Comparing the evolutionary dynamics of predominant SARS-CoV-2 virus lineages co-circulating in Mexico
- Consejo Nacional de Ciencia y Tecnología, Mexico
- CINVESTAV-Unidad Irapuato, Mexico
- University of Oxford, United Kingdom
- KU Leuven, Belgium
- Instituto Nacional de Enfermedades Respiratorias, Mexico
- Instituto Nacional de Medicina Genómica, Mexico
- Astronomer LTD, Mexico
- Universidad Nacional Autónoma de México, Mexico
- CINVESTAV-IPN, Mexico
- Instituto Mexicano del Seguro Social, Mexico
- Universidad Autónoma de San Luis Potosí, Mexico
- Unidad Regional Mazatlán en Acuicultura y Manejo Ambiental, Mexico
- Universidad Autónoma de la Ciudad de México, Mexico
- Universidad Nacional Autónoma de Méxic, Mexico
Abstract
Over 200 different SARS-CoV-2 lineages have been observed in Mexico by November 2021. To investigate lineage replacement dynamics, we applied a phylodynamic approach and explored the evolutionary trajectories of five dominant lineages that circulated during the first year of local transmission. For most lineages, peaks in sampling frequencies coincided with different epidemiological waves of infection in Mexico. Lineages B.1.1.222 and B.1.1.519 exhibited similar dynamics, constituting clades that likely originated in Mexico and persisted for >12 months. Lineages B.1.1.7, P.1 and B.1.617.2 also displayed similar dynamics, characterized by multiple introduction events leading to a few successful extended local transmission chains that persisted for several months. For the largest B.1.617.2 clades, we further explored viral lineage movements across Mexico. Many clades were located within the south region of the country, suggesting that this area played a key role in the spread of SARS-CoV-2 in Mexico.
Data availability
Virus genome IDs and GISAID accession numbers for the sequences used in each dataset are provided in the Supplementary file 1 file. All genomic and epidemiological data supporting the findings of this study is publicly available from GISAID/GenBank, from the Ministry Of Health Mexico102, and/or from the 'Our World in Data' coronavirus pandemic web portal 29. For the GISAID data used, the corresponding acknowledgement table is available on the 'GISAID Data Acknowledgement Locator' under the EPI_SET_20220405qd and EPI_SET_20220215at keys 49. Our bioinformatic pipeline implementing a migration data and phylogenetically-informed sequence subsampling approach is publicly available at https://github.com/rhysinward/Mexico_subsampling.
Article and author information
Author details
José Esteban Muñoz-Medina
Marina Escalera Zamudio
Funding
FNRS (F.4515.22)
- Simon Dellicour
UNAM (DGAPA-PAPIIT (IN214421)
- Antonio Lazcano
UNAM (DGAPA-PAPIME (PE204921))
- Antonio Lazcano
Research Foundation Flanders (G098321N)
- Simon Dellicour
European Horizon 2020 project MOOD (874850)
- Simon Dellicour
Leverhulme Trust (ECF-2019-542)
- Marina Escalera Zamudio
European Horizon 2020 project MOOD (874850)
- Oliver Pybus
European Horizon 2020 project MOOD (874850)
- Moritz U G Kraemer
CONACyT Vigilancia Genómica del Virus SARS-CoV-2 en México-2022"" (PP-F003)
- Carlos F Arias
Ministry of Education, Science, Technology and Innovation of Mexico City (057)
- Carlos F Arias
AHF Global Public Health Institute at the University of Miami (Genomic surveillance for SARS-CoV-2 variants in Mexico"")
- Carlos F Arias
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2023, Castelán-Sánchez et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 1,191
- views
-
- 223
- downloads
-
- 7
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Comparing the evolutionary dynamics of predominant SARS-CoV-2 virus lineages co-circulating in Mexico
eLife 12:e82069.
https://doi.org/10.7554/eLife.82069
Further reading
-
- Epidemiology and Global Health
- Microbiology and Infectious Disease
Several areas of the world suffer a notably high incidence of Shiga toxin-producing Escherichia coli. To assess the impact of persistent cross-species transmission systems on the epidemiology of E. coli O157:H7 in Alberta, Canada, we sequenced and assembled E. coli O157:H7 isolates originating from collocated cattle and human populations, 2007–2015. We constructed a timed phylogeny using BEAST2 using a structured coalescent model. We then extended the tree with human isolates through 2019 to assess the long-term disease impact of locally persistent lineages. During 2007–2015, we estimated that 88.5% of human lineages arose from cattle lineages. We identified 11 persistent lineages local to Alberta, which were associated with 38.0% (95% CI 29.3%, 47.3%) of human isolates. During the later period, six locally persistent lineages continued to be associated with human illness, including 74.7% (95% CI 68.3%, 80.3%) of reported cases in 2018 and 2019. Our study identified multiple locally evolving lineages transmitted between cattle and humans persistently associated with E. coli O157:H7 illnesses for up to 13 y. Locally persistent lineages may be a principal cause of the high incidence of E. coli O157:H7 in locations such as Alberta and provide opportunities for focused control efforts.
-
- Epidemiology and Global Health
Given the rapid cross-country spread of SARS-CoV-2 and the resulting difficulty in tracking lineage spread, we investigated the potential of combining mobile service data and fine-granular metadata (such as postal codes and genomic data) to advance integrated genomic surveillance of the pandemic in the federal state of Thuringia, Germany. We sequenced over 6500 SARS-CoV-2 Alpha genomes (B.1.1.7) across 7 months within Thuringia while collecting patients’ isolation dates and postal codes. Our dataset is complemented by over 66,000 publicly available German Alpha genomes and mobile service data for Thuringia. We identified the existence and spread of nine persistent mutation variants within the Alpha lineage, seven of which formed separate phylogenetic clusters with different spreading patterns in Thuringia. The remaining two are subclusters. Mobile service data can indicate these clusters’ spread and highlight a potential sampling bias, especially of low-prevalence variants. Thereby, mobile service data can be used either retrospectively to assess surveillance coverage and efficiency from already collected data or to actively guide part of a surveillance sampling process to districts where these variants are expected to emerge. The latter concept was successfully implemented as a proof-of-concept for a mobility-guided sampling strategy in response to the surveillance of Omicron sublineage BQ.1.1. The combination of mobile service data and SARS-CoV-2 surveillance by genome sequencing is a valuable tool for more targeted and responsive surveillance.
