Rise and fall of SARS-CoV-2 variants in Rotterdam: Comparison of wastewater and clinical surveillance

Ray W. Izquierdo-Lara, Leo Heijnen, Bas B. Oude Munnink, Claudia M.E. Schapendonk, Goffe Elsinga, Jeroen Langeveld, Johan Post, Divyae K. Prasad, Christian Carrizosa, Frederic Been, Janko van Beek, Remy Schilperoort, Rianne Vriend, Ewout Fanoy, Evelien I.T. de Schepper, Reina S. Sikkema, Richard Molenkamp, Frank M. Aarestrup, Gertjan Medema, Marion P.G. KoopmansMiranda de Graaf*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

5 Citations (Scopus)

Abstract

Monitoring of SARS-CoV-2 in wastewater (WW) is a promising tool for epidemiological surveillance, correlating not only viral RNA levels with the infection dynamics within the population, but also to viral diversity. However, the complex mixture of viral lineages in WW samples makes tracking of specific variants or lineages circulating in the population a challenging task. We sequenced sewage samples of 9 WW-catchment areas within the city of Rotterdam, used specific signature mutations from individual SARS-CoV-2 lineages to estimate their relative abundances in WW and compared them against those observed in clinical genomic surveillance of infected individuals between September 2020 and December 2021. We showed that especially for dominant lineages, the median of the frequencies of signature mutations coincides with the occurrence of those lineages in Rotterdam's clinical genomic surveillance. This, along with digital droplet RT-PCR targeting signature mutations of specific variants of concern (VOCs), showed that several VOCs emerged, became dominant and were replaced by the next VOC in Rotterdam at different time points during the study. In addition, single nucleotide variant (SNV) analysis provided evidence that spatio-temporal clusters can also be discerned from WW samples. We were able to detect specific SNVs in sewage, including one resulting in the Q183H amino acid change in the Spike gene, that was not captured by clinical genomic surveillance. Our results highlight the potential use of WW samples for genomic surveillance, increasing the set of epidemiological tools to monitor SARS-CoV-2 diversity.

Original languageEnglish
Article number162209
JournalScience of the Total Environment
Volume873
DOIs
Publication statusPublished - 15 May 2023

Bibliographical note

Funding Information:
We would like to thank I. Chestakova, A. van der Linden, M. Boter and B. Weller for excellent technical assistance. We would like to thank Dirk Eggink and Harry Vennema (Dutch Public Health Institute – RIVM) for their contribution to the Dutch clinical surveillance sequence dataset. We gratefully acknowledge the authors and laboratories originating and submitting the Dutch sequences from GISAID EpiCoV database (Shu and McCauley, 2017), which we used during this research. This work was supported by the European Union's H2020 grants VEO (grant no. 874735) and METASTAVA (grant no. 773830), the Dutch Research Council (NWO) under the 2018 Stevin award (Koopmans), the Erasmus MC Foundation and the Adessium Foundation.

Funding Information:
This work was supported by the European Union 's H2020 grants VEO (grant no. 874735 ) and METASTAVA (grant no. 773830 ), the Dutch Research Council (NWO) under the 2018 Stevin award (Koopmans), the Erasmus MC Foundation and the Adessium Foundation .

Publisher Copyright:
© 2023

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