key: cord-0899736-5utr3yx5
authors: Fayad, Nancy; Habib, Walid Abi; El-Shesheny, Rabeh; Kandeil, Ahmed; Mourad, Youmna; Mokhbat, Jacques; Kayali, Ghazi; Goldstein, Jimi; Abdallah, Jad
title: Lebanese SARS-CoV-2 genomics: 24 months of the pandemic
date: 2022-05-20
journal: Virus Res
DOI: 10.1016/j.virusres.2022.198824
sha: 2b999bef25c3bc88f9b5de82e853795853707d75
doc_id: 899736
cord_uid: 5utr3yx5

The COVID-19 pandemic continues to pose a global health concern, despite the ongoing vaccination campaigns, due to the emergence and rapid spread of new variants of the causative agent SARS-CoV-2. These variants are identified and tracked via the marker mutations they carry, and the classification system put in place following tremendous sequencing efforts. In this study, the genomes of 1,230 Lebanese SARS-CoV-2 strains collected throughout 2 years of the outbreak in Lebanon were analyzed, 115 of which sequenced within this project. Strains were classified into seven GISAID clades, the major one being GRY, and 36 Pango lineages, with three variants of concern identified: alpha, delta and omicron. A time course distribution of GISAID clades allowed the visualization of change throughout the 2 years of the Lebanese outbreak, in conjunction with major events and measures in the country. Subsequent phylogenetic analysis showed the clustering of strains belonging to the same clades. In addition, a mutational survey showed the presence of mutations in the structural, non-structural and accessory proteins. Twenty five (25) mutations were labeled as major, i.e. present in more than 30% of the strains, such as the common Spike_D614G and NSP3_T183I. Whereas 635 were labeled as uncommon, i.e. found in very few of the analyzed strains as well as GISAID records, such as NSP2_I349V. Distribution of these mutations differed between 2020, and the first and the second half of 2021. In summary, this study highlights key genomic aspects of the Lebanese SARS-CoV-2 strains collected in 2020, the first year of the outbreak in Lebanon, versus those collected in 2021, the second year of COVID-19 in Lebanon.

In late 2019, the world has been introduced to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of the coronavirus-19 disease which is later on officially declared as a global pandemic by the World Health Organization (WHO) on March 11, 2020 (World Health Organization, 2020 Zhang et al., 2020) . Until April 13, 2022, the WHO has reported over 499 million confirmed cases and around 6.2 million COVID-19 related deaths (World Health Organization, 2022b) . In the past two years, several strategies have been adopted by different countries to diminish the spread of the virus and reduce the severity of the symptoms, leading to the development and continuing administration of a number of vaccines (Flanagan et al., 2021; Sharun et al., 2021) .

SARS-CoV-2 is a rapidly mutating RNA virus, in which mutations in the virus' genome can lead to changes in the amino acid sequence of the protein in question, potentially changing its structure and/or activity (Duffy, 2018) (Duffy, 2018) (Duffy, 2018) (Duffy, 2018) . For instance, the D614G mutation in the spike protein leads to a more open conformation, hence a change in its interaction with the host's angiotensin-converting 2 (ACE2) receptor (Antony & Vijayan, 2021; Cecon et al., 2021; Mansbach et al., 2021; Tarek et al., 2021; Zhang et al., 2021) . Accumulation of mutations in encoded proteins, particularly structural ones, is responsible for the emergence of the numerous SARS-CoV-2 variants. The WHO and the Center for Disease Control (CDC) have labeled some of the latter as variants of concern (VOC) (Center for Disease Control and Prevention., 2022; World Health Organization, 2022a) .

Five variants are currently classified as VOC, while also being assigned (i) a Global Initiative on Sharing All Influenza Data (GISAID) clades that relies on marker mutations, and (ii) Pango Lineages, which relies on sequence relatedness and epidemiological events (Global Initiative on Sharing All Influenza Data (GISAID), 2022; Rambaut et al., 2020) . The first VOC is alpha (B.1.1.7 Pango Lineage; GRY GISAID clade), originating from the United Kingdom in December 2020 (Davies et al., 2021; Younes et al., 2021) .

Second is beta (B.1.351 Pango Lineage; GH GISAID clade), first detected in South Africa in October 2020 (Tegally et al., 2021) . Third, gamma, (P.1, P.1., and P.1.2 Pango Lineages; GR GISAID clade) originated in Brazil in December 2020 . The fourth variant is delta. This variant first emerged in the Maharashtra state in India in December 2020. It displaced the previous VOC, and is estimated to constitute around 98% of all cases detected after it emerged (Callaway, 2021; Planas et al., 2021) . It is designated the GK GISAID clade, with the main Pango Lineage B.1.617.2, accompanied by a number of AY sub-lineages, the latter being an alias of the former, with various geographical distributions (Callaway, 2021) . Finally, the most recent variant omicron, first detected in November 2021 and also known as the B.1.1.529 lineage, belongs to the newly formed GRA GISAID clade (Global Initiative on Sharing All Influenza Data (GISAID), 2022).

In Lebanon, a Mediterranean country with an estimated population of seven million (The World Bank, 2022), the outbreak began on February 21, 2020 (Bizri et al., 2021) have been previously analyzed and classified in four GISAID clades and 11 Pango Lineages that showed the GRY clade slowly taking over from the other clades, with the rapid spread of the alpha variant, between the end of December 2020 and early January 2021 (Fayad et al., 2021; Ministry of Public Health, 2022; Younes et al., 2021) . This is also the case globally (Global Initiative on Sharing All Influenza Data (GISAID), 2022).

However, globally and according to the GISAID time course distribution, the GK and GRA clades has become dominant, with almost 100% of new cases resulting from an infection with either the delta or omicron variant (Global Initiative on Sharing All Influenza Data (GISAID), 2022). Little is known about this evolution in Lebanese SARS-CoV-2 strains.

In this study, we aim to explore the evolution of COVID-19 in Lebanon on a genomic level. We analyzed the genomes of 1,230 Lebanese SARS-CoV-2 strains collected over the span of 24 months, between February 2020 and January 2022, and submitted prior to March 10, 2022. 115 of these strains were sequenced within this project. Following genomic analysis, we classified these strains, established their phylogenetic relationship and surveyed the mutations they carry, highlighting the changes that have occurred since the start of the outbreak in Lebanon.

115 Naso-and oro-pharyngeal swabs of confirmed COVID-19 patients were collected from the Lebanese American University Medical Center-Rizk Hospital (LAUMC-RH) and Al-Hadi Medical Center (AHMC), between May 1, 2020 and January 5, 2021, labeled LAU-R (75 strains) and LAU-H (40 strains) respectively.

SARS-CoV-2 RNA was extracted from each sample using QIAmp viral RNA mini kit (cat. No. 52906; Qiagen, Hilden, Germany) according to the manufacturer's instructions, and stored at -80°C. A real-time PCR using Verso 1-step RT-qPCR Kit (Cat. No. AB4100C; Thermo Fisher scientific), with primers targeting the S and ORF genes, confirmed the presence of SARS-CoV-2. Complementary DNA (cDNA) was generated using the SuperScript™ IV One-Step RT-PCR kit (cat. No. 12594025; Thermo Fisher Scientific, Waltham, MA) for genome sequencing, using the following protocol: reverse transcription for 10 min at 50°C; initial PCR activation for 2 min at 98°C, followed by standard initial denaturation for 10 sec at 98°C; annealing for 10 sec at 42°C; extension for 1 min at 72°C, with repeating the last three steps 40 times; and then final extension for 5 min at 72°C. Next Generation Sequencing (NGS) of SARS-CoV-2 genome was then performed using Nextera Illumina protocol as per manufacturer instructions, at Saint Jude Children's Research Hospital, Memphis, TN. 50 ng of SARS-CoV-2 genomic DNA was first tagmented and cleaned, i.e. fragmented and tagged, prior to DNA amplification for library preparation.

Libraries were then normalized and pooled for sequencing. Pooled libraries were sequenced with an Illumina MiSeq personal genome sequencer with 150-bp paired-end reads. CLC Genomics Workbench version 20 (CLC Bio, Qiagen) was used to analyze and process the sequencing reads through workflow.

Only reads aligned to SARS-CoV-2 reference (NC_045512.2) were retained. Unmapped reads were discarded.

In addition to 115 strains sequenced in this study, 1,115 Lebanese SARS-CoV-2 genomes were collected from the GISAID (1,085) and the NCBI GenBank/Virus (30) public databases. All 1,230 genomes were assigned a GISAID clade and Pango Lineage, via the built-in GISAID classifier or Pangolin COVID-19

Lineage Assigner (https://pangolin.cog-uk.io/, last accessed on March 20, 2022). Phylogenetic relationships between strains was established following a MAFFT alignment and using a FastTree v2.10.1 algorithm under the general time reversible (GTR) model (bootstrap = 1,000) using NGPhylogeny.fr online tool (Lemoine et al., 2019) . The resulting tree was annotated with iTOL v6.3.1 (Letunic & Bork, 2021) . Reference strains adopted by GISAID for each clade were included in the phylogenetic analysis. 

In this study, 115 samples were collected from walk-in patients of two medical centers: LAUMC-RH and AHMC. These patients presented to the centers for a RT-qPCR swab test after either being exposed or starting to show symptoms. 38.3% of the patients were identified as females, 47.0% as males and 14.8% did not disclose their gender. The biggest portion of the patients that disclosed their age were between 41 and 50 years old (18.26%), followed by 15.65 and 13.91% for the age ranges 21 to 30 and 31 to 40 years old, respectively (data not shown).

The 115 SARS-CoV-2 genomes sequenced within this study averaged a genome coverage of 30 -33x, with an average of one million read per sample. The genome length of these 115 sequences ranged between 29,897 and 29,905 bp, with a percentage of -N‖ nucleotides between 0 and 3.27%. As for the genomes retrieved from public databases (Supplementary Table S1 ), their length ranged between 28,603 and 29,893 bp, with 0 to 48.70% -N‖ nucleotides per genome.

From February 21, 2020, until December 31, 2020, 181,503 cases and 1,455 COVID-19 related deaths were confirmed in Lebanon (Table 1) (Table 1) .

The 1,230 Lebanese SARS-CoV-2 strains were first assigned a Pango Lineage, and labeled, when applicable, as a VOC. The strains belonged to 36 lineages, including VOCs. B.1.1.7 (alpha) was the most prevalent lineage, with 71.54% of the strains (Figure 1) . B.1.398 came next, with 11.71% of the strains.

As for the delta VOC, it constituted 6.87% of the total strains, with AY.4 being the most prevalent delta lineage (61.25% of the delta strains). Strains labeled as VOC formed 78.46% of the total strains.

As for GISAID clades, all except clades S, V and L were detected. GRY, the alpha GISAID clade, was the most prevalent (71.54%) ( Figure 2A ). The second most prevalent was the clade G (14.07%), followed by GK (6.50%), the delta variant clade. Finally, 0.41% were classified as the omicron variant, and 0.24% of the strains, not specifically classified, were assigned the -O/Other‖ clade.

Clade prevalence varied greatly over time. For GRY, only 1% of strains were collected in 2020 vs 99% in 2021 ( Figure 2B ). As for strains belonging to clades G, GH, and GR, most were collected in 2021. The GV clade is only found in 2021, as is the case with the GKdelta variantclade. As for the newly formed GRA clade, covering the omicron variant, three of the four analyzed strains were collected in December 2021.

Pango lineages classification, a more refined and detailed approach, was paralleled to the GISAID classification, a simpler and more global one. Each GISAID clade encompassed several lineages, except the alpha VOC GRY clade that only housed the B. The time course distribution of the GISAID clades showed an overlap between clades GR, GH, and G in the first months of the outbreak in Lebanon (Figure 3 ). The latter peaked with about 90% of the strains over the span of June, July, and August 2020, to reach around 80% then 50% in October and December 2020, respectively, giving way to the GRY clade (alpha) following its introduction to the Lebanese community. By March 2021, GRY had almost completely taken over until early May 2021 when the delta variant, GK clade, began to spread reaching 100% of the strains collected in June and July 2021, before giving way to the GRA clade, omicron variant in December 2021 -January 2022 ( Figure 3A ). This time course matches that of the GISAID database (Global Initiative on Sharing All Influenza Data (GISAID),

A comparison of the GISAID time course distribution to the evolution of the confirmed COVID-19 cases through time showed an overlap between key events, a surge of positive cases, and the prevalence of key VOC clades ( Figure 3B ). This is the case of the end of year holidays in December 2020 -January 2021: a surge of cases was seen reaching almost 120,000 confirmed cases per month, coinciding with the introduction of the GRY clade, also known as the alpha VOC, to Lebanon. Another high surge is seen again in July -August 2021, with the entry of the delta variant represented by the GK clade. However, the number of cases reached its highest peak at ca. 200,000 cases per month in January 2022, after the 2021/2022 end of year holidays, and the introduction of the omicron VOC, shown by the GRA clade.

The genomes of the sequenced 1,230 Lebanese SARS-CoV-2 strains were aligned and their phylogenetic relationships assessed. The resulting unrooted tree was annotated based on: (i) whether they were classified as a VOC or not, indicated by the symbol on the label, (ii) the GISAID clades to which belong the reference strains from each clade (circle closest to the tree leaves) and those analyzed in this study (second circle from the inside), (iii) whether they were sequenced within this study (third circle from the inside), and (iv), their collection year (outer-most circle).

Strains belonging to the same clade clustered together, with some being phylogenetically distant ( Figure   4 ). Such is the case, for example, of strains QIB-222/2021 and MDC-LAU-6/2021 (highlighted with a blue strip at about five o'clock position in the tree). These strains belong to the G clade, but are nonetheless phylogenetically distant from its cluster. Another example is that of strain QIB-283/2021, which belongs to the GR clade (highlighted with a gold strip at a 1 o'clock position).

Almost 66% of the strains collected in the year 2020 belonged to the G clade (Figure 3) , whereas around 82% of the 2021 strains were classified as GRY. Hence, the year 2020 strains (pointed-out by a gold strip on the outer-most circle) were all clustered together in the G, GH, and GR clades, with some exceptions in the GRY cluster for strains collected in late 2020, after the spread of the alpha variant. The strains sequenced within this study were mostly collected in the year 2020; hence, they belonged to the G, GH and GR clades, and their phylogenetic relatedness (Figure 4 ).

The phylogenetic tree was also annotated based on the three VOCs detected in the analyzed strains:

alpha, delta and omicron. Strains belonging to either one of the VOCs (indicated by colored arrowheads on the tips of the branches) clustered together, as expected. A noteworthy remark is the phylogenetic closeness of the omicron and alpha VOCs.

Much like other RNA viruses, SARS-CoV-2 is highly prone to mutations that might affect the amino acid composition of its encoded proteins. A survey of such changes in the 1,230 analyzed Lebanese SARS-CoV-2 genomes revealed 1,986 different mutations, out of which 22.10%, 66.21%, and 11.68% were located in the structural, non-structural, and accessory proteins, respectively.

In the four structural proteins encoded by SARS-CoV-2, and throughout the Lebanese outbreak, 14 major mutations, in more than 30% of the analyzed strains, were detected, 10 of which in the spike (S) protein.

Throughout the 2 years of the pandemic, the most prevalent S protein mutation is S_D614G, found in 1,226 (99.67%) strains. This mutation is the main marker of the G clade, and those that derive from it:

GH, GR, GRY, GRA and GK; hence its presence in almost all of the analyzed strains.

As shown above with the time course distribution of GISAID clades, in each time frame, one clade emerged as the most prevalent. Hence, this comparison was also drawn for the most prevalent mutations, where a large variability was detected throughout 2020 and 2021, and in the three designated time frames:: February-December 2020, January-May 2021 and June 2021-January 2022 (Table 2) . For instance, two mutations found in the nucleocapsid (N) protein, N_G204R and N_R203K, were at only 12.42% in 2020, and rose to about 90% in the period extending from January to May 2021. N_R203K was then replaced in the third period by N_R203M, a mutation associated with the VOC delta.

As for the S protein, the S_D614G remained, on one hand, the most prevalent since the beginning of the outbreak in Lebanon until January 2022. On the other hand, in 2020, the other major mutation was S_T95I, which was not found in 2021. In total, four mutations for the structural proteins were considered major in 2020, versus 14 in 2021. However, 13 of the latter, with the exception of S_D614G, were absent in the months after June 2021, during which ten other mutations were detected in more than 30% of the strains, with four, one and five in the N, M and S proteins, respectively ( Table 2) . One of the mutations found in 95.06% of the June 2021-January 2022 strains is S_P681R, previously detected in the January-May 2021 strains as S_P681H. The change from a proline to an arginine residue is a key marker of the delta variant (Callaway, 2021) , the prevalent variant in the second half of 2021. Moreover, in the latter, a major mutation in the membrane (M) protein was detected in 98.77% of the strains, whereas no major mutation in the M protein was detected in another time frame.Non-structural proteins (NSPs).

Sixteen non-structural proteins (NSP1-16) encoded by the SARS-CoV-2 genome are not directly involved in the virus's infectivity, but play key roles in viral replication, i.e. NSP12 (RNA-dependent RNA polymerase), NSP13 (helicase), and the Nsp3-Nsp4-Nsp6 subcomplex (Astuti & Ysrafil, 2020; Hillen et al., 2020; Lei et al., 2018; Mariano et al., 2020) . For the NSPs, the most prevalent mutation in the analyzed strains was NSP12_P323L detected in 1,218 (99.02%) strains. Six other major mutations were also detected in NSP3 and NSP6 (Supplementary Table S2A) .

A difference between mutations present in strains collected in 2020 and those collected in 2021 was also seen for the NSPs. In 2020, three major mutations were noted vs seven in January-May 2021 and ten in June-July 2021 (Table 2) . A constant was NSP12_P323L, the most prevalent NSP mutation, present in over 98% of the strains of the three timeframes. Six other major NSP mutations were seen in January-May 2021 but were absent from June 2021-January 2022, in which nine other major mutations were found. Six of the latter were located in the Nsp3 (3), Nsp4 (2) and Nsp6 (1) subcomplex, two in NSP12 and one in each of NSP13 and NSP14.

Within the five accessory proteins encoded by the SARS-CoV-2 genome, five major mutations were detected in NS3 and NS8 proteins. Two of these mutations resulted in a stop codon, NS8_Q27stop and NS8_K68stop, which may lead to the truncation of the NS8 protein.

As for the change between 2020 and 2021, no major mutations were found, contrary to five major mutations found in January-May 2021 ( Table S2A ).

In addition to the mutations labeled as major discussed above, a total of 635 were detected by CoVsurver and labeled as -unique‖ or -uncommon‖ by the mutation-detection server. After verification and crossreferencing with NCBI Virus Sequence Read Archive (SRA) data, it was confirmed that these mutations are found in a limited number of submitted SARS-CoV-2 sequences, ranging between 10 and 610 counts (Supplementary Table S2B ). In Lebanese SARS-CoV-2 strains, the majority of these uncommon mutations was detected in NSPs (475 mutations; 75%). As for the structural proteins, 70 mutations (11%)

were found in the S protein. However, some of these mutations, for example NSP14_E347D was most commonly found as an E347G. This is also true for other mutations, where the site of the mutation was previously reported, but the new amino acid was not. Another example is N_R203T, an uncommon mutation, whereas N_R203K and N_R203M are among the most prevalent detected mutations. Among the 1,230 Lebanese SARS-CoV-2, the most prevalent of these -uncommon‖ mutations were NSP2_I349V

and NSP5_V204I, detected in 12 (0.98%) and 10 (0.81%) strains, respectively. While the former was only found in 2020 strains, the latter was restricted to the first half of 2021 (Supplementary Table S2A ).

On another level, 28 of these mutations, most of which were located in the RNA dependent RNA polymerase NSP12, resulted in a stop codon, (Supplementary Table S2B ). This might lead to a truncation in the corresponding protein.

The rapidly mutating SARS-CoV-2, causative agent of COVID-19, is still spreading around the globe, despite mitigation and vaccination efforts, especially with the emergence of several infective and/or severe variants of concern. In Lebanon, the first COVID-19 case was reported on February 21, 2020, a During 2020, 161 strains were sequenced, 95 of which within this study, whereas the other 1,068 strains were sequenced in 2021, 20 of which within this study. The difference in the number of collected strains between 2020 and 2021 is due to the difference in the number of confirmed cases. In 2021, the number of confirmed cases is 3.6 times higher in comparison to 11 months of outbreak in 2020, with the number of COVID-19 related deaths being 5.5 times higher. This increase in the number of confirmed cases, seen in Lebanon and in other countries as well, was most likely due to a number of factors such as the relaxation of preventive measures, the end-of-year holidays, and a general -corona-fatigue‖ where the population was no longer willing to abide by social distancing rules (Tsai et al., 2021) . The latter is particularly true in Lebanon, after a series of socio-economic and political blows, including the Beirut port explosion on August 4, 2020 (Bizri et al., 2021) .

Moreover, the introduction of the alpha variant to the Lebanese community in late 2020 also contributed to the rapid increase in the number of confirmed cases, coinciding with its worldwide spread after its emergence in the United Kingdom in December 2020 (Davies et al., 2021) . This VOC, also known as GRY GISAID clade or the B. The phylogenetic analysis of the 1,230 strains revealed a clustering of same-clade strains, with several subclades within each cluster and some phylogenetic distance between strains of the same clade. This might be due to subtle variations on a nucleotide level, that do not necessarily reflect as marker mutations, affecting a strain's classification, but that are taken into consideration when conducting alignment of nucleotide sequences. The three VOCs detected in the analyzed strains, VOCs alpha, delta and omicron, formed the majority of the strains. On a phylogenetic level, the alpha and omicron variant are closer together, than they are with the delta VOC, as was also highlighted in a recent review, that (Peacock et al., 2021) .

As for -uncommon‖ mutations, an interesting case is that of N_R203T. This mutation was previously detected as N_R203K and N_R203M, in 90.64 and 91.76% of the strains collected in the first and second halves of 2021, respectively. These mutations involve amino acids of completely different natures: from arginine (R), a positively charged amino acid to either threonine (T), a polar uncharged, lysine (K), a positively charged or methionine (M), a hydrophobic amino acid. Whereas R203K is associated with the increased infectivity, virulence and fitness of the alpha VOC, N_R203M has been tagged among the main mutations in the delta VOC. N_R203M was shown to be associated with increased infectivity, as well as immune system evasion (Letizia et al., 2021) . Moreover, although 38 mutations resulted in a stop codon, mRNA in RNA viruses may follow a non-canonical translation, overtaking a stop codon to continue protein translation (Firth & Brierley, 2012; Namy & Rousset, 2010) .

Current evidence points towards a protection against the different variants (Andrews et al., 2022; Letizia et al., 2021) . Nevertheless, some studies have suggested that some mutations' combinations could affect neutralizing antibodies developed following natural infection or vaccination Zhou et al., 2021) . In fact, the B.1.351 variant was shown to escape from natural and vaccine-induced neutralization . In Lebanon, continued monitoring of the SARS-CoV-2 variants circulating among the Lebanese community is imperative, not only to follow-up on the entry and circulation of VOC, but also to monitor the mutations, be it major or uncommon.

Although SARS-CoV-2 sequencing has improved after the first year of the pandemic, the number of (Yadav et al., 2022) .

Strain collection and sequencing in Lebanon still needs to be improved, particularly after social mixing and touristic periods (summer and end-of-year holidays). . Finally, a detailed functional interpretation of uncommon or unique mutations is yet to be done, along with their effects on the proteins in question and their potential effect on neutralizing antibodies.

In conclusion, the Lebanese outbreak has seen many changes since it started in February 2020, passing through high and low points. After approximately two years of the outbreak, there are 1,230 sequenced

Lebanese SARS-CoV-2 strains, 115 of which in this study, and 28 in a previous one (Fayad et al., 2021) .

Thanks to the continuing sequencing effort, and the subsequent analysis of the genomes, an evolutionary track can be drawn concerning the variants circulating within the Lebanese community according to the available sequences. Mutational survey of these strains, collected at various times of the outbreak, 

SARS-CoV-2 sequences are available on GISAID (14; https://www.gisaid.org/) and NCBI's GenBank/Virus (https://www.ncbi.nlm.nih.gov/labs/virus/vssi/#/sars-cov-2).

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Tegally, H., Wilkinson, E., Giovanetti, M., Iranzadeh, A., Fonseca, V., Giandhari, J., Doolabh, D., Pillay, S., San, E. J., Msomi, N., Mlisana, K., von Gottberg, A., Walaza, S., Allam, M., Ismail, A., Mohale, T., Glass, A. J., Engelbrecht, S., van Zyl, G., … de Oliveira, T. (2021). Detection of a SARS-CoV-2 variant of concern in South Africa. Nature, 592 (7854) Legend key is shown under the tree for the tree tips -VOC; inner-most circles -GISAID clades for, one, the reference strains, and two, the analyzed Lebanese SARS-CoV-2 strains; middle circle -strains sequenced within this study, indicated with a black strip; and the outer-most circlecollection year. 

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The authors would like to acknowledge Rana Abou Salbi and Rebecca Badra for their administrative support and Hanna Semaan and Omar Bahlawan for their technical support.

The authors declare no conflict of interest.

For each mutation, we indicate the percentage of strains that present it, as well as the timeframe during which it was a major or a noteworthy one. a Major mutations: found in more than 30% of the strains; b Noteworthy mutations: found in more than 10% of the strains; * Common mutations found in 2020, 2021 January-May and 2021 June-July; # Different mutations occurring at the same position in the protein;