Genome-wide diversity of Zika virus: Exploring spatio-temporal dynamics to guide a new nomenclature proposal

Author:

Seabra Sofia G1ORCID,Libin Pieter J K234,Theys Kristof3,Zhukova Anna56,Potter Barney I3ORCID,Nebenzahl-Guimaraes Hanna1,Gorbalenya Alexander E78,Sidorov Igor A7,Pimentel Victor1,Pingarilho Marta1,de Vasconcelos Ana T R9ORCID,Dellicour Simon310,Khouri Ricardo311ORCID,Gascuel Olivier512,Vandamme Anne-Mieke13ORCID,Baele Guy3ORCID,Cuypers Lize13,Abecasis Ana B1

Affiliation:

1. Global Health and Tropical Medicine (GHTM), Instituto de Higiene e Medicina Tropical (IHMT), Universidade Nova de Lisboa (UNL), Rua da Junqueira 100, Lisboa 1349-008, Portugal

2. Department of Computer Science, Artificial Intelligence Lab, Vrije Universiteit Brussel, Brussels 1050, Belgium

3. Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Clinical and Epidemiological Virology, KU Leuven, Herestraat 49 - box 1030, Leuven 3000, Belgium

4. Data Science Institute, I-Biostat, Hasselt University, Agoralaan Gebouw D, Diepenbeek 3590, Belgium

5. Institut Pasteur, Université Paris Cité, Unité Bioinformatique Evolutive, 25-28 rue du Dr Roux, Paris F-75015, France

6. Institut Pasteur, Université Paris Cité, Bioinformatics and Biostatistics Hub, 25-28 rue du Dr Roux, Paris F-75015, France

7. Department of Medical Microbiology, Leiden University Medical Center, Postbus 9600, Leiden 2300 RC, The Netherlands

8. Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow 119899, Russia

9. National Laboratory for Scientific Computing, Av. Getulio Vargas, 333, Quitandinha, Petrópolis, Rio de Janeiro 25651-075, Brazil

10. Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, CP 264/3, 50 av. F.D. Roosevelt, Bruxelles B-1050, Belgium

11. Instituto Gonçalo Moniz, Fundação Oswaldo Cruz/MS, Salvador, Bahia 40296-710, Brazil

12. Institut de Systématique, Evolution, Biodiversité (UMR7205 - CNRS, MNHN, SU, EPHE, UA), Muséum National d’Histoire Naturelle, CP 50, 45 rue Buffon, Paris 75005, France

13. Department of Laboratory Medicine, University Hospitals Leuven, Herestraat 49, Leuven 3000, Belgium

Abstract

Abstract The Zika virus (ZIKV) disease caused a public health emergency of international concern that started in February 2016. The overall number of ZIKV-related cases increased until November 2016, after which it declined sharply. While the evaluation of the potential risk and impact of future arbovirus epidemics remains challenging, intensified surveillance efforts along with a scale-up of ZIKV whole-genome sequencing provide an opportunity to understand the patterns of genetic diversity, evolution, and spread of ZIKV. However, a classification system that reflects the true extent of ZIKV genetic variation is lacking. Our objective was to characterize ZIKV genetic diversity and phylodynamics, identify genomic footprints of differentiation patterns, and propose a dynamic classification system that reflects its divergence levels. We analysed a curated dataset of 762 publicly available sequences spanning the full-length coding region of ZIKV from across its geographical span and collected between 1947 and 2021. The definition of genetic groups was based on comprehensive evolutionary dynamics analyses, which included recombination and phylogenetic analyses, within- and between-group pairwise genetic distances comparison, detection of selective pressure, and clustering analyses. Evidence for potential recombination events was detected in a few sequences. However, we argue that these events are likely due to sequencing errors as proposed in previous studies. There was evidence of strong purifying selection, widespread across the genome, as also detected for other arboviruses. A total of 50 sites showed evidence of positive selection, and for a few of these sites, there was amino acid (AA) differentiation between genetic clusters. Two main genetic clusters were defined, ZA and ZB, which correspond to the already characterized ‘African’ and ‘Asian’ genotypes, respectively. Within ZB, two subgroups, ZB.1 and ZB.2, represent the Asiatic and the American (and Oceania) lineages, respectively. ZB.1 is further subdivided into ZB.1.0 (a basal Malaysia sequence sampled in the 1960s and a recent Indian sequence), ZB.1.1 (South-Eastern Asia, Southern Asia, and Micronesia sequences), and ZB.1.2 (very similar sequences from the outbreak in Singapore). ZB.2 is subdivided into ZB.2.0 (basal American sequences and the sequences from French Polynesia, the putative origin of South America introduction), ZB.2.1 (Central America), and ZB.2.2 (Caribbean and North America). This classification system does not use geographical references and is flexible to accommodate potential future lineages. It will be a helpful tool for studies that involve analyses of ZIKV genomic variation and its association with pathogenicity and serve as a starting point for the public health surveillance and response to on-going and future epidemics and to outbreaks that lead to the emergence of new variants.

Funder

Fonds voor Wetenschappelijk Onderzoek

Internal Fondsen KU Leuven/Internal Funds KU Leuven

Flemish Government

Fundação para a Ciência e a Tecnologia

Fonds de la Recherche Scientifique

European Union’s Horizon 2020 research and innovation program ZIKAlliance

Research council of the Vrije Universiteit Brussel

Publisher

Oxford University Press (OUP)

Subject

Virology,Microbiology

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