and March 2022 in the military airport. The colors identify the different SARS-CoV-2 variants during the time span.
Figure 3
Figure 3
(A) SARS-CoV-2 whole genome length. (B) Polyprotein subdivided in structural and non-structural proteins. (C) Amino acid substitutions of non-Omicron variants and their sub-lineages were reported for each variant with a different color according to the viral isolates (little square). The * symbol identified the stop codon.
Figure 4
Figure 4
(A) SARS-CoV-2 whole genome length. (B) Polyprotein subdivided in structural and non-structural proteins. (C) Amino acid substitutions of Omicron VOC and its sub-lineages were reported for each variant with a different color according to the viral isolates (little square). The * symbol identified the stop codon.
Figure 5
Figure 5
ML phylogenetic tree was estimated using 17 reference sequences and 67 SARS-CoV-2 newly generated sequences. The reliability of the phylogenetic clustering was evaluated using bootstrap analysis with 1000 replicates. The bootstrap support values > 70% are shown. The scale bar at the bottom of the figure represents genetic distance. The colors identify the several clusters of SARS-CoV-2 variants. The circles show the newly generated sequences, while the squares the reference sequences.

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