Mining genomic repositories to further our knowledge of the extent of SARS-CoV-2 co-infections.

Abstract

Recombination events between Delta and Omicron SARS-CoV-2 lineages highlight the need for co-infection research. Existing studies focus on late-phase co-infections, with few examining earlier pandemic stages. This new study aims to globally identify and characterize co-infections using a bioinformatic pipeline to analyse genomic data from diverse locations and pandemic phases. Among 26988 high-quality SARS-CoV-2 isolates from 11 diverse project databases, we identified 141 potential co-infection cases (0.52%), surpassing previous prevalence estimates. These co-infections were observed throughout the pandemic timeline, with an increase noted after the emergence of the Omicron variant. Co-infections involving the Omicron variant were the most prevalent, potentially influenced by the high level of diversity within this lineage and its impact on the viral landscape. Additionally, we found co-infections involving the pre-Alpha/Alpha lineages, which have been rarely described, raising possibilities of contributing to new lineage emergence through recombination events. The analysis revealed co-infection cases involving both different and the same lineages/sublineages. Our study showcases the potential of our pipeline to leverage valuable information stored in global sequence repositories, advancing our understanding of SARS-CoV-2 co-infections. The prevalence of co-infections highlights the importance of monitoring viral diversity and its potential implications on disease dynamics. Integrating clinical data with genomic findings can further shed light on the clinical implications and outcomes of co-infections.