Dispersal history of SARS-CoV-2 in Galicia, Spain

The dynamics of SARS-CoV-2 transmission are influenced by a variety of factors, including social restrictions and the emergence of distinct variants. In this study, we delve into the origins and dissemination of the Alpha, Delta, and Omicron variants of concern in Galicia, northwest Spain. For this, we leveraged genomic data collected by the EPICOVIGAL Consortium and from the GISAID database, along with mobility information from other Spanish regions and foreign countries. Our analysis indicates that initial introductions during the Alpha phase were predominantly from other Spanish regions and France. However, as the pandemic progressed, introductions from Portugal and the USA became increasingly significant. Notably, Galicia’s major coastal cities emerged as critical hubs for viral transmission, highlighting their role in sustaining and spreading the virus. This research emphasizes the critical role of regional connectivity in the spread of SARS-CoV-2 and offers essential insights for enhancing public health strategies and surveillance measures.This work was funded by grant EPICOVIGAL FONDO SUPERA-COVID19 from Banco Santander-CSIC-CRUE and grant CT850A-2 from ACIS SERGAS from the Consellería de Sanidade Xunta de Galicia. PGG was supported by grant ED481A-2021/345 from the Consellería de Cultura, Educación e Universidade Xunta de Galicia. SD acknowledges support from the Fonds National de la Recherche (F.R.S.-FNRS, Belgium; grant no. F.4515.22). SD and GB acknowledge support from the Research Foundation - Flanders (Fonds voor Wetenschappelijk Onderzoek - Vlaanderen, FWO, Belgium; grant no. G098321N) and from the European Union Horizon RIA 2023 project LEAPS (grant no. 101094685). GB acknowledges support from the Internal Funds KU Leuven (Grant No. C14/18/094), from the Research Foundation - Flanders (Fonds voor Wetenschappelijk Onderzoek - Vlaanderen, FWO, Belgium; grant no. G0E1420N) and from the DURABLE EU4Health project 02/2023-01/2027, which is co-funded by the European Union (call EU4H-2021-PJ4; grant no. 101102733). SD and PL acknowledge support from the European Union Horizon 2020 project MOOD (grant agreement no. 874850). PL and MAS acknowledge support from the European Union's Horizon 2020 research and innovation programme (grant agreement no. 725422 - ReservoirDOCS), from the Wellcome Trust through project 206298/Z/17/Z and from the National Institutes of Health grants R01 AI153044, R01 AI162611 and U19 AI135995. PL also acknowledges support from the Research Foundation - Flanders (Fonds voor Wetenschappelijk Onderzoek - Vlaanderen, G0D5117N, and G051322N); MIV, JCS and NSO acknowledge support from the Foundation for Science and Technology (FCT) (project UIDB/50026/2020, UIDP/50026/2020).N

Dispersal history of SARS-CoV-2 in Galicia, Spain

13 páginas, 4 figurasThe dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission are influenced by a variety of factors, including social restrictions and the emergence of distinct variants. In this study, we delve into the origins and dissemination of the Alpha, Delta, and Omicron-BA.1 variants of concern in Galicia, northwest Spain. For this, we leveraged genomic data collected by the EPICOVIGAL Consortium and from the GISAID database, along with mobility information from other Spanish regions and foreign countries. Our analysis indicates that initial introductions during the Alpha phase were predominantly from other Spanish regions and France. However, as the pandemic progressed, introductions from Portugal and the United States became increasingly significant. The number of detected introductions varied from 96 and 101 for Alpha and Delta to 39 for Omicron-BA.1. Most of these introductions left a low number of descendants (<10), suggesting a limited impact on the evolution of the pandemic in Galicia. Notably, Galicia's major coastal cities emerged as critical hubs for viral transmission, highlighting their role in sustaining and spreading the virus. This research emphasizes the critical role of regional connectivity in the spread of SARS-CoV-2 and offers essential insights for enhancing public health strategies and surveillance measures.This work was funded by grant EPICOVIGAL FONDO SUPERA-COVID19 from Banco Santander-CSIC-CRUE and grant CT850A-2 from ACIS SERGAS from the Consellería de Sanidade Xunta de Galicia. PGG was supported by grant ED481A-2021/345 from the Consellería de Cultura, Educación e Universidade Xunta de Galicia. SD acknowledges support from the Fonds National de la Recherche (F.R.S.-FNRS, Belgium; grant no. F.4515.22). SD and GB acknowledge support from the Research Foundation - Flanders (Fonds voor Wetenschappelijk Onderzoek - Vlaanderen, FWO, Belgium; grant no. G098321N) and from the European Union Horizon RIA 2023 project LEAPS (grant no. 101094685). GB acknowledges support from the Internal Funds KU Leuven (Grant No. C14/18/094), from the Research Foundation - Flanders (Fonds voor Wetenschappelijk Onderzoek - Vlaanderen, FWO, Belgium; grant no. G0E1420N) and from the DURABLE EU4Health project 02/2023-01/2027, which is co-funded by the European Union (call EU4H-2021-PJ4; grant no. 101102733). SD and PL acknowledge support from the European Union Horizon 2020 project MOOD (grant agreement no. 874850). PL and MAS acknowledge support from the European Union's Horizon 2020 research and innovation programme (grant agreement no. 725422 - ReservoirDOCS), from the Wellcome Trust through project 206298/Z/17/Z and from the National Institutes of Health grants R01 AI153044, R01 AI162611 and U19 AI135995. PL also acknowledges support from the Research Foundation - Flanders (Fonds voor Wetenschappelijk Onderzoek - Vlaanderen, G0D5117N, and G051322N); MIV, JCS and NSO acknowledge support from the Foundation for Science and Technology (FCT) (project UIDB/50026/2020, UIDP/50026/2020).Peer reviewe

Custom protocol for RT-PCR amplification of SARS-CoV-2 RNA.

Custom protocol for RT-PCR amplification of SARS-CoV-2 RNA.</p

Overall results of sequencing of SARS-CoV-2 using an amplicon-based method and a capture-based method for enrichment.

a) Violin plot and boxplot of the median read depth divided by cohorts. (For Amplicon enrichment, Wilcoxon test; p p = 0.92). b,c) Genome coverage, percentage of the genome with a read depth over 10. Each data point corresponds to one sample. Amplicon: ARTIC panel, amplicon-based enrichment. Capture: KAPA RNA HyperCap, capture-based enrichment.</p

S1 Dataset -

To control the SARS-CoV-2 pandemic, healthcare systems have focused on ramping up their capacity for epidemiological surveillance through viral whole genome sequencing. In this paper, we tested the performance of two protocols of SARS-CoV-2 nucleic acid enrichment, an amplicon enrichment using different versions of the ARTIC primer panel and a hybrid-capture method using KAPA RNA Hypercap. We focused on the challenge of the Omicron variant sequencing, the advantages of automated library preparation and the influence of the bioinformatic analysis in the final consensus sequence. All 94 samples were sequenced using Illumina iSeq 100 and analysed with two bioinformatic pipelines: a custom-made pipeline and an Illumina-owned pipeline. We were unsuccessful in sequencing six samples using the capture enrichment due to low reads. On the other hand, amplicon dropout and mispriming caused the loss of mutation G21987A and the erroneous addition of mutation T15521A respectively using amplicon enrichment. Overall, we found high sequence agreement regardless of method of enrichment, bioinformatic pipeline or the use of automation for library preparation in eight different SARS-CoV-2 variants. Automation and the use of a simple app for bioinformatic analysis can simplify the genotyping process, making it available for more diagnostic facilities and increasing global vigilance.</div

Phylogenetic tree for all samples analysed in the study.

Samples are coloured by clade, with undesignated recombinant samples shown in yellow. The tip label indicates the Pango lineage. Tree generated by Neighbour-Joining method; Maximum Composite Likelihood. Amplicon: ARTIC panel, amplicon-based enrichment. Capture: KAPA RNA HyperCap, capture-based enrichment.</p

Variant allele frequency plot for three possible undesignated recombinant samples.

Only BA.1-specific and BA.2-specific mutations were plotted, with the amplicon enrichment (ARTIC panel) on the left (ABE) and the capture enrichment (KAPA RNA HyperCap) on the right (CBE).The high allele frequency, with most SNPs called with over 95% allele frequency, suggesting recombination and not co-infection. Samples 2 and 3 (panels c-f) show likely the same breakpoint, suggesting both coming from the same origin. The lines represent a LOESS local regression for the allele frequency of each variant.</p

Coverage and depth per sample using all enrichment methods and bioinformatic analysis.

Coverage and depth per sample using all enrichment methods and bioinformatic analysis.</p

Histograms of discrepancies in final consensus sequences.

a) Base mismatches in all studied samples using the amplicon-enrichment method or capture-enrichment method. b-c) Discrepancies using two different bioinformatic pipelines, a customised bioinformatic pipeline and Illumina® DRAGEN™ COVID lineage app. b) For ARTIC panel, amplicon-based enrichment. c) For KAPA RNA HyperCap, capture-based enrichment.</p