Your browser doesn't support javascript.
ABSTRACT
The SARS-CoV-2 has infected almost 200 million people worldwide by July 2021 and the pandemic has been characterized by infection waves of viral lineages showing distinct fitness profiles. The simultaneous infection of a single individual by two distinct SARS-CoV-2 lineages provides a window of opportunity for viral recombination and the emergence of new lineages with differential phenotype. Several hundred SARS-CoV-2 lineages are currently well characterized but two main factors have precluded major coinfection/codetection analysis thus far i) the low diversity of SARS-CoV-2 lineages during the first year of the pandemic which limited the identification of lineage defining mutations necessary to distinguish coinfecting viral lineages; and the ii) limited availability of raw sequencing data where abundance and distribution of intrasample/intrahost variability can be accessed. Here, we have put together a large sequencing dataset from Brazilian samples covering a period of 18 May 2020 to 30 April 2021 and probed it for unexpected patterns of high intrasample/intrahost variability. It enabled us to detect nine cases of SARS-CoV-2 coinfection with well characterized lineage-defining mutations. In addition, we matched these SARS-CoV-2 coinfections with spatio-temporal epidemiological data confirming their plausibility with the co-circulating lineages at the timeframe investigated. These coinfections represent around 0.61% of all samples investigated. Although our data suggests that coinfection with distinct SARS-CoV-2 lineages is a rare phenomenon, it is likely an underestimation and coinfection rates warrants further investigation. DATA SUMMARYThe raw fastq data of codetection cases are deposited on gisaid.org and correlated to gisaid codes EPI_ISL_1068258, EPI_ISL_2491769, EPI_ISL_2491781, EPI_ISL_2645599, EPI_ISL_2661789, EPI_ISL_2661931, EPI_ISL_2677092, EPI_ISL_2777552, EPI_ISL_3869215. Supplementary data are available on https//doi.org/10.6084/m9.figshare.16570602.v1. The workflow code used in this study is publicly available on https//github.com/dezordi/IAM_SARSCOV2.
Subject(s)

Full text: Available Collection: Preprints Database: medRxiv Main subject: Coinfection Language: English Year: 2021 Document Type: Preprint

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: Preprints Database: medRxiv Main subject: Coinfection Language: English Year: 2021 Document Type: Preprint