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. 2025 Aug 29;17(9):1189.
doi: 10.3390/v17091189.

Molecular Epidemiology of SARS-CoV-2 Detected from Different Areas of the Kandy District of Sri Lanka from November 2020-March 2022

Affiliations

Molecular Epidemiology of SARS-CoV-2 Detected from Different Areas of the Kandy District of Sri Lanka from November 2020-March 2022

Bushran N Iqbal et al. Viruses. .

Abstract

A comprehensive analysis of the molecular epidemiology of SARS-CoV-2 in the Kandy District of Sri Lanka from November 2020 to March 2022 was conducted to address the limited genomic surveillance data available across the country. The study investigated the circulating SARS-CoV-2 lineages, their temporal dynamics, and the associated mutational profiles in the study area. A total of 280 SARS-CoV-2-positive samples were selected, and 252 complete genomes were successfully sequenced using Oxford Nanopore Technology. Lineage classification was performed using the EPI2ME tool, while phylogenetic relationships were inferred through maximum likelihood and time-scaled phylogenetic trees using IQ-TREE2 and BEAST, respectively. Amino acid substitutions were analyzed to understand lineage-specific mutation patterns. Fifteen SARS-CoV-2 lineages were identified, and of those B.1.411 (36%) was the most prevalent, followed by Q.8 (21%), AY.28 (9.5%), and the Delta and Omicron variants. The lineage distribution showed a temporal shift from B.1.411 to Alpha, Delta, and finally the Omicron, mirroring the global trends. Time to the most recent common ancestor analyses provided estimates for the introduction of major variants, while mutation analysis revealed the widespread occurrence of D614G in the spike protein and lineage-specific mutations across structural, non-structural, and accessory proteins.Detection of the Epsilon variant (absent in other national-level studies) in November 2020, highlighted the regional heterogeneity viral spread. This study emphasizes the importance of localized genomic surveillance to capture the true diversity and evolution of SARS-CoV-2, to facilitate containment strategies in resource-limited settings.

Keywords: Kandy district; SARS-CoV-2 infection; Sri Lanka; mutation profile; phylogenetic analysis.

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Conflict of interest statement

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
Distribution of SARS-CoV-2 lineages in the study area between November 2020 and March 2022.
Figure 2
Figure 2
Bayesian time-scale phylogeny of SARS CoV-2 from the Kandy District. Tips are coloured by the sample location, and the external layer on the right shows the sample lineages.
Figure 3
Figure 3
Phylogenetic analysis of Sri Lankan sequences from the study area in a global context. Maximum likelihood tree of 243 Sri Lankan sequences from the study area and 3363 representative global sequences obtained from GISAID and NCB. The tips are coloured by Sri Lankan lineages, and the external layer indicates the regions from where the representative samples are taken.
Figure 4
Figure 4
Comparison of amino acid mutations in the structural proteins of (A) B.1, B.1.411, B.1.427, and B.1.428 lineages, (B) of B.1.1, B.1.1.7, and Q.8 lineages, (C) Delta variant and its sublineages, and (D) Omicron variant and its sublineages circulated in the study area.
Figure 5
Figure 5
Comparison of amino acid mutations in the non-structural proteins of (A) B.1, B.1.411, B.1.427, and B.1.428 lineages, (B) of B.1.1, B.1.1.7, and Q.8 lineages, (C) Delta variant and its sublineages, and (D) Omicron variant and its sublineages circulated in the study area.
Figure 6
Figure 6
Comparison of amino acid mutations in the accessory proteins of (A) B.1, B.1.411, B.1.427, and B.1.428 lineages, (B) of B.1.1, B.1.1.7 and Q.8 lineages, (C) Delta variant and its sublineages, and (D) Omicron variant and its sublineages circulated in the study area.

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