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

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.

Bibliographic Details

Main Authors:	Goya, Stephanie, Sosa, Ezequiel Jorge, Nabaes Jodar, Mercedes Soledad, Torres, Carolina, Konig, Guido Alberto, Acuña, Dolores, Ceballos, Santiago, Distefano, Ana Julia, Dopazo, Hernán, Dus Santos, Maria Jose, Fass, Monica Irinia, Fernandez Do Porto, Darío Augusto, Fernandez, Ailen, Gallego, Fernando, Gismondi, Maria Ines, Gramundi, Ivan, Lusso, Silvina, Marti, Marcelo Adrián, Mazzeo, Melina, Mistchenko, Alicia Susana, Muñoz Hidalgo, Marianne Graziel, Natale, Mónica, Nardi, Cristina, Ousset, Julia, Peralta, Andrea Veronica, Pintos, Carolina, Puebla, Andrea Fabiana, Pianciola, Luis, Rivarola, Maximo Lisandro, Turjanski, Adrián, Valinotto, Laura, Vera, Pablo Alfredo, Zaiat, Jonathan, Zubrycki, Jeremias Enrique, Aulicino, Paula, Viegas, Mariana
Format:	info:ar-repo/semantics/artículo biblioteca
Language:	eng
Published:	Elsevier 2023-02
Subjects:	Severe Acute Respiratory Syndrome Coronavirus 2, Bioinformatics, Viruses, Coronavirus del Síndrome Respiratorio Agudo Grave 2, Bioinformática, Virus, Coinfection, Intra-host Evolution, Coinfección, Evolución Intrahospedador,
Online Access:	http://hdl.handle.net/20.500.12123/15828 https://www.sciencedirect.com/science/article/pii/S0168170222003641 https://doi.org/10.1016/j.virusres.2022.199035
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