Dataset Information

Assessing the hidden diversity underlying consensus sequences of SARS-CoV-2 using VICOS, a novel bioinformatic pipeline for identification of mixed viral populations.

ABSTRACT:

Introduction

Coinfection with two SARS-CoV-2 viruses is still a very understudied phenomenon. Although next generation sequencing methods are very sensitive to detect heterogeneous viral populations in a sample, there is no standardized method for their characterization, so their clinical and epidemiological importance is unknown.

Material and methods

We developed VICOS (Viral COinfection Surveillance), a new bioinformatic algorithm for variant calling, filtering and statistical analysis to identify samples suspected of being mixed SARS-CoV-2 populations from a large dataset in the framework of a community genomic surveillance. VICOS was used to detect SARS-CoV-2 coinfections in a dataset of 1,097 complete genomes collected between March 2020 and August 2021 in Argentina.

Results

We detected 23 cases (2%) of SARS-CoV-2 coinfections. Detailed study of VICOS's results together with additional phylogenetic analysis revealed 3 cases of coinfections by two viruses of the same lineage, 2 cases by viruses of different genetic lineages, 13 were compatible with both coinfection and intra-host evolution, and 5 cases were likely a product of laboratory contamination.

Discussion

Intra-sample viral diversity provides important information to understand the transmission dynamics of SARS-CoV-2. Advanced bioinformatics tools, such as VICOS, are a necessary resource to help unveil the hidden diversity of SARS-CoV-2.

SUBMITTER: Goya S

PROVIDER: S-EPMC9795804 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Publications

Assessing the hidden diversity underlying consensus sequences of SARS-CoV-2 using VICOS, a novel bioinformatic pipeline for identification of mixed viral populations.

Goya Stephanie S Sosa Ezequiel E Nabaes Jodar Mercedes M Torres Carolina C König Guido G Acuña Dolores D Ceballos Santiago S Distéfano Ana J AJ Dopazo Hernán H Dus Santos María M Fass Mónica M Fernández Do Porto Darío D Fernández Ailen A Gallego Fernando F Gismondi María I MI Gramundi Ivan I Lusso Silvina S Martí Marcelo M Mazzeo Melina M Mistchenko Alicia S AS Muñoz Hidalgo Marianne M Natale Mónica M Nardi Cristina C Ousset Julia J Peralta Andrea V AV Pintos Carolina C Puebla Andrea F AF Pianciola Luis L Rivarola Máximo M Turjanski Adrian A Valinotto Laura L Vera Pablo A PA Zaiat Jonathan J Zubrycki Jeremías J Aulicino Paula P Viegas Mariana M

Virus research 20221228

<h4>Introduction</h4>Coinfection with two SARS-CoV-2 viruses is still a very understudied phenomenon. Although next generation sequencing methods are very sensitive to detect heterogeneous viral populations in a sample, there is no standardized method for their characterization, so their clinical and epidemiological importance is unknown.<h4>Material and methods</h4>We developed VICOS (Viral COinfection Surveillance), a new bioinformatic algorithm for variant calling, filtering and statistical a ...[more]

PMID: 36586487

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Dataset Information

Assessing the hidden diversity underlying consensus sequences of SARS-CoV-2 using VICOS, a novel bioinformatic pipeline for identification of mixed viral populations.

Introduction

Material and methods

Results

Discussion

Publications

Assessing the hidden diversity underlying consensus sequences of SARS-CoV-2 using VICOS, a novel bioinformatic pipeline for identification of mixed viral populations.

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