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.
Reviewing Editor
- Diane M Harper, University of Michigan, United States
Version history
- Preprint posted: July 5, 2022 (view preprint)
- Received: July 21, 2022
- Accepted: July 23, 2023
- Accepted Manuscript published: July 27, 2023 (version 1)
- Version of Record published: August 16, 2023 (version 2)
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.
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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
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- Epidemiology and Global Health
Background:
The Zanzibar archipelago of Tanzania has become a low-transmission area for Plasmodium falciparum. Despite being considered an area of pre-elimination for years, achieving elimination has been difficult, likely due to a combination of imported infections from mainland Tanzania and continued local transmission.
Methods:
To shed light on these sources of transmission, we applied highly multiplexed genotyping utilizing molecular inversion probes to characterize the genetic relatedness of 282 P. falciparum isolates collected across Zanzibar and in Bagamoyo district on the coastal mainland from 2016 to 2018.
Results:
Overall, parasite populations on the coastal mainland and Zanzibar archipelago remain highly related. However, parasite isolates from Zanzibar exhibit population microstructure due to the rapid decay of parasite relatedness over very short distances. This, along with highly related pairs within shehias, suggests ongoing low-level local transmission. We also identified highly related parasites across shehias that reflect human mobility on the main island of Unguja and identified a cluster of highly related parasites, suggestive of an outbreak, in the Micheweni district on Pemba island. Parasites in asymptomatic infections demonstrated higher complexity of infection than those in symptomatic infections, but have similar core genomes.
Conclusions:
Our data support importation as a main source of genetic diversity and contribution to the parasite population in Zanzibar, but they also show local outbreak clusters where targeted interventions are essential to block local transmission. These results highlight the need for preventive measures against imported malaria and enhanced control measures in areas that remain receptive to malaria reemergence due to susceptible hosts and competent vectors.
Funding:
This research was funded by the National Institutes of Health, grants R01AI121558, R01AI137395, R01AI155730, F30AI143172, and K24AI134990. Funding was also contributed from the Swedish Research Council, Erling-Persson Family Foundation, and the Yang Fund. RV acknowledges funding from the MRC Centre for Global Infectious Disease Analysis (reference MR/R015600/1), jointly funded by the UK Medical Research Council (MRC) and the UK Foreign, Commonwealth & Development Office (FCDO), under the MRC/FCDO Concordat agreement and is also part of the EDCTP2 program supported by the European Union. RV also acknowledges funding by Community Jameel.
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- Computational and Systems Biology
- Epidemiology and Global Health
The chemical composition of foods is complex, variable, and dependent on many factors. This has a major impact on nutrition research as it foundationally affects our ability to adequately assess the actual intake of nutrients and other compounds. In spite of this, accurate data on nutrient intake are key for investigating the associations and causal relationships between intake, health, and disease risk at the service of developing evidence-based dietary guidance that enables improvements in population health. Here, we exemplify the importance of this challenge by investigating the impact of food content variability on nutrition research using three bioactives as model: flavan-3-ols, (–)-epicatechin, and nitrate. Our results show that common approaches aimed at addressing the high compositional variability of even the same foods impede the accurate assessment of nutrient intake generally. This suggests that the results of many nutrition studies using food composition data are potentially unreliable and carry greater limitations than commonly appreciated, consequently resulting in dietary recommendations with significant limitations and unreliable impact on public health. Thus, current challenges related to nutrient intake assessments need to be addressed and mitigated by the development of improved dietary assessment methods involving the use of nutritional biomarkers.
