Genomic and Epidemiological Surveillance of SARS-CoV-2 Epidemic in Northwestern Greece

Abstract

In early 2020, Greece was affected by the SARS-CoV-2 epidemic, and since then, the continuous emergence of fast-spreading variants has caused surges of new SARS-CoV-2 infections. In this study, we performed genomic, phylogenetic, and epidemiological analyses to investigate the SARS-CoV-2 epidemic in northwestern Greece. From March 2020 to February 2022, nasopharyngeal samples obtained from patients suspected to have COVID-19 were tested for SARS-CoV-2 detection. Complete SARS-CoV-2 genomic sequences were generated from selected positive samples. Northwestern Greece experienced four distinct waves of the epidemic following the first wave, which was mainly observed in Attica and other parts of Greece. The positivity index was rising throughout the pandemic waves in several geographical units, with the highest levels recorded in prominent tourist destinations characterized by high agricultural density. The phylogenetic analyses revealed 34 different lineages, with B.1, B.1.1, B.1.1.305, B.1.1.318, B.1.177, B.1.1.7, B.1.617.2, AY.43, and BA.1 being the most prevalent lineages in the region. Although multiple lineages were co-circulating, each pandemic wave was dominated by a different lineage. The SARS-CoV-2 epidemic in northwestern Greece was characterized by the successive introduction of new lineages, resulting in surges of new SARS-CoV-2 infections.

1. Introduction

Severe acute respiratory syndrome CoronaVirus-2 (SARS-CoV-2) emerged in Wuhan, China, in December 2019, leading to the coronavirus disease 2019 (COVID-19) outbreak [1,2,3,4]. As a novel coronavirus, SARS-CoV-2 posed unprecedented public health challenges due to its ability to spread rapidly through respiratory droplets and, in some cases, asymptomatic carriers. The World Health Organization (WHO) declared the disease a Public Health Emergency of International Concern on 11 March 2020, highlighting the global threat posed by the virus [5,6,7].

In response to the pandemic, many countries implemented infection prevention measures such as lockdowns, social distancing, travel restrictions, and the promotion of hygiene practices [8,9]. Despite these interventions, the virus has continued to evolve, leading to the emergence of new variants, such as the Alpha, Beta, Gamma, Delta, and Omicron variants, each characterized by varying degrees of transmissibility and virulence [10]. These variants have led to successive waves of infections with varying durations and peak intensities across regions, often overwhelming healthcare systems [10,11].

The first laboratory-confirmed case of a patient with COVID-19 in Greece was reported on 26 February 2020 [12]. Since then, the country has experienced several pandemic waves driven by different variants of the virus [13]. Several factors, including viral mutations, the introduction of vaccines, public health measures, and population behavior, have shaped the pandemic waves. Northwestern Greece, like many other regions, has experienced significant increases in COVID-19 cases, necessitating detailed epidemiological and genomic surveillance.

The aim of this study is to determine the pandemic waves of SARS-CoV-2-positive cases in northwestern Greece that occurred from March 2020 to February 2022 and to provide and analyze high-quality, full-length SARS-CoV-2 genome sequences that reflect the genetic diversity of circulating variants in this region. By performing phylogenetic and genetic analyses on 435 SARS-CoV-2 sequences from infected individuals, the study seeks to contribute valuable data on the progression and evolution of the pandemic in northwestern Greece. This genomic data is crucial for understanding the spread of SARS-CoV-2, monitoring the emergence of new variants, and guiding public health responses in the region.

2. Materials and Methods

2.1. Study Participants

Between March 2020 and February 2022, nasopharyngeal samples were collected from patients meeting the clinical criteria for SARS-CoV-2 infection at the Emergency Department of the University Hospital of Ioannina, as well as at other hospitals and primary care centers in northwestern Greece. The Microbiology Laboratory of the University Hospital of Ioannina serves as the reference laboratory for SARS-CoV-2 laboratory confirmation for all healthcare facilities in the Epirus region. A total of 235.000 clinical specimens were collected and submitted for SARS-CoV-2 testing. Viral genomes from SARS-CoV-2-positive specimens were selected for NGS analysis according to the stratified random sampling technique to divide the samples into homogenous subpopulations between the pandemic waves. The samples were stratified using two criteria: (i) a threshold detection cycle (Ct value) of equal to or less than 28, and (ii) their regional unit of origin.

2.2. RNA Extraction and SARS-CoV-2 Detection

Total RNA was extracted from 200 to 400 μL of nasopharyngeal swab samples using either the MagMAX Viral/Pathogen Nucleic Acid Isolation Kit (Applied Biosystems, Waltham, MA, USA) on an automated RNA extraction system (KingFisher, Thermo Fisher Scientific, Waltham, MA, USA) or the TANBead OptiPure Viral Auto Plate Kit (TANBead, Taoyuan, Taiwan) on an automated RNA extraction system (Maelstrom 9600, TANBead, Taoyuan, Taiwan) according to the manufacturer’s specifications. The presence of SARS-CoV-2 in the samples was confirmed using commercially available real-time reverse transcription polymerase chain reaction (real-time RT-PCR) assays targeting either the ORF1ab region and the N gene (Viasure Real Time PCR Detection Kit for SARS-CoV-2, CerTest Biotec, Zaragoza, Spain) or the E, N, and RdRP/S genes (Allplex™ SARS-CoV-2 Assay, Seegene, Seoul, Republic of Korea) of SARS-CoV-2. All the amplification reactions were performed on the CFX Touch 96-well Real-Time PCR System (Bio-Rad Laboratories, Inc., Hercules, CA, USA).

2.3. SARS-CoV-2 Genome Sequence Analysis

2.3.1. Library Preparation—Illumina

Libraries for 450 SARS-CoV-2-positive RNA samples originated from non-repetitive individuals and were prepared for sequencing using the QIAseq SARS-CoV-2 Primer Panel (Qiagen, Hilden, Germany) in combination with the QIAseq FX DNA library kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. The extracted RNA was reverse-transcribed to generate cDNA using random hexamers. The generated cDNA was amplified by dividing 5 μL of cDNA into two PCR pools (2.5 mL for each pool) and amplified into 400 bp amplicons using two sets of primers that cover 99% of the entire SARS-CoV-2 genome. The two pools were then recombined into a single tube for each sample to be simultaneously fragmented and tagmented. The tagmented amplicons were subjected to a post-tagmentation clean-up step and amplified once more with the addition of indexes to each sample using the QIAseq FX DNA library kit for Illumina. The indexed libraries were then pooled and cleaned in batches of 96 and quantified using the Qubit High-Sensitivity Assay on a Qubit 3.0 fluorometer (Invitrogen, Carlsbad, CA, USA).

2.3.2. Next-Generation Sequencing

Libraries from each preparation were pooled based on a quality control evaluation. In addition, libraries for MiSeq (prepared as described above) were diluted and denatured according to the MiSeq Denature and Dilute Guides (February 2019, v10 version, and November 2020, v03 version).

2.4. Bioinformatic Analysis

2.4.1. Reference Mapping Data Analysis

The CLC Genomics Workbench 20.0.4 (QIAGEN Gmbh; Hilden, Germany) bioinformatics workflow was used for raw read trimming, quality control, and reference mapping with default settings. Trimmed reads were mapped to the Wuhan SARS-CoV-2 reference genome (NC_045512).

2.4.2. Assign Epidemiological Lineages to the SARS-CoV-2 Genome Sequences

The Phylogenetic Assignment of Named Global Outbreak Lineages (pangolin) computational method was used to identify and assign SARS-CoV-2 phylogenetic lineages. The pangolin web tool extracts genomic information from SARS-CoV-2 sequence data using the currently accepted lineage designations for extracting lineage classification results according to the selected sequences in FASTA format [QIAGEN CLC Genomics Workbench] (version 4.3, pangolin data version v1.22) (https://pangolin.cog-uk.io/, accessed on 3 March 2023).

2.5. Detection of Mutations

We identified the mutations on our sequence data using the Nextclade Webtool Web version 3.3.0 (https://clades.nextstrain.org/Nextclade, accessed on 3 March 2023) [14]. A total of 15 out of 450 sequences that did not meet stricter quality control criteria were removed from the analysis to prevent any misinterpretation of mutations caused by sequencing and assembly artifacts.

2.6. Dataset Compilation

The AliView v.1.26 algorithm [15] was used to manually edit and examine the genomic sequences of the present study. In order to have a complete overview of the extensive sequence dataset and an efficient way of visually inspecting the alignments later on, we employed the lightweight fast alignment viewer and editor. All newly generated genomic sequences were multiple-aligned using the R package msa (Bioconductor version 3.20) for multiple sequence alignment [16]. The multiple sequence alignment file was manually updated with the AliView v.1.26 methodology [15].

2.7. Phylogenetic Analysis

A lineage-specific phylogenetic tree was constructed to depict how lineages evolved during the early stages of the pandemic. Sequence data from the most prevalent lineages within the reported period of the pandemic were submitted to the Nextclade Webtool (https://clades.nextstrain.org, date accessed on 15 March 2024) [14] for clade assignment.

To infer the phylogenetic tree by maximum likelihood (ML), the IQ-TREE software (version 2.3.6) was used [17]. IQ-TREE is a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies, enabling (i) approximately unbiased branch support values, (ii) fast and accurate model selection while supporting huge datasets with thousands of sequences and millions of alignment sites [14]. In the present work, phylogenetic analysis included the sequences of the most prevalent lineages and sub-lineages detected in northwestern Greece during the reported time period for reconstructing the evolutionary tree, determining the tree topology, and estimating the branch lengths. On this basis, the ML tree was constructed from the edited alignment file, with unbiased clade support values estimated through the ultrafast bootstrap (UFBoot) procedure [18] and the SH-aLRT test [19] using the default values (i.e., 100 and 1000, respectively). Each branch was then assigned with SH-aLRT and UFBoot supports, based only on those clades with SH-aLRT ≥ 80% and UFboot ≥ 95%.

3. Results

3.1. COVID-19 Pandemic Waves in Northwestern Greece

In Greece, after the first confirmed case on February 26, 2020, the overall pattern of the coronavirus pandemic has been a series of COVID-19 waves where surges in new cases were followed by declines (National Public Health Organization (EODY), Available online: https://eody.gov.gr/en/, accessed on 9 October 2022). From March 2020 to February 2022, the COVID-19 cases that were confirmed positive for SARS-CoV-2 by RT-PCR demonstrated that northwestern Greece experienced four distinct epidemic waves (Figure 1). These waves are clearly delineated and placed in autumn 2020, early 2021, summer 2021, and from mid-autumn to early 2022. While the duration of the waves remained almost constant, the peak of each subsequent wave increased each time, resulting in a higher number of new COVID-19 cases (Figure 1) and in increasing percent-positive rates (Figure 2). During the pandemic, the highest rates were among the regional units of Preveza, Lefkada, and Thesprotia, while the lowest index was in the regional unit of Ioannina (Figure 2). It is also noteworthy that in this region we do not have the appearance of the first wave, which took place in spring 2020 and was mainly observed in Attica as well as in other parts of Greece [20].

3.2. The Appearance (Emergence) of SARS-CoV-2 Lineages in Northwestern Greece

In the current study, 435 SARS-CoV-2 genome sequences were analyzed from March 2020 to February 2022. According to the classification of the identified lineages, a plethora of 34 different lineages were extracted, distributed by wave (

Table 1. Lineage and sub-lineage observed per pandemic wave during the study period (% per pandemic wave). The most prevalent lineages in each pandemic wave are shown in bold.

1st Wave		2nd Wave		3rd Wave		4th Wave		5th Wave
Lineage	N (%)	Lineage	N (%)	Lineage	N (%)	Lineage	N (%)	Lineage	N (%)
B.1	37.5	B.1.1	26.47	B.1.1.7	71.43	B.1.617.2	72.87	AY.43	39.66
B.1.1	37.5	B.1.1.305	26.47	B.1.1.318	21	B.1.1.7	13.18	BA.1	25.86
B.1.1.305	12.5	B.1.177	20.59	B.1.258	3.36	B.1.1.318	4.65	AY.122	12.07
B.3	12.5	B.1.36	11.77	B.1.221	1.68	B.1.351.3	2.32	AY.121	10.35
		B.1.258	5.88	B.1.177.35	0.84	AY.122	2.32	B.1.617.2	1.72
		B.1.1.218	5.88	B.1.177	0.84	AY.43	1.54	AY.4	1.72
		C30	2.94	B.1.617.2	0.84	AY.7.1	0.78	AY.9	1.72
						AY.23	0.78	AY.9.2	1.72
						AY.33	0.78	AY.446.6	1.72
						B.1.351	0.78	AY.84	1.72
								AY.122.1s	1.72

) and by month (Figure 3) for the specific period. The sequence data revealed multiple lineages, with B.1, B.1.1, B.1.1.305, B.1.1.318, B.1.177, B.1.1.7, B.1.617.2, AY.43, and BA.1 being the most prevalent lineages in northwestern Greece. Further analysis showed the predominance of seven lineages at different periods, with B.1 (37.5%) and B.1.1.305 (26.47%) being co-dominant with B.1.1 during the first and second pandemic waves, respectively; B.1.1.7 (71.43%) and B.1.617.2 (72.87%) being predominant during the third and fourth waves, respectively; and AY.43 (39.66%) and BA.1 (25.86%) during the fifth pandemic wave. The most prevalent lineages overall were B.1.1.7 and B.1.617.2, accounting for a total of 205 sequences in the SARS-CoV-2-positive samples included in our study (Table 1). The introduction of new variants into the population is followed by waves of infection. A more transmissible SARS-CoV-2 variant would increase the total infected population. It is worth mentioning that the emergence of the new predominant variant of each pandemic wave was characterized by a substantially increasing percent positive rate.

3.3. Phylogeny and S Protein Mutational Analysis of the Most Prevalent SARS-CoV-2 Lineages in Northwestern Greece

The most prevalent lineages that were identified in northwestern Greece during the study period were B.1.1.7 and its sub-lineages, B.1.617.2, and AY. sub-lineages. The mutational analysis in this section is based on the S protein due to its important role in the transmissibility of the virus and in diagnostic assays [21]. In addition, the S protein exhibits two regions of high mutagenic plasticity on its surface where a substantial fraction of the mutations that define the emerging lineages occur [22]. The maximum likelihood tree was generated using the Nextclade Webtool for clade assignment, including the reference genome and the sequences of the most prevalent lineages identified using the entire dataset of the 435 SARS-CoV-2 genomic sequences detected in northwestern Greece. To identify the S protein mutations of these lineages, sequences were input into the Nextclade Webtool [14], and the output was sorted to isolate S protein mutations (deletions and substitutions) (Nextstrain. Available online: https://nextstrain.org/, accessed on 3 March 2023). The evolution of the lineages and clades is depicted in Figure 4 in a rectangular tree layout colored by the assigned Nextclade Webtool Pango lineages and the assigned clades, respectively. The mutational analysis shows that the SARS-CoV-2 variants incorporated a progressively wide range of mutations during the course of the pandemic. The differences between the sequences of the current work and the reference genome were used for clade assignment, revealing their genetic relationship with the construction of a maximum likelihood (ML) phylogenetic tree (Figure 5).

4. Discussion

In the current study, 435 SARS-CoV-2 genome sequences were analyzed to track circulating clades, and 34 SARS-CoV-2 lineages were identified in northwestern Greece during the period from March 2020 to February 2022. The most prevalent lineages were B.1.258 and its sub-lineages; B.1.1.7 and its sub-lineages; B.1.617.2; and AY. sub-lineages. Except for the first pandemic wave, which was almost unnoticeable in northwestern Greece, the timeline and the surge pattern of the following pandemic waves are similar to those observed in the other geographical regions of Greece. In comparison with other Greek regions (e.g., the Attica Region), Epirus exhibited markedly lower incidence rates but still maintained a considerable number of confirmed cases. Based on our data and publicly available data from the Greek Ministry of Health, the relative impact of COVID-19 in northwestern Greece was among the lowest regarding the number of positive case per capita (National Public Health Organization (EODY), Available online: https://eody.gov.gr/en/, accessed on 9 October 2022). Several factors could contribute to the relatively lower number of COVID-19 cases observed in northwestern Greece, including geographical location and cultural and social behaviors [23].

At the beginning of the pandemic, a few lineages with limited mutations were circulating [12]. This study indicated a significant divergence between the predominant lineages from one pandemic wave to next. The first pandemic wave, which was not clearly recorded in our study, was characterized by a predominance of the B.1 and B.1.1 lineages, as in other regions of Greece [12,24]. Infection prevention policies, including lockdown and travel restrictions, helped to mitigate the spread of SARS-CoV-2 [24]. The restrictions were lifted over the summer period, and the emergence of VOCs, mainly the B.1.1, B.1.1.305, and B.1.177 lineages, has led to an increase in COVID-19 cases and a subsequent wave of the pandemic until the beginning of September 2020. The third wave was characterized by the prevalence of the B.1.1.7 lineage, while the B.1, B.1.1, and B.1.1.305 were no longer detected circulating in the population. The prevalence of B.1.1.7 was ended by the Delta variants (B.1.617.2 and AY. sub-lineages), which showed increased transmissibility and infectivity and became dominant, leading to the fourth wave. In October 2021, the prevalence of B.1.617.2 came to an end, and shortly after, the emergence of predominate AY.43 and BA.1 lineages led to a surge of COVID-19 cases, the highest of all five waves in a short period. The positivity index was rising throughout the pandemic waves among the different regional units, with the highest values observed in the major tourist destination areas, such as Preveza, Lefkada, and Thesprotia, with high agricultural density. The emergence of variants with enhanced transmissibility and the increased social interactions after lockdown probably contributed to maintaining high community transmission rates.

The very high rate at which new SARS-CoV-2 variants were being produced has led to the accumulation of new mutations throughout the viral genome, including the ORF genes and the S protein, and the continuous emergence of new variants with a diversity of transmission rates, viral infectivity, and disease severity [25,26,27,28]. Eight GISAID clades and thirty-four PANGOLIN lineages and sub-lineages were found circulating in northwestern Greece. Phylogeny and S protein mutational analysis of the SARS-CoV-2 genomes revealed that the S protein had undergone multiple mutations, indicating the potential for further accumulation and several combinations of mutations that may lead to the emergence of a variant with increased transmissibility and infectivity [29,30,31]. Additional data or research could provide further insights into understanding COVID-19 dynamics in northwestern Greece.

The two main drawbacks of our study were the random sampling selection and the geographically restricted area of the research. Considering also that our sample pool represents 3.4% of the new SARS-CoV-2-positive cases and acknowledging that the real number of SARS-CoV-2 infections is likely significantly underreported, the various lineages identified in northwestern Greece are expected to exceed our estimation.

In conclusion, the present study reports the molecular epidemiology of SARS-CoV-2 variants circulating during the pandemic waves in northwestern Greece. Multiple lineages were co-circulating while a different predominant lineage was observed in each pandemic wave. SARS-CoV-2 lineages that circulated in the northwestern region were similar to those described in Greece, revealing a uniform distribution in the country after preventive measures were reduced. Our work is the only one that provides genomic and epidemiological insights into the SARS-CoV-2 epidemic in northwestern Greece and may serve as a reference for future studies in the area.